Adds timezone support

.github/workflows/ci.yml

@@ -15,7 +15,7 @@ jobs:
     needs: qa
 
     runs-on: ubuntu-latest
-    
+
     services:
       postgres:
         image: timescale/timescaledb-ha:pg14-latest
@@ -30,10 +30,10 @@ jobs:
 
     steps:
     - uses: actions/checkout@v2
-    - name: Set up Python 3.8
+    - name: Set up Python 3.11
       uses: actions/setup-python@v2
       with:
-        python-version: 3.8
+        python-version: 3.11
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip wheel

djangomain/settings.py

@@ -77,6 +77,7 @@
     "drf_yasg",
     "management",
     "crispy_forms",
+    "crispy_bootstrap4",
 ]
 
 MIDDLEWARE = [
@@ -157,7 +158,7 @@
 TIME_ZONE = "UTC"
 USE_I18N = True
 USE_L10N = True
-USE_TZ = False
+USE_TZ = True
 
 # Static files (CSS, JavaScript, Images)
 # https://docs.djangoproject.com/en/3.0/howto/static-files/
@@ -242,3 +243,6 @@
 }
 
 DEFAULT_AUTO_FIELD = "django.db.models.AutoField"
+
+CRISPY_ALLOWED_TEMPLATE_PACKS = "bootstrap4"
+CRISPY_TEMPLATE_PACK = "bootstrap4"

importing/functions.py

@@ -14,6 +14,7 @@
 import os
 import shutil
 import time
+import zoneinfo
 from datetime import datetime
 from logging import getLogger
 from numbers import Number
@@ -93,19 +94,21 @@ def get_last_uploaded_date(station_id, var_code):
     return datetime
 
 
-def preformat_matrix(source_file, file_format):
+def preformat_matrix(source_file, file_format, timezone: str):
     """
     First step for importing data. Works out what sort of file is being read and adds
     standardised columns for date and datetime (str). This is used in construct_matrix.
     Args:
         source_file: path to raw data file.
         file_format: formatting.models.Format object.
+        timezone: Timezone name, eg. 'America/Chicago'.
     Returns:
         Pandas.DataFrame with raw data read and extra column(s) for date and datetime
         (Str), which should be parsed correctly here.
     """
     firstline = file_format.first_row if file_format.first_row else 0
     skipfooter = file_format.footer_rows if file_format.footer_rows else 0
+    tz = zoneinfo.ZoneInfo(timezone)
 
     if file_format.extension.value in ["xlsx", "xlx"]:
         # If in Excel format
@@ -152,7 +155,6 @@ def preformat_matrix(source_file, file_format):
                 skipfooter=skipfooter,
                 engine=engine,
                 encoding="ISO-8859-1",
-                error_bad_lines=False,
             )
         else:
             file = pd.read_csv(
@@ -164,14 +166,13 @@ def preformat_matrix(source_file, file_format):
                 skipfooter=skipfooter,
                 engine=engine,
                 encoding="ISO-8859-1",
-                error_bad_lines=False,
             )
 
     datetime_format = file_format.date.code + " " + file_format.time.code
     if file_format.date_column == file_format.time_column:
         file["date"] = pd.Series(
             [
-                standardise_datetime(row, datetime_format)
+                standardise_datetime(row, datetime_format).replace(tzinfo=tz)
                 for row in file[file_format.date_column - 1].values
             ],
             index=file.index,
@@ -198,7 +199,7 @@ def preformat_matrix(source_file, file_format):
         )
         file["date"] = pd.Series(
             [
-                standardise_datetime(row, datetime_format)
+                standardise_datetime(row, datetime_format).replace(tzinfo=tz)
                 for row in file["datetime_str"].values
             ],
             index=file.index,
@@ -208,7 +209,7 @@ def preformat_matrix(source_file, file_format):
     return file.reset_index(drop=True)
 
 
-def standardise_datetime(date_time, datetime_format):
+def standardise_datetime(date_time, datetime_format) -> datetime:
     """
     Returns a datetime object in the case that date_time is not already in that form.
     Args:
@@ -220,7 +221,9 @@ def standardise_datetime(date_time, datetime_format):
     if isinstance(date_time, datetime):
         return date_time
     elif isinstance(date_time, np.datetime64):
-        date_time = datetime.utcfromtimestamp((date_time - unix_epoch) / one_second)
+        date_time = datetime.utcfromtimestamp(
+            float((date_time - unix_epoch) / one_second)
+        )
         return date_time
     elif isinstance(date_time, str):
         pass
@@ -271,36 +274,52 @@ def save_temp_data_to_permanent(data_import_temp):
             station_id=station.station_id,
         ).delete()
 
+        # The following is a hack to account for the different possible name of the
+        # fields that the models might have. Will be made "nicer" at some point.
+        # This should always work as a measurement model should always have one and only
+        # one of "value", "average", "sum" fields.
+        value_field = (
+            set([field.name for field in Model._meta.fields])
+            .intersection(["value", "average", "sum"])
+            .pop()
+        )
+
         # Bulk add new data
         # TODO improve this logic to cope with variables that might have max/min
         # AND depth.
         if "maximum" in table.columns:
             model_instances = [
                 Model(
-                    time=record["date"],
-                    value=record["value"],
-                    station_id=record["station_id"],
-                    maximum=record["maximum"],
-                    minimum=record["minimum"],
+                    {
+                        "time": record["date"],
+                        value_field: record["value"],
+                        "station_id": record["station_id"],
+                        "maximum": record["maximum"],
+                        "minimum": record["minimum"],
+                    },
                 )
                 for record in records
             ]
         elif "depth" in [f.name for f in Model._meta.fields]:
             model_instances = [
                 Model(
-                    time=record["date"],
-                    value=record["value"],
-                    depth=record["depth"],
-                    station_id=record["station_id"],
+                    {
+                        "time": record["date"],
+                        value_field: record["value"],
+                        "depth": record["depth"],
+                        "station_id": record["station_id"],
+                    },
                 )
                 for record in records
             ]
         else:
             model_instances = [
                 Model(
-                    time=record["date"],
-                    value=record["value"],
-                    station_id=record["station_id"],
+                    {
+                        "time": record["date"],
+                        value_field: record["value"],
+                        "station_id": record["station_id"],
+                    },
                 )
                 for record in records
             ]
@@ -321,7 +340,7 @@ def construct_matrix(matrix_source, file_format, station):
     """
 
     # Get the "preformatted matrix" sorted by date col
-    matrix = preformat_matrix(matrix_source, file_format)
+    matrix = preformat_matrix(matrix_source, file_format, station.timezone)
     # Find start and end dates from top and bottom row
     start_date = matrix.loc[0, "date"]
     end_date = matrix.loc[matrix.shape[0] - 1, "date"]

importing/views.py

@@ -18,7 +18,9 @@
 import os
 import shutil
 import urllib
+from logging import getLogger
 
+import pandas as pd
 from django.contrib.auth.decorators import permission_required
 from django.http import HttpResponse, JsonResponse
 from rest_framework import generics
@@ -58,7 +60,9 @@ class DataImportTempCreate(generics.CreateAPIView):
 
     def perform_create(self, serializer):
         file = copy.deepcopy(self.request.FILES["file"])
-        matrix = preformat_matrix(file, serializer.validated_data["format"])
+        timezone = serializer.validated_data["station"].timezone
+        getLogger().warning(timezone)
+        matrix = preformat_matrix(file, serializer.validated_data["format"], timezone)
         del file
         # Set start and end date based on cleaned data from the file
         serializer.validated_data["start_date"] = matrix.loc[0, "date"]

requirements.txt

@@ -18,6 +18,7 @@ psycopg2==2.9.9
 pytz==2023.3.post1
 PyYAML==6.0.1
 uritemplate==4.1.1
+crispy-bootstrap4==2023.1
 
 ## Legacy dependency versions
 # asgiref==3.3.4

station/migrations/0002_station_timezone.py

@@ -0,0 +1,31 @@
+# Generated by Django 4.2.7 on 2023-11-16 11:45
+
+import datetime
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("station", "0001_initial"),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name="station",
+            name="timezone",
+            field=models.CharField(
+                choices=[
+                    ("London", "Europe/London"),
+                    ("Paris", "Europe/Paris"),
+                    ("New York", "America/New_York"),
+                ],
+                default=datetime.datetime(
+                    2023, 11, 16, 11, 45, 57, 843717, tzinfo=datetime.timezone.utc
+                ),
+                max_length=100,
+                verbose_name="Timezone",
+            ),
+            preserve_default=False,
+        ),
+    ]

station/models.py

@@ -11,10 +11,14 @@
 #  creadoras, ya sea en uso total o parcial del código.
 ########################################################################################
 
+import zoneinfo
+
 from django.core.validators import MaxValueValidator, MinValueValidator
 from django.db import models
 from django.urls import reverse
 
+TIMEZONES = tuple([(val, val) for val in sorted(zoneinfo.available_timezones())])
+
 # Global variables used in Basin model
 BASIN_IMAGE_PATH = "station/basin_image/"
 BASIN_FILE_PATH = "station/basin_file/"
@@ -265,6 +269,7 @@ class Station(models.Model):
     influence_km = models.DecimalField(
         "Área of input (km)", max_digits=12, decimal_places=4, null=True, blank=True
     )
+    timezone = models.CharField("Timezone", max_length=100, choices=TIMEZONES)
 
     def __str__(self):
         return str(self.station_code)

tests/importing/test_functions.py

@@ -28,18 +28,19 @@ class TestMatrixFunctions(TestCase):
 
     def setUp(self):
         from formatting.models import Format
-        from station.models import Station
+        from station.models import TIMEZONES, Station
 
         self.file_format = Format.objects.get(format_id=45)
         self.data_file = str(
             Path(__file__).parent.parent / "test_data/iMHEA_HMT_01_HI_01_raw.csv"
         )
         self.station = Station.objects.get(station_id=8)
+        self.station.timezone = TIMEZONES[0][0]
 
     def test_preformat_matrix(self):
         from importing.functions import preformat_matrix
 
-        df = preformat_matrix(self.data_file, self.file_format)
+        df = preformat_matrix(self.data_file, self.file_format, self.station.timezone)
         self.assertEqual(df.shape, (263371, 5))
 
     def test_construct_matrix(self):
@@ -85,15 +86,18 @@ def setUp(self):
         from importing.functions import preformat_matrix
         from importing.models import DataImportTemp
         from measurement.models import Flow
-        from station.models import Station
+        from station.models import TIMEZONES, Station
 
         self.file_format = Format.objects.get(format_id=45)
         self.data_file = str(
             Path(__file__).parent.parent / "test_data" / "iMHEA_HMT_01_HI_01_raw.csv"
         )
         self.station = Station.objects.get(station_id=8)
+        self.station.timezone = TIMEZONES[0][0]
 
-        matrix = preformat_matrix(self.data_file, self.file_format)
+        matrix = preformat_matrix(
+            self.data_file, self.file_format, self.station.timezone
+        )
         start_date = matrix.loc[0, "date"]
         end_date = matrix.loc[matrix.shape[0] - 1, "date"]
 
@@ -114,12 +118,12 @@ def setUp(self):
         flow1 = Flow.objects.create(
             station_id=8,
             time=datetime(2014, 6, 28, 0, 35, 0, tzinfo=pytz.UTC),
-            value=3.4,
+            average=3.4,
         )
         flow2 = Flow.objects.create(
             station_id=8,
             time=datetime(2016, 3, 7, 18, 5, 0, tzinfo=pytz.UTC),
-            value=5.7,
+            average=5.7,
         )
 
     def test_get_last_uploaded_date(self):

tests/importing/test_models.py

@@ -26,21 +26,24 @@ class TestSaveImportModels(TestCase):
 
     def setUp(self):
         from formatting.models import Format
-        from station.models import Station
+        from station.models import TIMEZONES, Station
 
         self.file_format = Format.objects.get(format_id=45)
         self.data_file = str(
             Path(__file__).parent.parent / "test_data/iMHEA_HMT_01_HI_01_raw.csv"
         )
         self.station = Station.objects.get(station_id=8)
+        self.station.timezone = TIMEZONES[0][0]
 
     def test_save_import_temp(self):
         from django.core.files.uploadedfile import SimpleUploadedFile
 
         from importing.functions import preformat_matrix
         from importing.models import DataImportTemp
 
-        matrix = preformat_matrix(self.data_file, self.file_format)
+        matrix = preformat_matrix(
+            self.data_file, self.file_format, self.station.timezone
+        )
         start_date = matrix.loc[0, "date"]
         end_date = matrix.loc[matrix.shape[0] - 1, "date"]
 

tests/measurement/test_models.py

@@ -13,22 +13,22 @@ def setUp(self):
         flow1 = Flow.objects.create(
             station_id=1,
             time=datetime(2015, 10, 9, 23, 55, 59, tzinfo=pytz.UTC),
-            value=10.2,
+            average=10.2,
         )
         flow2 = Flow.objects.create(
             station_id=1,
             time=datetime(2016, 11, 9, 23, 55, 59, tzinfo=pytz.UTC),
-            value=5.7,
+            average=5.7,
         )
         precip1 = Precipitation.objects.create(
             station_id=2,
             time=datetime(2017, 12, 9, 23, 55, 59, tzinfo=pytz.UTC),
-            value=11.1,
+            sum=11.1,
         )
         precip2 = Precipitation.objects.create(
             station_id=2,
             time=datetime(2018, 1, 9, 23, 55, 59, tzinfo=pytz.UTC),
-            value=0.3,
+            sum=0.3,
         )
 
     def test_flow(self):