Documentation: https://dyvenia.github.io/viadot/
Source Code: https://github.com/dyvenia/viadot
A simple data ingestion library to guide data flows from some places to other places.
Viadot supports several API and RDBMS sources, private and public. Currently, we support the UK Carbon Intensity public API and base the examples on it.
from viadot.sources.uk_carbon_intensity import UKCarbonIntensity
ukci = UKCarbonIntensity()
ukci.query("/intensity")
ukci.to_df()
The above code pulls data from the API to a pandas DataFrame
.
Depending on the source, viadot provides different methds of uploading data. For instance, for SQL sources, this would be bulk inserts. For data lake sources, it would be a file upload. We also provide ready-made pipelines including data valiadation steps using Great Expectations.
An example of loading data into SQLite from a pandas DataFrame
using the SQLiteInsert
task:
from viadot.tasks import SQLiteInsert
insert_task = SQLiteInsert()
insert_task.run(table_name=TABLE_NAME, dtypes=dtypes, db_path=database_path, df=df, if_exists="replace")
To run tests, log into the container and run pytest:
cd viadot/docker
run.sh
docker exec -it viadot_testing bash
pytest
You can run the example flows from the terminal:
run.sh
docker exec -it viadot_testing bash
FLOW_NAME=hello_world; python -m viadot.examples.$FLOW_NAME
However, when developing, the easiest way is to use the provided Jupyter Lab container available at http://localhost:9000/
.
- Clone the release branch
- Pull the docker env by running
viadot/docker/update.sh
- Run the env with
viadot/docker/run.sh
- Log into the dev container and install viadot in development mode:
docker exec -it viadot_testing bash
pip install -e .
- Edit and test your changes with
pytest
- Submit a PR. The PR should contain the following:
- new/changed functionality
- tests for the changes
- changes added to
CHANGELOG.md
- any other relevant resources updated (esp.
viadot/docs
)
Please follow the standards and best practices used within the library (eg. when adding tasks, see how other tasks are constructed, etc.). For any questions, please reach out to us here on GitHub.