48 lines
1.4 KiB
Markdown
48 lines
1.4 KiB
Markdown
This is the ETL ppipeline to read elements from a CSV file, parsing/cleaning
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them up and inserting into a PostgreSQL
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It has been tested only with DirectRunner, but it could be moved to run on
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DataFlow easily.
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## Running
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This is intended to be scheduled by Airflow but it the necessary packages are
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available it can also be run manually with:
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```sh
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python3 /etl/main.py \
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--runner=DirectRunner \
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--input="$CSV_INPUT_FILE" \
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--pg_hostname="$PG_HOSTNAME" \
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--pg_port="$PG_PORT" \
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--pg_username="$PG_USERNAME" \
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--pg_password="$PG_PASSWORD" \
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--pg_database="$PG_DATABASE" \
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--pg_table="$PG_TABLE"
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```
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## Testing and linting
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To help with development and testing a `Dockerfile`, a `Makefile` and
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`justfile` files are also provided.
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The `Makefile` provides a mechanism to
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* automate the generation of `dev-requirements.txt` and `requirements.txt` out
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of `pyproject.toml`
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* automate the creation of a python virtual environment which contains the
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right python version (installed by pyenv) and the packages defined in `pyproject.toml`
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* automate the building of an OCI image with the necessary dependencies
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The provided `Dockerfile` is used to build an image with the necessary packages
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to run `pytest` and `pylint`.
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The provided `justfile` provides the commands to run `pytest` and `pylint` from
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a container.
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If [`just`](https://github.com/casey/just) is installed, `pytest` and `pylint` can be run like so:
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```sh
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just test
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just lint
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```
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