Utility functions
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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyplatform-udf-0.0.1.tar.gz
(5.5 kB
view hashes)
Built Distribution
Close
Hashes for pyplatform_udf-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d5f569515993ea024595cc7b2cbee4246cecd2fb4a3f046f6342dab9db9be293 |
|
MD5 | 7d979347c3f956d84d26c6bf9d5b02af |
|
BLAKE2b-256 | 6c28761cc0a4fb435941a621bfb1a6b577a7d7c851bb1f70d32d10c780b80f30 |