Pyplatform is a data analytics platform architeture built around Google BigQuery in a hybrid cloud environment.
Project description
Pyplatform is a data analytics platform architeture built around Google BigQuery in a hybrid cloud environment.
the platorm:
- provides fast, scalable and reliable SQL database solution
- abstracts away the infrastuture by builiding data pipelines with serverless compute solutions in python runtime environments
- simplifies development environment by using jupyter lab as the main tool
Installation
pip install pyplatform
Setting up development environment
git clone https://github.com/mhadi813/pyplatform
cd pyplatform
conda env create -f pyplatform_dev.yml
Environment variables
import os
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = 'path/to/default_service_account.json'
os.environ['DATASET'] = 'default_bigquery_dataset_name'
os.environ['STORAGE_BUCKET'] = 'default_storage_bucket_id'
Usage
common data pipeline architectures:
- Http sources
- On-prem servers
- Bigquery integration with Azure Logic Apps
- Event driven ETL process
- Streaming pipelines
Exploring modules
import pyplatform as pyp
pyp.show_me()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyplatform-2020.5.2.tar.gz
(2.4 kB
view hashes)
Built Distribution
Close
Hashes for pyplatform-2020.5.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 82fce7653d2f5e0dd1f31c07aa83b8e898cf8573925782f2f0dd5613c6fefc31 |
|
MD5 | 7f1ddc1af5c503aa177a30acf97c8545 |
|
BLAKE2b-256 | 32b581b885c59c89fec0abc654038e25f00d8d499a2a568c89498f42297e698e |