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https://github.com/allegro/bigflow
A Python framework for data processing on GCP.
https://github.com/allegro/bigflow
airflow-dag beam bigquery composer dag dataflow dataproc gcp python python-framework workflows
Last synced: 2 days ago
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A Python framework for data processing on GCP.
- Host: GitHub
- URL: https://github.com/allegro/bigflow
- Owner: allegro
- License: other
- Created: 2019-07-25T12:32:33.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2024-07-30T14:48:16.000Z (about 2 months ago)
- Last Synced: 2024-09-24T23:02:51.111Z (2 days ago)
- Topics: airflow-dag, beam, bigquery, composer, dag, dataflow, dataproc, gcp, python, python-framework, workflows
- Language: Python
- Homepage:
- Size: 107 MB
- Stars: 116
- Watchers: 10
- Forks: 22
- Open Issues: 47
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# BigFlow
## Documentation
1. [What is BigFlow?](#what-is-bigflow)
1. [Getting started](#getting-started)
1. [Installing Bigflow](#installing-bigflow)
1. [Help me](#help-me)
1. [BigFlow tutorial](docs/tutorial.md)
1. [CLI](docs/cli.md)
1. [Configuration](./docs/configuration.md)
1. [Project structure and build](./docs/project_structure_and_build.md)
1. [Deployment](docs/deployment.md)
1. [Workflow & Job](./docs/workflow-and-job.md)
1. [Starter](./docs/scaffold.md)
1. [Technologies](./docs/technologies.md)
1. [Development](./docs/development.md)
## Cookbook
* [Monitoring](./docs/monitoring.md)
* [Automated end-to-end testing](./docs/e2e_testing.md)
* [Dockerized, GPU based ML prediction process](./docs/ml-prediction.md)
## What is BigFlow?
BigFlow is a Python framework for data processing pipelines on [GCP](https://cloud.google.com/).
The main features are:
* [Dockerized deployment environment](./docs/project_structure_and_build.md#overview)
* [Powerful CLI](./docs/cli.md)
* [Automated build](./docs/project_structure_and_build.md#overview), [deployment](./docs/deployment.md),
[versioning](./docs/project_structure_and_build.md#project-versioning) and [configuration](./docs/configuration.md)
* [Unified project structure](./docs/project_structure_and_build.md#project-structure)
* [Support for GCP data processing technologies](./docs/technologies.md) — [Dataflow](https://beam.apache.org/) (Apache Beam) and [BigQuery](https://cloud.google.com/bigquery)
* [Project starter](./docs/scaffold.md)
## Getting started
Start from installing BigFlow on your local machine.
Next, go through the BigFlow [tutorial](./docs/tutorial.md).
## Installing BigFlow
**Prerequisites**. Before you start, make sure you have the following software installed:
1. [Python](https://www.python.org/downloads/) = 3.8
2. [Google Cloud SDK](https://cloud.google.com/sdk/docs/downloads-interactive)
3. [Docker Engine](https://docs.docker.com/engine/install/)
You can install the `bigflow` package globally, but we recommend
installing it locally with `venv`, in your project's folder:
```bash
python -m venv .bigflow_env
source .bigflow_env/bin/activate
```
Install the `bigflow` PIP package:
```bash
pip install bigflow[bigquery,dataflow]
```
Test it:
```shell
bigflow -h
```
Read more about [BigFlow CLI](docs/cli.md).
To interact with GCP you need to set a default project and log in:
```shell script
gcloud config set project
gcloud auth application-default login
```
Finally, check if your Docker is running:
```shell script
docker info
```
## Help me
You can ask questions on our [gitter channel](https://gitter.im/allegro/bigflow) or [stackoverflow](https://stackoverflow.com/questions/tagged/bigflow).