[daggy-u] - Misc. formatting changes

docs/dagster-university/pages/dagster-essentials/lesson-2/project-files.md

@@ -56,63 +56,63 @@ The columns in the following table are as follows:
 
 ---
 
-- **README.md**
+- `README.md`
 - Python
 - A description and starter guide for the Dagster project.
 
 ---
 
-- **dagster_university/**
+- `dagster_university/`
 - Dagster
 - A Python module that will contain your Dagster code. This directory also contains the following:
   - `__init__.py` - This file includes a `Definitions` object that defines that is loaded in your project, such as assets and sensors. This allows Dagster to load the definitions in a module. We’ll discuss this topic, and this file, later in this course.
   - Several directories, for example: `/assets`. These directories follow our recommended best practices and will be used to contain the definitions - like assets - you create in the following lessons. We’ll discuss the files they contain later, too.
 
 ---
 
-- **dagster_university/**init**.py**
+- `dagster_university/__init__.py`
 - Dagster
 - Each Python module has an `__init__.py`. This root-level `__init__.py` is specifically used to import and combine the different aspects of your Dagster project. This is called defining your Code Location. You’ll learn more about this in a future lesson.
 
 ---
 
-- **dagster_university/assets/constants.py**
+- `dagster_university/assets/constants.py`
 - Dagster U
 - A pre-made file with some string constants that you’ll reference for convenience.
 
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-- **dagster_university_tests/**
+- `dagster_university_tests/`
 - Dagster
 - A Python module that contains unit tests for `dagster_university`
 
 ---
 
-- **data/**
+- `data/`
 - Dagster U
 - This directory (and directories within it) is where you’ll store the data assets you’ll make during this course. In production settings, this could be Amazon S3 or a data warehouse.
 
 ---
 
-- **.env**
+- `.env`
 - Python
 - A text file containing pre-configured environment variables. We’ll talk more about this file in Lesson 6, when we cover connecting to external services.
 
 ---
 
-- **pyproject.toml**
+- `pyproject.toml`
 - Python
 - A file that specifies package core metadata in a static, tool-agnostic way. This file includes a `tool.dagster` section which references the Python module with your Dagster definitions defined and discoverable at the top level. This allows you to use the `dagster dev` command to load your Dagster code without any parameters.
 
 ---
 
-- **setup.py**
+- `setup.py`
 - Python
 - A build script with Python package dependencies for your new project as a package. This file is used to specify dependencies.
 
 ---
 
-- **setup.cfg**
+- `setup.cfg`
 - Python
 - A file that contains option defaults for `setup.py` commands.
 

docs/dagster-university/pages/dagster-essentials/lesson-8/coding-practice-partition-taxi-trips.md

@@ -12,19 +12,23 @@ To practice what you’ve learned, partition the `taxi_trips` asset by month usi
 
 - With every partition, insert the new data into the `taxi_trips` table
 
-- For convenience, add a `partition_date` column to represent which partition the record was inserted from. You’ll need to drop the existing `taxi_trips` because of the new `partition_date` column. In a Python REPL or scratch script, run the following:
+- For convenience, add a `partition_date` column to represent which partition the record was inserted from. 
+
+  {% callout %}
+  You’ll need to drop the existing `taxi_trips` because of the new `partition_date` column. In a Python REPL or scratch script, run the following:
 
   ```yaml
   import duckdb
   conn = duckdb.connect(database="data/staging/data.duckdb")
   conn.execute("drop table trips;")
   ```
+  {% /callout %}
 
 - Because the `taxi_trips` table will exist after the first partition materializes, the SQL query will have to change
 
 - In this asset, you’ll need to do three actions:
   - Create the `taxi_trips` table if it doesn’t already exist
-  - Delete any old data from that `partition_date` to prevent duplicates when backfilling
+  - Delete any old data from `partition_date` to prevent duplicates when backfilling
   - Insert new records from the month’s parquet file
 
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