Metadata-Version: 2.1
Name: pygbq
Version: 0.21
Summary: Easily integrate data in BigQuery
Home-page: https://github.com/ZiggerZZ/pygbq
Author: Zigfrid Zvezdin
Author-email: ziggerzz@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: pandas-gbq
Requires-Dist: pytz
Requires-Dist: google-auth
Requires-Dist: google-cloud-bigquery
Requires-Dist: google-cloud-logging
Requires-Dist: google-cloud-secret-manager
Requires-Dist: bigquery-schema-generator

# PyGBQ

> Easily integrate data in BigQuery

## Example

The following snippet

```python
from pygbq import Client
import requests
client = Client(default_dataset='Finance')

@client.gbq(how='replace')
def transactions(start_date):
    data = requests.get(url='some/api/endpoint', headers={'start_date': start_date}).json()
    return data

if __name__ == "__main__":
    transactions("2020-11-25")
```

will (re)create table `Finance.transactions` in your default project.

## Install and set up

`pip install pygbq`

Set up the [authentication](https://cloud.google.com/docs/authentication/getting-started).

## Documentation

* gbq - main decorator  
* update_table_using_temp - if you want to use the decorator as a function  
* table - friendly interface to get a table from BigQuery  
* set_dataset - set default dataset in the project  
* MyError - if you need to return a value with Flask  
* read_jsonl - read newline delimited json  
* generate_schema - might be useful for the first integration when you want to see schema  
* get_secret - get a secret version from Secret Manager  
* add_secret - add a secret version to Secret Manager

