Viadot

UV formatting

Documentation: https://viadot.docs.dyvenia.com

Source Code: https://github.com/dyvenia/viadot/tree/main

A simple data ingestion library to guide data flows from some places to other places.

Getting Data from a Source

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")
df = ukci.to_df()

print(df)

Output:

from to forecast actual index
0 2021-08-10T11:00Z 2021-08-10T11:30Z 211 216 moderate

The above df is a pandas DataFrame object. It contains data downloaded by viadot from the Carbon Intensity UK API.

Loading data to a destination

Depending on the destination, viadot provides different methods of uploading data. For instance, for databases, this would be bulk inserts. For data lakes, it would be file uploads.

For example:

from viadot.sources import UKCarbonIntensity
from viadot.sources import AzureDataLake

ukci = UKCarbonIntensity()
ukci.query("/intensity")
df = ukci.to_df()

adls = AzureDataLake(config_key="my_adls_creds")
adls.from_df(df, "my_folder/my_file.parquet")

Getting started

Prerequisites

We use uv. You can install it like so:

curl -LsSf https://astral.sh/uv/install.sh | sh

Installation

pip install viadot2

Running the Docker Environment

The project provides the run.sh script located in the docker/ directory to initialize Docker environment with optional configuration for image tags and target platform.

Make sure the script is executable.

chmod +x docker/run.sh

Usage

docker/run.sh [-t <image_tag>] [-p <platform>]
  • -t <image_tag> - set Docker image tag (default: latest)
  • -p - set the target platform for Docker (default: linux/amd64)
    • This default ensures compatibility on macOS (Apple Silicon). Optionally, you can provide a different platform.

Examples

Run with default settings:

docker/run.sh

Run with a specific image tag and platform:

docker/run.sh -t dev -p linux/amd64

Configuration

In order to start using sources, you must configure them with required credentials. Credentials can be specified either in the viadot config file (by default, $HOME/.config/viadot/config.yaml), or passed directly to each source's credentials parameter.

You can find specific information about each source's credentials in the documentation.

Next steps

Check out the documentation for more information on how to use viadot.

Key dates

PyPI data
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  • Released:
Newer release available (2.13.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for dyvenia from gravatar.com dyvenia

Credits

Author: acivitillo

Requires

Python >=3.10

Provides Extra

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