From 597a57ea2f6304725fa638504d49e2de5a8b0b98 Mon Sep 17 00:00:00 2001 From: colton Date: Thu, 25 Apr 2024 13:18:09 -0400 Subject: [PATCH 01/56] [daggy-u] include data folders with .gitkeep (#21422) ## Summary & Motivation - User informed us that missing folders caused errors when using the project scaffolding - This makes sure the folders are present using `.gitkeep` files --- examples/project_du_dbt_starter/data/outputs/.gitkeep | 0 examples/project_du_dbt_starter/data/raw/.gitkeep | 0 examples/project_du_dbt_starter/data/requests/.gitkeep | 0 examples/project_du_dbt_starter/data/staging/.gitkeep | 0 4 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 examples/project_du_dbt_starter/data/outputs/.gitkeep create mode 100644 examples/project_du_dbt_starter/data/raw/.gitkeep create mode 100644 examples/project_du_dbt_starter/data/requests/.gitkeep create mode 100644 examples/project_du_dbt_starter/data/staging/.gitkeep diff --git a/examples/project_du_dbt_starter/data/outputs/.gitkeep b/examples/project_du_dbt_starter/data/outputs/.gitkeep new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/examples/project_du_dbt_starter/data/raw/.gitkeep b/examples/project_du_dbt_starter/data/raw/.gitkeep new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/examples/project_du_dbt_starter/data/requests/.gitkeep b/examples/project_du_dbt_starter/data/requests/.gitkeep new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/examples/project_du_dbt_starter/data/staging/.gitkeep b/examples/project_du_dbt_starter/data/staging/.gitkeep new file mode 100644 index 0000000000000..e69de29bb2d1d From 730e7dbe2cf9a3c6347df6deb688dc63440e52e9 Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Thu, 25 Apr 2024 10:21:26 -0700 Subject: [PATCH 02/56] move auto-materialize rule impls into own module (#21386) ## Summary & Motivation I wanted to include `AutoMaterializePolicy` as a field in a pydantic class, but pydantic didn't like that some of its attributes had quoted types. This allows importing the auto_materialize_rule module from the auto_materialize_policy module, outside of a TYPE_CHECKING block. ## How I Tested These Changes --- .../schema/auto_materialize_policy.py | 2 +- python_modules/dagster/dagster/__init__.py | 4 +- .../_core/definitions/asset_daemon_cursor.py | 2 +- .../definitions/auto_materialize_policy.py | 28 +- .../definitions/auto_materialize_rule.py | 1105 +---------------- .../auto_materialize_rule_evaluation.py | 6 +- .../auto_materialize_rule_impls.py | 1065 ++++++++++++++++ .../auto_materialize_policy_scenarios.py | 8 +- .../test_auto_materialize_policy.py | 8 +- .../updated_scenarios/basic_scenarios.py | 2 +- .../updated_scenarios/cron_scenarios.py | 2 +- .../cursor_migration_scenarios.py | 4 +- .../updated_scenarios/partition_scenarios.py | 4 +- .../dlt_tests/test_dlt.py | 2 +- 14 files changed, 1152 insertions(+), 1090 deletions(-) create mode 100644 python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_impls.py diff --git a/python_modules/dagster-graphql/dagster_graphql/schema/auto_materialize_policy.py b/python_modules/dagster-graphql/dagster_graphql/schema/auto_materialize_policy.py index 56de3d2728d26..f9fe6f3f0e2f0 100644 --- a/python_modules/dagster-graphql/dagster_graphql/schema/auto_materialize_policy.py +++ b/python_modules/dagster-graphql/dagster_graphql/schema/auto_materialize_policy.py @@ -4,7 +4,7 @@ AutoMaterializePolicy, AutoMaterializePolicyType, ) -from dagster._core.definitions.auto_materialize_rule import ( +from dagster._core.definitions.auto_materialize_rule_impls import ( AutoMaterializeDecisionType, DiscardOnMaxMaterializationsExceededRule, ) diff --git a/python_modules/dagster/dagster/__init__.py b/python_modules/dagster/dagster/__init__.py index 0e72faf29d4dd..04ef1c78d5f2a 100644 --- a/python_modules/dagster/dagster/__init__.py +++ b/python_modules/dagster/dagster/__init__.py @@ -131,9 +131,11 @@ AutoMaterializePolicy as AutoMaterializePolicy, ) from dagster._core.definitions.auto_materialize_rule import ( - AutoMaterializeAssetPartitionsFilter as AutoMaterializeAssetPartitionsFilter, AutoMaterializeRule as AutoMaterializeRule, ) +from dagster._core.definitions.auto_materialize_rule_impls import ( + AutoMaterializeAssetPartitionsFilter as AutoMaterializeAssetPartitionsFilter, +) from dagster._core.definitions.auto_materialize_sensor_definition import ( AutoMaterializeSensorDefinition as AutoMaterializeSensorDefinition, ) diff --git a/python_modules/dagster/dagster/_core/definitions/asset_daemon_cursor.py b/python_modules/dagster/dagster/_core/definitions/asset_daemon_cursor.py index fb09977f2bc75..3ab4c53c54517 100644 --- a/python_modules/dagster/dagster/_core/definitions/asset_daemon_cursor.py +++ b/python_modules/dagster/dagster/_core/definitions/asset_daemon_cursor.py @@ -152,7 +152,7 @@ def get_backcompat_asset_condition_evaluation_state( AssetConditionEvaluationState, RuleCondition, ) - from dagster._core.definitions.auto_materialize_rule import MaterializeOnMissingRule + from dagster._core.definitions.auto_materialize_rule_impls import MaterializeOnMissingRule return AssetConditionEvaluationState( previous_evaluation=latest_evaluation, diff --git a/python_modules/dagster/dagster/_core/definitions/auto_materialize_policy.py b/python_modules/dagster/dagster/_core/definitions/auto_materialize_policy.py index d5b9d32ac5274..eaecf18cc7bb9 100644 --- a/python_modules/dagster/dagster/_core/definitions/auto_materialize_policy.py +++ b/python_modules/dagster/dagster/_core/definitions/auto_materialize_policy.py @@ -1,8 +1,13 @@ from enum import Enum -from typing import TYPE_CHECKING, AbstractSet, Dict, FrozenSet, NamedTuple, Optional, Sequence +from typing import AbstractSet, Dict, FrozenSet, NamedTuple, Optional, Sequence import dagster._check as check from dagster._annotations import deprecated, experimental, public +from dagster._core.definitions.asset_condition.asset_condition import AssetCondition +from dagster._core.definitions.auto_materialize_rule import ( + AutoMaterializeRule, + AutoMaterializeRuleSnapshot, +) from dagster._serdes.serdes import ( NamedTupleSerializer, UnpackContext, @@ -10,20 +15,11 @@ whitelist_for_serdes, ) -if TYPE_CHECKING: - from dagster._core.definitions.asset_condition.asset_condition import AssetCondition - from dagster._core.definitions.auto_materialize_rule import ( - AutoMaterializeRule, - AutoMaterializeRuleSnapshot, - ) - class AutoMaterializePolicySerializer(NamedTupleSerializer): def before_unpack( self, context: UnpackContext, unpacked_dict: Dict[str, UnpackedValue] ) -> Dict[str, UnpackedValue]: - from dagster._core.definitions.auto_materialize_rule import AutoMaterializeRule - backcompat_map = { "on_missing": AutoMaterializeRule.materialize_on_missing(), "on_new_parent_data": AutoMaterializeRule.materialize_on_parent_updated(), @@ -61,9 +57,9 @@ class AutoMaterializePolicy( NamedTuple( "_AutoMaterializePolicy", [ - ("rules", FrozenSet["AutoMaterializeRule"]), + ("rules", FrozenSet[AutoMaterializeRule]), ("max_materializations_per_minute", Optional[int]), - ("asset_condition", Optional["AssetCondition"]), + ("asset_condition", Optional[AssetCondition]), ], ) ): @@ -126,7 +122,7 @@ def __new__( cls, rules: AbstractSet["AutoMaterializeRule"], max_materializations_per_minute: Optional[int] = 1, - asset_condition: Optional["AssetCondition"] = None, + asset_condition: Optional[AssetCondition] = None, ): from dagster._core.definitions.auto_materialize_rule import AutoMaterializeRule @@ -173,7 +169,7 @@ def skip_rules(self) -> AbstractSet["AutoMaterializeRule"]: } @staticmethod - def from_asset_condition(asset_condition: "AssetCondition") -> "AutoMaterializePolicy": + def from_asset_condition(asset_condition: AssetCondition) -> "AutoMaterializePolicy": """Constructs an AutoMaterializePolicy which will materialize an asset partition whenever the provided asset_condition evaluates to True. @@ -285,14 +281,14 @@ def policy_type(self) -> AutoMaterializePolicyType: def rule_snapshots(self) -> Sequence["AutoMaterializeRuleSnapshot"]: return [rule.to_snapshot() for rule in self.rules] - def to_asset_condition(self) -> "AssetCondition": + def to_asset_condition(self) -> AssetCondition: """Converts a set of materialize / skip rules into a single binary expression.""" from .asset_condition.asset_condition import ( AndAssetCondition, NotAssetCondition, OrAssetCondition, ) - from .auto_materialize_rule import DiscardOnMaxMaterializationsExceededRule + from .auto_materialize_rule_impls import DiscardOnMaxMaterializationsExceededRule if self.asset_condition is not None: return self.asset_condition diff --git a/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule.py b/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule.py index 9fe7277d66413..2242ab46a401f 100644 --- a/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule.py +++ b/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule.py @@ -1,61 +1,35 @@ -import datetime -import os from abc import ABC, abstractmethod, abstractproperty -from collections import defaultdict -from typing import ( - TYPE_CHECKING, - AbstractSet, - Dict, - Iterable, - List, - Mapping, - NamedTuple, - Optional, - Sequence, - Set, -) +from typing import TYPE_CHECKING, Optional import pytz import dagster._check as check -from dagster._annotations import deprecated, experimental, public -from dagster._core.definitions.asset_subset import AssetSubset, ValidAssetSubset +from dagster._annotations import public from dagster._core.definitions.auto_materialize_rule_evaluation import ( AutoMaterializeDecisionType, AutoMaterializeRuleSnapshot, - ParentUpdatedRuleEvaluationData, - WaitingOnAssetsRuleEvaluationData, -) -from dagster._core.definitions.events import AssetKey, AssetKeyPartitionKey -from dagster._core.definitions.freshness_based_auto_materialize import ( - freshness_evaluation_results_for_asset_key, -) -from dagster._core.definitions.multi_dimensional_partitions import MultiPartitionsDefinition -from dagster._core.definitions.time_window_partitions import ( - TimeWindow, - TimeWindowPartitionsDefinition, - get_time_partitions_def, -) -from dagster._core.errors import DagsterInvariantViolationError -from dagster._core.event_api import AssetRecordsFilter -from dagster._core.storage.dagster_run import IN_PROGRESS_RUN_STATUSES, RunsFilter -from dagster._core.storage.tags import AUTO_MATERIALIZE_TAG -from dagster._serdes.serdes import ( - whitelist_for_serdes, ) -from dagster._utils.schedules import ( - cron_string_iterator, - is_valid_cron_string, - reverse_cron_string_iterator, -) - -from .base_asset_graph import sort_key_for_asset_partition +from dagster._utils.schedules import is_valid_cron_string if TYPE_CHECKING: from dagster._core.definitions.asset_condition.asset_condition import ( AssetCondition, AssetConditionResult, ) + from dagster._core.definitions.auto_materialize_rule_impls import ( + AutoMaterializeAssetPartitionsFilter, + MaterializeOnCronRule, + MaterializeOnMissingRule, + MaterializeOnParentUpdatedRule, + MaterializeOnRequiredForFreshnessRule, + SkipOnBackfillInProgressRule, + SkipOnNotAllParentsUpdatedRule, + SkipOnNotAllParentsUpdatedSinceCronRule, + SkipOnParentMissingRule, + SkipOnParentOutdatedRule, + SkipOnRequiredButNonexistentParentsRule, + SkipOnRunInProgressRule, + ) from .asset_condition.asset_condition_evaluation_context import AssetConditionEvaluationContext @@ -108,6 +82,10 @@ def materialize_on_required_for_freshness() -> "MaterializeOnRequiredForFreshnes Note: This rule has no effect on partitioned assets. """ + from dagster._core.definitions.auto_materialize_rule_impls import ( + MaterializeOnRequiredForFreshnessRule, + ) + return MaterializeOnRequiredForFreshnessRule() @public @@ -134,6 +112,8 @@ def materialize_on_cron( check.param_invariant( timezone in pytz.all_timezones_set, "timezone", "must be a valid timezone" ) + from dagster._core.definitions.auto_materialize_rule_impls import MaterializeOnCronRule + return MaterializeOnCronRule( cron_schedule=cron_schedule, timezone=timezone, all_partitions=all_partitions ) @@ -154,6 +134,10 @@ def materialize_on_parent_updated( to updated parents. If a parent was updated but does not pass the filter criteria, then it won't count as updated for the sake of this rule. """ + from dagster._core.definitions.auto_materialize_rule_impls import ( + MaterializeOnParentUpdatedRule, + ) + return MaterializeOnParentUpdatedRule(updated_parent_filter=updated_parent_filter) @public @@ -162,6 +146,8 @@ def materialize_on_missing() -> "MaterializeOnMissingRule": """Materialize an asset partition if it has never been materialized before. This rule will not fire for non-root assets unless that asset's parents have been updated. """ + from dagster._core.definitions.auto_materialize_rule_impls import MaterializeOnMissingRule + return MaterializeOnMissingRule() @public @@ -170,6 +156,8 @@ def skip_on_parent_missing() -> "SkipOnParentMissingRule": """Skip materializing an asset partition if one of its parent asset partitions has never been materialized (for regular assets) or observed (for observable source assets). """ + from dagster._core.definitions.auto_materialize_rule_impls import SkipOnParentMissingRule + return SkipOnParentMissingRule() @public @@ -178,6 +166,8 @@ def skip_on_parent_outdated() -> "SkipOnParentOutdatedRule": """Skip materializing an asset partition if any of its parents has not incorporated the latest data from its ancestors. """ + from dagster._core.definitions.auto_materialize_rule_impls import SkipOnParentOutdatedRule + return SkipOnParentOutdatedRule() @public @@ -196,6 +186,10 @@ def skip_on_not_all_parents_updated( least one upstream partition in each upstream asset to be materialized since the downstream asset's last materialization in order to update it. Defaults to false. """ + from dagster._core.definitions.auto_materialize_rule_impls import ( + SkipOnNotAllParentsUpdatedRule, + ) + return SkipOnNotAllParentsUpdatedRule(require_update_for_all_parent_partitions) @staticmethod @@ -210,6 +204,10 @@ def skip_on_not_all_parents_updated_since_cron( timezone (str): The timezone in which this cron schedule should be evaluated. Defaults to "UTC". """ + from dagster._core.definitions.auto_materialize_rule_impls import ( + SkipOnNotAllParentsUpdatedSinceCronRule, + ) + return SkipOnNotAllParentsUpdatedSinceCronRule( cron_schedule=cron_schedule, timezone=timezone ) @@ -223,6 +221,10 @@ def skip_on_required_but_nonexistent_parents() -> "SkipOnRequiredButNonexistentP time-partitioned parent which starts in 2023. This rule will skip attempting to materialize downstream partitions from before 2023, since the parent partitions do not exist. """ + from dagster._core.definitions.auto_materialize_rule_impls import ( + SkipOnRequiredButNonexistentParentsRule, + ) + return SkipOnRequiredButNonexistentParentsRule() @public @@ -237,10 +239,16 @@ def skip_on_backfill_in_progress( regardless of whether the specific partition is targeted by a backfill. If False, skips only partitions targeted by a backfill. Defaults to False. """ + from dagster._core.definitions.auto_materialize_rule_impls import ( + SkipOnBackfillInProgressRule, + ) + return SkipOnBackfillInProgressRule(all_partitions) @staticmethod def skip_on_run_in_progress() -> "SkipOnRunInProgressRule": + from dagster._core.definitions.auto_materialize_rule_impls import SkipOnRunInProgressRule + return SkipOnRunInProgressRule() def to_snapshot(self) -> AutoMaterializeRuleSnapshot: @@ -258,1014 +266,3 @@ def __eq__(self, other) -> bool: def __hash__(self) -> int: # override the default NamedTuple __hash__ method to factor in types return hash(hash(type(self)) + super().__hash__()) - - -@deprecated( - breaking_version="1.8", - additional_warn_text="Lazy auto-materialize is deprecated, in favor of explicit cron-based " - "scheduling rules. Additional alternatives to replicate more of the lazy auto-materialize " - "behavior will be provided before this is fully removed.", -) -@whitelist_for_serdes -class MaterializeOnRequiredForFreshnessRule( - AutoMaterializeRule, NamedTuple("_MaterializeOnRequiredForFreshnessRule", []) -): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.MATERIALIZE - - @property - def description(self) -> str: - return "required to meet this or downstream asset's freshness policy" - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - true_subset, subsets_with_metadata = freshness_evaluation_results_for_asset_key( - context.root_context - ) - return AssetConditionResult.create(context, true_subset, subsets_with_metadata) - - -@whitelist_for_serdes -class MaterializeOnCronRule( - AutoMaterializeRule, - NamedTuple( - "_MaterializeOnCronRule", - [("cron_schedule", str), ("timezone", str), ("all_partitions", bool)], - ), -): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.MATERIALIZE - - @property - def description(self) -> str: - return f"not materialized since last cron schedule tick of '{self.cron_schedule}' (timezone: {self.timezone})" - - def missed_cron_ticks( - self, context: "AssetConditionEvaluationContext" - ) -> Sequence[datetime.datetime]: - """Returns the cron ticks which have been missed since the previous cursor was generated.""" - # if it's the first time evaluating this rule, then just count the latest tick as missed - if not context.previous_evaluation or not context.previous_evaluation_timestamp: - previous_dt = next( - reverse_cron_string_iterator( - end_timestamp=context.evaluation_time.timestamp(), - cron_string=self.cron_schedule, - execution_timezone=self.timezone, - ) - ) - return [previous_dt] - missed_ticks = [] - for dt in cron_string_iterator( - start_timestamp=context.previous_evaluation_timestamp, - cron_string=self.cron_schedule, - execution_timezone=self.timezone, - ): - if dt > context.evaluation_time: - break - missed_ticks.append(dt) - return missed_ticks - - def get_new_candidate_asset_partitions( - self, context: "AssetConditionEvaluationContext", missed_ticks: Sequence[datetime.datetime] - ) -> AbstractSet[AssetKeyPartitionKey]: - if not missed_ticks: - return set() - - partitions_def = context.partitions_def - if partitions_def is None: - return {AssetKeyPartitionKey(context.asset_key)} - - # if all_partitions is set, then just return all partitions if any ticks have been missed - if self.all_partitions: - return { - AssetKeyPartitionKey(context.asset_key, partition_key) - for partition_key in partitions_def.get_partition_keys( - current_time=context.evaluation_time, - dynamic_partitions_store=context.instance_queryer, - ) - } - - # for partitions_defs without a time component, just return the last partition if any ticks - # have been missed - time_partitions_def = get_time_partitions_def(partitions_def) - if time_partitions_def is None: - return { - AssetKeyPartitionKey( - context.asset_key, - partitions_def.get_last_partition_key( - dynamic_partitions_store=context.instance_queryer - ), - ) - } - - missed_time_partition_keys = filter( - None, - [ - time_partitions_def.get_last_partition_key( - current_time=missed_tick, - dynamic_partitions_store=context.instance_queryer, - ) - for missed_tick in missed_ticks - ], - ) - # for multi partitions definitions, request to materialize all partitions for each missed - # cron schedule tick - if isinstance(partitions_def, MultiPartitionsDefinition): - return { - AssetKeyPartitionKey(context.asset_key, partition_key) - for time_partition_key in missed_time_partition_keys - for partition_key in partitions_def.get_multipartition_keys_with_dimension_value( - partitions_def.time_window_dimension.name, - time_partition_key, - dynamic_partitions_store=context.instance_queryer, - ) - } - else: - return { - AssetKeyPartitionKey(context.asset_key, time_partition_key) - for time_partition_key in missed_time_partition_keys - } - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - missed_ticks = self.missed_cron_ticks(context) - new_asset_partitions = self.get_new_candidate_asset_partitions(context, missed_ticks) - - # if it's the first time evaluating this rule, must query for the actual subset that has - # been materialized since the previous cron tick, as materializations may have happened - # before the previous evaluation, which - # `context.materialized_requested_or_discarded_since_previous_tick_subset` would not capture - if context.previous_evaluation is None: - new_asset_partitions -= context.instance_queryer.get_asset_subset_updated_after_time( - asset_key=context.asset_key, after_time=missed_ticks[-1] - ).asset_partitions - - asset_subset_to_request = AssetSubset.from_asset_partitions_set( - context.asset_key, context.partitions_def, new_asset_partitions - ) | ( - context.previous_true_subset.as_valid(context.partitions_def) - - context.materialized_requested_or_discarded_since_previous_tick_subset - ) - - return AssetConditionResult.create(context, true_subset=asset_subset_to_request) - - -@whitelist_for_serdes -@experimental -class AutoMaterializeAssetPartitionsFilter( - NamedTuple( - "_AutoMaterializeAssetPartitionsFilter", - [("latest_run_required_tags", Optional[Mapping[str, str]])], - ) -): - """A filter that can be applied to an asset partition, during auto-materialize evaluation, and - returns a boolean for whether it passes. - - Attributes: - latest_run_required_tags (Optional[Sequence[str]]): `passes` returns - True if the run responsible for the latest materialization of the asset partition - has all of these tags. - """ - - @property - def description(self) -> str: - return f"latest run includes required tags: {self.latest_run_required_tags}" - - def passes( - self, - context: "AssetConditionEvaluationContext", - asset_partitions: Iterable[AssetKeyPartitionKey], - ) -> Iterable[AssetKeyPartitionKey]: - if self.latest_run_required_tags is None: - return asset_partitions - - will_update_asset_partitions: Set[AssetKeyPartitionKey] = set() - storage_ids_to_fetch_by_key: Dict[AssetKey, List[int]] = defaultdict(list) - - for asset_partition in asset_partitions: - if context.will_update_asset_partition(asset_partition): - will_update_asset_partitions.add(asset_partition) - else: - latest_storage_id = ( - context.instance_queryer.get_latest_materialization_or_observation_storage_id( - asset_partition=asset_partition - ) - ) - if latest_storage_id is not None: - storage_ids_to_fetch_by_key[asset_partition.asset_key].append(latest_storage_id) - - asset_partitions_by_latest_run_id: Dict[str, Set[AssetKeyPartitionKey]] = defaultdict(set) - - step = int(os.getenv("DAGSTER_ASSET_DAEMON_RUN_TAGS_EVENT_FETCH_LIMIT", "1000")) - - for asset_key, storage_ids_to_fetch in storage_ids_to_fetch_by_key.items(): - for i in range(0, len(storage_ids_to_fetch), step): - storage_ids = storage_ids_to_fetch[i : i + step] - fetch_records = ( - context.instance_queryer.instance.fetch_observations - if context.asset_graph.get(asset_key).is_observable - else context.instance_queryer.instance.fetch_materializations - ) - for record in fetch_records( - records_filter=AssetRecordsFilter( - asset_key=asset_key, - storage_ids=storage_ids, - ), - limit=step, - ).records: - asset_partitions_by_latest_run_id[record.run_id].add( - AssetKeyPartitionKey(asset_key, record.partition_key) - ) - - if len(asset_partitions_by_latest_run_id) > 0: - run_ids_with_required_tags = context.instance_queryer.instance.get_run_ids( - filters=RunsFilter( - run_ids=list(asset_partitions_by_latest_run_id.keys()), - tags=self.latest_run_required_tags, - ) - ) - else: - run_ids_with_required_tags = set() - - updated_partitions_with_required_tags = { - asset_partition - for run_id, run_id_asset_partitions in asset_partitions_by_latest_run_id.items() - if run_id in run_ids_with_required_tags - for asset_partition in run_id_asset_partitions - } - - if ( - self.latest_run_required_tags.items() - <= { - AUTO_MATERIALIZE_TAG: "true", - **context.daemon_context.auto_materialize_run_tags, - }.items() - ): - return will_update_asset_partitions | updated_partitions_with_required_tags - else: - return updated_partitions_with_required_tags - - def __hash__(self): - return hash(frozenset((self.latest_run_required_tags or {}).items())) - - -@whitelist_for_serdes -class MaterializeOnParentUpdatedRule( - AutoMaterializeRule, - NamedTuple( - "_MaterializeOnParentUpdatedRule", - [("updated_parent_filter", Optional[AutoMaterializeAssetPartitionsFilter])], - ), -): - def __new__(cls, updated_parent_filter: Optional[AutoMaterializeAssetPartitionsFilter] = None): - return super().__new__(cls, updated_parent_filter=updated_parent_filter) - - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.MATERIALIZE - - @property - def description(self) -> str: - base = "upstream data has changed since latest materialization" - if self.updated_parent_filter is not None: - return f"{base} and matches filter '{self.updated_parent_filter.description}'" - else: - return base - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - """Evaluates the set of asset partitions of this asset whose parents have been updated, - or will update on this tick. - """ - from .asset_condition.asset_condition import AssetConditionResult - - asset_partitions_by_updated_parents: Mapping[ - AssetKeyPartitionKey, Set[AssetKeyPartitionKey] - ] = defaultdict(set) - asset_partitions_by_will_update_parents: Mapping[ - AssetKeyPartitionKey, Set[AssetKeyPartitionKey] - ] = defaultdict(set) - - subset_to_evaluate = context.parent_has_or_will_update_subset - for asset_partition in subset_to_evaluate.asset_partitions: - parent_asset_partitions = context.asset_graph.get_parents_partitions( - dynamic_partitions_store=context.instance_queryer, - current_time=context.instance_queryer.evaluation_time, - asset_key=asset_partition.asset_key, - partition_key=asset_partition.partition_key, - ).parent_partitions - - updated_parent_asset_partitions = context.instance_queryer.get_parent_asset_partitions_updated_after_child( - asset_partition, - parent_asset_partitions, - # do a precise check for updated parents, factoring in data versions, as long as - # we're within reasonable limits on the number of partitions to check - respect_materialization_data_versions=context.daemon_context.respect_materialization_data_versions - and len(parent_asset_partitions) + subset_to_evaluate.size < 100, - # ignore self-dependencies when checking for updated parents, to avoid historical - # rematerializations from causing a chain of materializations to be kicked off - ignored_parent_keys={context.asset_key}, - ) - for parent in updated_parent_asset_partitions: - asset_partitions_by_updated_parents[parent].add(asset_partition) - - for parent in parent_asset_partitions: - if context.will_update_asset_partition(parent): - asset_partitions_by_will_update_parents[parent].add(asset_partition) - - updated_and_will_update_parents = ( - asset_partitions_by_updated_parents.keys() - | asset_partitions_by_will_update_parents.keys() - ) - filtered_updated_and_will_update_parents = ( - self.updated_parent_filter.passes(context, updated_and_will_update_parents) - if self.updated_parent_filter - else updated_and_will_update_parents - ) - - updated_parent_assets_by_asset_partition: Dict[AssetKeyPartitionKey, Set[AssetKey]] = ( - defaultdict(set) - ) - will_update_parent_assets_by_asset_partition: Dict[AssetKeyPartitionKey, Set[AssetKey]] = ( - defaultdict(set) - ) - - for updated_or_will_update_parent in filtered_updated_and_will_update_parents: - for child in asset_partitions_by_updated_parents.get(updated_or_will_update_parent, []): - updated_parent_assets_by_asset_partition[child].add( - updated_or_will_update_parent.asset_key - ) - - for child in asset_partitions_by_will_update_parents.get( - updated_or_will_update_parent, [] - ): - will_update_parent_assets_by_asset_partition[child].add( - updated_or_will_update_parent.asset_key - ) - - asset_partitions_by_evaluation_data = defaultdict(set) - for asset_partition in ( - updated_parent_assets_by_asset_partition.keys() - | will_update_parent_assets_by_asset_partition.keys() - ): - asset_partitions_by_evaluation_data[ - ParentUpdatedRuleEvaluationData( - updated_asset_keys=frozenset( - updated_parent_assets_by_asset_partition.get(asset_partition, []) - ), - will_update_asset_keys=frozenset( - will_update_parent_assets_by_asset_partition.get(asset_partition, []) - ), - ).frozen_metadata - ].add(asset_partition) - - true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( - asset_partitions_by_evaluation_data, - ignore_subset=context.materialized_requested_or_discarded_since_previous_tick_subset, - ) - return AssetConditionResult.create(context, true_subset, subsets_with_metadata) - - -@whitelist_for_serdes -class MaterializeOnMissingRule(AutoMaterializeRule, NamedTuple("_MaterializeOnMissingRule", [])): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.MATERIALIZE - - @property - def description(self) -> str: - return "materialization is missing" - - def get_handled_subset(self, context: "AssetConditionEvaluationContext") -> AssetSubset: - """Returns the AssetSubset which has been handled (materialized, requested, or discarded). - Accounts for cases in which the partitions definition may have changed between ticks. - """ - previous_handled_subset = ( - context.previous_evaluation_state.get_extra_state(context.condition, AssetSubset) - if context.previous_evaluation_state - else None - ) or context.instance_queryer.get_materialized_asset_subset(asset_key=context.asset_key) - - return ( - context.materialized_since_previous_tick_subset - | context.previous_tick_requested_subset - | previous_handled_subset - ) - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - """Evaluates the set of asset partitions for this asset which are missing and were not - previously discarded. - """ - from .asset_condition.asset_condition import AssetConditionResult - - if context.asset_key in context.asset_graph.root_executable_asset_keys: - handled_subset = self.get_handled_subset(context) - unhandled_candidates = ( - context.candidate_subset - & handled_subset.as_valid(context.partitions_def).inverse( - context.partitions_def, context.evaluation_time, context.instance_queryer - ) - if handled_subset.size > 0 - else context.candidate_subset - ) - else: - # to avoid causing potential perf issues, we are maintaing the previous behavior of - # only marking a non-root asset as missing if at least one of its parents has updated - # since the previous tick. - # on top of this, we also check the latest time partition of the asset to see if it's - # missing on the tick that it pops into existence - asset_partitions_to_evaluate = ( - context.candidate_parent_has_or_will_update_subset.asset_partitions - ) - if isinstance(context.partitions_def, TimeWindowPartitionsDefinition): - last_partition_key = context.partitions_def.get_last_partition_key( - current_time=context.evaluation_time - ) - previous_last_partition_key = context.partitions_def.get_last_partition_key( - current_time=datetime.datetime.fromtimestamp( - context.previous_evaluation_timestamp or 0, tz=datetime.timezone.utc - ) - ) - if last_partition_key != previous_last_partition_key: - asset_partitions_to_evaluate |= { - AssetKeyPartitionKey(context.asset_key, last_partition_key) - } - - handled_subset = None - unhandled_candidates = ( - AssetSubset.from_asset_partitions_set( - context.asset_key, - context.partitions_def, - { - ap - for ap in asset_partitions_to_evaluate - if not context.instance_queryer.asset_partition_has_materialization_or_observation( - ap - ) - }, - ) - | context.previous_true_subset - ) - context.previous_tick_requested_subset - - return AssetConditionResult.create( - context, - true_subset=unhandled_candidates, - # we keep track of the handled subset instead of the unhandled subset because new - # partitions may spontaneously jump into existence at any time - extra_state=handled_subset, - ) - - -@whitelist_for_serdes -class SkipOnParentOutdatedRule(AutoMaterializeRule, NamedTuple("_SkipOnParentOutdatedRule", [])): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.SKIP - - @property - def description(self) -> str: - return "waiting on upstream data to be up to date" - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - asset_partitions_by_evaluation_data = defaultdict(set) - - # only need to evaluate net-new candidates and candidates whose parents have changed - subset_to_evaluate = ( - context.candidates_not_evaluated_on_previous_tick_subset - | context.candidate_parent_has_or_will_update_subset - ) - for candidate in subset_to_evaluate.asset_partitions: - outdated_ancestors = set() - # find the root cause of why this asset partition's parents are outdated (if any) - for parent in context.get_parents_that_will_not_be_materialized_on_current_tick( - asset_partition=candidate - ): - if context.instance_queryer.have_ignorable_partition_mapping_for_outdated( - candidate.asset_key, parent.asset_key - ): - continue - outdated_ancestors.update( - context.instance_queryer.get_outdated_ancestors(asset_partition=parent) - ) - if outdated_ancestors: - asset_partitions_by_evaluation_data[ - WaitingOnAssetsRuleEvaluationData(frozenset(outdated_ancestors)).frozen_metadata - ].add(candidate) - - true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( - asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate - ) - return AssetConditionResult.create(context, true_subset, subsets_with_metadata) - - -@whitelist_for_serdes -class SkipOnParentMissingRule(AutoMaterializeRule, NamedTuple("_SkipOnParentMissingRule", [])): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.SKIP - - @property - def description(self) -> str: - return "waiting on upstream data to be present" - - def evaluate_for_asset( - self, - context: "AssetConditionEvaluationContext", - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - asset_partitions_by_evaluation_data = defaultdict(set) - - # only need to evaluate net-new candidates and candidates whose parents have changed - subset_to_evaluate = ( - context.candidates_not_evaluated_on_previous_tick_subset - | context.candidate_parent_has_or_will_update_subset - ) - for candidate in subset_to_evaluate.asset_partitions: - missing_parent_asset_keys = set() - for parent in context.get_parents_that_will_not_be_materialized_on_current_tick( - asset_partition=candidate - ): - # ignore missing or unexecutable assets, which will never have a materialization or - # observation - if not ( - context.asset_graph.has(parent.asset_key) - and context.asset_graph.get(parent.asset_key).is_executable - ): - continue - if not context.instance_queryer.asset_partition_has_materialization_or_observation( - parent - ): - missing_parent_asset_keys.add(parent.asset_key) - if missing_parent_asset_keys: - asset_partitions_by_evaluation_data[ - WaitingOnAssetsRuleEvaluationData( - frozenset(missing_parent_asset_keys) - ).frozen_metadata - ].add(candidate) - - true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( - asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate - ) - return AssetConditionResult.create(context, true_subset, subsets_with_metadata) - - -@whitelist_for_serdes -class SkipOnNotAllParentsUpdatedRule( - AutoMaterializeRule, - NamedTuple( - "_SkipOnNotAllParentsUpdatedRule", [("require_update_for_all_parent_partitions", bool)] - ), -): - """An auto-materialize rule that enforces that an asset can only be materialized if all parents - have been materialized since the asset's last materialization. - - Attributes: - require_update_for_all_parent_partitions (Optional[bool]): Applies only to an unpartitioned - asset or an asset partition that depends on more than one partition in any upstream asset. - If true, requires all upstream partitions in each upstream asset to be materialized since - the downstream asset's last materialization in order to update it. If false, requires at - least one upstream partition in each upstream asset to be materialized since the downstream - asset's last materialization in order to update it. Defaults to false. - """ - - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.SKIP - - @property - def description(self) -> str: - if self.require_update_for_all_parent_partitions is False: - return "waiting on upstream data to be updated" - else: - return "waiting until all upstream partitions are updated" - - def evaluate_for_asset( - self, - context: "AssetConditionEvaluationContext", - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - asset_partitions_by_evaluation_data = defaultdict(set) - - # only need to evaluate net-new candidates and candidates whose parents have changed - subset_to_evaluate = ( - context.candidates_not_evaluated_on_previous_tick_subset - | context.candidate_parent_has_or_will_update_subset - ) - for candidate in subset_to_evaluate.asset_partitions: - parent_partitions = context.asset_graph.get_parents_partitions( - context.instance_queryer, - context.instance_queryer.evaluation_time, - context.asset_key, - candidate.partition_key, - ).parent_partitions - - updated_parent_partitions = ( - context.instance_queryer.get_parent_asset_partitions_updated_after_child( - candidate, - parent_partitions, - context.daemon_context.respect_materialization_data_versions, - ignored_parent_keys=set(), - ) - | context.parent_will_update_subset.asset_partitions - ) - - if self.require_update_for_all_parent_partitions: - # All upstream partitions must be updated in order for the candidate to be updated - non_updated_parent_keys = { - parent.asset_key for parent in parent_partitions - updated_parent_partitions - } - else: - # At least one upstream partition in each upstream asset must be updated in order - # for the candidate to be updated - parent_asset_keys = context.asset_graph.get(context.asset_key).parent_keys - updated_parent_keys = {ap.asset_key for ap in updated_parent_partitions} - non_updated_parent_keys = parent_asset_keys - updated_parent_keys - - # do not require past partitions of this asset to be updated - non_updated_parent_keys -= {context.asset_key} - - if non_updated_parent_keys: - asset_partitions_by_evaluation_data[ - WaitingOnAssetsRuleEvaluationData( - frozenset(non_updated_parent_keys) - ).frozen_metadata - ].add(candidate) - - true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( - asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate - ) - return AssetConditionResult.create(context, true_subset, subsets_with_metadata) - - -@whitelist_for_serdes -class SkipOnNotAllParentsUpdatedSinceCronRule( - AutoMaterializeRule, - NamedTuple( - "_SkipOnNotAllParentsUpdatedSinceCronRule", - [("cron_schedule", str), ("timezone", str)], - ), -): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.SKIP - - @property - def description(self) -> str: - return f"waiting until all upstream assets have updated since the last cron schedule tick of '{self.cron_schedule}' (timezone: {self.timezone})" - - def passed_time_window(self, context: "AssetConditionEvaluationContext") -> TimeWindow: - """Returns the window of time that has passed between the previous two cron ticks. All - parent assets must contain all data from this time window in order for this asset to be - materialized. - """ - previous_ticks = reverse_cron_string_iterator( - end_timestamp=context.evaluation_time.timestamp(), - cron_string=self.cron_schedule, - execution_timezone=self.timezone, - ) - end_time = next(previous_ticks) - start_time = next(previous_ticks) - - return TimeWindow(start=start_time, end=end_time) - - def get_parent_subset_updated_since_cron( - self, - context: "AssetConditionEvaluationContext", - parent_asset_key: AssetKey, - passed_time_window: TimeWindow, - ) -> ValidAssetSubset: - """Returns the AssetSubset of a given parent asset that has been updated since the end of - the previous cron tick. If a value for this parent asset was computed on the previous - evaluation, and that evaluation happened within the same cron tick as the current evaluation, - then this value will be calculated incrementally from the previous value to avoid expensive - queries. - """ - if ( - # first tick of evaluating this condition - context.previous_evaluation_state is None - or context.previous_evaluation_timestamp is None - # This additional check is neccessary as it is possible for this cursor to be None - # even if the previous state is not None in the case that this asset and none of its - # parents have been detected as materialized at any point. While in theory this should - # not cause issues, in past versions we were not properly capturing materializations - # of external assets, causing this detection to be faulty. This ensures that we can - # properly re-calculate this value even in the case that we've incorrectly considered - # a parent as unmaterialized in the past. - or context.previous_max_storage_id is None - # new cron tick has happened since the previous tick - or passed_time_window.end.timestamp() > context.previous_evaluation_timestamp - ): - return context.instance_queryer.get_asset_subset_updated_after_time( - asset_key=parent_asset_key, after_time=passed_time_window.end - ) - else: - # previous state still valid - previous_parent_subsets = ( - context.previous_evaluation_state.get_extra_state(context.condition, list) or [] - ) - previous_parent_subset = next( - (s for s in previous_parent_subsets if s.asset_key == parent_asset_key), - context.empty_subset(), - ) - - # the set of asset partitions that have been updated since the previous evaluation - new_parent_subset = context.instance_queryer.get_asset_subset_updated_after_cursor( - asset_key=parent_asset_key, after_cursor=context.previous_max_storage_id - ) - return new_parent_subset | previous_parent_subset - - def get_parent_subsets_updated_since_cron_by_key( - self, context: "AssetConditionEvaluationContext", passed_time_window: TimeWindow - ) -> Mapping[AssetKey, ValidAssetSubset]: - """Returns a mapping of parent asset keys to the AssetSubset of each parent that has been - updated since the end of the previous cron tick. Does not compute this value for time-window - partitioned parents, as their partitions encode the time windows they have processed. - """ - updated_subsets_by_key = {} - for parent_asset_key in context.asset_graph.get(context.asset_key).parent_keys: - # no need to incrementally calculate updated time-window partitions definitions, as - # their partitions encode the time windows they have processed. - if isinstance( - context.asset_graph.get(parent_asset_key).partitions_def, - TimeWindowPartitionsDefinition, - ): - continue - updated_subsets_by_key[parent_asset_key] = self.get_parent_subset_updated_since_cron( - context, parent_asset_key, passed_time_window - ) - return updated_subsets_by_key - - def parent_updated_since_cron( - self, - context: "AssetConditionEvaluationContext", - passed_time_window: TimeWindow, - parent_asset_key: AssetKey, - child_asset_partition: AssetKeyPartitionKey, - updated_parent_subset: ValidAssetSubset, - ) -> bool: - """Returns if, for a given child asset partition, the given parent asset been updated with - information from the required time window. - """ - parent_partitions_def = context.asset_graph.get(parent_asset_key).partitions_def - - if isinstance(parent_partitions_def, TimeWindowPartitionsDefinition): - # for time window partitions definitions, we simply assert that all time partitions that - # were newly created between the previous cron ticks have been materialized - required_parent_partitions = parent_partitions_def.get_partition_keys_in_time_window( - time_window=passed_time_window - ) - - # for time window partitions definitions, we simply assert that all time partitions that - return all( - AssetKeyPartitionKey(parent_asset_key, partition_key) - in context.instance_queryer.get_materialized_asset_subset( - asset_key=parent_asset_key - ) - for partition_key in required_parent_partitions - ) - # for all other partitions definitions, we assert that all parent partition keys have - # been materialized since the previous cron tick - else: - if parent_partitions_def is None: - non_updated_parent_asset_partitions = updated_parent_subset.inverse( - parent_partitions_def - ).asset_partitions - else: - parent_subset = context.asset_graph.get_parent_partition_keys_for_child( - child_asset_partition.partition_key, - parent_asset_key, - child_asset_partition.asset_key, - context.instance_queryer, - context.evaluation_time, - ).partitions_subset - - non_updated_parent_asset_partitions = ( - ValidAssetSubset(asset_key=parent_asset_key, value=parent_subset) - - updated_parent_subset - ).asset_partitions - - return not any( - not context.will_update_asset_partition(p) - for p in non_updated_parent_asset_partitions - ) - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - passed_time_window = self.passed_time_window(context) - has_new_passed_time_window = passed_time_window.end.timestamp() > ( - context.previous_evaluation_timestamp or 0 - ) - updated_subsets_by_key = self.get_parent_subsets_updated_since_cron_by_key( - context, passed_time_window - ) - - # only need to evaluate net-new candidates and candidates whose parents have updated, unless - # this is the first tick after a new cron schedule tick - subset_to_evaluate = ( - ( - context.candidates_not_evaluated_on_previous_tick_subset - | context.candidate_parent_has_or_will_update_subset - ) - if not has_new_passed_time_window - else context.candidate_subset - ) - - # the set of candidates for whom all parents have been updated since the previous cron tick - all_parents_updated_subset = AssetSubset.from_asset_partitions_set( - context.asset_key, - context.partitions_def, - { - candidate - for candidate in subset_to_evaluate.asset_partitions - if all( - self.parent_updated_since_cron( - context, - passed_time_window, - parent_asset_key, - candidate, - updated_subsets_by_key.get(parent_asset_key, context.empty_subset()), - ) - for parent_asset_key in context.asset_graph.get(candidate.asset_key).parent_keys - ) - }, - ) - # if your parents were all updated since the previous cron tick on the previous evaluation, - # that will still be true unless a new cron tick has happened since the previous evaluation - if not has_new_passed_time_window: - all_parents_updated_subset = ( - context.previous_candidate_subset.as_valid(context.partitions_def) - - context.previous_true_subset - ) | all_parents_updated_subset - - return AssetConditionResult.create( - context, - true_subset=context.candidate_subset - all_parents_updated_subset, - extra_state=list(updated_subsets_by_key.values()), - ) - - -@whitelist_for_serdes -class SkipOnRequiredButNonexistentParentsRule( - AutoMaterializeRule, NamedTuple("_SkipOnRequiredButNonexistentParentsRule", []) -): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.SKIP - - @property - def description(self) -> str: - return "required parent partitions do not exist" - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - asset_partitions_by_evaluation_data = defaultdict(set) - - subset_to_evaluate = ( - context.candidates_not_evaluated_on_previous_tick_subset - | context.candidate_parent_has_or_will_update_subset - ) - for candidate in subset_to_evaluate.asset_partitions: - nonexistent_parent_partitions = context.asset_graph.get_parents_partitions( - context.instance_queryer, - context.instance_queryer.evaluation_time, - candidate.asset_key, - candidate.partition_key, - ).required_but_nonexistent_parents_partitions - - nonexistent_parent_keys = {parent.asset_key for parent in nonexistent_parent_partitions} - if nonexistent_parent_keys: - asset_partitions_by_evaluation_data[ - WaitingOnAssetsRuleEvaluationData( - frozenset(nonexistent_parent_keys) - ).frozen_metadata - ].add(candidate) - - true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( - asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate - ) - return AssetConditionResult.create(context, true_subset, subsets_with_metadata) - - -@whitelist_for_serdes -class SkipOnBackfillInProgressRule( - AutoMaterializeRule, - NamedTuple("_SkipOnBackfillInProgressRule", [("all_partitions", bool)]), -): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.SKIP - - @property - def description(self) -> str: - if self.all_partitions: - return "part of an asset targeted by an in-progress backfill" - else: - return "targeted by an in-progress backfill" - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - backfilling_subset = ( - # this backfilling subset is aware of the current partitions definitions, and so will - # be valid - (context.instance_queryer.get_active_backfill_target_asset_graph_subset()) - .get_asset_subset(context.asset_key, context.asset_graph) - .as_valid(context.partitions_def) - ) - - if backfilling_subset.size == 0: - true_subset = context.empty_subset() - elif self.all_partitions: - true_subset = context.candidate_subset - else: - true_subset = context.candidate_subset & backfilling_subset - - return AssetConditionResult.create(context, true_subset) - - -@whitelist_for_serdes -class DiscardOnMaxMaterializationsExceededRule( - AutoMaterializeRule, NamedTuple("_DiscardOnMaxMaterializationsExceededRule", [("limit", int)]) -): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.DISCARD - - @property - def description(self) -> str: - return f"exceeds {self.limit} materialization(s) per minute" - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - # the set of asset partitions which exceed the limit - rate_limited_asset_partitions = set( - sorted( - context.candidate_subset.asset_partitions, - key=lambda x: sort_key_for_asset_partition(context.asset_graph, x), - )[self.limit :] - ) - - return AssetConditionResult.create( - context, - AssetSubset.from_asset_partitions_set( - context.asset_key, context.partitions_def, rate_limited_asset_partitions - ), - ) - - -@whitelist_for_serdes -class SkipOnRunInProgressRule(AutoMaterializeRule, NamedTuple("_SkipOnRunInProgressRule", [])): - @property - def decision_type(self) -> AutoMaterializeDecisionType: - return AutoMaterializeDecisionType.SKIP - - @property - def description(self) -> str: - return "in-progress run for asset" - - def evaluate_for_asset( - self, context: "AssetConditionEvaluationContext" - ) -> "AssetConditionResult": - from .asset_condition.asset_condition import AssetConditionResult - - if context.partitions_def is not None: - raise DagsterInvariantViolationError( - "SkipOnRunInProgressRule is currently only support for non-partitioned assets." - ) - instance = context.instance_queryer.instance - planned_materialization_info = ( - instance.event_log_storage.get_latest_planned_materialization_info(context.asset_key) - ) - if planned_materialization_info: - dagster_run = instance.get_run_by_id(planned_materialization_info.run_id) - if dagster_run and dagster_run.status in IN_PROGRESS_RUN_STATUSES: - return AssetConditionResult.create(context, context.candidate_subset) - return AssetConditionResult.create(context, context.empty_subset()) diff --git a/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_evaluation.py b/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_evaluation.py index 4418f3a87c10d..108cab9e2d0d7 100644 --- a/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_evaluation.py +++ b/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_evaluation.py @@ -473,10 +473,8 @@ def unpack( whitelist_map: WhitelistMap, context: UnpackContext, ) -> AutoMaterializeRuleEvaluation: - from .auto_materialize_rule import ( - AutoMaterializeRule, - DiscardOnMaxMaterializationsExceededRule, - ) + from .auto_materialize_rule import AutoMaterializeRule + from .auto_materialize_rule_impls import DiscardOnMaxMaterializationsExceededRule if self.klass in ( FreshnessAutoMaterializeCondition, diff --git a/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_impls.py b/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_impls.py new file mode 100644 index 0000000000000..82c65fd57016d --- /dev/null +++ b/python_modules/dagster/dagster/_core/definitions/auto_materialize_rule_impls.py @@ -0,0 +1,1065 @@ +import datetime +import os +from collections import defaultdict +from typing import ( + TYPE_CHECKING, + AbstractSet, + Dict, + Iterable, + List, + Mapping, + NamedTuple, + Optional, + Sequence, + Set, +) + +from dagster._annotations import deprecated, experimental +from dagster._core.definitions.asset_subset import AssetSubset, ValidAssetSubset +from dagster._core.definitions.auto_materialize_rule import AutoMaterializeRule +from dagster._core.definitions.auto_materialize_rule_evaluation import ( + AutoMaterializeDecisionType, + ParentUpdatedRuleEvaluationData, + WaitingOnAssetsRuleEvaluationData, +) +from dagster._core.definitions.events import AssetKey, AssetKeyPartitionKey +from dagster._core.definitions.freshness_based_auto_materialize import ( + freshness_evaluation_results_for_asset_key, +) +from dagster._core.definitions.multi_dimensional_partitions import MultiPartitionsDefinition +from dagster._core.definitions.time_window_partitions import ( + TimeWindow, + TimeWindowPartitionsDefinition, + get_time_partitions_def, +) +from dagster._core.errors import DagsterInvariantViolationError +from dagster._core.event_api import AssetRecordsFilter +from dagster._core.storage.dagster_run import IN_PROGRESS_RUN_STATUSES, RunsFilter +from dagster._core.storage.tags import AUTO_MATERIALIZE_TAG +from dagster._serdes.serdes import ( + whitelist_for_serdes, +) +from dagster._utils.schedules import ( + cron_string_iterator, + reverse_cron_string_iterator, +) + +from .base_asset_graph import sort_key_for_asset_partition + +if TYPE_CHECKING: + from dagster._core.definitions.asset_condition.asset_condition import ( + AssetConditionResult, + ) + + from .asset_condition.asset_condition_evaluation_context import AssetConditionEvaluationContext + + +@deprecated( + breaking_version="1.8", + additional_warn_text="Lazy auto-materialize is deprecated, in favor of explicit cron-based " + "scheduling rules. Additional alternatives to replicate more of the lazy auto-materialize " + "behavior will be provided before this is fully removed.", +) +@whitelist_for_serdes +class MaterializeOnRequiredForFreshnessRule( + AutoMaterializeRule, NamedTuple("_MaterializeOnRequiredForFreshnessRule", []) +): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.MATERIALIZE + + @property + def description(self) -> str: + return "required to meet this or downstream asset's freshness policy" + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + true_subset, subsets_with_metadata = freshness_evaluation_results_for_asset_key( + context.root_context + ) + return AssetConditionResult.create(context, true_subset, subsets_with_metadata) + + +@whitelist_for_serdes +class MaterializeOnCronRule( + AutoMaterializeRule, + NamedTuple( + "_MaterializeOnCronRule", + [("cron_schedule", str), ("timezone", str), ("all_partitions", bool)], + ), +): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.MATERIALIZE + + @property + def description(self) -> str: + return f"not materialized since last cron schedule tick of '{self.cron_schedule}' (timezone: {self.timezone})" + + def missed_cron_ticks( + self, context: "AssetConditionEvaluationContext" + ) -> Sequence[datetime.datetime]: + """Returns the cron ticks which have been missed since the previous cursor was generated.""" + # if it's the first time evaluating this rule, then just count the latest tick as missed + if not context.previous_evaluation or not context.previous_evaluation_timestamp: + previous_dt = next( + reverse_cron_string_iterator( + end_timestamp=context.evaluation_time.timestamp(), + cron_string=self.cron_schedule, + execution_timezone=self.timezone, + ) + ) + return [previous_dt] + missed_ticks = [] + for dt in cron_string_iterator( + start_timestamp=context.previous_evaluation_timestamp, + cron_string=self.cron_schedule, + execution_timezone=self.timezone, + ): + if dt > context.evaluation_time: + break + missed_ticks.append(dt) + return missed_ticks + + def get_new_candidate_asset_partitions( + self, context: "AssetConditionEvaluationContext", missed_ticks: Sequence[datetime.datetime] + ) -> AbstractSet[AssetKeyPartitionKey]: + if not missed_ticks: + return set() + + partitions_def = context.partitions_def + if partitions_def is None: + return {AssetKeyPartitionKey(context.asset_key)} + + # if all_partitions is set, then just return all partitions if any ticks have been missed + if self.all_partitions: + return { + AssetKeyPartitionKey(context.asset_key, partition_key) + for partition_key in partitions_def.get_partition_keys( + current_time=context.evaluation_time, + dynamic_partitions_store=context.instance_queryer, + ) + } + + # for partitions_defs without a time component, just return the last partition if any ticks + # have been missed + time_partitions_def = get_time_partitions_def(partitions_def) + if time_partitions_def is None: + return { + AssetKeyPartitionKey( + context.asset_key, + partitions_def.get_last_partition_key( + dynamic_partitions_store=context.instance_queryer + ), + ) + } + + missed_time_partition_keys = filter( + None, + [ + time_partitions_def.get_last_partition_key( + current_time=missed_tick, + dynamic_partitions_store=context.instance_queryer, + ) + for missed_tick in missed_ticks + ], + ) + # for multi partitions definitions, request to materialize all partitions for each missed + # cron schedule tick + if isinstance(partitions_def, MultiPartitionsDefinition): + return { + AssetKeyPartitionKey(context.asset_key, partition_key) + for time_partition_key in missed_time_partition_keys + for partition_key in partitions_def.get_multipartition_keys_with_dimension_value( + partitions_def.time_window_dimension.name, + time_partition_key, + dynamic_partitions_store=context.instance_queryer, + ) + } + else: + return { + AssetKeyPartitionKey(context.asset_key, time_partition_key) + for time_partition_key in missed_time_partition_keys + } + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + missed_ticks = self.missed_cron_ticks(context) + new_asset_partitions = self.get_new_candidate_asset_partitions(context, missed_ticks) + + # if it's the first time evaluating this rule, must query for the actual subset that has + # been materialized since the previous cron tick, as materializations may have happened + # before the previous evaluation, which + # `context.materialized_requested_or_discarded_since_previous_tick_subset` would not capture + if context.previous_evaluation is None: + new_asset_partitions -= context.instance_queryer.get_asset_subset_updated_after_time( + asset_key=context.asset_key, after_time=missed_ticks[-1] + ).asset_partitions + + asset_subset_to_request = AssetSubset.from_asset_partitions_set( + context.asset_key, context.partitions_def, new_asset_partitions + ) | ( + context.previous_true_subset.as_valid(context.partitions_def) + - context.materialized_requested_or_discarded_since_previous_tick_subset + ) + + return AssetConditionResult.create(context, true_subset=asset_subset_to_request) + + +@whitelist_for_serdes +@experimental +class AutoMaterializeAssetPartitionsFilter( + NamedTuple( + "_AutoMaterializeAssetPartitionsFilter", + [("latest_run_required_tags", Optional[Mapping[str, str]])], + ) +): + """A filter that can be applied to an asset partition, during auto-materialize evaluation, and + returns a boolean for whether it passes. + + Attributes: + latest_run_required_tags (Optional[Sequence[str]]): `passes` returns + True if the run responsible for the latest materialization of the asset partition + has all of these tags. + """ + + @property + def description(self) -> str: + return f"latest run includes required tags: {self.latest_run_required_tags}" + + def passes( + self, + context: "AssetConditionEvaluationContext", + asset_partitions: Iterable[AssetKeyPartitionKey], + ) -> Iterable[AssetKeyPartitionKey]: + if self.latest_run_required_tags is None: + return asset_partitions + + will_update_asset_partitions: Set[AssetKeyPartitionKey] = set() + storage_ids_to_fetch_by_key: Dict[AssetKey, List[int]] = defaultdict(list) + + for asset_partition in asset_partitions: + if context.will_update_asset_partition(asset_partition): + will_update_asset_partitions.add(asset_partition) + else: + latest_storage_id = ( + context.instance_queryer.get_latest_materialization_or_observation_storage_id( + asset_partition=asset_partition + ) + ) + if latest_storage_id is not None: + storage_ids_to_fetch_by_key[asset_partition.asset_key].append(latest_storage_id) + + asset_partitions_by_latest_run_id: Dict[str, Set[AssetKeyPartitionKey]] = defaultdict(set) + + step = int(os.getenv("DAGSTER_ASSET_DAEMON_RUN_TAGS_EVENT_FETCH_LIMIT", "1000")) + + for asset_key, storage_ids_to_fetch in storage_ids_to_fetch_by_key.items(): + for i in range(0, len(storage_ids_to_fetch), step): + storage_ids = storage_ids_to_fetch[i : i + step] + fetch_records = ( + context.instance_queryer.instance.fetch_observations + if context.asset_graph.get(asset_key).is_observable + else context.instance_queryer.instance.fetch_materializations + ) + for record in fetch_records( + records_filter=AssetRecordsFilter( + asset_key=asset_key, + storage_ids=storage_ids, + ), + limit=step, + ).records: + asset_partitions_by_latest_run_id[record.run_id].add( + AssetKeyPartitionKey(asset_key, record.partition_key) + ) + + if len(asset_partitions_by_latest_run_id) > 0: + run_ids_with_required_tags = context.instance_queryer.instance.get_run_ids( + filters=RunsFilter( + run_ids=list(asset_partitions_by_latest_run_id.keys()), + tags=self.latest_run_required_tags, + ) + ) + else: + run_ids_with_required_tags = set() + + updated_partitions_with_required_tags = { + asset_partition + for run_id, run_id_asset_partitions in asset_partitions_by_latest_run_id.items() + if run_id in run_ids_with_required_tags + for asset_partition in run_id_asset_partitions + } + + if ( + self.latest_run_required_tags.items() + <= { + AUTO_MATERIALIZE_TAG: "true", + **context.daemon_context.auto_materialize_run_tags, + }.items() + ): + return will_update_asset_partitions | updated_partitions_with_required_tags + else: + return updated_partitions_with_required_tags + + def __hash__(self): + return hash(frozenset((self.latest_run_required_tags or {}).items())) + + +@whitelist_for_serdes +class MaterializeOnParentUpdatedRule( + AutoMaterializeRule, + NamedTuple( + "_MaterializeOnParentUpdatedRule", + [("updated_parent_filter", Optional[AutoMaterializeAssetPartitionsFilter])], + ), +): + def __new__(cls, updated_parent_filter: Optional[AutoMaterializeAssetPartitionsFilter] = None): + return super().__new__(cls, updated_parent_filter=updated_parent_filter) + + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.MATERIALIZE + + @property + def description(self) -> str: + base = "upstream data has changed since latest materialization" + if self.updated_parent_filter is not None: + return f"{base} and matches filter '{self.updated_parent_filter.description}'" + else: + return base + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + """Evaluates the set of asset partitions of this asset whose parents have been updated, + or will update on this tick. + """ + from .asset_condition.asset_condition import AssetConditionResult + + asset_partitions_by_updated_parents: Mapping[ + AssetKeyPartitionKey, Set[AssetKeyPartitionKey] + ] = defaultdict(set) + asset_partitions_by_will_update_parents: Mapping[ + AssetKeyPartitionKey, Set[AssetKeyPartitionKey] + ] = defaultdict(set) + + subset_to_evaluate = context.parent_has_or_will_update_subset + for asset_partition in subset_to_evaluate.asset_partitions: + parent_asset_partitions = context.asset_graph.get_parents_partitions( + dynamic_partitions_store=context.instance_queryer, + current_time=context.instance_queryer.evaluation_time, + asset_key=asset_partition.asset_key, + partition_key=asset_partition.partition_key, + ).parent_partitions + + updated_parent_asset_partitions = context.instance_queryer.get_parent_asset_partitions_updated_after_child( + asset_partition, + parent_asset_partitions, + # do a precise check for updated parents, factoring in data versions, as long as + # we're within reasonable limits on the number of partitions to check + respect_materialization_data_versions=context.daemon_context.respect_materialization_data_versions + and len(parent_asset_partitions) + subset_to_evaluate.size < 100, + # ignore self-dependencies when checking for updated parents, to avoid historical + # rematerializations from causing a chain of materializations to be kicked off + ignored_parent_keys={context.asset_key}, + ) + for parent in updated_parent_asset_partitions: + asset_partitions_by_updated_parents[parent].add(asset_partition) + + for parent in parent_asset_partitions: + if context.will_update_asset_partition(parent): + asset_partitions_by_will_update_parents[parent].add(asset_partition) + + updated_and_will_update_parents = ( + asset_partitions_by_updated_parents.keys() + | asset_partitions_by_will_update_parents.keys() + ) + filtered_updated_and_will_update_parents = ( + self.updated_parent_filter.passes(context, updated_and_will_update_parents) + if self.updated_parent_filter + else updated_and_will_update_parents + ) + + updated_parent_assets_by_asset_partition: Dict[AssetKeyPartitionKey, Set[AssetKey]] = ( + defaultdict(set) + ) + will_update_parent_assets_by_asset_partition: Dict[AssetKeyPartitionKey, Set[AssetKey]] = ( + defaultdict(set) + ) + + for updated_or_will_update_parent in filtered_updated_and_will_update_parents: + for child in asset_partitions_by_updated_parents.get(updated_or_will_update_parent, []): + updated_parent_assets_by_asset_partition[child].add( + updated_or_will_update_parent.asset_key + ) + + for child in asset_partitions_by_will_update_parents.get( + updated_or_will_update_parent, [] + ): + will_update_parent_assets_by_asset_partition[child].add( + updated_or_will_update_parent.asset_key + ) + + asset_partitions_by_evaluation_data = defaultdict(set) + for asset_partition in ( + updated_parent_assets_by_asset_partition.keys() + | will_update_parent_assets_by_asset_partition.keys() + ): + asset_partitions_by_evaluation_data[ + ParentUpdatedRuleEvaluationData( + updated_asset_keys=frozenset( + updated_parent_assets_by_asset_partition.get(asset_partition, []) + ), + will_update_asset_keys=frozenset( + will_update_parent_assets_by_asset_partition.get(asset_partition, []) + ), + ).frozen_metadata + ].add(asset_partition) + + true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( + asset_partitions_by_evaluation_data, + ignore_subset=context.materialized_requested_or_discarded_since_previous_tick_subset, + ) + return AssetConditionResult.create(context, true_subset, subsets_with_metadata) + + +@whitelist_for_serdes +class MaterializeOnMissingRule(AutoMaterializeRule, NamedTuple("_MaterializeOnMissingRule", [])): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.MATERIALIZE + + @property + def description(self) -> str: + return "materialization is missing" + + def get_handled_subset(self, context: "AssetConditionEvaluationContext") -> AssetSubset: + """Returns the AssetSubset which has been handled (materialized, requested, or discarded). + Accounts for cases in which the partitions definition may have changed between ticks. + """ + previous_handled_subset = ( + context.previous_evaluation_state.get_extra_state(context.condition, AssetSubset) + if context.previous_evaluation_state + else None + ) or context.instance_queryer.get_materialized_asset_subset(asset_key=context.asset_key) + + return ( + context.materialized_since_previous_tick_subset + | context.previous_tick_requested_subset + | previous_handled_subset + ) + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + """Evaluates the set of asset partitions for this asset which are missing and were not + previously discarded. + """ + from .asset_condition.asset_condition import AssetConditionResult + + if context.asset_key in context.asset_graph.root_executable_asset_keys: + handled_subset = self.get_handled_subset(context) + unhandled_candidates = ( + context.candidate_subset + & handled_subset.as_valid(context.partitions_def).inverse( + context.partitions_def, context.evaluation_time, context.instance_queryer + ) + if handled_subset.size > 0 + else context.candidate_subset + ) + else: + # to avoid causing potential perf issues, we are maintaing the previous behavior of + # only marking a non-root asset as missing if at least one of its parents has updated + # since the previous tick. + # on top of this, we also check the latest time partition of the asset to see if it's + # missing on the tick that it pops into existence + asset_partitions_to_evaluate = ( + context.candidate_parent_has_or_will_update_subset.asset_partitions + ) + if isinstance(context.partitions_def, TimeWindowPartitionsDefinition): + last_partition_key = context.partitions_def.get_last_partition_key( + current_time=context.evaluation_time + ) + previous_last_partition_key = context.partitions_def.get_last_partition_key( + current_time=datetime.datetime.fromtimestamp( + context.previous_evaluation_timestamp or 0, tz=datetime.timezone.utc + ) + ) + if last_partition_key != previous_last_partition_key: + asset_partitions_to_evaluate |= { + AssetKeyPartitionKey(context.asset_key, last_partition_key) + } + + handled_subset = None + unhandled_candidates = ( + AssetSubset.from_asset_partitions_set( + context.asset_key, + context.partitions_def, + { + ap + for ap in asset_partitions_to_evaluate + if not context.instance_queryer.asset_partition_has_materialization_or_observation( + ap + ) + }, + ) + | context.previous_true_subset + ) - context.previous_tick_requested_subset + + return AssetConditionResult.create( + context, + true_subset=unhandled_candidates, + # we keep track of the handled subset instead of the unhandled subset because new + # partitions may spontaneously jump into existence at any time + extra_state=handled_subset, + ) + + +@whitelist_for_serdes +class SkipOnParentOutdatedRule(AutoMaterializeRule, NamedTuple("_SkipOnParentOutdatedRule", [])): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.SKIP + + @property + def description(self) -> str: + return "waiting on upstream data to be up to date" + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + asset_partitions_by_evaluation_data = defaultdict(set) + + # only need to evaluate net-new candidates and candidates whose parents have changed + subset_to_evaluate = ( + context.candidates_not_evaluated_on_previous_tick_subset + | context.candidate_parent_has_or_will_update_subset + ) + for candidate in subset_to_evaluate.asset_partitions: + outdated_ancestors = set() + # find the root cause of why this asset partition's parents are outdated (if any) + for parent in context.get_parents_that_will_not_be_materialized_on_current_tick( + asset_partition=candidate + ): + if context.instance_queryer.have_ignorable_partition_mapping_for_outdated( + candidate.asset_key, parent.asset_key + ): + continue + outdated_ancestors.update( + context.instance_queryer.get_outdated_ancestors(asset_partition=parent) + ) + if outdated_ancestors: + asset_partitions_by_evaluation_data[ + WaitingOnAssetsRuleEvaluationData(frozenset(outdated_ancestors)).frozen_metadata + ].add(candidate) + + true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( + asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate + ) + return AssetConditionResult.create(context, true_subset, subsets_with_metadata) + + +@whitelist_for_serdes +class SkipOnParentMissingRule(AutoMaterializeRule, NamedTuple("_SkipOnParentMissingRule", [])): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.SKIP + + @property + def description(self) -> str: + return "waiting on upstream data to be present" + + def evaluate_for_asset( + self, + context: "AssetConditionEvaluationContext", + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + asset_partitions_by_evaluation_data = defaultdict(set) + + # only need to evaluate net-new candidates and candidates whose parents have changed + subset_to_evaluate = ( + context.candidates_not_evaluated_on_previous_tick_subset + | context.candidate_parent_has_or_will_update_subset + ) + for candidate in subset_to_evaluate.asset_partitions: + missing_parent_asset_keys = set() + for parent in context.get_parents_that_will_not_be_materialized_on_current_tick( + asset_partition=candidate + ): + # ignore missing or unexecutable assets, which will never have a materialization or + # observation + if not ( + context.asset_graph.has(parent.asset_key) + and context.asset_graph.get(parent.asset_key).is_executable + ): + continue + if not context.instance_queryer.asset_partition_has_materialization_or_observation( + parent + ): + missing_parent_asset_keys.add(parent.asset_key) + if missing_parent_asset_keys: + asset_partitions_by_evaluation_data[ + WaitingOnAssetsRuleEvaluationData( + frozenset(missing_parent_asset_keys) + ).frozen_metadata + ].add(candidate) + + true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( + asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate + ) + return AssetConditionResult.create(context, true_subset, subsets_with_metadata) + + +@whitelist_for_serdes +class SkipOnNotAllParentsUpdatedRule( + AutoMaterializeRule, + NamedTuple( + "_SkipOnNotAllParentsUpdatedRule", [("require_update_for_all_parent_partitions", bool)] + ), +): + """An auto-materialize rule that enforces that an asset can only be materialized if all parents + have been materialized since the asset's last materialization. + + Attributes: + require_update_for_all_parent_partitions (Optional[bool]): Applies only to an unpartitioned + asset or an asset partition that depends on more than one partition in any upstream asset. + If true, requires all upstream partitions in each upstream asset to be materialized since + the downstream asset's last materialization in order to update it. If false, requires at + least one upstream partition in each upstream asset to be materialized since the downstream + asset's last materialization in order to update it. Defaults to false. + """ + + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.SKIP + + @property + def description(self) -> str: + if self.require_update_for_all_parent_partitions is False: + return "waiting on upstream data to be updated" + else: + return "waiting until all upstream partitions are updated" + + def evaluate_for_asset( + self, + context: "AssetConditionEvaluationContext", + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + asset_partitions_by_evaluation_data = defaultdict(set) + + # only need to evaluate net-new candidates and candidates whose parents have changed + subset_to_evaluate = ( + context.candidates_not_evaluated_on_previous_tick_subset + | context.candidate_parent_has_or_will_update_subset + ) + for candidate in subset_to_evaluate.asset_partitions: + parent_partitions = context.asset_graph.get_parents_partitions( + context.instance_queryer, + context.instance_queryer.evaluation_time, + context.asset_key, + candidate.partition_key, + ).parent_partitions + + updated_parent_partitions = ( + context.instance_queryer.get_parent_asset_partitions_updated_after_child( + candidate, + parent_partitions, + context.daemon_context.respect_materialization_data_versions, + ignored_parent_keys=set(), + ) + | context.parent_will_update_subset.asset_partitions + ) + + if self.require_update_for_all_parent_partitions: + # All upstream partitions must be updated in order for the candidate to be updated + non_updated_parent_keys = { + parent.asset_key for parent in parent_partitions - updated_parent_partitions + } + else: + # At least one upstream partition in each upstream asset must be updated in order + # for the candidate to be updated + parent_asset_keys = context.asset_graph.get(context.asset_key).parent_keys + updated_parent_keys = {ap.asset_key for ap in updated_parent_partitions} + non_updated_parent_keys = parent_asset_keys - updated_parent_keys + + # do not require past partitions of this asset to be updated + non_updated_parent_keys -= {context.asset_key} + + if non_updated_parent_keys: + asset_partitions_by_evaluation_data[ + WaitingOnAssetsRuleEvaluationData( + frozenset(non_updated_parent_keys) + ).frozen_metadata + ].add(candidate) + + true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( + asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate + ) + return AssetConditionResult.create(context, true_subset, subsets_with_metadata) + + +@whitelist_for_serdes +class SkipOnNotAllParentsUpdatedSinceCronRule( + AutoMaterializeRule, + NamedTuple( + "_SkipOnNotAllParentsUpdatedSinceCronRule", + [("cron_schedule", str), ("timezone", str)], + ), +): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.SKIP + + @property + def description(self) -> str: + return f"waiting until all upstream assets have updated since the last cron schedule tick of '{self.cron_schedule}' (timezone: {self.timezone})" + + def passed_time_window(self, context: "AssetConditionEvaluationContext") -> TimeWindow: + """Returns the window of time that has passed between the previous two cron ticks. All + parent assets must contain all data from this time window in order for this asset to be + materialized. + """ + previous_ticks = reverse_cron_string_iterator( + end_timestamp=context.evaluation_time.timestamp(), + cron_string=self.cron_schedule, + execution_timezone=self.timezone, + ) + end_time = next(previous_ticks) + start_time = next(previous_ticks) + + return TimeWindow(start=start_time, end=end_time) + + def get_parent_subset_updated_since_cron( + self, + context: "AssetConditionEvaluationContext", + parent_asset_key: AssetKey, + passed_time_window: TimeWindow, + ) -> ValidAssetSubset: + """Returns the AssetSubset of a given parent asset that has been updated since the end of + the previous cron tick. If a value for this parent asset was computed on the previous + evaluation, and that evaluation happened within the same cron tick as the current evaluation, + then this value will be calculated incrementally from the previous value to avoid expensive + queries. + """ + if ( + # first tick of evaluating this condition + context.previous_evaluation_state is None + or context.previous_evaluation_timestamp is None + # This additional check is neccessary as it is possible for this cursor to be None + # even if the previous state is not None in the case that this asset and none of its + # parents have been detected as materialized at any point. While in theory this should + # not cause issues, in past versions we were not properly capturing materializations + # of external assets, causing this detection to be faulty. This ensures that we can + # properly re-calculate this value even in the case that we've incorrectly considered + # a parent as unmaterialized in the past. + or context.previous_max_storage_id is None + # new cron tick has happened since the previous tick + or passed_time_window.end.timestamp() > context.previous_evaluation_timestamp + ): + return context.instance_queryer.get_asset_subset_updated_after_time( + asset_key=parent_asset_key, after_time=passed_time_window.end + ) + else: + # previous state still valid + previous_parent_subsets = ( + context.previous_evaluation_state.get_extra_state(context.condition, list) or [] + ) + previous_parent_subset = next( + (s for s in previous_parent_subsets if s.asset_key == parent_asset_key), + context.empty_subset(), + ) + + # the set of asset partitions that have been updated since the previous evaluation + new_parent_subset = context.instance_queryer.get_asset_subset_updated_after_cursor( + asset_key=parent_asset_key, after_cursor=context.previous_max_storage_id + ) + return new_parent_subset | previous_parent_subset + + def get_parent_subsets_updated_since_cron_by_key( + self, context: "AssetConditionEvaluationContext", passed_time_window: TimeWindow + ) -> Mapping[AssetKey, ValidAssetSubset]: + """Returns a mapping of parent asset keys to the AssetSubset of each parent that has been + updated since the end of the previous cron tick. Does not compute this value for time-window + partitioned parents, as their partitions encode the time windows they have processed. + """ + updated_subsets_by_key = {} + for parent_asset_key in context.asset_graph.get(context.asset_key).parent_keys: + # no need to incrementally calculate updated time-window partitions definitions, as + # their partitions encode the time windows they have processed. + if isinstance( + context.asset_graph.get(parent_asset_key).partitions_def, + TimeWindowPartitionsDefinition, + ): + continue + updated_subsets_by_key[parent_asset_key] = self.get_parent_subset_updated_since_cron( + context, parent_asset_key, passed_time_window + ) + return updated_subsets_by_key + + def parent_updated_since_cron( + self, + context: "AssetConditionEvaluationContext", + passed_time_window: TimeWindow, + parent_asset_key: AssetKey, + child_asset_partition: AssetKeyPartitionKey, + updated_parent_subset: ValidAssetSubset, + ) -> bool: + """Returns if, for a given child asset partition, the given parent asset been updated with + information from the required time window. + """ + parent_partitions_def = context.asset_graph.get(parent_asset_key).partitions_def + + if isinstance(parent_partitions_def, TimeWindowPartitionsDefinition): + # for time window partitions definitions, we simply assert that all time partitions that + # were newly created between the previous cron ticks have been materialized + required_parent_partitions = parent_partitions_def.get_partition_keys_in_time_window( + time_window=passed_time_window + ) + + # for time window partitions definitions, we simply assert that all time partitions that + return all( + AssetKeyPartitionKey(parent_asset_key, partition_key) + in context.instance_queryer.get_materialized_asset_subset( + asset_key=parent_asset_key + ) + for partition_key in required_parent_partitions + ) + # for all other partitions definitions, we assert that all parent partition keys have + # been materialized since the previous cron tick + else: + if parent_partitions_def is None: + non_updated_parent_asset_partitions = updated_parent_subset.inverse( + parent_partitions_def + ).asset_partitions + else: + parent_subset = context.asset_graph.get_parent_partition_keys_for_child( + child_asset_partition.partition_key, + parent_asset_key, + child_asset_partition.asset_key, + context.instance_queryer, + context.evaluation_time, + ).partitions_subset + + non_updated_parent_asset_partitions = ( + ValidAssetSubset(asset_key=parent_asset_key, value=parent_subset) + - updated_parent_subset + ).asset_partitions + + return not any( + not context.will_update_asset_partition(p) + for p in non_updated_parent_asset_partitions + ) + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + passed_time_window = self.passed_time_window(context) + has_new_passed_time_window = passed_time_window.end.timestamp() > ( + context.previous_evaluation_timestamp or 0 + ) + updated_subsets_by_key = self.get_parent_subsets_updated_since_cron_by_key( + context, passed_time_window + ) + + # only need to evaluate net-new candidates and candidates whose parents have updated, unless + # this is the first tick after a new cron schedule tick + subset_to_evaluate = ( + ( + context.candidates_not_evaluated_on_previous_tick_subset + | context.candidate_parent_has_or_will_update_subset + ) + if not has_new_passed_time_window + else context.candidate_subset + ) + + # the set of candidates for whom all parents have been updated since the previous cron tick + all_parents_updated_subset = AssetSubset.from_asset_partitions_set( + context.asset_key, + context.partitions_def, + { + candidate + for candidate in subset_to_evaluate.asset_partitions + if all( + self.parent_updated_since_cron( + context, + passed_time_window, + parent_asset_key, + candidate, + updated_subsets_by_key.get(parent_asset_key, context.empty_subset()), + ) + for parent_asset_key in context.asset_graph.get(candidate.asset_key).parent_keys + ) + }, + ) + # if your parents were all updated since the previous cron tick on the previous evaluation, + # that will still be true unless a new cron tick has happened since the previous evaluation + if not has_new_passed_time_window: + all_parents_updated_subset = ( + context.previous_candidate_subset.as_valid(context.partitions_def) + - context.previous_true_subset + ) | all_parents_updated_subset + + return AssetConditionResult.create( + context, + true_subset=context.candidate_subset - all_parents_updated_subset, + extra_state=list(updated_subsets_by_key.values()), + ) + + +@whitelist_for_serdes +class SkipOnRequiredButNonexistentParentsRule( + AutoMaterializeRule, NamedTuple("_SkipOnRequiredButNonexistentParentsRule", []) +): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.SKIP + + @property + def description(self) -> str: + return "required parent partitions do not exist" + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + asset_partitions_by_evaluation_data = defaultdict(set) + + subset_to_evaluate = ( + context.candidates_not_evaluated_on_previous_tick_subset + | context.candidate_parent_has_or_will_update_subset + ) + for candidate in subset_to_evaluate.asset_partitions: + nonexistent_parent_partitions = context.asset_graph.get_parents_partitions( + context.instance_queryer, + context.instance_queryer.evaluation_time, + candidate.asset_key, + candidate.partition_key, + ).required_but_nonexistent_parents_partitions + + nonexistent_parent_keys = {parent.asset_key for parent in nonexistent_parent_partitions} + if nonexistent_parent_keys: + asset_partitions_by_evaluation_data[ + WaitingOnAssetsRuleEvaluationData( + frozenset(nonexistent_parent_keys) + ).frozen_metadata + ].add(candidate) + + true_subset, subsets_with_metadata = context.add_evaluation_data_from_previous_tick( + asset_partitions_by_evaluation_data, ignore_subset=subset_to_evaluate + ) + return AssetConditionResult.create(context, true_subset, subsets_with_metadata) + + +@whitelist_for_serdes +class SkipOnBackfillInProgressRule( + AutoMaterializeRule, + NamedTuple("_SkipOnBackfillInProgressRule", [("all_partitions", bool)]), +): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.SKIP + + @property + def description(self) -> str: + if self.all_partitions: + return "part of an asset targeted by an in-progress backfill" + else: + return "targeted by an in-progress backfill" + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + backfilling_subset = ( + # this backfilling subset is aware of the current partitions definitions, and so will + # be valid + (context.instance_queryer.get_active_backfill_target_asset_graph_subset()) + .get_asset_subset(context.asset_key, context.asset_graph) + .as_valid(context.partitions_def) + ) + + if backfilling_subset.size == 0: + true_subset = context.empty_subset() + elif self.all_partitions: + true_subset = context.candidate_subset + else: + true_subset = context.candidate_subset & backfilling_subset + + return AssetConditionResult.create(context, true_subset) + + +@whitelist_for_serdes +class DiscardOnMaxMaterializationsExceededRule( + AutoMaterializeRule, NamedTuple("_DiscardOnMaxMaterializationsExceededRule", [("limit", int)]) +): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.DISCARD + + @property + def description(self) -> str: + return f"exceeds {self.limit} materialization(s) per minute" + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + # the set of asset partitions which exceed the limit + rate_limited_asset_partitions = set( + sorted( + context.candidate_subset.asset_partitions, + key=lambda x: sort_key_for_asset_partition(context.asset_graph, x), + )[self.limit :] + ) + + return AssetConditionResult.create( + context, + AssetSubset.from_asset_partitions_set( + context.asset_key, context.partitions_def, rate_limited_asset_partitions + ), + ) + + +@whitelist_for_serdes +class SkipOnRunInProgressRule(AutoMaterializeRule, NamedTuple("_SkipOnRunInProgressRule", [])): + @property + def decision_type(self) -> AutoMaterializeDecisionType: + return AutoMaterializeDecisionType.SKIP + + @property + def description(self) -> str: + return "in-progress run for asset" + + def evaluate_for_asset( + self, context: "AssetConditionEvaluationContext" + ) -> "AssetConditionResult": + from .asset_condition.asset_condition import AssetConditionResult + + if context.partitions_def is not None: + raise DagsterInvariantViolationError( + "SkipOnRunInProgressRule is currently only support for non-partitioned assets." + ) + instance = context.instance_queryer.instance + planned_materialization_info = ( + instance.event_log_storage.get_latest_planned_materialization_info(context.asset_key) + ) + if planned_materialization_info: + dagster_run = instance.get_run_by_id(planned_materialization_info.run_id) + if dagster_run and dagster_run.status in IN_PROGRESS_RUN_STATUSES: + return AssetConditionResult.create(context, context.candidate_subset) + return AssetConditionResult.create(context, context.empty_subset()) diff --git a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/scenarios/auto_materialize_policy_scenarios.py b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/scenarios/auto_materialize_policy_scenarios.py index c6772c95c2ae1..dd3b876702d32 100644 --- a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/scenarios/auto_materialize_policy_scenarios.py +++ b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/scenarios/auto_materialize_policy_scenarios.py @@ -7,15 +7,15 @@ ) from dagster._core.definitions.asset_selection import AssetSelection from dagster._core.definitions.auto_materialize_policy import AutoMaterializePolicy -from dagster._core.definitions.auto_materialize_rule import ( - AutoMaterializeRule, - DiscardOnMaxMaterializationsExceededRule, -) +from dagster._core.definitions.auto_materialize_rule import AutoMaterializeRule from dagster._core.definitions.auto_materialize_rule_evaluation import ( AutoMaterializeRuleEvaluation, ParentUpdatedRuleEvaluationData, WaitingOnAssetsRuleEvaluationData, ) +from dagster._core.definitions.auto_materialize_rule_impls import ( + DiscardOnMaxMaterializationsExceededRule, +) from dagster._core.definitions.events import AssetKey from dagster._core.definitions.freshness_policy import FreshnessPolicy from dagster._seven.compat.pendulum import create_pendulum_time diff --git a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/test_auto_materialize_policy.py b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/test_auto_materialize_policy.py index 35231ad7f40d0..3bc4ea4321083 100644 --- a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/test_auto_materialize_policy.py +++ b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/test_auto_materialize_policy.py @@ -2,15 +2,15 @@ from dagster import AssetKey, AutoMaterializePolicy from dagster._check import CheckError from dagster._core.definitions.auto_materialize_policy import AutoMaterializePolicyType -from dagster._core.definitions.auto_materialize_rule import ( - AutoMaterializeRule, - DiscardOnMaxMaterializationsExceededRule, -) +from dagster._core.definitions.auto_materialize_rule import AutoMaterializeRule from dagster._core.definitions.auto_materialize_rule_evaluation import ( AutoMaterializeRuleEvaluation, ParentUpdatedRuleEvaluationData, WaitingOnAssetsRuleEvaluationData, ) +from dagster._core.definitions.auto_materialize_rule_impls import ( + DiscardOnMaxMaterializationsExceededRule, +) from dagster._serdes import deserialize_value, serialize_value diff --git a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/basic_scenarios.py b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/basic_scenarios.py index 97e4dfec40ab2..5a13f56d51bb9 100644 --- a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/basic_scenarios.py +++ b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/basic_scenarios.py @@ -1,8 +1,8 @@ from dagster import AssetSpec, AutoMaterializePolicy, AutoMaterializeRule -from dagster._core.definitions.auto_materialize_rule import SkipOnRunInProgressRule from dagster._core.definitions.auto_materialize_rule_evaluation import ( ParentUpdatedRuleEvaluationData, ) +from dagster._core.definitions.auto_materialize_rule_impls import SkipOnRunInProgressRule from ..base_scenario import run_request from ..scenario_specs import ( diff --git a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cron_scenarios.py b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cron_scenarios.py index a9b34ccf866ab..8a1027fe430fb 100644 --- a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cron_scenarios.py +++ b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cron_scenarios.py @@ -1,7 +1,7 @@ import pytest from dagster import AutoMaterializePolicy, AutoMaterializeRule from dagster._check import ParameterCheckError -from dagster._core.definitions.auto_materialize_rule import ( +from dagster._core.definitions.auto_materialize_rule_impls import ( WaitingOnAssetsRuleEvaluationData, ) diff --git a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cursor_migration_scenarios.py b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cursor_migration_scenarios.py index aeecd32e5ca1e..25d779b9a52d2 100644 --- a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cursor_migration_scenarios.py +++ b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/cursor_migration_scenarios.py @@ -1,5 +1,7 @@ from dagster import AutoMaterializeRule -from dagster._core.definitions.auto_materialize_rule import DiscardOnMaxMaterializationsExceededRule +from dagster._core.definitions.auto_materialize_rule_impls import ( + DiscardOnMaxMaterializationsExceededRule, +) from dagster_tests.definitions_tests.auto_materialize_tests.updated_scenarios.cron_scenarios import ( basic_hourly_cron_rule, diff --git a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/partition_scenarios.py b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/partition_scenarios.py index 79923137fde3d..231b237814c6f 100644 --- a/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/partition_scenarios.py +++ b/python_modules/dagster/dagster_tests/definitions_tests/auto_materialize_tests/updated_scenarios/partition_scenarios.py @@ -9,7 +9,9 @@ MultiPartitionMapping, TimeWindowPartitionMapping, ) -from dagster._core.definitions.auto_materialize_rule import DiscardOnMaxMaterializationsExceededRule +from dagster._core.definitions.auto_materialize_rule_impls import ( + DiscardOnMaxMaterializationsExceededRule, +) from ..base_scenario import run_request from ..scenario_specs import ( diff --git a/python_modules/libraries/dagster-embedded-elt/dagster_embedded_elt_tests/dlt_tests/test_dlt.py b/python_modules/libraries/dagster-embedded-elt/dagster_embedded_elt_tests/dlt_tests/test_dlt.py index 968a57acd522c..a648ede97b55e 100644 --- a/python_modules/libraries/dagster-embedded-elt/dagster_embedded_elt_tests/dlt_tests/test_dlt.py +++ b/python_modules/libraries/dagster-embedded-elt/dagster_embedded_elt_tests/dlt_tests/test_dlt.py @@ -8,7 +8,7 @@ AutoMaterializeRule, Definitions, ) -from dagster._core.definitions.auto_materialize_rule import MaterializeOnCronRule +from dagster._core.definitions.auto_materialize_rule_impls import MaterializeOnCronRule from dagster._core.definitions.materialize import materialize from dagster_embedded_elt.dlt import DagsterDltResource, DagsterDltTranslator, dlt_assets from dlt import Pipeline From 04265a1244dd29695fdc70bf3a7feddb7a6834df Mon Sep 17 00:00:00 2001 From: Alex Langenfeld Date: Thu, 25 Apr 2024 12:25:18 -0500 Subject: [PATCH 03/56] remove useless assert (#21429) I think this assert is no longer useful given the current implementation, also it does not work across pydantic 1 and 2 ## How I Tested These Changes ran test --- 2 | 2 ++ .../dagster/dagster_tests/model_tests/test_dagster_model.py | 4 +--- 2 files changed, 3 insertions(+), 3 deletions(-) create mode 100644 2 diff --git a/2 b/2 new file mode 100644 index 0000000000000..4876f9a53860c --- /dev/null +++ b/2 @@ -0,0 +1,2 @@ +Requirement already satisfied: pydantic in /Users/alangenfeld/venvs/arm/py311/lib/python3.11/site-packages (1.10.14) +Requirement already satisfied: typing-extensions>=4.2.0 in /Users/alangenfeld/venvs/arm/py311/lib/python3.11/site-packages (from pydantic) (4.9.0) diff --git a/python_modules/dagster/dagster_tests/model_tests/test_dagster_model.py b/python_modules/dagster/dagster_tests/model_tests/test_dagster_model.py index 760d4ba994350..9d06bce67877c 100644 --- a/python_modules/dagster/dagster_tests/model_tests/test_dagster_model.py +++ b/python_modules/dagster/dagster_tests/model_tests/test_dagster_model.py @@ -1,6 +1,6 @@ import pytest from dagster._model import DagsterModel -from dagster._utils.cached_method import CACHED_METHOD_CACHE_FIELD, cached_method +from dagster._utils.cached_method import cached_method from pydantic import ValidationError @@ -67,8 +67,6 @@ class MyModel(DagsterModel): def test_cached_method() -> None: - assert DagsterModel._cached_method_cache__internal__.__name__ == CACHED_METHOD_CACHE_FIELD # noqa # type: ignore - class CoolModel(DagsterModel): name: str From bd9ba7ca787caaaaf250e8e04cc37179870299d3 Mon Sep 17 00:00:00 2001 From: Marco polo Date: Thu, 25 Apr 2024 13:35:21 -0400 Subject: [PATCH 04/56] Wrap suspense api (#21414) ## Summary & Motivation We're planning to use Suspense in order to track pageload performance. In order to accomplish that we need to know when Suspense boundaries are suspended (when their fallbacks are rendered) and when they have completed (the fallback was removed and the content was rendered). That's where `TrackedSuspenseProvider` and `TrackedSuspense` come in. As long as we use `TrackedSuspsense` in place of `Suspense` then the cloud app can use this to track how many suspense boundaries are active and to know when all suspense boundaries have resolved. ## How I Tested These Changes jest --- .../ui-core/src/app/TrackedSuspense.tsx | 100 ++++++++++++++++ .../app/__tests__/TrackedSuspense.test.tsx | 110 ++++++++++++++++++ 2 files changed, 210 insertions(+) create mode 100644 js_modules/dagster-ui/packages/ui-core/src/app/TrackedSuspense.tsx create mode 100644 js_modules/dagster-ui/packages/ui-core/src/app/__tests__/TrackedSuspense.test.tsx diff --git a/js_modules/dagster-ui/packages/ui-core/src/app/TrackedSuspense.tsx b/js_modules/dagster-ui/packages/ui-core/src/app/TrackedSuspense.tsx new file mode 100644 index 0000000000000..b54df600f51ad --- /dev/null +++ b/js_modules/dagster-ui/packages/ui-core/src/app/TrackedSuspense.tsx @@ -0,0 +1,100 @@ +import { + ComponentProps, + ReactNode, + Suspense, + createContext, + useCallback, + useContext, + useLayoutEffect, + useMemo, +} from 'react'; + +// Context to store the active suspense count and a method to manipulate it +const TrackedSuspenseContext = createContext({ + useBoundary: (_id: string) => { + return { + onFallbackRendered: () => { + return () => {}; + }, + onContentRendered: () => { + return () => {}; + }, + }; + }, +}); + +export type Boundary = { + id: string; + name: string; +}; + +export const TrackedSuspenseProvider = ({ + children, + onContentRendered, + onContentRemoved, + onFallbackRendered, + onFallbackRemoved, +}: { + children: ReactNode; + onContentRendered: (boundary: Boundary) => void; + onContentRemoved: (boundary: Boundary) => void; + onFallbackRendered: (boundary: Boundary) => void; + onFallbackRemoved: (boundary: Boundary) => void; +}) => { + const useBoundary = useCallback( + (name: string) => { + // eslint-disable-next-line react-hooks/rules-of-hooks + const boundary: Boundary = useMemo(() => ({name, id: uniqueId()}), [name]); + + return { + onFallbackRendered: () => { + onFallbackRendered(boundary); + return () => { + onFallbackRemoved(boundary); + }; + }, + onContentRendered: () => { + onContentRendered(boundary); + return () => { + onContentRemoved(boundary); + }; + }, + }; + }, + [onContentRemoved, onContentRendered, onFallbackRemoved, onFallbackRendered], + ); + + return ( + ({useBoundary}), [useBoundary])}> + {children} + + ); +}; + +export const TrackedSuspense = (props: ComponentProps & {id: string}) => { + const {useBoundary} = useContext(TrackedSuspenseContext); + const boundary = useBoundary(props.id); + return ( + {props.fallback}} + > + {props.children} + + ); +}; +const OnRendered = ({ + onRendered, + children, +}: { + children: React.ReactNode; + onRendered: () => () => void; +}) => { + useLayoutEffect(onRendered, [onRendered]); + return children; +}; + +let id = 0; +function uniqueId() { + return `boundaryId${id++}`; +} diff --git a/js_modules/dagster-ui/packages/ui-core/src/app/__tests__/TrackedSuspense.test.tsx b/js_modules/dagster-ui/packages/ui-core/src/app/__tests__/TrackedSuspense.test.tsx new file mode 100644 index 0000000000000..ab41c13ace1b8 --- /dev/null +++ b/js_modules/dagster-ui/packages/ui-core/src/app/__tests__/TrackedSuspense.test.tsx @@ -0,0 +1,110 @@ +import {act, render, waitFor} from '@testing-library/react'; + +import {TrackedSuspense, TrackedSuspenseProvider} from '../TrackedSuspense'; + +describe('TrackedSuspenseProvider', () => { + it('manages boundaries correctly', async () => { + const mockContentRendered = jest.fn(); + const mockContentRemoved = jest.fn(); + const mockFallbackRendered = jest.fn(); + const mockFallbackRemoved = jest.fn(); + + const state = { + promises: {} as Record>, + resolvers: {} as Record void>, + resolved: {} as Record, + }; + + function Suspender({id}: {id: string}) { + if (!state.promises[id]) { + state.promises[id] = new Promise((res) => { + state.resolvers[id] = (value: any) => { + state.resolved[id] = true; + res(value); + }; + }); + } + if (!state.resolved[id]) { + throw state.promises[id]; + } + return id; + } + + render( + + Loading 1...}> + Loading 2...}> + + + Loading 3...}> + + + + Loading 4...}> + + + , + ); + + // test1 is rendered since it doesn't suspend + expect(mockContentRendered).toHaveBeenCalledTimes(1); + expect(mockContentRendered).toHaveBeenNthCalledWith(1, { + name: 'test1', + id: 'boundaryId0', + }); + + expect(mockFallbackRendered).toHaveBeenCalledTimes(3); + + expect(mockFallbackRendered).toHaveBeenNthCalledWith(1, { + name: 'test2', + id: 'boundaryId1', + }); + expect(mockFallbackRendered).toHaveBeenNthCalledWith(2, { + name: 'test3', + id: 'boundaryId2', + }); + expect(mockFallbackRendered).toHaveBeenNthCalledWith(3, { + name: 'test4', + id: 'boundaryId3', + }); + expect(mockFallbackRemoved).toHaveBeenCalledTimes(0); + act(() => { + state.resolvers['test2']!(1); + }); + await waitFor(() => { + expect(mockFallbackRemoved).toHaveBeenCalledTimes(1); + expect(mockContentRendered).toHaveBeenCalledTimes(2); + expect(mockContentRendered).toHaveBeenNthCalledWith(2, { + name: 'test2', + id: 'boundaryId1', + }); + }); + act(() => { + state.resolvers['test3']!(1); + }); + await waitFor(() => { + expect(mockFallbackRemoved).toHaveBeenCalledTimes(2); + expect(mockContentRendered).toHaveBeenCalledTimes(3); + expect(mockContentRendered).toHaveBeenNthCalledWith(3, { + name: 'test3', + id: 'boundaryId2', + }); + }); + act(() => { + state.resolvers['test4']!(1); + }); + await waitFor(() => { + expect(mockFallbackRemoved).toHaveBeenCalledTimes(3); + expect(mockContentRendered).toHaveBeenCalledTimes(4); + expect(mockContentRendered).toHaveBeenNthCalledWith(4, { + name: 'test4', + id: 'boundaryId3', + }); + }); + }); +}); From fa89a262e407c62f8e6762dcf0c703872a0e19c7 Mon Sep 17 00:00:00 2001 From: Alex Langenfeld Date: Thu, 25 Apr 2024 12:41:24 -0500 Subject: [PATCH 05/56] [shame] remove accident file addition (#21430) :( --- 2 | 2 -- 1 file changed, 2 deletions(-) delete mode 100644 2 diff --git a/2 b/2 deleted file mode 100644 index 4876f9a53860c..0000000000000 --- a/2 +++ /dev/null @@ -1,2 +0,0 @@ -Requirement already satisfied: pydantic in /Users/alangenfeld/venvs/arm/py311/lib/python3.11/site-packages (1.10.14) -Requirement already satisfied: typing-extensions>=4.2.0 in /Users/alangenfeld/venvs/arm/py311/lib/python3.11/site-packages (from pydantic) (4.9.0) From e82cbe0ade5d03d5bf8c1d15a9f9464d86b552ab Mon Sep 17 00:00:00 2001 From: Sean Mackesey Date: Thu, 25 Apr 2024 15:59:03 -0400 Subject: [PATCH 06/56] 1.7.3 changelog (#21431) --- CHANGES.md | 41 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 41 insertions(+) diff --git a/CHANGES.md b/CHANGES.md index eff35c5f4f65e..ff9cee687868d 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -1,5 +1,46 @@ # Changelog +# 1.7.3 (core) / 0.23.3 (libraries) + +### New + +- `@graph_asset` now accepts a `tags` argument +- [ui] For users whose light/dark mode theme setting is set to match their system setting, the theme will update automatically when the system changes modes (e.g. based on time of day), with no page reload required. +- [ui] We have introduced the typefaces Geist and Geist Mono as our new default fonts throughout the Dagster app, with the goal of improving legibility, consistency, and maintainability. +- [ui] [experimental] We have begun experimenting with a [new navigation structure](https://github.com/dagster-io/dagster/discussions/21370) for the Dagster UI. The change can be enabled via User Settings. +- [ui] [experimental] Made performance improvements to the Concurrency settings page. +- [dagster-azure] [community-contribution] ADLS2 IOManager supports custom timeout. Thanks @tomas-gajarsky! +- [dagster-fivetran] [community-contribution] It’s now possible to specify destination ids in `load_asset_defs_from_fivetran_instance`. Thanks @lamalex! + +### Bugfixes + +- Fixed an issue where pressing the “Reset sensor status” button in the UI would also reset the sensor’s cursor. +- Fixed a bug that caused input loading time not to be included in the reported step duration. +- Pydantic warnings are no longer raised when importing Dagster with Pydantic 2.0+. +- Fixed an issue which would cause incorrect behavior when auto-materializing partitioned assets based on updates to a parent asset in a different code location. +- Fixed an issue which would cause every tick of the auto-materialize sensor to produce an evaluation for each asset, even if nothing had changed from the previous tick. +- [dagster-dbt] Fixed a bug that could raise `Duplicate check specs` errors with singular tests ingested as asset checks. +- [embedded-elt] resolved an issue where subset of resources were not recognized when using `source.with_resources(...)` +- [ui] Fixed an issue where a sensor that targeted an invalid set of asset keys could cause the asset catalog to fail to load. +- [ui] Fixed an issue in which runs in the Timeline that should have been considered overlapping were not correctly grouped together, leading to visual bugs. +- [ui] On the asset overview page, job tags no longer render poorly when an asset appears in several jobs. +- [ui] On the asset overview page, hovering over the timestamp tags in the metadata table explains where each entry originated. +- [ui] Right clicking the background of the asset graph now consistently shows a context menu, and the lineage view supports vertical as well as horizontal layout. + +### Documentation + +- Sidebar navigation now appropriately handles command-click and middle-click to open links in a new tab. +- Added a section for asset checks to the [Testing guide](https://docs.dagster.io/concepts/testing#testing-asset-checks). +- Added a guide about [Column-level lineage for assets](https://docs.dagster.io/concepts/metadata-tags/asset-metadata/column-level-lineage). +- Lots of updates to examples to reflect the new opt-in approach to I/O managers. + +### Dagster+ + +- [ui] [experimental] A new Overview > Asset Health page provides visibility into failed and missing materializations, check warnings and check errors. +- [ui] You can now share feedback with the Dagster team directly from the app. Open the Help menu in the top nav, then “Share feedback”. Bugs and feature requests are submitted directly to the Dagster team. +- [ui] When editing a team, the list of team members is now virtualized, allowing for the UI to scale better for very large team sizes. +- [ui] Fixed dark mode for billing components. + # 1.7.2 (core) / 0.23.2 (libraries) ### New From 357f26d4106076df61874ec6cd263512c5aeb2d8 Mon Sep 17 00:00:00 2001 From: elementl Date: Thu, 25 Apr 2024 20:44:18 +0000 Subject: [PATCH 07/56] Automation: versioned docs for 1.7.3 --- docs/next/.versioned_content/_versions_with_static_links.json | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/next/.versioned_content/_versions_with_static_links.json b/docs/next/.versioned_content/_versions_with_static_links.json index c8956205d921a..57950b170091c 100644 --- a/docs/next/.versioned_content/_versions_with_static_links.json +++ b/docs/next/.versioned_content/_versions_with_static_links.json @@ -474,5 +474,9 @@ { "url": "https://release-1-7-2.dagster.dagster-docs.io/", "version": "1.7.2" + }, + { + "url": "https://release-1-7-3.dagster.dagster-docs.io/", + "version": "1.7.3" } ] \ No newline at end of file From 658f1b0745ef03ddb8866dfad561d4c2840fff7c Mon Sep 17 00:00:00 2001 From: Erin Cochran Date: Thu, 25 Apr 2024 16:44:35 -0400 Subject: [PATCH 08/56] [docs] - Fix redirects in Cloud docs (#21434) ## Summary & Motivation This PR fixes some redirects that got bungled in the Plus switch. ## How I Tested These Changes Local --- docs/next/util/redirectUrls.json | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/docs/next/util/redirectUrls.json b/docs/next/util/redirectUrls.json index 1088b53499d62..b16077c0913de 100644 --- a/docs/next/util/redirectUrls.json +++ b/docs/next/util/redirectUrls.json @@ -654,6 +654,11 @@ "destination": "/dagster-plus/managing-deployments/alerts", "statusCode": 302 }, + { + "source": "/dagster-cloud/managing-deployments/code-locations", + "destination": "/dagster-plus/managing-deployments/code-locations", + "statusCode": 302 + }, { "source": "/dagster-cloud/developing-testing/code-locations", "destination": "/dagster-plus/managing-deployments/code-locations", @@ -1046,11 +1051,11 @@ }, { "source": "/dagster-cloud/managing-deployments/dagster-cloud-yaml", - "destination": "/dagster-plus/managing-deployments/dagster-plus-yaml", + "destination": "/dagster-plus/managing-deployments/dagster-cloud-yaml", "statusCode": 302 }, { - "source": "/dagster-cloud/managing-deployments/dagster-plus-cli", + "source": "/dagster-cloud/managing-deployments/dagster-cloud-cli", "destination": "/dagster-plus/managing-deployments/dagster-plus-cli", "statusCode": 302 }, From ca751f3411a20e45cb7e31807492aa1322c35dd4 Mon Sep 17 00:00:00 2001 From: Erin Cochran Date: Thu, 25 Apr 2024 20:26:21 -0400 Subject: [PATCH 09/56] [docs] - Add external assets disclaimer to Insights docs (DOC-197) (#21225) --- .../managing-deployments/alerts.mdx | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) diff --git a/docs/content/dagster-plus/managing-deployments/alerts.mdx b/docs/content/dagster-plus/managing-deployments/alerts.mdx index e2e5a65e3017a..cd0311344f4d3 100644 --- a/docs/content/dagster-plus/managing-deployments/alerts.mdx +++ b/docs/content/dagster-plus/managing-deployments/alerts.mdx @@ -66,7 +66,11 @@ Alert policies are configured on a **per-deployment basis**. This means, for exa asset owners - . + .
+
+ Note: + External assets + do not trigger asset alerts. @@ -113,8 +117,7 @@ Alert policies are configured on a **per-deployment basis**. This means, for exa Insights metric alert - A Dagster+ Pro plan is required to use this feature. -
+ A Dagster+ Pro plan is required to use this feature.{" "} Sends a notification when a{" "} Dagster+ Insights metric exceeds or falls below a specified threshold over a specified time window. This can @@ -129,10 +132,10 @@ Alert policies are configured on a **per-deployment basis**. This means, for exa Alerts can be scoped to the sum of any metric across an entire deployment, or for a specific job, asset group, or asset key.
- Note: Alerts are sent only when the threshold is first - crossed, and will not be sent again until the value returns to expected - levels. Insights data may become available up to 24 hours after run - completion. +
+ Note: Alerts are sent only when the threshold is first crossed, + and will not be sent again until the value returns to expected levels. Insights + data may become available up to 24 hours after run completion. From 2a8ac8104e7147c31c225dc547390cdc0ed243fa Mon Sep 17 00:00:00 2001 From: OwenKephart Date: Fri, 26 Apr 2024 07:31:59 -0700 Subject: [PATCH 10/56] [AMP] add flag for child partition limit (#21447) ## Summary & Motivation ## How I Tested These Changes --- .../asset_condition/asset_condition_evaluation_context.py | 5 +++++ .../dagster/dagster/_utils/caching_instance_queryer.py | 7 +++---- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/python_modules/dagster/dagster/_core/definitions/asset_condition/asset_condition_evaluation_context.py b/python_modules/dagster/dagster/_core/definitions/asset_condition/asset_condition_evaluation_context.py index fc3830b77cb70..8dafbe8ff9193 100644 --- a/python_modules/dagster/dagster/_core/definitions/asset_condition/asset_condition_evaluation_context.py +++ b/python_modules/dagster/dagster/_core/definitions/asset_condition/asset_condition_evaluation_context.py @@ -1,6 +1,7 @@ import dataclasses import datetime import functools +import os from collections import defaultdict from dataclasses import dataclass from typing import ( @@ -242,6 +243,7 @@ def _parent_has_updated_subset_and_new_latest_storage_id( """Returns the set of asset partitions whose parents have updated since the last time this condition was evaluated. """ + max_child_partitions_str = os.getenv("DAGSTER_MAX_AMP_CHILD_PARTITIONS", None) ( asset_partitions, cursor, @@ -249,6 +251,9 @@ def _parent_has_updated_subset_and_new_latest_storage_id( latest_storage_id=self.previous_max_storage_id, child_asset_key=self.root_context.asset_key, map_old_time_partitions=False, + max_child_partitions=int(max_child_partitions_str) + if max_child_partitions_str + else None, ) return AssetSubset.from_asset_partitions_set( self.asset_key, self.partitions_def, asset_partitions diff --git a/python_modules/dagster/dagster/_utils/caching_instance_queryer.py b/python_modules/dagster/dagster/_utils/caching_instance_queryer.py index d2a211ae77345..e30dd6ed3af89 100644 --- a/python_modules/dagster/dagster/_utils/caching_instance_queryer.py +++ b/python_modules/dagster/dagster/_utils/caching_instance_queryer.py @@ -1,5 +1,4 @@ import logging -import os from collections import defaultdict from datetime import datetime from typing import ( @@ -538,6 +537,7 @@ def asset_partitions_with_newly_updated_parents_and_new_cursor( latest_storage_id: Optional[int], child_asset_key: AssetKey, map_old_time_partitions: bool = True, + max_child_partitions: Optional[int] = None, ) -> Tuple[AbstractSet[AssetKeyPartitionKey], Optional[int]]: """Finds asset partitions of the given child whose parents have been materialized since latest_storage_id. @@ -648,9 +648,8 @@ def asset_partitions_with_newly_updated_parents_and_new_cursor( ) from e child_partitions = reversed(list(child_partitions_subset.get_partition_keys())) - max_child_partitions = os.getenv("DAGSTER_MAX_AMP_CHILD_PARTITIONS", None) - if max_child_partitions: - child_partitions = list(child_partitions)[: int(max_child_partitions)] + if max_child_partitions is not None: + child_partitions = list(child_partitions)[:max_child_partitions] for child_partition in child_partitions: # we need to see if the child is planned for the same run, but this is From 1834ce3c0b5e2b705567a483e26d52f1e7adf12a Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Fri, 26 Apr 2024 07:54:30 -0700 Subject: [PATCH 11/56] smooth over pydantic 2 and pydantic 1 in alias serializing (#21432) ## Summary & Motivation Were getting warnings and divergent behavior. ## How I Tested These Changes --- .../dagster/_model/pydantic_compat_layer.py | 15 ++- .../dagster/dagster/_serdes/serdes.py | 8 +- .../general_tests/test_serdes.py | 82 -------------- .../model_tests/test_dagster_model_serdes.py | 100 ++++++++++++++++++ 4 files changed, 117 insertions(+), 88 deletions(-) create mode 100644 python_modules/dagster/dagster_tests/model_tests/test_dagster_model_serdes.py diff --git a/python_modules/dagster/dagster/_model/pydantic_compat_layer.py b/python_modules/dagster/dagster/_model/pydantic_compat_layer.py index 0ba63764e8627..5beb85a702f7c 100644 --- a/python_modules/dagster/dagster/_model/pydantic_compat_layer.py +++ b/python_modules/dagster/dagster/_model/pydantic_compat_layer.py @@ -41,8 +41,19 @@ def metadata(self) -> List[str]: return getattr(self.field, "metadata", []) @property - def alias(self) -> str: - return self.field.alias + def alias(self) -> Optional[str]: + if USING_PYDANTIC_2: + return self.field.alias + else: + return self.field.alias if self.field.alias != self.field.name else None + + @property + def serialization_alias(self) -> Optional[str]: + return getattr(self.field, "serialization_alias", None) + + @property + def validation_alias(self) -> Optional[str]: + return getattr(self.field, "serialization_alias", None) @property def default(self) -> Any: diff --git a/python_modules/dagster/dagster/_serdes/serdes.py b/python_modules/dagster/dagster/_serdes/serdes.py index ecfd86739522a..3213b3ae38c9b 100644 --- a/python_modules/dagster/dagster/_serdes/serdes.py +++ b/python_modules/dagster/dagster/_serdes/serdes.py @@ -47,6 +47,7 @@ import dagster._check as check import dagster._seven as seven +from dagster._model.pydantic_compat_layer import model_fields from dagster._utils import is_named_tuple_instance, is_named_tuple_subclass from dagster._utils.cached_method import cached_method from dagster._utils.warnings import disable_dagster_warnings @@ -675,10 +676,9 @@ def object_as_mapping(self, value: T_PydanticModel) -> Mapping[str, Any]: value_dict = value.__dict__ result = {} - for key, field in self.klass.__fields__.items(): + for key, field in model_fields(self.klass).items(): if field.alias is None and ( - getattr(field, "serialization_alias", None) is not None - or getattr(field, "validation_alias", None) is not None + field.serialization_alias is not None or field.validation_alias is not None ): raise SerializationError( "Can't serialize pydantic models with serialization or validation aliases. Use " @@ -691,7 +691,7 @@ def object_as_mapping(self, value: T_PydanticModel) -> Mapping[str, Any]: @property def constructor_param_names(self) -> Sequence[str]: - return [field.alias or key for key, field in self.klass.__fields__.items()] + return [field.alias or key for key, field in model_fields(self.klass).items()] class FieldSerializer(Serializer): diff --git a/python_modules/dagster/dagster_tests/general_tests/test_serdes.py b/python_modules/dagster/dagster_tests/general_tests/test_serdes.py index e48b4cf0ad236..c4f08d2b3d7d5 100644 --- a/python_modules/dagster/dagster_tests/general_tests/test_serdes.py +++ b/python_modules/dagster/dagster_tests/general_tests/test_serdes.py @@ -25,7 +25,6 @@ unpack_value, ) from dagster._serdes.utils import hash_str -from pydantic import Field def test_deserialize_value_ok(): @@ -891,84 +890,3 @@ class MyEnt(pydantic.BaseModel): # can deserialize previous NamedTuples in to future pydantic models py_dc_ent = deserialize_value(ser_nt_ent, whitelist_map=py_m_env) assert py_dc_ent - - -def test_pydantic_alias(): - test_env = WhitelistMap.create() - - @_whitelist_for_serdes(test_env) - class SomeDagsterModel(DagsterModel): - unaliased_id: int = Field(..., alias="id_alias") - name: str - - o = SomeDagsterModel(id_alias=5, name="fdsk") - packed_o = pack_value(o, whitelist_map=test_env) - assert packed_o == {"__class__": "SomeDagsterModel", "id_alias": 5, "name": "fdsk"} - assert unpack_value(packed_o, whitelist_map=test_env, as_type=SomeDagsterModel) == o - - ser_o = serialize_value(o, whitelist_map=test_env) - assert deserialize_value(ser_o, whitelist_map=test_env) == o - - -def test_pydantic_serialization_alias(): - test_env = WhitelistMap.create() - - @_whitelist_for_serdes(test_env) - class SomeDagsterModel(DagsterModel): - unaliased_id: int = Field(..., serialization_alias="id_alias") - name: str - - o = SomeDagsterModel(unaliased_id=5, name="fdsk") - with pytest.raises( - SerializationError, - match="Can't serialize pydantic models with serialization or validation aliases.", - ): - serialize_value(o, whitelist_map=test_env) - - with pytest.raises( - SerializationError, - match="Can't serialize pydantic models with serialization or validation aliases.", - ): - pack_value(o, whitelist_map=test_env) - - -def test_pydantic_validation_alias(): - test_env = WhitelistMap.create() - - @_whitelist_for_serdes(test_env) - class SomeDagsterModel(DagsterModel): - unaliased_id: int = Field(..., validation_alias="id_alias") - name: str - - o = SomeDagsterModel(id_alias=5, name="fdsk") - with pytest.raises( - SerializationError, - match="Can't serialize pydantic models with serialization or validation aliases.", - ): - serialize_value(o, whitelist_map=test_env) - - with pytest.raises( - SerializationError, - match="Can't serialize pydantic models with serialization or validation aliases.", - ): - pack_value(o, whitelist_map=test_env) - - -def test_pydantic_alias_generator(): - test_env = WhitelistMap.create() - - @_whitelist_for_serdes(test_env) - class SomeDagsterModel(DagsterModel): - id: int = Field(...) - name: str - - class Config: - alias_generator = lambda field_name: f"{field_name}_alias" - - o = SomeDagsterModel(id_alias=5, name_alias="fdsk") - packed_o = pack_value(o, whitelist_map=test_env) - assert packed_o == {"__class__": "SomeDagsterModel", "id_alias": 5, "name_alias": "fdsk"} - assert unpack_value(packed_o, whitelist_map=test_env, as_type=SomeDagsterModel) == o - - ser_o = serialize_value(o, whitelist_map=test_env) - assert deserialize_value(ser_o, whitelist_map=test_env) == o diff --git a/python_modules/dagster/dagster_tests/model_tests/test_dagster_model_serdes.py b/python_modules/dagster/dagster_tests/model_tests/test_dagster_model_serdes.py new file mode 100644 index 0000000000000..5fe14ee5e61e4 --- /dev/null +++ b/python_modules/dagster/dagster_tests/model_tests/test_dagster_model_serdes.py @@ -0,0 +1,100 @@ +"""These tests are included here instead of in test_serdes, because the model_tests run on both +Pydantic 1 and 2, while the general_tests do not. +""" + +import pytest +from dagster._model import DagsterModel +from dagster._model.pydantic_compat_layer import USING_PYDANTIC_1 +from dagster._serdes.errors import SerializationError +from dagster._serdes.serdes import ( + WhitelistMap, + _whitelist_for_serdes, + deserialize_value, + pack_value, + serialize_value, + unpack_value, +) +from pydantic import Field + + +def test_pydantic_alias(): + test_env = WhitelistMap.create() + + @_whitelist_for_serdes(test_env) + class SomeDagsterModel(DagsterModel): + unaliased_id: int = Field(..., alias="id_alias") + name: str + + o = SomeDagsterModel(id_alias=5, name="fdsk") + packed_o = pack_value(o, whitelist_map=test_env) + assert packed_o == {"__class__": "SomeDagsterModel", "id_alias": 5, "name": "fdsk"} + assert unpack_value(packed_o, whitelist_map=test_env, as_type=SomeDagsterModel) == o + + ser_o = serialize_value(o, whitelist_map=test_env) + assert deserialize_value(ser_o, whitelist_map=test_env) == o + + +def test_pydantic_alias_generator(): + test_env = WhitelistMap.create() + + @_whitelist_for_serdes(test_env) + class SomeDagsterModel(DagsterModel): + id: int = Field(...) + name: str + + class Config: + alias_generator = lambda field_name: f"{field_name}_alias" + + o = SomeDagsterModel(id_alias=5, name_alias="fdsk") + packed_o = pack_value(o, whitelist_map=test_env) + assert packed_o == {"__class__": "SomeDagsterModel", "id_alias": 5, "name_alias": "fdsk"} + assert unpack_value(packed_o, whitelist_map=test_env, as_type=SomeDagsterModel) == o + + ser_o = serialize_value(o, whitelist_map=test_env) + assert deserialize_value(ser_o, whitelist_map=test_env) == o + + +@pytest.mark.skipif(USING_PYDANTIC_1, reason="No serialization_alias in pydantic 1") +def test_pydantic_serialization_alias(): + test_env = WhitelistMap.create() + + @_whitelist_for_serdes(test_env) + class SomeDagsterModel(DagsterModel): + unaliased_id: int = Field(..., serialization_alias="id_alias") + name: str + + o = SomeDagsterModel(unaliased_id=5, name="fdsk") + with pytest.raises( + SerializationError, + match="Can't serialize pydantic models with serialization or validation aliases.", + ): + serialize_value(o, whitelist_map=test_env) + + with pytest.raises( + SerializationError, + match="Can't serialize pydantic models with serialization or validation aliases.", + ): + pack_value(o, whitelist_map=test_env) + + +@pytest.mark.skipif(USING_PYDANTIC_1, reason="No validation_alias in pydantic 1") +def test_pydantic_validation_alias(): + test_env = WhitelistMap.create() + + @_whitelist_for_serdes(test_env) + class SomeDagsterModel(DagsterModel): + unaliased_id: int = Field(..., validation_alias="id_alias") + name: str + + o = SomeDagsterModel(id_alias=5, name="fdsk") + with pytest.raises( + SerializationError, + match="Can't serialize pydantic models with serialization or validation aliases.", + ): + serialize_value(o, whitelist_map=test_env) + + with pytest.raises( + SerializationError, + match="Can't serialize pydantic models with serialization or validation aliases.", + ): + pack_value(o, whitelist_map=test_env) From c64a47d3cda1bad2bab36d79b99ee715a0002905 Mon Sep 17 00:00:00 2001 From: Marco polo Date: Fri, 26 Apr 2024 11:19:30 -0400 Subject: [PATCH 12/56] Remove custom graphql error handling logic (#21398) ## Summary & Motivation - This logic is nonsense according to new @apollo/client types when we upgrade. I recently also removed it from cloud: - https://github.com/dagster-io/internal/blob/master/dagster-cloud/js_modules/app-cloud/src/App.tsx#L54-L74 From 638a4d40df6fae2355e70b97db2e1027d9d983a7 Mon Sep 17 00:00:00 2001 From: gibsondan Date: Fri, 26 Apr 2024 10:20:21 -0500 Subject: [PATCH 13/56] Add a recovery interval when a daemon raises an exception in its core_loop function (#21408) Summary: I think https://github.com/dagster-io/dagster/pull/21384 caught all the places that we were actually sending an exception up into core_loop - but if we do again, make it wait a few seconds instead of potentially spamming errors in a tight loop. Test Plan: Add an exception to a core_loop call, run dagster dev locally, see errors spaced apart ## Summary & Motivation ## How I Tested These Changes --- .../test_dagster_daemon_health.py | 180 +++++++++--------- .../dagster/dagster/_daemon/daemon.py | 9 + 2 files changed, 100 insertions(+), 89 deletions(-) diff --git a/integration_tests/test_suites/daemon-test-suite/test_dagster_daemon_health.py b/integration_tests/test_suites/daemon-test-suite/test_dagster_daemon_health.py index 5aef588885117..49530c50439e4 100644 --- a/integration_tests/test_suites/daemon-test-suite/test_dagster_daemon_health.py +++ b/integration_tests/test_suites/daemon-test-suite/test_dagster_daemon_health.py @@ -3,7 +3,7 @@ import pendulum import pytest from dagster import DagsterInvariantViolationError -from dagster._core.test_utils import instance_for_test +from dagster._core.test_utils import environ, instance_for_test from dagster._core.workspace.load_target import EmptyWorkspaceTarget from dagster._daemon.controller import ( DEFAULT_DAEMON_HEARTBEAT_TOLERANCE_SECONDS, @@ -215,25 +215,91 @@ def _get_error_number(error): gen_daemons = lambda instance: [SensorDaemon(instance.get_sensor_settings())] init_time = pendulum.now("UTC") - with daemon_controller_from_instance( - instance, - workspace_load_target=EmptyWorkspaceTarget(), - heartbeat_interval_seconds=heartbeat_interval_seconds, - gen_daemons=gen_daemons, - error_interval_seconds=10, - ) as controller: - while True: - now = pendulum.now("UTC") + with environ({"DAGSTER_DAEMON_CORE_LOOP_EXCEPTION_SLEEP_INTERVAL": "1"}): + with daemon_controller_from_instance( + instance, + workspace_load_target=EmptyWorkspaceTarget(), + heartbeat_interval_seconds=heartbeat_interval_seconds, + gen_daemons=gen_daemons, + error_interval_seconds=10, + ) as controller: + while True: + now = pendulum.now("UTC") - if get_daemon_statuses( - instance, - [SensorDaemon.daemon_type()], - heartbeat_interval_seconds=heartbeat_interval_seconds, - ignore_errors=True, - )[SensorDaemon.daemon_type()].healthy: - # Despite error, daemon should still be running - controller.check_daemon_threads() - controller.check_daemon_heartbeats() + if get_daemon_statuses( + instance, + [SensorDaemon.daemon_type()], + heartbeat_interval_seconds=heartbeat_interval_seconds, + ignore_errors=True, + )[SensorDaemon.daemon_type()].healthy: + # Despite error, daemon should still be running + controller.check_daemon_threads() + controller.check_daemon_heartbeats() + + status = get_daemon_statuses( + instance, + [SensorDaemon.daemon_type()], + now.float_timestamp, + heartbeat_interval_seconds=heartbeat_interval_seconds, + )[SensorDaemon.daemon_type()] + + # Errors build up until there are > 5, then pull off the last + if status.healthy is False and len(status.last_heartbeat.errors) >= 5: + first_error_number = _get_error_number(status.last_heartbeat.errors[0]) + + if first_error_number > 5: + # Verify error numbers decrease consecutively + assert [ + _get_error_number(error) + for error in status.last_heartbeat.errors + ] == list(range(first_error_number, first_error_number - 5, -1)) + + assert not get_daemon_statuses( + instance, + [SensorDaemon.daemon_type()], + curr_time_seconds=now.float_timestamp, + heartbeat_interval_seconds=heartbeat_interval_seconds, + )[SensorDaemon.daemon_type()].healthy + assert get_daemon_statuses( + instance, + [SensorDaemon.daemon_type()], + curr_time_seconds=now.float_timestamp, + heartbeat_interval_seconds=heartbeat_interval_seconds, + ignore_errors=True, + )[SensorDaemon.daemon_type()].healthy + + time.sleep(3) + + status = get_daemon_statuses( + instance, + [SensorDaemon.daemon_type()], + now.float_timestamp, + heartbeat_interval_seconds=heartbeat_interval_seconds, + )[SensorDaemon.daemon_type()] + + # Error count does not rise above 5, continues to increase + assert len(status.last_heartbeat.errors) == 5 + + new_first_error_number = _get_error_number( + status.last_heartbeat.errors[0] + ) + + assert new_first_error_number > first_error_number + + break + + if (now - init_time).total_seconds() > 15: + raise Exception("timed out waiting for heartbeat error") + + time.sleep(0.5) + + # Once the sensor no longer raises errors, they should return to 0 once + # enough time passes + should_raise_errors = False + init_time = pendulum.now("UTC") + + while True: + now = pendulum.now("UTC") status = get_daemon_statuses( instance, @@ -242,78 +308,14 @@ def _get_error_number(error): heartbeat_interval_seconds=heartbeat_interval_seconds, )[SensorDaemon.daemon_type()] - # Errors build up until there are > 5, then pull off the last - if status.healthy is False and len(status.last_heartbeat.errors) >= 5: - first_error_number = _get_error_number(status.last_heartbeat.errors[0]) - - if first_error_number > 5: - # Verify error numbers decrease consecutively - assert [ - _get_error_number(error) for error in status.last_heartbeat.errors - ] == list(range(first_error_number, first_error_number - 5, -1)) - - assert not get_daemon_statuses( - instance, - [SensorDaemon.daemon_type()], - curr_time_seconds=now.float_timestamp, - heartbeat_interval_seconds=heartbeat_interval_seconds, - )[SensorDaemon.daemon_type()].healthy - assert get_daemon_statuses( - instance, - [SensorDaemon.daemon_type()], - curr_time_seconds=now.float_timestamp, - heartbeat_interval_seconds=heartbeat_interval_seconds, - ignore_errors=True, - )[SensorDaemon.daemon_type()].healthy - - time.sleep(3) - - status = get_daemon_statuses( - instance, - [SensorDaemon.daemon_type()], - now.float_timestamp, - heartbeat_interval_seconds=heartbeat_interval_seconds, - )[SensorDaemon.daemon_type()] - - # Error count does not rise above 5, continues to increase - assert len(status.last_heartbeat.errors) == 5 - - new_first_error_number = _get_error_number( - status.last_heartbeat.errors[0] - ) - - assert new_first_error_number > first_error_number - - break - - if (now - init_time).total_seconds() > 15: - raise Exception("timed out waiting for heartbeat error") - - time.sleep(0.5) - - # Once the sensor no longer raises errors, they should return to 0 once - # enough time passes - should_raise_errors = False - init_time = pendulum.now("UTC") - - while True: - now = pendulum.now("UTC") - - status = get_daemon_statuses( - instance, - [SensorDaemon.daemon_type()], - now.float_timestamp, - heartbeat_interval_seconds=heartbeat_interval_seconds, - )[SensorDaemon.daemon_type()] - - # Error count does not rise above 5 - if len(status.last_heartbeat.errors) == 0: - break + # Error count does not rise above 5 + if len(status.last_heartbeat.errors) == 0: + break - if (now - init_time).total_seconds() > 15: - raise Exception("timed out waiting for hearrteat errors to return to 0") + if (now - init_time).total_seconds() > 15: + raise Exception("timed out waiting for hearrteat errors to return to 0") - time.sleep(0.5) + time.sleep(0.5) def test_multiple_error_daemon(monkeypatch): diff --git a/python_modules/dagster/dagster/_daemon/daemon.py b/python_modules/dagster/dagster/_daemon/daemon.py index d5092ca9b4a0b..30beea270a2f1 100644 --- a/python_modules/dagster/dagster/_daemon/daemon.py +++ b/python_modules/dagster/dagster/_daemon/daemon.py @@ -1,4 +1,5 @@ import logging +import os import sys import time import uuid @@ -47,6 +48,10 @@ def get_default_daemon_logger(daemon_name) -> logging.Logger: _telemetry_daemon_session_id = str(uuid.uuid4()) +def _get_error_sleep_interval(): + return int(os.getenv("DAGSTER_DAEMON_CORE_LOOP_EXCEPTION_SLEEP_INTERVAL", "5")) + + def get_telemetry_daemon_session_id() -> str: return _telemetry_daemon_session_id @@ -132,6 +137,10 @@ def run_daemon_loop( ) self._errors.appendleft((error_info, pendulum.now("UTC"))) daemon_generator.close() + + # Wait a bit to ensure that errors don't happen in a tight loop + daemon_shutdown_event.wait(_get_error_sleep_interval()) + daemon_generator = self.core_loop( workspace_process_context, daemon_shutdown_event ) From 5b6e979d4fb355ec701f650e66c603366c6a3b17 Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Fri, 26 Apr 2024 08:34:00 -0700 Subject: [PATCH 14/56] correct mistake in pydantic compat layer (#21448) ## Summary & Motivation ## How I Tested These Changes --- python_modules/dagster/dagster/_model/pydantic_compat_layer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python_modules/dagster/dagster/_model/pydantic_compat_layer.py b/python_modules/dagster/dagster/_model/pydantic_compat_layer.py index 5beb85a702f7c..cbabc906597df 100644 --- a/python_modules/dagster/dagster/_model/pydantic_compat_layer.py +++ b/python_modules/dagster/dagster/_model/pydantic_compat_layer.py @@ -53,7 +53,7 @@ def serialization_alias(self) -> Optional[str]: @property def validation_alias(self) -> Optional[str]: - return getattr(self.field, "serialization_alias", None) + return getattr(self.field, "validation_alias", None) @property def default(self) -> Any: From e81bb9088cbb90ff09a406770ac91d68ec42e598 Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Fri, 26 Apr 2024 08:36:55 -0700 Subject: [PATCH 15/56] fix error typo in asset_job.py (#21449) ## Summary & Motivation ## How I Tested These Changes --- python_modules/dagster/dagster/_core/definitions/asset_job.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python_modules/dagster/dagster/_core/definitions/asset_job.py b/python_modules/dagster/dagster/_core/definitions/asset_job.py index 30e563f79f985..64c4e9968e1ea 100644 --- a/python_modules/dagster/dagster/_core/definitions/asset_job.py +++ b/python_modules/dagster/dagster/_core/definitions/asset_job.py @@ -291,7 +291,7 @@ def get_asset_graph_for_job( invalid_keys = selected_keys - parent_asset_graph.executable_asset_keys if invalid_keys: raise DagsterInvalidDefinitionError( - "Selected keys keys must be a subset of existing executable asset keys." + "Selected keys must be a subset of existing executable asset keys." f" Invalid selected keys: {invalid_keys}", ) From 4f5139af8bb111c4e565b98b5bfc05d7f942a2a9 Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Fri, 26 Apr 2024 09:03:37 -0700 Subject: [PATCH 16/56] MetadataValue subclasses to DagsterModel (#21324) ## Summary & Motivation This is a tricky one because it lies at the intersection of generics, inheritance, and pydantic. I tried a bunch of different approaches here. The obvious approach, where `IntMetadataValue` has a `value: Optional[int]`, raises this error: ``` NameError: Field name "value" shadows an attribute in parent "MetadataValue"; you might want to use a different field name with "alias='value'". ``` This approach depends on serializing using field aliases: https://github.com/dagster-io/dagster/pull/21325. ## How I Tested These Changes --- .../_core/definitions/metadata/__init__.py | 345 ++++++++---------- .../dagster_tests/core_tests/test_metadata.py | 82 ++++- .../execution_tests/test_metadata.py | 30 -- 3 files changed, 232 insertions(+), 225 deletions(-) diff --git a/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py b/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py index 175503943ef05..2a49d7c1763a0 100644 --- a/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py +++ b/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py @@ -17,6 +17,7 @@ cast, ) +from pydantic import Field from typing_extensions import Self, TypeAlias, TypeVar import dagster._check as check @@ -614,129 +615,124 @@ def null() -> "NullMetadataValue": @whitelist_for_serdes(storage_name="TextMetadataEntryData") -class TextMetadataValue( - NamedTuple( - "_TextMetadataValue", - [ - ("text", PublicAttr[Optional[str]]), - ], - ), - MetadataValue[str], -): +class TextMetadataValue(DagsterModel, MetadataValue[str]): """Container class for text metadata entry data. Args: text (Optional[str]): The text data. """ - def __new__(cls, text: Optional[str]): - return super(TextMetadataValue, cls).__new__( - cls, check.opt_str_param(text, "text", default="") - ) + text_inner: Optional[str] = Field(..., alias="text") + + def __init__(self, text: Optional[str]): + super().__init__(text=text or "") + + @public + @property + def text(self) -> Optional[str]: + return self.text_inner @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped text data.""" - return self.text + return self.text_inner @whitelist_for_serdes(storage_name="UrlMetadataEntryData") -class UrlMetadataValue( - NamedTuple( - "_UrlMetadataValue", - [ - ("url", PublicAttr[Optional[str]]), - ], - ), - MetadataValue[str], -): +class UrlMetadataValue(DagsterModel, MetadataValue[str]): """Container class for URL metadata entry data. Args: url (Optional[str]): The URL as a string. """ - def __new__(cls, url: Optional[str]): - return super(UrlMetadataValue, cls).__new__( - cls, check.opt_str_param(url, "url", default="") - ) + url_inner: Optional[str] = Field(..., alias="url") + + def __init__(self, url: Optional[str]): + super().__init__(url=url or "") @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped URL.""" - return self.url + return self.url_inner + + @public + @property + def url(self) -> Optional[str]: + """Optional[str]: The wrapped URL.""" + return self.url_inner @whitelist_for_serdes(storage_name="PathMetadataEntryData") -class PathMetadataValue( - NamedTuple("_PathMetadataValue", [("path", PublicAttr[Optional[str]])]), MetadataValue[str] -): +class PathMetadataValue(DagsterModel, MetadataValue[str]): """Container class for path metadata entry data. Args: path (Optional[str]): The path as a string or conforming to os.PathLike. """ - def __new__(cls, path: Optional[Union[str, os.PathLike]]): - return super(PathMetadataValue, cls).__new__( - cls, check.opt_path_param(path, "path", default="") - ) + path_inner: Optional[str] = Field(..., alias="path") + + def __init__(self, path: Optional[Union[str, os.PathLike]]): + super().__init__(path=check.opt_path_param(path, "path", default="")) + + @public + @property + def path(self) -> Optional[str]: + return self.path_inner @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped path.""" - return self.path + return self.path_inner @whitelist_for_serdes(storage_name="NotebookMetadataEntryData") -class NotebookMetadataValue( - NamedTuple("_NotebookMetadataValue", [("path", PublicAttr[Optional[str]])]), MetadataValue[str] -): +class NotebookMetadataValue(DagsterModel, MetadataValue[str]): """Container class for notebook metadata entry data. Args: path (Optional[str]): The path to the notebook as a string or conforming to os.PathLike. """ - def __new__(cls, path: Optional[Union[str, os.PathLike]]): - return super(NotebookMetadataValue, cls).__new__( - cls, check.opt_path_param(path, "path", default="") - ) + path_inner: Optional[str] = Field(..., alias="path") + + def __init__(self, path: Optional[Union[str, os.PathLike]]): + super().__init__(path=check.opt_path_param(path, "path", default="")) + + @public + @property + def path(self) -> Optional[str]: + return self.path_inner @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped path to the notebook as a string.""" - return self.path + return self.path_inner @whitelist_for_serdes(storage_name="JsonMetadataEntryData") -class JsonMetadataValue( - NamedTuple( - "_JsonMetadataValue", - [ - ("data", PublicAttr[Optional[Union[Sequence[Any], Mapping[str, Any]]]]), - ], - ), - MetadataValue[Union[Sequence[Any], Mapping[str, Any]]], -): +class JsonMetadataValue(DagsterModel, MetadataValue[Union[Sequence[Any], Mapping[str, Any]]]): """Container class for JSON metadata entry data. Args: data (Union[Sequence[Any], Dict[str, Any]]): The JSON data. """ - def __new__(cls, data: Optional[Union[Sequence[Any], Mapping[str, Any]]]): + data: PublicAttr[Optional[Union[Sequence[Any], Mapping[str, Any]]]] + + def __init__(self, data: Optional[Union[Sequence[Any], Mapping[str, Any]]]): data = check.opt_inst_param(data, "data", (Sequence, Mapping)) try: # check that the value is JSON serializable seven.dumps(data) except TypeError: raise DagsterInvalidMetadata("Value is not JSON serializable.") - return super(JsonMetadataValue, cls).__new__(cls, data) + super().__init__(data=data) @public @property @@ -746,25 +742,17 @@ def value(self) -> Optional[Union[Sequence[Any], Mapping[str, Any]]]: @whitelist_for_serdes(storage_name="MarkdownMetadataEntryData") -class MarkdownMetadataValue( - NamedTuple( - "_MarkdownMetadataValue", - [ - ("md_str", PublicAttr[Optional[str]]), - ], - ), - MetadataValue[str], -): +class MarkdownMetadataValue(DagsterModel, MetadataValue[str]): """Container class for markdown metadata entry data. Args: md_str (Optional[str]): The markdown as a string. """ - def __new__(cls, md_str: Optional[str]): - return super(MarkdownMetadataValue, cls).__new__( - cls, check.opt_str_param(md_str, "md_str", default="") - ) + md_str: PublicAttr[Optional[str]] + + def __init__(self, md_str: Optional[str]): + super().__init__(md_str=md_str or "") @public @property @@ -775,16 +763,7 @@ def value(self) -> Optional[str]: # This should be deprecated or fixed so that `value` does not return itself. @whitelist_for_serdes(storage_name="PythonArtifactMetadataEntryData") -class PythonArtifactMetadataValue( - NamedTuple( - "_PythonArtifactMetadataValue", - [ - ("module", PublicAttr[str]), - ("name", PublicAttr[str]), - ], - ), - MetadataValue["PythonArtifactMetadataValue"], -): +class PythonArtifactMetadataValue(DagsterModel, MetadataValue["PythonArtifactMetadataValue"]): """Container class for python artifact metadata entry data. Args: @@ -792,10 +771,11 @@ class PythonArtifactMetadataValue( name (str): The name of the python artifact """ - def __new__(cls, module: str, name: str): - return super(PythonArtifactMetadataValue, cls).__new__( - cls, check.str_param(module, "module"), check.str_param(name, "name") - ) + module: PublicAttr[str] + name: PublicAttr[str] + + def __init__(self, module: str, name: str): + super().__init__(module=module, name=name) @public @property @@ -805,96 +785,93 @@ def value(self) -> Self: @whitelist_for_serdes(storage_name="FloatMetadataEntryData") -class FloatMetadataValue( - NamedTuple( - "_FloatMetadataValue", - [ - ("value", PublicAttr[Optional[float]]), - ], - ), - MetadataValue[float], -): +class FloatMetadataValue(DagsterModel, MetadataValue[float]): """Container class for float metadata entry data. Args: value (Optional[float]): The float value. """ - def __new__(cls, value: Optional[float]): - return super(FloatMetadataValue, cls).__new__(cls, check.opt_float_param(value, "value")) + value_inner: Optional[float] = Field(..., alias="value") + + def __init__(self, value: Optional[float]): + super().__init__(value=value) + + @public + @property + def value(self) -> Optional[float]: + return self.value_inner @whitelist_for_serdes(storage_name="IntMetadataEntryData") -class IntMetadataValue( - NamedTuple( - "_IntMetadataValue", - [ - ("value", PublicAttr[Optional[int]]), - ], - ), - MetadataValue[int], -): +class IntMetadataValue(DagsterModel, MetadataValue[int]): """Container class for int metadata entry data. Args: value (Optional[int]): The int value. """ - def __new__(cls, value: Optional[int]): - return super(IntMetadataValue, cls).__new__(cls, check.opt_int_param(value, "value")) + value_inner: Optional[int] = Field(..., alias="value") + + def __init__(self, value: Optional[int]): + super().__init__(value=value) + + @public + @property + def value(self) -> Optional[int]: + return self.value_inner @whitelist_for_serdes(storage_name="BoolMetadataEntryData") -class BoolMetadataValue( - NamedTuple("_BoolMetadataValue", [("value", PublicAttr[Optional[bool]])]), - MetadataValue[bool], -): +class BoolMetadataValue(DagsterModel, MetadataValue[bool]): """Container class for bool metadata entry data. Args: value (Optional[bool]): The bool value. """ - def __new__(cls, value: Optional[bool]): - return super(BoolMetadataValue, cls).__new__(cls, check.opt_bool_param(value, "value")) + value_inner: Optional[bool] = Field(..., alias="value") + + def __init__(self, value: Optional[bool]): + super().__init__(value=value) + + @public + @property + def value(self) -> Optional[bool]: + return self.value_inner @whitelist_for_serdes -class TimestampMetadataValue( - NamedTuple( - "_DateTimeMetadataValue", - [("value", PublicAttr[float])], - ), - MetadataValue[float], -): +class TimestampMetadataValue(DagsterModel, MetadataValue[float]): """Container class for metadata value that's a unix timestamp. Args: value (float): Seconds since the unix epoch. """ - def __new__(cls, value: float): - return super(TimestampMetadataValue, cls).__new__(cls, check.float_param(value, "value")) + value_inner: Optional[float] = Field(..., alias="value") + + def __init__(self, value: float): + super().__init__(value=value) + + @public + @property + def value(self) -> Optional[float]: + return self.value_inner @whitelist_for_serdes(storage_name="DagsterPipelineRunMetadataEntryData") -class DagsterRunMetadataValue( - NamedTuple( - "_DagsterRunMetadataValue", - [ - ("run_id", PublicAttr[str]), - ], - ), - MetadataValue[str], -): +class DagsterRunMetadataValue(DagsterModel, MetadataValue[str]): """Representation of a dagster run. Args: run_id (str): The run id """ - def __new__(cls, run_id: str): - return super(DagsterRunMetadataValue, cls).__new__(cls, check.str_param(run_id, "run_id")) + run_id: PublicAttr[str] + + def __init__(self, run_id: str): + super().__init__(run_id=run_id) @public @property @@ -904,17 +881,7 @@ def value(self) -> str: @whitelist_for_serdes -class DagsterJobMetadataValue( - NamedTuple( - "_DagsterJobMetadataValue", - [ - ("job_name", PublicAttr[str]), - ("location_name", PublicAttr[str]), - ("repository_name", PublicAttr[Optional[str]]), - ], - ), - MetadataValue["DagsterJobMetadataValue"], -): +class DagsterJobMetadataValue(DagsterModel, MetadataValue["DagsterJobMetadataValue"]): """Representation of a dagster run. Args: @@ -924,17 +891,20 @@ class DagsterJobMetadataValue( assumed to be in the same repository as this object. """ - def __new__( - cls, + job_name: PublicAttr[str] + location_name: PublicAttr[str] + repository_name: PublicAttr[Optional[str]] + + def __init__( + self, job_name: str, location_name: str, repository_name: Optional[str] = None, ): - return super(DagsterJobMetadataValue, cls).__new__( - cls, - check.str_param(job_name, "job_name"), - check.str_param(location_name, "location_name"), - check.opt_str_param(repository_name, "repository_name"), + super().__init__( + job_name=job_name, + location_name=location_name, + repository_name=repository_name, ) @public @@ -944,22 +914,17 @@ def value(self) -> Self: @whitelist_for_serdes(storage_name="DagsterAssetMetadataEntryData") -class DagsterAssetMetadataValue( - NamedTuple("_DagsterAssetMetadataValue", [("asset_key", PublicAttr["AssetKey"])]), - MetadataValue["AssetKey"], -): +class DagsterAssetMetadataValue(DagsterModel, MetadataValue[AssetKey]): """Representation of a dagster asset. Args: asset_key (AssetKey): The dagster asset key """ - def __new__(cls, asset_key: "AssetKey"): - from dagster._core.definitions.events import AssetKey + asset_key: PublicAttr[AssetKey] - return super(DagsterAssetMetadataValue, cls).__new__( - cls, check.inst_param(asset_key, "asset_key", AssetKey) - ) + def __init__(self, asset_key: AssetKey): + super().__init__(asset_key=asset_key) @public @property @@ -971,16 +936,7 @@ def value(self) -> "AssetKey": # This should be deprecated or fixed so that `value` does not return itself. @experimental @whitelist_for_serdes(storage_name="TableMetadataEntryData") -class TableMetadataValue( - NamedTuple( - "_TableMetadataValue", - [ - ("records", PublicAttr[Sequence[TableRecord]]), - ("schema", PublicAttr[TableSchema]), - ], - ), - MetadataValue["TableMetadataValue"], -): +class TableMetadataValue(DagsterModel, MetadataValue["TableMetadataValue"]): """Container class for table metadata entry data. Args: @@ -1001,6 +957,9 @@ class TableMetadataValue( ) """ + records: PublicAttr[Sequence[TableRecord]] + schema_inner: TableSchema = Field(..., alias="schema") + @public @staticmethod def infer_column_type(value: object) -> str: @@ -1014,7 +973,7 @@ def infer_column_type(value: object) -> str: else: return "string" - def __new__(cls, records: Sequence[TableRecord], schema: Optional[TableSchema]): + def __init__(self, records: Sequence[TableRecord], schema: Optional[TableSchema] = None): check.sequence_param(records, "records", of_type=TableRecord) check.opt_inst_param(schema, "schema", TableSchema) @@ -1033,11 +992,12 @@ def __new__(cls, records: Sequence[TableRecord], schema: Optional[TableSchema]): ] ) - return super(TableMetadataValue, cls).__new__( - cls, - records, - schema, - ) + super().__init__(records=records, schema=schema) + + @public + @property + def schema(self) -> TableSchema: + return self.schema_inner @public @property @@ -1047,35 +1007,32 @@ def value(self) -> Self: @whitelist_for_serdes(storage_name="TableSchemaMetadataEntryData") -class TableSchemaMetadataValue( - NamedTuple("_TableSchemaMetadataValue", [("schema", PublicAttr[TableSchema])]), - MetadataValue[TableSchema], -): +class TableSchemaMetadataValue(DagsterModel, MetadataValue[TableSchema]): """Representation of a schema for arbitrary tabular data. Args: schema (TableSchema): The dictionary containing the schema representation. """ - def __new__(cls, schema: TableSchema): - return super(TableSchemaMetadataValue, cls).__new__( - cls, check.inst_param(schema, "schema", TableSchema) - ) + schema_inner: TableSchema = Field(..., alias="schema") + + def __init__(self, schema: TableSchema): + super().__init__(schema=schema) @public @property def value(self) -> TableSchema: """TableSchema: The wrapped :py:class:`TableSchema`.""" - return self.schema + return self.schema_inner + + @public + @property + def schema(self) -> TableSchema: + return self.schema_inner @whitelist_for_serdes -class TableColumnLineageMetadataValue( - NamedTuple( - "_TableColumnLineageMetadataValue", [("column_lineage", PublicAttr[TableColumnLineage])] - ), - MetadataValue[TableColumnLineage], -): +class TableColumnLineageMetadataValue(DagsterModel, MetadataValue[TableColumnLineage]): """Representation of the lineage of column inputs to column outputs of arbitrary tabular data. Args: @@ -1083,20 +1040,20 @@ class TableColumnLineageMetadataValue( for the table. """ - def __new__(cls, column_lineage: TableColumnLineage): - return super(TableColumnLineageMetadataValue, cls).__new__( - cls, check.inst_param(column_lineage, "column_lineage", TableColumnLineage) - ) + column_lineage_inner: TableColumnLineage = Field(..., alias="column_lineage") + + def __init__(self, column_lineage: TableColumnLineage): + super().__init__(column_lineage=column_lineage) @public @property def value(self) -> TableColumnLineage: """TableSpec: The wrapped :py:class:`TableSpec`.""" - return self.column_lineage + return self.column_lineage_inner @whitelist_for_serdes(storage_name="NullMetadataEntryData") -class NullMetadataValue(NamedTuple("_NullMetadataValue", []), MetadataValue[None]): +class NullMetadataValue(DagsterModel, MetadataValue[None]): """Representation of null.""" @public diff --git a/python_modules/dagster/dagster_tests/core_tests/test_metadata.py b/python_modules/dagster/dagster_tests/core_tests/test_metadata.py index 1f30f2a37ef15..c96b2a28e6460 100644 --- a/python_modules/dagster/dagster_tests/core_tests/test_metadata.py +++ b/python_modules/dagster/dagster_tests/core_tests/test_metadata.py @@ -1,4 +1,21 @@ -from dagster import GraphDefinition, NodeInvocation, op +from dagster import ( + AssetKey, + GraphDefinition, + IntMetadataValue, + JsonMetadataValue, + MetadataValue, + NodeInvocation, + TableColumn, + TableColumnDep, + TableColumnLineage, + TableMetadataValue, + TableRecord, + TableSchema, + TableSchemaMetadataValue, + UrlMetadataValue, + op, +) +from dagster._serdes.serdes import deserialize_value, serialize_value def test_op_instance_tags(): @@ -25,3 +42,66 @@ def metadata_op(context): assert result.success assert called["yup"] + + +def test_table_schema_from_name_type_dict(): + assert TableSchema.from_name_type_dict({"foo": "customtype", "bar": "string"}) == TableSchema( + columns=[ + TableColumn(name="foo", type="customtype"), + TableColumn(name="bar", type="string"), + ], + ) + + +def test_table_serialization(): + table_metadata = MetadataValue.table( + records=[ + TableRecord(dict(foo=1, bar=2)), + ], + ) + serialized = serialize_value(table_metadata) + assert deserialize_value(serialized, TableMetadataValue) == table_metadata + + +def test_metadata_value_column_lineage() -> None: + expected_column_lineage = TableColumnLineage( + {"foo": [TableColumnDep(asset_key=AssetKey("bar"), column_name="baz")]} + ) + column_lineage_metadata_value = MetadataValue.column_lineage(expected_column_lineage) + + assert column_lineage_metadata_value.value == expected_column_lineage + + +def test_int_metadata_value(): + assert IntMetadataValue(5).value == 5 + assert IntMetadataValue(value=5).value == 5 + + +def test_url_metadata_value(): + url = "http://dagster.io" + assert UrlMetadataValue(url).value == url + assert UrlMetadataValue(url).url == url + assert UrlMetadataValue(url=url).value == url + + +def test_table_metadata_value(): + records = [TableRecord(dict(foo=1, bar=2))] + schema = TableSchema( + columns=[TableColumn(name="foo", type="int"), TableColumn(name="bar", type="int")] + ) + metadata_val = TableMetadataValue(records, schema=schema) + + assert metadata_val.records == records + assert metadata_val.schema == schema + + +def test_table_schema_metadata_value(): + schema = TableSchema( + columns=[TableColumn(name="foo", type="int"), TableColumn(name="bar", type="int")] + ) + assert TableSchemaMetadataValue(schema).schema == schema + + +def test_json_metadata_value(): + assert JsonMetadataValue({"a": "b"}).data == {"a": "b"} + assert JsonMetadataValue({"a": "b"}).value == {"a": "b"} diff --git a/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py b/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py index 4bc99b6c46669..9c5b51b774960 100644 --- a/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py +++ b/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py @@ -29,7 +29,6 @@ from dagster._core.definitions.metadata import ( DagsterInvalidMetadata, TableColumnLineageMetadataValue, - TableMetadataValue, normalize_metadata, ) from dagster._core.definitions.metadata.table import ( @@ -43,7 +42,6 @@ ) from dagster._core.execution.execution_result import ExecutionResult from dagster._core.snap.node import build_node_defs_snapshot -from dagster._serdes.serdes import deserialize_value, serialize_value def step_events_of_type(result: ExecutionResult, node_name: str, event_type: DagsterEventType): @@ -370,34 +368,6 @@ def test_complex_table_schema(): ) -def test_table_schema_from_name_type_dict(): - assert TableSchema.from_name_type_dict({"foo": "customtype", "bar": "string"}) == TableSchema( - columns=[ - TableColumn(name="foo", type="customtype"), - TableColumn(name="bar", type="string"), - ], - ) - - -def test_table_serialization(): - table_metadata = MetadataValue.table( - records=[ - TableRecord(dict(foo=1, bar=2)), - ], - ) - serialized = serialize_value(table_metadata) - assert deserialize_value(serialized, TableMetadataValue) == table_metadata - - -def test_metadata_value_column_lineage() -> None: - expected_column_lineage = TableColumnLineage( - {"foo": [TableColumnDep(asset_key=AssetKey("bar"), column_name="baz")]} - ) - column_lineage_metadata_value = MetadataValue.column_lineage(expected_column_lineage) - - assert column_lineage_metadata_value.value == expected_column_lineage - - def test_bool_metadata_value(): @op(out={}) def the_op(): From 8247864fb3cc8dea679512e69d3f43ec7cf5e135 Mon Sep 17 00:00:00 2001 From: Marco polo Date: Fri, 26 Apr 2024 12:38:17 -0400 Subject: [PATCH 17/56] Make `usePageContext` return the correct path no matter where its called (#21433) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ## Summary & Motivation To log page load we need to inform datadog when a new view starts. To do this we currently rely on `usePageContext` to change when the path changes. Currently it doesn't do that because `usePageContext` relies on `useRouteMatch` from react-router-dom which finds the path from the closest parent `Route`. The issue is that we're calling `usePageContext` from a provider that is very high up in the tree, so `useRouteMatch` can't access the context of the `` currently being rendered. Instead of using `useRouteMatch` lets store the path in global state when `useTrackPageView` is called and have `usePageContext` rely on that global state. Cloud requires this change to dedupe recoil: https://github.com/dagster-io/internal/pull/9471 ## How I Tested These Changes 👀 , play around with the app make sure nothing is broken --- .../dagster-ui/packages/app-oss/package.json | 1 + .../dagster-ui/packages/app-oss/src/App.tsx | 35 ++++++----- .../dagster-ui/packages/ui-core/package.json | 1 + .../src/app/__tests__/analytics.test.tsx | 63 ++++++++++--------- .../packages/ui-core/src/app/analytics.tsx | 32 ++++++---- .../backfill/__tests__/BackfillPage.test.tsx | 61 ++++++++++-------- .../ui-core/src/testing/TestProvider.tsx | 43 +++++++------ js_modules/dagster-ui/yarn.lock | 25 ++++++++ 8 files changed, 159 insertions(+), 102 deletions(-) diff --git a/js_modules/dagster-ui/packages/app-oss/package.json b/js_modules/dagster-ui/packages/app-oss/package.json index 1a66dbddeba87..6b880703f5e2f 100644 --- a/js_modules/dagster-ui/packages/app-oss/package.json +++ b/js_modules/dagster-ui/packages/app-oss/package.json @@ -22,6 +22,7 @@ "react-router": "^5.2.1", "react-router-dom": "^5.3.0", "react-router-dom-v5-compat": "^6.3.0", + "recoil": "^0.7.7", "styled-components": "^5.3.3", "uuid": "^9.0.0", "validator": "^13.7.0", diff --git a/js_modules/dagster-ui/packages/app-oss/src/App.tsx b/js_modules/dagster-ui/packages/app-oss/src/App.tsx index ea164669840a7..7533e97739d11 100644 --- a/js_modules/dagster-ui/packages/app-oss/src/App.tsx +++ b/js_modules/dagster-ui/packages/app-oss/src/App.tsx @@ -10,6 +10,7 @@ import {logLink, timeStartLink} from '@dagster-io/ui-core/app/apolloLinks'; import {DeploymentStatusType} from '@dagster-io/ui-core/instance/DeploymentStatusProvider'; import {LiveDataPollRateContext} from '@dagster-io/ui-core/live-data-provider/LiveDataProvider'; import {Suspense} from 'react'; +import {RecoilRoot} from 'recoil'; import {InjectedComponents} from './InjectedComponents'; import {CommunityNux} from './NUX/CommunityNux'; @@ -40,21 +41,23 @@ const appCache = createAppCache(); // eslint-disable-next-line import/no-default-export export default function AppPage() { return ( - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + ); } diff --git a/js_modules/dagster-ui/packages/ui-core/package.json b/js_modules/dagster-ui/packages/ui-core/package.json index 02d34ef6f190c..d4a10b3dcb97b 100644 --- a/js_modules/dagster-ui/packages/ui-core/package.json +++ b/js_modules/dagster-ui/packages/ui-core/package.json @@ -62,6 +62,7 @@ "react-is": "^18.2.0", "react-markdown": "^8.0.6", "react-virtualized": "^9.22.3", + "recoil": "^0.7.7", "rehype-highlight": "^6.0.0", "rehype-sanitize": "^5.0.1", "remark": "^14.0.2", diff --git a/js_modules/dagster-ui/packages/ui-core/src/app/__tests__/analytics.test.tsx b/js_modules/dagster-ui/packages/ui-core/src/app/__tests__/analytics.test.tsx index d7251bc697b76..ae559965aeb15 100644 --- a/js_modules/dagster-ui/packages/ui-core/src/app/__tests__/analytics.test.tsx +++ b/js_modules/dagster-ui/packages/ui-core/src/app/__tests__/analytics.test.tsx @@ -2,6 +2,7 @@ import {render, screen, waitFor} from '@testing-library/react'; import userEvent from '@testing-library/user-event'; import * as React from 'react'; import {MemoryRouter, Route, Switch} from 'react-router-dom'; +import {RecoilRoot} from 'recoil'; import {AnalyticsContext, GenericAnalytics, useTrackEvent, useTrackPageView} from '../analytics'; @@ -32,15 +33,17 @@ describe('Analytics', () => { const mockAnalytics = createMockAnalytics(); render( - - - - - - - - - , + + + + + + + + + + + , ); jest.advanceTimersByTime(400); @@ -68,15 +71,17 @@ describe('Analytics', () => { const mockAnalytics = createMockAnalytics(); render( - - - - - - - - - , + + + + + + + + + + + , ); const button = screen.getByRole('button'); @@ -103,17 +108,19 @@ describe('Analytics', () => { const overrideAnalytics = createMockAnalytics(); render( - - - - - - - - + + + + + + + + + + - - , + + , ); jest.advanceTimersByTime(400); diff --git a/js_modules/dagster-ui/packages/ui-core/src/app/analytics.tsx b/js_modules/dagster-ui/packages/ui-core/src/app/analytics.tsx index 54d06c8652d9e..422ab08e65202 100644 --- a/js_modules/dagster-ui/packages/ui-core/src/app/analytics.tsx +++ b/js_modules/dagster-ui/packages/ui-core/src/app/analytics.tsx @@ -1,5 +1,11 @@ -import {createContext, useCallback, useContext, useEffect, useMemo} from 'react'; +import {createContext, useCallback, useContext, useLayoutEffect} from 'react'; import {useLocation, useRouteMatch} from 'react-router-dom'; +import {atom, useRecoilValue, useSetRecoilState} from 'recoil'; + +export const currentPageAtom = atom<{path: string; specificPath: string}>({ + key: 'currentPageAtom', + default: {path: '/', specificPath: '/'}, +}); export interface GenericAnalytics { group?: (groupId: string, traits?: Record) => void; @@ -13,10 +19,7 @@ export const AnalyticsContext = createContext(undefined!); const PAGEVIEW_DELAY = 300; export const usePageContext = () => { - const match = useRouteMatch(); - const {pathname: specificPath} = useLocation(); - const {path} = match; - return useMemo(() => ({path, specificPath}), [path, specificPath]); + return useRecoilValue(currentPageAtom); }; const useAnalytics = () => { @@ -52,28 +55,35 @@ export const dummyAnalytics = () => ({ export const useTrackPageView = () => { const analytics = useAnalytics(); - const {path, specificPath} = usePageContext(); + const match = useRouteMatch(); + const {pathname: specificPath} = useLocation(); + const {path} = match; + + const setCurrentPage = useSetRecoilState(currentPageAtom); - useEffect(() => { + useLayoutEffect(() => { // Wait briefly to allow redirects. const timer = setTimeout(() => { analytics.page(path, specificPath); }, PAGEVIEW_DELAY); + setCurrentPage({path, specificPath}); return () => { clearTimeout(timer); }; - }, [analytics, path, specificPath]); + }, [analytics, path, setCurrentPage, specificPath]); }; export const useTrackEvent = () => { const analytics = useAnalytics(); - const pathValues = usePageContext(); + const match = useRouteMatch(); + const {pathname: specificPath} = useLocation(); + const {path} = match; return useCallback( (eventName: string, properties?: Record) => { - analytics.track(eventName, {...properties, ...pathValues}); + analytics.track(eventName, {...properties, path, specificPath}); }, - [analytics, pathValues], + [analytics, path, specificPath], ); }; diff --git a/js_modules/dagster-ui/packages/ui-core/src/instance/backfill/__tests__/BackfillPage.test.tsx b/js_modules/dagster-ui/packages/ui-core/src/instance/backfill/__tests__/BackfillPage.test.tsx index 6b96256d21108..f66a41e1c5f17 100644 --- a/js_modules/dagster-ui/packages/ui-core/src/instance/backfill/__tests__/BackfillPage.test.tsx +++ b/js_modules/dagster-ui/packages/ui-core/src/instance/backfill/__tests__/BackfillPage.test.tsx @@ -1,6 +1,7 @@ import {MockedProvider} from '@apollo/client/testing'; import {getAllByText, getByText, render, screen, waitFor} from '@testing-library/react'; import {MemoryRouter, Route} from 'react-router-dom'; +import {RecoilRoot} from 'recoil'; import {AnalyticsContext} from '../../../app/analytics'; import { @@ -82,15 +83,17 @@ const mocks = [ describe('BackfillPage', () => { it('renders the loading state', async () => { render( - {}} as any}> - - - - - - - - , + + {}} as any}> + + + + + + + + + , ); expect(await screen.findByTestId('page-loading-indicator')).toBeInTheDocument(); @@ -116,15 +119,17 @@ describe('BackfillPage', () => { ]; const {getByText} = render( - {}} as any}> - - - - - - - - , + + {}} as any}> + + + + + + + + + , ); await waitFor(() => expect(getByText('An error occurred')).toBeVisible()); @@ -132,15 +137,17 @@ describe('BackfillPage', () => { it('renders the loaded state', async () => { render( - {}} as any}> - - - - - - - - , + + {}} as any}> + + + + + + + + + , ); // Check if the loaded content is displayed diff --git a/js_modules/dagster-ui/packages/ui-core/src/testing/TestProvider.tsx b/js_modules/dagster-ui/packages/ui-core/src/testing/TestProvider.tsx index 9f9a1dc464b7f..c4fa454c51176 100644 --- a/js_modules/dagster-ui/packages/ui-core/src/testing/TestProvider.tsx +++ b/js_modules/dagster-ui/packages/ui-core/src/testing/TestProvider.tsx @@ -1,6 +1,7 @@ import {loader} from 'graphql.macro'; import * as React from 'react'; import {MemoryRouter, MemoryRouterProps} from 'react-router-dom'; +import {RecoilRoot} from 'recoil'; import {ApolloTestProps, ApolloTestProvider} from './ApolloTestProvider'; import {AppContext, AppContextValue} from '../app/AppContext'; @@ -73,25 +74,27 @@ export const TestProvider = (props: Props) => { ); return ( - - - - - - - {props.children} - - - - - - + + + + + + + + {props.children} + + + + + + + ); }; diff --git a/js_modules/dagster-ui/yarn.lock b/js_modules/dagster-ui/yarn.lock index 8fa65dd6c0740..2bb517650d27a 100644 --- a/js_modules/dagster-ui/yarn.lock +++ b/js_modules/dagster-ui/yarn.lock @@ -2406,6 +2406,7 @@ __metadata: react-router: "npm:^5.2.1" react-router-dom: "npm:^5.3.0" react-router-dom-v5-compat: "npm:^6.3.0" + recoil: "npm:^0.7.7" styled-components: "npm:^5.3.3" typescript: "npm:5.4.5" uuid: "npm:^9.0.0" @@ -2648,6 +2649,7 @@ __metadata: react-router-dom: "npm:^5.3.0" react-router-dom-v5-compat: "npm:^6.3.0" react-virtualized: "npm:^9.22.3" + recoil: "npm:^0.7.7" rehype-highlight: "npm:^6.0.0" rehype-sanitize: "npm:^5.0.1" remark: "npm:^14.0.2" @@ -14932,6 +14934,13 @@ __metadata: languageName: node linkType: hard +"hamt_plus@npm:1.0.2": + version: 1.0.2 + resolution: "hamt_plus@npm:1.0.2" + checksum: 10/3680a1820b8e03c79e5977edb7e1ccb48b9db853f5a1fbee2d3b3615f8dded7fa276e158f52d3eea8cb6192a27b2622ae2112e197be7602a8f99814793dc096f + languageName: node + linkType: hard + "handlebars@npm:^4.7.7": version: 4.7.8 resolution: "handlebars@npm:4.7.8" @@ -21288,6 +21297,22 @@ __metadata: languageName: node linkType: hard +"recoil@npm:^0.7.7": + version: 0.7.7 + resolution: "recoil@npm:0.7.7" + dependencies: + hamt_plus: "npm:1.0.2" + peerDependencies: + react: ">=16.13.1" + peerDependenciesMeta: + react-dom: + optional: true + react-native: + optional: true + checksum: 10/4ac9dfeddda2795f213b14290de09767b04fb98f1a760bcabe796c53830229f51de63a02cf54c18991c557f25cfeb9571a129ae0a19d734bd98cfc45eebbc82d + languageName: node + linkType: hard + "redent@npm:^3.0.0": version: 3.0.0 resolution: "redent@npm:3.0.0" From 1c3ad4ca087f13dddc720188e1fdcb7e98de68ee Mon Sep 17 00:00:00 2001 From: colton Date: Fri, 26 Apr 2024 14:29:11 -0400 Subject: [PATCH 18/56] [daggy-u][dbt] remove strptime for incremental model (#21425) ## Summary & Motivation - the `%c` format string being used with `strptime` in this context does not appropriately parse `pendulum.datetime` ISO timestampsa linked: https://github.com/dagster-io/project-dagster-university/pull/23 ## How I Tested These Changes - Ran backfill of partitioned model ```python >>> pendulum.now().isoformat() '2024-04-25T11:45:47.749103-04:00' ``` ```sql D select strptime('2024-04-25T11:29:18.217685', '%c'); Invalid Input Error: Could not parse string "2024-04-25T11:29:18.217685" according to format specifier "%c" 2024-04-25T11:29:18.217685 ^ Error: Space does not match, expected ``` --- .../lesson-6/3-creating-a-partitioned-dbt-asset.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/dagster-university/pages/dagster-dbt/lesson-6/3-creating-a-partitioned-dbt-asset.md b/docs/dagster-university/pages/dagster-dbt/lesson-6/3-creating-a-partitioned-dbt-asset.md index a1ed644d3b896..51f1643c78598 100644 --- a/docs/dagster-university/pages/dagster-dbt/lesson-6/3-creating-a-partitioned-dbt-asset.md +++ b/docs/dagster-university/pages/dagster-dbt/lesson-6/3-creating-a-partitioned-dbt-asset.md @@ -86,8 +86,8 @@ First, add the following to the `@dbt_assets` function body, before the `yield`: ```bash time_window = context.partition_time_window dbt_vars = { - "min_date": time_window.start.isoformat(), - "max_date": time_window.end.isoformat() + "min_date": time_window.start.strftime('%Y-%m-%d'), + "max_date": time_window.end.strftime('%Y-%m-%d') } ``` @@ -174,8 +174,8 @@ def dbt_analytics(context: AssetExecutionContext, dbt: DbtCliResource): def incremental_dbt_models(context: AssetExecutionContext, dbt: DbtCliResource): time_window = context.partition_time_window dbt_vars = { - "min_date": time_window.start.isoformat(), - "max_date": time_window.end.isoformat(), + "min_date": time_window.start.strftime('%Y-%m-%d'), + "max_date": time_window.end.strftime('%Y-%m-%d') } yield from dbt.cli( @@ -193,10 +193,10 @@ Finally, we’ll modify the `daily_metrics.sql` file to reflect that dbt knows w In `analytics/models/marts/daily_metrics.sql`, update the contents of the model's incremental logic (`% if is_incremental %}`) to the following: ```sql -where date_of_business >= strptime('{{ var('min_date') }}', '%c') and date_of_business < strptime('{{ var('max_date') }}', '%c') +where date_of_business between '{{ var('min_date') }}' and '{{ var('max_date') }}' ``` -Here, we’ve changed the logic to say that we only want to select rows between the `min_date` and the `max_date`. Note that we are turning the variables into timestamps using `strptime` because they’re loaded as strings. +Here, we’ve changed the logic to say that we only want to select rows between the `min_date` and the `max_date`. --- From 264beb66e97fcc68eb7afac3d8c4bb6085293914 Mon Sep 17 00:00:00 2001 From: colton Date: Fri, 26 Apr 2024 14:33:41 -0400 Subject: [PATCH 19/56] [daggy-u] add pyarrow dependency to dbt course; required for pandas (#21421) - `pyarrow` is required for pandas when reading duckdb/parquet --- examples/project_du_dbt_starter/setup.py | 1 + 1 file changed, 1 insertion(+) diff --git a/examples/project_du_dbt_starter/setup.py b/examples/project_du_dbt_starter/setup.py index 64b30cf00917c..17a7c7162c57f 100644 --- a/examples/project_du_dbt_starter/setup.py +++ b/examples/project_du_dbt_starter/setup.py @@ -18,6 +18,7 @@ "s3fs", "smart_open", "boto3", + "pyarrow", ], extras_require={"dev": ["dagster-webserver", "pytest"]}, ) From 05a8770f6a08bbdd872ceb9d37dceba16c8a8a6a Mon Sep 17 00:00:00 2001 From: prha <1040172+prha@users.noreply.github.com> Date: Fri, 26 Apr 2024 11:33:50 -0700 Subject: [PATCH 20/56] make run id uuid in asset check tests (#21453) ## Summary & Motivation We want stricter enforcement to save disk storing run ids. ## How I Tested These Changes BK --- .../storage_tests/utils/event_log_storage.py | 39 ++++++++++--------- 1 file changed, 21 insertions(+), 18 deletions(-) diff --git a/python_modules/dagster/dagster_tests/storage_tests/utils/event_log_storage.py b/python_modules/dagster/dagster_tests/storage_tests/utils/event_log_storage.py index 8a773e6bbfaeb..4da7a771812b6 100644 --- a/python_modules/dagster/dagster_tests/storage_tests/utils/event_log_storage.py +++ b/python_modules/dagster/dagster_tests/storage_tests/utils/event_log_storage.py @@ -4971,6 +4971,7 @@ def test_asset_checks( if self.can_wipe(): storage.wipe() + run_id_1, run_id_2, run_id_3 = [make_new_run_id() for _ in range(3)] check_key_1 = AssetCheckKey(AssetKey(["my_asset"]), "my_check") check_key_2 = AssetCheckKey(AssetKey(["my_asset"]), "my_check_2") @@ -4979,7 +4980,7 @@ def test_asset_checks( error_info=None, user_message="", level="debug", - run_id="foo", + run_id=run_id_1, timestamp=time.time(), dagster_event=DagsterEvent( DagsterEventType.ASSET_CHECK_EVALUATION_PLANNED.value, @@ -4994,14 +4995,14 @@ def test_asset_checks( checks = storage.get_asset_check_execution_history(check_key_1, limit=10) assert len(checks) == 1 assert checks[0].status == AssetCheckExecutionRecordStatus.PLANNED - assert checks[0].run_id == "foo" + assert checks[0].run_id == run_id_1 assert checks[0].event assert checks[0].event.dagster_event_type == DagsterEventType.ASSET_CHECK_EVALUATION_PLANNED latest_checks = storage.get_latest_asset_check_execution_by_key([check_key_1, check_key_2]) assert len(latest_checks) == 1 assert latest_checks[check_key_1].status == AssetCheckExecutionRecordStatus.PLANNED - assert latest_checks[check_key_1].run_id == "foo" + assert latest_checks[check_key_1].run_id == run_id_1 # update the planned check storage.store_event( @@ -5009,7 +5010,7 @@ def test_asset_checks( error_info=None, user_message="", level="debug", - run_id="foo", + run_id=run_id_1, timestamp=time.time(), dagster_event=DagsterEvent( DagsterEventType.ASSET_CHECK_EVALUATION.value, @@ -5052,7 +5053,7 @@ def test_asset_checks( error_info=None, user_message="", level="debug", - run_id="foobar", + run_id=run_id_2, timestamp=time.time(), dagster_event=DagsterEvent( DagsterEventType.ASSET_CHECK_EVALUATION_PLANNED.value, @@ -5067,31 +5068,31 @@ def test_asset_checks( checks = storage.get_asset_check_execution_history(check_key_1, limit=10) assert len(checks) == 2 assert checks[0].status == AssetCheckExecutionRecordStatus.PLANNED - assert checks[0].run_id == "foobar" + assert checks[0].run_id == run_id_2 assert checks[1].status == AssetCheckExecutionRecordStatus.SUCCEEDED - assert checks[1].run_id == "foo" + assert checks[1].run_id == run_id_1 checks = storage.get_asset_check_execution_history(check_key_1, limit=1) assert len(checks) == 1 - assert checks[0].run_id == "foobar" + assert checks[0].run_id == run_id_2 checks = storage.get_asset_check_execution_history( check_key_1, limit=1, cursor=checks[0].id ) assert len(checks) == 1 - assert checks[0].run_id == "foo" + assert checks[0].run_id == run_id_1 latest_checks = storage.get_latest_asset_check_execution_by_key([check_key_1, check_key_2]) assert len(latest_checks) == 1 assert latest_checks[check_key_1].status == AssetCheckExecutionRecordStatus.PLANNED - assert latest_checks[check_key_1].run_id == "foobar" + assert latest_checks[check_key_1].run_id == run_id_2 storage.store_event( EventLogEntry( error_info=None, user_message="", level="debug", - run_id="fizbuz", + run_id=run_id_3, timestamp=time.time(), dagster_event=DagsterEvent( DagsterEventType.ASSET_CHECK_EVALUATION_PLANNED.value, @@ -5106,21 +5107,22 @@ def test_asset_checks( latest_checks = storage.get_latest_asset_check_execution_by_key([check_key_1, check_key_2]) assert len(latest_checks) == 2 assert latest_checks[check_key_1].status == AssetCheckExecutionRecordStatus.PLANNED - assert latest_checks[check_key_1].run_id == "foobar" + assert latest_checks[check_key_1].run_id == run_id_2 assert latest_checks[check_key_2].status == AssetCheckExecutionRecordStatus.PLANNED - assert latest_checks[check_key_2].run_id == "fizbuz" + assert latest_checks[check_key_2].run_id == run_id_3 def test_duplicate_asset_check_planned_events(self, storage: EventLogStorage): if self.can_wipe(): storage.wipe() + run_id = make_new_run_id() for _ in range(2): storage.store_event( EventLogEntry( error_info=None, user_message="", level="debug", - run_id="fizbuz", + run_id=run_id, timestamp=time.time(), dagster_event=DagsterEvent( DagsterEventType.ASSET_CHECK_EVALUATION_PLANNED.value, @@ -5141,7 +5143,7 @@ def test_duplicate_asset_check_planned_events(self, storage: EventLogStorage): error_info=None, user_message="", level="debug", - run_id="fizbuz", + run_id=run_id, timestamp=time.time(), dagster_event=DagsterEvent( DagsterEventType.ASSET_CHECK_EVALUATION.value, @@ -5152,7 +5154,7 @@ def test_duplicate_asset_check_planned_events(self, storage: EventLogStorage): passed=True, metadata={}, target_materialization_data=AssetCheckEvaluationTargetMaterializationData( - storage_id=42, run_id="fizbuz", timestamp=3.3 + storage_id=42, run_id=run_id, timestamp=3.3 ), severity=AssetCheckSeverity.ERROR, ), @@ -5161,12 +5163,13 @@ def test_duplicate_asset_check_planned_events(self, storage: EventLogStorage): ) def test_asset_check_evaluation_without_planned_event(self, storage: EventLogStorage): + run_id = make_new_run_id() storage.store_event( EventLogEntry( error_info=None, user_message="", level="debug", - run_id="fizbuz", + run_id=run_id, timestamp=time.time(), dagster_event=DagsterEvent( DagsterEventType.ASSET_CHECK_EVALUATION.value, @@ -5177,7 +5180,7 @@ def test_asset_check_evaluation_without_planned_event(self, storage: EventLogSto passed=True, metadata={}, target_materialization_data=AssetCheckEvaluationTargetMaterializationData( - storage_id=42, run_id="fizbuz", timestamp=3.3 + storage_id=42, run_id=run_id, timestamp=3.3 ), severity=AssetCheckSeverity.ERROR, ), From 7b103db9438bb4e5018c7ae67e845982a9a376ac Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Fri, 26 Apr 2024 14:38:04 -0700 Subject: [PATCH 21/56] Revert "MetadataValue subclasses to DagsterModel (#21324)" (#21462) This reverts commit 4f5139af8bb111c4e565b98b5bfc05d7f942a2a9. ## Summary & Motivation Causing an error in dagstermill logging ## How I Tested These Changes --- .../_core/definitions/metadata/__init__.py | 345 ++++++++++-------- .../dagster_tests/core_tests/test_metadata.py | 82 +---- .../execution_tests/test_metadata.py | 30 ++ 3 files changed, 225 insertions(+), 232 deletions(-) diff --git a/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py b/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py index 2a49d7c1763a0..175503943ef05 100644 --- a/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py +++ b/python_modules/dagster/dagster/_core/definitions/metadata/__init__.py @@ -17,7 +17,6 @@ cast, ) -from pydantic import Field from typing_extensions import Self, TypeAlias, TypeVar import dagster._check as check @@ -615,124 +614,129 @@ def null() -> "NullMetadataValue": @whitelist_for_serdes(storage_name="TextMetadataEntryData") -class TextMetadataValue(DagsterModel, MetadataValue[str]): +class TextMetadataValue( + NamedTuple( + "_TextMetadataValue", + [ + ("text", PublicAttr[Optional[str]]), + ], + ), + MetadataValue[str], +): """Container class for text metadata entry data. Args: text (Optional[str]): The text data. """ - text_inner: Optional[str] = Field(..., alias="text") - - def __init__(self, text: Optional[str]): - super().__init__(text=text or "") - - @public - @property - def text(self) -> Optional[str]: - return self.text_inner + def __new__(cls, text: Optional[str]): + return super(TextMetadataValue, cls).__new__( + cls, check.opt_str_param(text, "text", default="") + ) @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped text data.""" - return self.text_inner + return self.text @whitelist_for_serdes(storage_name="UrlMetadataEntryData") -class UrlMetadataValue(DagsterModel, MetadataValue[str]): +class UrlMetadataValue( + NamedTuple( + "_UrlMetadataValue", + [ + ("url", PublicAttr[Optional[str]]), + ], + ), + MetadataValue[str], +): """Container class for URL metadata entry data. Args: url (Optional[str]): The URL as a string. """ - url_inner: Optional[str] = Field(..., alias="url") - - def __init__(self, url: Optional[str]): - super().__init__(url=url or "") + def __new__(cls, url: Optional[str]): + return super(UrlMetadataValue, cls).__new__( + cls, check.opt_str_param(url, "url", default="") + ) @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped URL.""" - return self.url_inner - - @public - @property - def url(self) -> Optional[str]: - """Optional[str]: The wrapped URL.""" - return self.url_inner + return self.url @whitelist_for_serdes(storage_name="PathMetadataEntryData") -class PathMetadataValue(DagsterModel, MetadataValue[str]): +class PathMetadataValue( + NamedTuple("_PathMetadataValue", [("path", PublicAttr[Optional[str]])]), MetadataValue[str] +): """Container class for path metadata entry data. Args: path (Optional[str]): The path as a string or conforming to os.PathLike. """ - path_inner: Optional[str] = Field(..., alias="path") - - def __init__(self, path: Optional[Union[str, os.PathLike]]): - super().__init__(path=check.opt_path_param(path, "path", default="")) - - @public - @property - def path(self) -> Optional[str]: - return self.path_inner + def __new__(cls, path: Optional[Union[str, os.PathLike]]): + return super(PathMetadataValue, cls).__new__( + cls, check.opt_path_param(path, "path", default="") + ) @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped path.""" - return self.path_inner + return self.path @whitelist_for_serdes(storage_name="NotebookMetadataEntryData") -class NotebookMetadataValue(DagsterModel, MetadataValue[str]): +class NotebookMetadataValue( + NamedTuple("_NotebookMetadataValue", [("path", PublicAttr[Optional[str]])]), MetadataValue[str] +): """Container class for notebook metadata entry data. Args: path (Optional[str]): The path to the notebook as a string or conforming to os.PathLike. """ - path_inner: Optional[str] = Field(..., alias="path") - - def __init__(self, path: Optional[Union[str, os.PathLike]]): - super().__init__(path=check.opt_path_param(path, "path", default="")) - - @public - @property - def path(self) -> Optional[str]: - return self.path_inner + def __new__(cls, path: Optional[Union[str, os.PathLike]]): + return super(NotebookMetadataValue, cls).__new__( + cls, check.opt_path_param(path, "path", default="") + ) @public @property def value(self) -> Optional[str]: """Optional[str]: The wrapped path to the notebook as a string.""" - return self.path_inner + return self.path @whitelist_for_serdes(storage_name="JsonMetadataEntryData") -class JsonMetadataValue(DagsterModel, MetadataValue[Union[Sequence[Any], Mapping[str, Any]]]): +class JsonMetadataValue( + NamedTuple( + "_JsonMetadataValue", + [ + ("data", PublicAttr[Optional[Union[Sequence[Any], Mapping[str, Any]]]]), + ], + ), + MetadataValue[Union[Sequence[Any], Mapping[str, Any]]], +): """Container class for JSON metadata entry data. Args: data (Union[Sequence[Any], Dict[str, Any]]): The JSON data. """ - data: PublicAttr[Optional[Union[Sequence[Any], Mapping[str, Any]]]] - - def __init__(self, data: Optional[Union[Sequence[Any], Mapping[str, Any]]]): + def __new__(cls, data: Optional[Union[Sequence[Any], Mapping[str, Any]]]): data = check.opt_inst_param(data, "data", (Sequence, Mapping)) try: # check that the value is JSON serializable seven.dumps(data) except TypeError: raise DagsterInvalidMetadata("Value is not JSON serializable.") - super().__init__(data=data) + return super(JsonMetadataValue, cls).__new__(cls, data) @public @property @@ -742,17 +746,25 @@ def value(self) -> Optional[Union[Sequence[Any], Mapping[str, Any]]]: @whitelist_for_serdes(storage_name="MarkdownMetadataEntryData") -class MarkdownMetadataValue(DagsterModel, MetadataValue[str]): +class MarkdownMetadataValue( + NamedTuple( + "_MarkdownMetadataValue", + [ + ("md_str", PublicAttr[Optional[str]]), + ], + ), + MetadataValue[str], +): """Container class for markdown metadata entry data. Args: md_str (Optional[str]): The markdown as a string. """ - md_str: PublicAttr[Optional[str]] - - def __init__(self, md_str: Optional[str]): - super().__init__(md_str=md_str or "") + def __new__(cls, md_str: Optional[str]): + return super(MarkdownMetadataValue, cls).__new__( + cls, check.opt_str_param(md_str, "md_str", default="") + ) @public @property @@ -763,7 +775,16 @@ def value(self) -> Optional[str]: # This should be deprecated or fixed so that `value` does not return itself. @whitelist_for_serdes(storage_name="PythonArtifactMetadataEntryData") -class PythonArtifactMetadataValue(DagsterModel, MetadataValue["PythonArtifactMetadataValue"]): +class PythonArtifactMetadataValue( + NamedTuple( + "_PythonArtifactMetadataValue", + [ + ("module", PublicAttr[str]), + ("name", PublicAttr[str]), + ], + ), + MetadataValue["PythonArtifactMetadataValue"], +): """Container class for python artifact metadata entry data. Args: @@ -771,11 +792,10 @@ class PythonArtifactMetadataValue(DagsterModel, MetadataValue["PythonArtifactMet name (str): The name of the python artifact """ - module: PublicAttr[str] - name: PublicAttr[str] - - def __init__(self, module: str, name: str): - super().__init__(module=module, name=name) + def __new__(cls, module: str, name: str): + return super(PythonArtifactMetadataValue, cls).__new__( + cls, check.str_param(module, "module"), check.str_param(name, "name") + ) @public @property @@ -785,93 +805,96 @@ def value(self) -> Self: @whitelist_for_serdes(storage_name="FloatMetadataEntryData") -class FloatMetadataValue(DagsterModel, MetadataValue[float]): +class FloatMetadataValue( + NamedTuple( + "_FloatMetadataValue", + [ + ("value", PublicAttr[Optional[float]]), + ], + ), + MetadataValue[float], +): """Container class for float metadata entry data. Args: value (Optional[float]): The float value. """ - value_inner: Optional[float] = Field(..., alias="value") - - def __init__(self, value: Optional[float]): - super().__init__(value=value) - - @public - @property - def value(self) -> Optional[float]: - return self.value_inner + def __new__(cls, value: Optional[float]): + return super(FloatMetadataValue, cls).__new__(cls, check.opt_float_param(value, "value")) @whitelist_for_serdes(storage_name="IntMetadataEntryData") -class IntMetadataValue(DagsterModel, MetadataValue[int]): +class IntMetadataValue( + NamedTuple( + "_IntMetadataValue", + [ + ("value", PublicAttr[Optional[int]]), + ], + ), + MetadataValue[int], +): """Container class for int metadata entry data. Args: value (Optional[int]): The int value. """ - value_inner: Optional[int] = Field(..., alias="value") - - def __init__(self, value: Optional[int]): - super().__init__(value=value) - - @public - @property - def value(self) -> Optional[int]: - return self.value_inner + def __new__(cls, value: Optional[int]): + return super(IntMetadataValue, cls).__new__(cls, check.opt_int_param(value, "value")) @whitelist_for_serdes(storage_name="BoolMetadataEntryData") -class BoolMetadataValue(DagsterModel, MetadataValue[bool]): +class BoolMetadataValue( + NamedTuple("_BoolMetadataValue", [("value", PublicAttr[Optional[bool]])]), + MetadataValue[bool], +): """Container class for bool metadata entry data. Args: value (Optional[bool]): The bool value. """ - value_inner: Optional[bool] = Field(..., alias="value") - - def __init__(self, value: Optional[bool]): - super().__init__(value=value) - - @public - @property - def value(self) -> Optional[bool]: - return self.value_inner + def __new__(cls, value: Optional[bool]): + return super(BoolMetadataValue, cls).__new__(cls, check.opt_bool_param(value, "value")) @whitelist_for_serdes -class TimestampMetadataValue(DagsterModel, MetadataValue[float]): +class TimestampMetadataValue( + NamedTuple( + "_DateTimeMetadataValue", + [("value", PublicAttr[float])], + ), + MetadataValue[float], +): """Container class for metadata value that's a unix timestamp. Args: value (float): Seconds since the unix epoch. """ - value_inner: Optional[float] = Field(..., alias="value") - - def __init__(self, value: float): - super().__init__(value=value) - - @public - @property - def value(self) -> Optional[float]: - return self.value_inner + def __new__(cls, value: float): + return super(TimestampMetadataValue, cls).__new__(cls, check.float_param(value, "value")) @whitelist_for_serdes(storage_name="DagsterPipelineRunMetadataEntryData") -class DagsterRunMetadataValue(DagsterModel, MetadataValue[str]): +class DagsterRunMetadataValue( + NamedTuple( + "_DagsterRunMetadataValue", + [ + ("run_id", PublicAttr[str]), + ], + ), + MetadataValue[str], +): """Representation of a dagster run. Args: run_id (str): The run id """ - run_id: PublicAttr[str] - - def __init__(self, run_id: str): - super().__init__(run_id=run_id) + def __new__(cls, run_id: str): + return super(DagsterRunMetadataValue, cls).__new__(cls, check.str_param(run_id, "run_id")) @public @property @@ -881,7 +904,17 @@ def value(self) -> str: @whitelist_for_serdes -class DagsterJobMetadataValue(DagsterModel, MetadataValue["DagsterJobMetadataValue"]): +class DagsterJobMetadataValue( + NamedTuple( + "_DagsterJobMetadataValue", + [ + ("job_name", PublicAttr[str]), + ("location_name", PublicAttr[str]), + ("repository_name", PublicAttr[Optional[str]]), + ], + ), + MetadataValue["DagsterJobMetadataValue"], +): """Representation of a dagster run. Args: @@ -891,20 +924,17 @@ class DagsterJobMetadataValue(DagsterModel, MetadataValue["DagsterJobMetadataVal assumed to be in the same repository as this object. """ - job_name: PublicAttr[str] - location_name: PublicAttr[str] - repository_name: PublicAttr[Optional[str]] - - def __init__( - self, + def __new__( + cls, job_name: str, location_name: str, repository_name: Optional[str] = None, ): - super().__init__( - job_name=job_name, - location_name=location_name, - repository_name=repository_name, + return super(DagsterJobMetadataValue, cls).__new__( + cls, + check.str_param(job_name, "job_name"), + check.str_param(location_name, "location_name"), + check.opt_str_param(repository_name, "repository_name"), ) @public @@ -914,17 +944,22 @@ def value(self) -> Self: @whitelist_for_serdes(storage_name="DagsterAssetMetadataEntryData") -class DagsterAssetMetadataValue(DagsterModel, MetadataValue[AssetKey]): +class DagsterAssetMetadataValue( + NamedTuple("_DagsterAssetMetadataValue", [("asset_key", PublicAttr["AssetKey"])]), + MetadataValue["AssetKey"], +): """Representation of a dagster asset. Args: asset_key (AssetKey): The dagster asset key """ - asset_key: PublicAttr[AssetKey] + def __new__(cls, asset_key: "AssetKey"): + from dagster._core.definitions.events import AssetKey - def __init__(self, asset_key: AssetKey): - super().__init__(asset_key=asset_key) + return super(DagsterAssetMetadataValue, cls).__new__( + cls, check.inst_param(asset_key, "asset_key", AssetKey) + ) @public @property @@ -936,7 +971,16 @@ def value(self) -> "AssetKey": # This should be deprecated or fixed so that `value` does not return itself. @experimental @whitelist_for_serdes(storage_name="TableMetadataEntryData") -class TableMetadataValue(DagsterModel, MetadataValue["TableMetadataValue"]): +class TableMetadataValue( + NamedTuple( + "_TableMetadataValue", + [ + ("records", PublicAttr[Sequence[TableRecord]]), + ("schema", PublicAttr[TableSchema]), + ], + ), + MetadataValue["TableMetadataValue"], +): """Container class for table metadata entry data. Args: @@ -957,9 +1001,6 @@ class TableMetadataValue(DagsterModel, MetadataValue["TableMetadataValue"]): ) """ - records: PublicAttr[Sequence[TableRecord]] - schema_inner: TableSchema = Field(..., alias="schema") - @public @staticmethod def infer_column_type(value: object) -> str: @@ -973,7 +1014,7 @@ def infer_column_type(value: object) -> str: else: return "string" - def __init__(self, records: Sequence[TableRecord], schema: Optional[TableSchema] = None): + def __new__(cls, records: Sequence[TableRecord], schema: Optional[TableSchema]): check.sequence_param(records, "records", of_type=TableRecord) check.opt_inst_param(schema, "schema", TableSchema) @@ -992,12 +1033,11 @@ def __init__(self, records: Sequence[TableRecord], schema: Optional[TableSchema] ] ) - super().__init__(records=records, schema=schema) - - @public - @property - def schema(self) -> TableSchema: - return self.schema_inner + return super(TableMetadataValue, cls).__new__( + cls, + records, + schema, + ) @public @property @@ -1007,32 +1047,35 @@ def value(self) -> Self: @whitelist_for_serdes(storage_name="TableSchemaMetadataEntryData") -class TableSchemaMetadataValue(DagsterModel, MetadataValue[TableSchema]): +class TableSchemaMetadataValue( + NamedTuple("_TableSchemaMetadataValue", [("schema", PublicAttr[TableSchema])]), + MetadataValue[TableSchema], +): """Representation of a schema for arbitrary tabular data. Args: schema (TableSchema): The dictionary containing the schema representation. """ - schema_inner: TableSchema = Field(..., alias="schema") - - def __init__(self, schema: TableSchema): - super().__init__(schema=schema) + def __new__(cls, schema: TableSchema): + return super(TableSchemaMetadataValue, cls).__new__( + cls, check.inst_param(schema, "schema", TableSchema) + ) @public @property def value(self) -> TableSchema: """TableSchema: The wrapped :py:class:`TableSchema`.""" - return self.schema_inner - - @public - @property - def schema(self) -> TableSchema: - return self.schema_inner + return self.schema @whitelist_for_serdes -class TableColumnLineageMetadataValue(DagsterModel, MetadataValue[TableColumnLineage]): +class TableColumnLineageMetadataValue( + NamedTuple( + "_TableColumnLineageMetadataValue", [("column_lineage", PublicAttr[TableColumnLineage])] + ), + MetadataValue[TableColumnLineage], +): """Representation of the lineage of column inputs to column outputs of arbitrary tabular data. Args: @@ -1040,20 +1083,20 @@ class TableColumnLineageMetadataValue(DagsterModel, MetadataValue[TableColumnLin for the table. """ - column_lineage_inner: TableColumnLineage = Field(..., alias="column_lineage") - - def __init__(self, column_lineage: TableColumnLineage): - super().__init__(column_lineage=column_lineage) + def __new__(cls, column_lineage: TableColumnLineage): + return super(TableColumnLineageMetadataValue, cls).__new__( + cls, check.inst_param(column_lineage, "column_lineage", TableColumnLineage) + ) @public @property def value(self) -> TableColumnLineage: """TableSpec: The wrapped :py:class:`TableSpec`.""" - return self.column_lineage_inner + return self.column_lineage @whitelist_for_serdes(storage_name="NullMetadataEntryData") -class NullMetadataValue(DagsterModel, MetadataValue[None]): +class NullMetadataValue(NamedTuple("_NullMetadataValue", []), MetadataValue[None]): """Representation of null.""" @public diff --git a/python_modules/dagster/dagster_tests/core_tests/test_metadata.py b/python_modules/dagster/dagster_tests/core_tests/test_metadata.py index c96b2a28e6460..1f30f2a37ef15 100644 --- a/python_modules/dagster/dagster_tests/core_tests/test_metadata.py +++ b/python_modules/dagster/dagster_tests/core_tests/test_metadata.py @@ -1,21 +1,4 @@ -from dagster import ( - AssetKey, - GraphDefinition, - IntMetadataValue, - JsonMetadataValue, - MetadataValue, - NodeInvocation, - TableColumn, - TableColumnDep, - TableColumnLineage, - TableMetadataValue, - TableRecord, - TableSchema, - TableSchemaMetadataValue, - UrlMetadataValue, - op, -) -from dagster._serdes.serdes import deserialize_value, serialize_value +from dagster import GraphDefinition, NodeInvocation, op def test_op_instance_tags(): @@ -42,66 +25,3 @@ def metadata_op(context): assert result.success assert called["yup"] - - -def test_table_schema_from_name_type_dict(): - assert TableSchema.from_name_type_dict({"foo": "customtype", "bar": "string"}) == TableSchema( - columns=[ - TableColumn(name="foo", type="customtype"), - TableColumn(name="bar", type="string"), - ], - ) - - -def test_table_serialization(): - table_metadata = MetadataValue.table( - records=[ - TableRecord(dict(foo=1, bar=2)), - ], - ) - serialized = serialize_value(table_metadata) - assert deserialize_value(serialized, TableMetadataValue) == table_metadata - - -def test_metadata_value_column_lineage() -> None: - expected_column_lineage = TableColumnLineage( - {"foo": [TableColumnDep(asset_key=AssetKey("bar"), column_name="baz")]} - ) - column_lineage_metadata_value = MetadataValue.column_lineage(expected_column_lineage) - - assert column_lineage_metadata_value.value == expected_column_lineage - - -def test_int_metadata_value(): - assert IntMetadataValue(5).value == 5 - assert IntMetadataValue(value=5).value == 5 - - -def test_url_metadata_value(): - url = "http://dagster.io" - assert UrlMetadataValue(url).value == url - assert UrlMetadataValue(url).url == url - assert UrlMetadataValue(url=url).value == url - - -def test_table_metadata_value(): - records = [TableRecord(dict(foo=1, bar=2))] - schema = TableSchema( - columns=[TableColumn(name="foo", type="int"), TableColumn(name="bar", type="int")] - ) - metadata_val = TableMetadataValue(records, schema=schema) - - assert metadata_val.records == records - assert metadata_val.schema == schema - - -def test_table_schema_metadata_value(): - schema = TableSchema( - columns=[TableColumn(name="foo", type="int"), TableColumn(name="bar", type="int")] - ) - assert TableSchemaMetadataValue(schema).schema == schema - - -def test_json_metadata_value(): - assert JsonMetadataValue({"a": "b"}).data == {"a": "b"} - assert JsonMetadataValue({"a": "b"}).value == {"a": "b"} diff --git a/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py b/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py index 9c5b51b774960..4bc99b6c46669 100644 --- a/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py +++ b/python_modules/dagster/dagster_tests/execution_tests/test_metadata.py @@ -29,6 +29,7 @@ from dagster._core.definitions.metadata import ( DagsterInvalidMetadata, TableColumnLineageMetadataValue, + TableMetadataValue, normalize_metadata, ) from dagster._core.definitions.metadata.table import ( @@ -42,6 +43,7 @@ ) from dagster._core.execution.execution_result import ExecutionResult from dagster._core.snap.node import build_node_defs_snapshot +from dagster._serdes.serdes import deserialize_value, serialize_value def step_events_of_type(result: ExecutionResult, node_name: str, event_type: DagsterEventType): @@ -368,6 +370,34 @@ def test_complex_table_schema(): ) +def test_table_schema_from_name_type_dict(): + assert TableSchema.from_name_type_dict({"foo": "customtype", "bar": "string"}) == TableSchema( + columns=[ + TableColumn(name="foo", type="customtype"), + TableColumn(name="bar", type="string"), + ], + ) + + +def test_table_serialization(): + table_metadata = MetadataValue.table( + records=[ + TableRecord(dict(foo=1, bar=2)), + ], + ) + serialized = serialize_value(table_metadata) + assert deserialize_value(serialized, TableMetadataValue) == table_metadata + + +def test_metadata_value_column_lineage() -> None: + expected_column_lineage = TableColumnLineage( + {"foo": [TableColumnDep(asset_key=AssetKey("bar"), column_name="baz")]} + ) + column_lineage_metadata_value = MetadataValue.column_lineage(expected_column_lineage) + + assert column_lineage_metadata_value.value == expected_column_lineage + + def test_bool_metadata_value(): @op(out={}) def the_op(): From 557627c3758c664492c98af7cabb29aff2b8b53a Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Mon, 29 Apr 2024 08:28:29 -0700 Subject: [PATCH 22/56] in dagstermill test, don't dump entire dagster event to json (#21463) ## Summary & Motivation In general, DagsterEvents are not always json-dumpable (e.g. they contain enums), but this test assumes they are. This causes problems when moving from `NamedTuple` (which are json-dumpable) to `DagsterModel` (which are not json-dumpable) for classes within `DagsterEvent`s. ## How I Tested These Changes --- .../dagstermill/dagstermill_tests/test_logging.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/python_modules/libraries/dagstermill/dagstermill_tests/test_logging.py b/python_modules/libraries/dagstermill/dagstermill_tests/test_logging.py index e98fddd156ab8..07eb6dc0afcb8 100644 --- a/python_modules/libraries/dagstermill/dagstermill_tests/test_logging.py +++ b/python_modules/libraries/dagstermill/dagstermill_tests/test_logging.py @@ -30,7 +30,10 @@ def __init__(self, file_path): def emit(self, record): with open(self.file_path, "a", encoding="utf8") as fd: - fd.write(seven.json.dumps(record.__dict__) + "\n") + fd.write( + seven.json.dumps({"the_message": record.__dict__["dagster_meta"]["orig_message"]}) + + "\n" + ) @logger(config_schema={"name": String, "log_level": String, "file_path": String}) @@ -123,10 +126,10 @@ def test_logging(hello_logging_job_type) -> None: if line ] - messages = [x["dagster_meta"]["orig_message"] for x in records] + messages = [x["the_message"] for x in records] assert "Hello, there!" in messages - critical_messages = [x["dagster_meta"]["orig_message"] for x in critical_records] + critical_messages = [x["the_message"] for x in critical_records] assert "Hello, there!" not in critical_messages From a4c7102e4584e8ed3dd173b75135b746f7d335b4 Mon Sep 17 00:00:00 2001 From: Erin Cochran Date: Mon, 29 Apr 2024 11:38:31 -0400 Subject: [PATCH 23/56] [daggy-u] [dbt] - Rename to Dagster+ (#21455) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ## Summary & Motivation This PR renames `Dagster Cloud` to `Dagster+` in the Dagster University content. ## How I Tested These Changes 👀 --- docs/dagster-university/pages/dagster-dbt.md | 2 +- .../dagster-dbt/lesson-1/4-project-preview.md | 2 +- .../pages/dagster-dbt/lesson-7/1-overview.md | 4 ++-- .../2-pushing-the-project-to-github.md | 2 +- .../lesson-7/3-setting-up-dagster-cloud.md | 20 +++++++++---------- ...creating-the-manifest-during-deployment.md | 10 +++++----- .../5-preparing-for-a-successful-run.md | 19 +++++++++--------- 7 files changed, 29 insertions(+), 30 deletions(-) diff --git a/docs/dagster-university/pages/dagster-dbt.md b/docs/dagster-university/pages/dagster-dbt.md index 16b7b21abb1a5..cf3ec0b5568f6 100644 --- a/docs/dagster-university/pages/dagster-dbt.md +++ b/docs/dagster-university/pages/dagster-dbt.md @@ -44,7 +44,7 @@ title: Dagster + dbt - Lesson 7: Deploying to Production - [Overview](/dagster-dbt/lesson-7/1-overview) - [Pushing the project to GitHub](/dagster-dbt/lesson-7/2-pushing-the-project-to-github) - - [Setting up Dagster Cloud](/dagster-dbt/lesson-7/3-setting-up-dagster-cloud) + - [Setting up Dagster+](/dagster-dbt/lesson-7/3-setting-up-dagster-cloud) - [Creating the manifest during deployment](/dagster-dbt/lesson-7/4-creating-the-manifest-during-deployment) - [Preparing for a successful run](/dagster-dbt/lesson-7/5-preparing-for-a-successful-run) - [Capstone](/dagster-dbt/capstone) \ No newline at end of file diff --git a/docs/dagster-university/pages/dagster-dbt/lesson-1/4-project-preview.md b/docs/dagster-university/pages/dagster-dbt/lesson-1/4-project-preview.md index 4abbc87d7dfbd..cc2b67180cc2f 100644 --- a/docs/dagster-university/pages/dagster-dbt/lesson-1/4-project-preview.md +++ b/docs/dagster-university/pages/dagster-dbt/lesson-1/4-project-preview.md @@ -13,6 +13,6 @@ By the end of the course, you will: - Create dbt models and load them into Dagster as assets - Run dbt and store the transformed data in a DuckDB database - Apply partitions to incremental dbt models -- Deploy the dbt + Dagster project to Dagster Cloud +- Deploy the Dagster project to Dagster+ If you get stuck or want to jump ahead, check out the [finished project here on GitHub](https://github.com/dagster-io/project-dagster-university/tree/module/dagster-and-dbt). \ No newline at end of file diff --git a/docs/dagster-university/pages/dagster-dbt/lesson-7/1-overview.md b/docs/dagster-university/pages/dagster-dbt/lesson-7/1-overview.md index abb2dfb7d8365..a217e4e0bdcc3 100644 --- a/docs/dagster-university/pages/dagster-dbt/lesson-7/1-overview.md +++ b/docs/dagster-university/pages/dagster-dbt/lesson-7/1-overview.md @@ -8,6 +8,6 @@ lesson: '7' At this point, you have a fully integrated Dagster and dbt project! You’ve learned how to load dbt models as Dagster assets, create dependencies, add partitions, and execute and monitor the resulting pipeline in the Dagster UI. -In this lesson, we’ll deploy your Dagster+dbt project to have it running in both local and production environments. We’ll walk through some considerations involved in bundling your dbt project up with Dagster. +In this lesson, we’ll deploy your Dagster and dbt project to have it running in both local and production environments. We’ll walk through some considerations involved in bundling your dbt project up with Dagster. -You’ll learn how to deploy your unified Dagster and dbt project to production, including pushing the project to GitHub and setting up CI/CD to factor in your dbt project. We’ll use Dagster Cloud because it’s a standardized and controlled experience that we can walk you through, but all of the general patterns can be applied to however you deploy Dagster. +You’ll learn how to deploy your unified Dagster and dbt project to production, including pushing the project to GitHub and setting up CI/CD to factor in your dbt project. We’ll use Dagster+ because it’s a standardized and controlled experience that we can walk you through, but all of the general patterns can be applied to however you deploy Dagster. diff --git a/docs/dagster-university/pages/dagster-dbt/lesson-7/2-pushing-the-project-to-github.md b/docs/dagster-university/pages/dagster-dbt/lesson-7/2-pushing-the-project-to-github.md index d80d7ec64f769..730922585f316 100644 --- a/docs/dagster-university/pages/dagster-dbt/lesson-7/2-pushing-the-project-to-github.md +++ b/docs/dagster-university/pages/dagster-dbt/lesson-7/2-pushing-the-project-to-github.md @@ -6,7 +6,7 @@ lesson: '7' # Pushing the project to GitHub -We’ll be using GitHub in this lesson because Dagster Cloud has a native integration with GitHub to quickly get deployment set up. This functionality can be easily replicated if your company uses a different version control provider, but we’ll standardize on using GitHub for now. Whether you use the command line or an app like GitHub Desktop is up to you. +We’ll be using GitHub in this lesson because Dagster+ has a native integration with GitHub to quickly get deployment set up. This functionality can be easily replicated if your company uses a different version control provider, but we’ll standardize on using GitHub for now. Whether you use the command line or an app like GitHub Desktop is up to you. 1. Because you cloned this project, it’ll already have a git history and context. Let’s delete that by running `rm -rf .git`. 2. Create a new repository on GitHub. diff --git a/docs/dagster-university/pages/dagster-dbt/lesson-7/3-setting-up-dagster-cloud.md b/docs/dagster-university/pages/dagster-dbt/lesson-7/3-setting-up-dagster-cloud.md index 6a008b2fbfc11..c94e3359a09ec 100644 --- a/docs/dagster-university/pages/dagster-dbt/lesson-7/3-setting-up-dagster-cloud.md +++ b/docs/dagster-university/pages/dagster-dbt/lesson-7/3-setting-up-dagster-cloud.md @@ -1,21 +1,21 @@ --- -title: "Lesson 7: Setting up Dagster Cloud" +title: "Lesson 7: Setting up Dagster+" module: 'dbt_dagster' lesson: '7' --- -# Setting up Dagster Cloud +# Setting up Dagster+ -Now that the project is set up and ready in GitHub, it’s time to move to Dagster Cloud. To keep things simple, we’ll use a [Serverless deployment](https://docs.dagster.io/dagster-cloud/deployment/serverless) to deploy our project. This option offloads managing the required infrastructure to Dagster Labs. +Now that the project is set up and ready in GitHub, it’s time to move to Dagster+. To keep things simple, we’ll use a [Serverless deployment](https://docs.dagster.io/dagster-plus/deployment/serverless) to deploy our project. This option offloads managing the required infrastructure to Dagster Labs. -1. Sign up for a new [Dagster Cloud trial account](https://dagster.cloud/signup). Even if you already have an account, create a new one for this course. **Note:** When you sign up for a new account, you’ll automatically begin a free trial. You won’t be charged for anything after the trial unless you enter a credit card. +1. Sign up for a new [Dagster+ trial account](https://dagster.cloud/signup). Even if you already have an account, create a new one for this course. **Note:** When you sign up for a new account, you’ll automatically begin a free trial. You won’t be charged for anything after the trial unless you enter a credit card. 2. Complete the signup flow by creating an organization and finishing your user profile. 3. When prompted to select a deployment type, click **Serverless.** -4. The next step is to add our project to Dagster Cloud! Click the **Import a Dagster project** option and do the following: +4. The next step is to add our project to Dagster+! Click the **Import a Dagster project** option and do the following: 1. In the **Git scope** field, select the GitHub account or organization that contains your project repository. {% callout %} - > 💡 **Don’t see the right account/organization?** You may need to install the Dagster Cloud GitHub app first. To do this, click **+ Add account or organization.** You’ll be redirected to GitHub to complete the setup, and then automatically sent back to Dagster Cloud when finished. If you’re installing within your company’s GitHub organization, you may need your company’s GitHub admin to approve the app. + > 💡 **Don’t see the right account/organization?** You may need to install the Dagster+ GitHub app first. To do this, click **+ Add account or organization.** You’ll be redirected to GitHub to complete the setup, and then automatically sent back to Dagster+ when finished. If you’re installing within your company’s GitHub organization, you may need your company’s GitHub admin to approve the app. {% /callout %} 2. In the **Repository** field, select the repository containing your Dagster project. @@ -23,14 +23,14 @@ Now that the project is set up and ready in GitHub, it’s time to move to Dagst --- -## What happens when Dagster Cloud deploys code? +## What happens when Dagster+ deploys code? When Dagster deploys the code, a few things happen: -- Dagster creates a new code location for the repository in Dagster Cloud in the `prod` deployment +- Dagster creates a new code location for the repository in Dagster+ in the `prod` deployment - Dagster adds two GitHub Action files to the repository: - - `.github/workflows/deploy.yml` - This file sets up Continuous Deployment (CD) for the repository. We won’t talk through all the steps here, but a high-level summary is that every time a change is made to the `main` branch of your repository, this GitHub Action will build your Dagster project and deploy it to Dagster Cloud. - - `.github/workflows/branch_deployments.yml` - This file enables the use of [Branch Deployments](https://docs.dagster.io/dagster-cloud/managing-deployments/branch-deployments), a Dagster Cloud feature that automatically creates staging environments for your Dagster code with every pull request. We won’t work with Branch Deployments during this lesson, but we highly recommend trying them out! + - `.github/workflows/deploy.yml` - This file sets up Continuous Deployment (CD) for the repository. We won’t talk through all the steps here, but a high-level summary is that every time a change is made to the `main` branch of your repository, this GitHub Action will build your Dagster project and deploy it to Dagster+. + - `.github/workflows/branch_deployments.yml` - This file enables the use of [Branch Deployments](https://docs.dagster.io/dagster-cloud/managing-deployments/branch-deployments), a Dagster+ feature that automatically creates staging environments for your Dagster code with every pull request. We won’t work with Branch Deployments during this lesson, but we highly recommend trying them out! --- diff --git a/docs/dagster-university/pages/dagster-dbt/lesson-7/4-creating-the-manifest-during-deployment.md b/docs/dagster-university/pages/dagster-dbt/lesson-7/4-creating-the-manifest-during-deployment.md index 39dddab51774e..25f09d1a0c90a 100644 --- a/docs/dagster-university/pages/dagster-dbt/lesson-7/4-creating-the-manifest-during-deployment.md +++ b/docs/dagster-university/pages/dagster-dbt/lesson-7/4-creating-the-manifest-during-deployment.md @@ -8,7 +8,7 @@ lesson: '7' To recap, our deployment failed in the last section because Dagster couldn’t find a dbt manifest file, which it needs to turn dbt models into Dagster assets. This is because we built this file by running `dbt parse` during local development. You ran this manually in Lesson 3 and improved the experience in Lesson 4. However, you'll also need to build your dbt manifest file during deployment, which will require a couple additional steps. We recommend adopting CI/CD to automate this process. -Building your manifest for your production deployment will will be needed for both open source and Dagster Cloud deployments. In this case, Dagster Cloud’s out-of-the-box `deploy.yml` GitHub Action isn’t aware that you’re also trying to deploy a dbt project with Dagster. +Building your manifest for your production deployment will will be needed for both open source and Dagster+ deployments. In this case, Dagster+’s out-of-the-box `deploy.yml` GitHub Action isn’t aware that you’re also trying to deploy a dbt project with Dagster. Since your CI/CD will be running in a fresh environment, you'll need to install dbt and run `dbt deps` before building your manifest with `dbt parse`. @@ -35,7 +35,7 @@ To get our deployment working, we need to add a step to our GitHub Actions workf Once the new step is pushed to the remote, GitHub will automatically try to run a new job using the updated workflow. -At this point, your dbt project will be successfully deployed onto Dagster Cloud and you should be able to see your models in the asset graph! +At this point, your dbt project will be successfully deployed onto Dagster+ and you should be able to see your models in the asset graph! {% table %} @@ -44,8 +44,8 @@ At this point, your dbt project will be successfully deployed onto Dagster Cloud --- -- ![Successful deployment screen in Dagster Cloud](/images/dagster-dbt/lesson-7/successful-cloud-setup.png) -- ![dbt models in the Asset graph in Dagster Cloud](/images/dagster-dbt/lesson-7/asset-graph.png) +- ![Successful deployment screen in Dagster+](/images/dagster-dbt/lesson-7/successful-cloud-setup.png) +- ![dbt models in the Asset graph in Dagster+](/images/dagster-dbt/lesson-7/asset-graph.png) {% /table %} @@ -53,7 +53,7 @@ At this point, your dbt project will be successfully deployed onto Dagster Cloud ## Experiencing issues? -There are two ways to deploy Dagster Cloud Serverless. In our case, we only made changes to deploy dbt with the default option, called Fast Deploys with PEX (Python Executable). +There are two ways to deploy Dagster+ Serverless. In our case, we only made changes to deploy dbt with the default option, called Fast Deploys with PEX (Python Executable). **If you receive an error message to turn off Fast Deploys**, GitHub Actions will skip the steps that build the dbt project. We recommend staying with Fast Deploys, if possible. diff --git a/docs/dagster-university/pages/dagster-dbt/lesson-7/5-preparing-for-a-successful-run.md b/docs/dagster-university/pages/dagster-dbt/lesson-7/5-preparing-for-a-successful-run.md index e7ad9aa4b9be4..2f3b1b0b7ba61 100644 --- a/docs/dagster-university/pages/dagster-dbt/lesson-7/5-preparing-for-a-successful-run.md +++ b/docs/dagster-university/pages/dagster-dbt/lesson-7/5-preparing-for-a-successful-run.md @@ -7,7 +7,7 @@ lesson: '7' # Preparing for a successful run {% callout %} ->💡 **Heads up! This section is optional.** The goal of this lesson was to teach you how to successfully **deploy** to Dagster Cloud, which you completed in the last section. Preparing for a successful run in Dagster Cloud requires using some external services, which may not translate to the external services you prefer to use. As such, we’ve opted to make this section optional. +>💡 **Heads up! This section is optional.** The goal of this lesson was to teach you how to successfully **deploy** to Dagster+, which you completed in the last section. Preparing for a successful run in Dagster+ requires using some external services, which may not translate to the external services you prefer to use. As such, we’ve opted to make this section optional. {% /callout %} In previous lessons, you followed along by adding our example code to your local project. You successfully materialized the assets in the project and stored the resulting data in a local DuckDB database. @@ -25,13 +25,13 @@ Since you'll be deploying your project in production, you'll need production sys The code you cloned in the starter project already has some logic to dynamically switch between local and cloud storage, along with the paths to reference. To trigger the switch, you can set an environment variable called `DAGSTER_ENVIRONMENT` and set it to `prod`. This will tell the pipeline to use the production paths and storage. -In summary, before you can run this pipeline in Dagster Cloud, you’ll need to: +In summary, before you can run this pipeline in Dagster+, you’ll need to: 1. Set up an S3 bucket to store the files/assets that we download and generate 2. Sign up for a free Motherduck account to replace our local DuckDB instance 3. Connect an S3 user with access to the S3 bucket to the Motherduck account 4. Add a new production target to the dbt project -5. Add the environment variables for the S3 user and Motherduck token to Dagster Cloud +5. Add the environment variables for the S3 user and Motherduck token to Dagster+ We’ll show you how to do 4 and 5 so you can do this with your credentials when you’re ready. @@ -63,7 +63,7 @@ Because we’re still using a DuckDB-backed database, our `type` will also be `d ## Adding a prod target to deploy.yml -Next, we need to update the dbt commands in the `.github/workflows/deploy.yml` file to target the new `prod` profile. This will ensure that dbt uses the correct connection details when the GitHub Action runs as part of our Dagster Cloud deployment. +Next, we need to update the dbt commands in the `.github/workflows/deploy.yml` file to target the new `prod` profile. This will ensure that dbt uses the correct connection details when the GitHub Action runs as part of our Dagster+ deployment. Open the file, scroll to the dbt step you added, and add `-- target prod` after the `dbt parse` command. This command should be on or around line 52: @@ -83,13 +83,13 @@ Save and commit the file to git. Don’t forget to push to remote! --- -## Adding environment variables to Dagster Cloud +## Adding environment variables to Dagster+ -The last step in preparing for a successful run is to move environment variables to Dagster Cloud. These variables were available to us via the `.env` file while we were working locally, but now that we’ve moved to a different environment, we’ll need to make them accessible again. +The last step in preparing for a successful run is to move environment variables to Dagster+. These variables were available to us via the `.env` file while we were working locally, but now that we’ve moved to a different environment, we’ll need to make them accessible again. ### Environment variables -The following table contains the environment variables we need to create in Dagster Cloud: +The following table contains the environment variables we need to create in Dagster+: {% table %} @@ -130,7 +130,7 @@ The following table contains the environment variables we need to create in Dags ### Creating environment variables -1. In the Dagster Cloud UI, click **Deployment > Environment variables**. +1. In the Dagster+ UI, click **Deployment > Environment variables**. 2. Click the **Add environment variable** button on the right side of the screen. 3. In the **Create environment variable** window, fill in the following: 1. **Name** - The name of the environment variable. For example: `DUCKDB_DATABASE` @@ -144,5 +144,4 @@ Repeat these steps until all the environment variables have been added. ## Running the pipeline -At this point, you're ready to run the pipeline in production! Navigate to the asset graph, click **Materialize all**, and watch as it all comes together: - +At this point, you're ready to run the pipeline in production! Navigate to the asset graph, click **Materialize all**, and watch as it all comes together. \ No newline at end of file From c4b328c9cc3b005b7ccdf093171a8e23b1b1770b Mon Sep 17 00:00:00 2001 From: Maxime Armstrong <46797220+maximearmstrong@users.noreply.github.com> Date: Mon, 29 Apr 2024 12:07:34 -0400 Subject: [PATCH 24/56] Update sources in with_openai (#21405) ## Summary & Motivation This PR updates and add doc sources in the `with_openai` example so that we can showcase a more complete example in the blog post. This PR also fixes the summaries of the sources provided to the model. Long story short, passing a list of summaries caused the model to always answer "I don't know", although it was working just fine before. Passing a string created by joining the summaries fixed the problem. ## How I Tested These Changes dagster dev BK --- examples/with_openai/setup.py | 11 +++++++- examples/with_openai/with_openai/assets.py | 30 +++++++++++++++++----- examples/with_openai/with_openai/utils.py | 30 ++++++++++------------ 3 files changed, 46 insertions(+), 25 deletions(-) diff --git a/examples/with_openai/setup.py b/examples/with_openai/setup.py index 059512d846910..3d9549b21bb17 100644 --- a/examples/with_openai/setup.py +++ b/examples/with_openai/setup.py @@ -3,6 +3,15 @@ setup( name="with_openai", packages=find_packages(exclude=["with_openai_tests"]), - install_requires=["dagster", "dagster-openai", "langchain==0.1.11"], + install_requires=[ + "dagster", + "dagster-openai", + "dagster-cloud", + "faiss-cpu==1.8.0", + "filelock", + "langchain==0.1.11", + "langchain-community==0.0.34", + "langchain-openai==0.1.3", + ], extras_require={"dev": ["dagster-webserver", "pytest"]}, ) diff --git a/examples/with_openai/with_openai/assets.py b/examples/with_openai/with_openai/assets.py index a5d2bd4e93869..20449960f5677 100644 --- a/examples/with_openai/with_openai/assets.py +++ b/examples/with_openai/with_openai/assets.py @@ -22,7 +22,17 @@ from .utils import get_github_docs docs_partitions_def = StaticPartitionsDefinition( - ["concepts", "dagster-cloud", "deployment", "guides", "integrations"] + [ + "about", + "community", + "concepts", + "dagster-plus", + "deployment", + "getting-started", + "guides", + "integrations", + "tutorial", + ] ) @@ -63,18 +73,24 @@ class OpenAIConfig(Config): question: str -@asset(compute_kind="OpenAI") -def completion(context: AssetExecutionContext, openai: OpenAIResource, config: OpenAIConfig): +@asset(compute_kind="OpenAI", deps=[search_index]) +def completion( + context: AssetExecutionContext, + openai: OpenAIResource, + config: OpenAIConfig, +): with open(SEARCH_INDEX_FILE, "rb") as f: serialized_search_index = pickle.load(f) search_index = FAISS.deserialize_from_bytes(serialized_search_index, OpenAIEmbeddings()) with openai.get_client(context) as client: prompt = stuff_prompt.PROMPT model = ChatOpenAI(client=client.chat.completions, model=config.model, temperature=0) - summaries = [ - SUMMARY_TEMPLATE.format(content=doc.page_content, source=doc.metadata["source"]) - for doc in search_index.similarity_search(config.question, k=4) - ] + summaries = " ".join( + [ + SUMMARY_TEMPLATE.format(content=doc.page_content, source=doc.metadata["source"]) + for doc in search_index.similarity_search(config.question, k=4) + ] + ) output_parser = StrOutputParser() chain = prompt | model | output_parser context.log.info(chain.invoke({"summaries": summaries, "question": config.question})) diff --git a/examples/with_openai/with_openai/utils.py b/examples/with_openai/with_openai/utils.py index d34c9dfb5cb9b..be78e8eff6c79 100644 --- a/examples/with_openai/with_openai/utils.py +++ b/examples/with_openai/with_openai/utils.py @@ -1,7 +1,8 @@ +import io import os import pathlib -import subprocess import tempfile +import zipfile import requests from langchain.docstore.document import Document @@ -18,22 +19,17 @@ def get_wiki_data(title, first_paragraph_only): ) -def get_github_docs(repo_owner, repo_name, category): +def get_github_docs(repo_owner, repo_name, category, archive_name="master"): with tempfile.TemporaryDirectory() as d: - subprocess.check_call( - f"git clone --depth 1 https://github.com/{repo_owner}/{repo_name}.git .", - cwd=d, - shell=True, - ) - git_sha = ( - subprocess.check_output("git rev-parse HEAD", shell=True, cwd=d).decode("utf-8").strip() - ) - docs_path = pathlib.Path(os.path.join(d, "docs/content", category)) - markdown_files = list(docs_path.glob("*/*.md")) + list(docs_path.glob("*/*.mdx")) - for index, markdown_file in enumerate(markdown_files): + # The archive name can be a branch, tag or commit. + r = requests.get(f"https://github.com/{repo_owner}/{repo_name}/archive/{archive_name}.zip") + z = zipfile.ZipFile(io.BytesIO(r.content)) + z.extractall(d) + root_path = pathlib.Path(os.path.join(d, f"{repo_name}-{archive_name}")) + docs_path = root_path.joinpath("docs/content", category) + markdown_files = list(docs_path.glob("*.md*")) + list(docs_path.glob("*/*.md*")) + for markdown_file in markdown_files: with open(markdown_file, "r") as f: - relative_path = markdown_file.relative_to(docs_path) - github_url = ( - f"https://github.com/{repo_owner}/{repo_name}/blob/{git_sha}/{relative_path}" - ) + relative_path = markdown_file.relative_to(root_path) + github_url = f"https://github.com/{repo_owner}/{repo_name}/blob/{archive_name}/{relative_path}" yield Document(page_content=f.read(), metadata={"source": github_url}) From 13904a79666f07937c95068227fa384ca3dbda60 Mon Sep 17 00:00:00 2001 From: Maxime Armstrong <46797220+maximearmstrong@users.noreply.github.com> Date: Mon, 29 Apr 2024 12:16:02 -0400 Subject: [PATCH 25/56] Handle `dbt deps` in DbtProject (#21296) ## Summary & Motivation This PR updates `DbtProject` and `DagsterDbtManifestPreparer` to handle `dbt deps`. Process in `DagsterDbtManifestPreparer`: - Check for the presence of `dependencies.yml` or `packages.yml` - Check for the presence of `dbt_packages` - If (a) exists and (b) is not present, then run `dbt deps`. On subsequent manifest creation, we shouldn't need to redownload the deps. 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