wrapg 0.2.0

Wrapper around psycopg3 using easy functions to interact with postgres.

wrapg

Wrapper around psycopg 3.x meant to make easy use of postgres within scripts using simple functions.

Project is in infancy, work in progress.

Installing Wrapg

Wrapg is available on PyPI:

pip install wrapg

Wrapg officially supports Python 3.10+.

Table of Contents

• Features
• Setup
• Usage
• Todo
• Acknowledgements
• Contact
• License

Features

• Simple functions to run postgres sql via python
• Pass various data structutes into sql functions
  • supports pandas dataframe out of box
• Auto import default postgres connection parameters via .env
  • saves on repeating code to specify connection
  • overide default connection parameters with kwargs in each function
  • see examples for more details (future)
• Upsert, insert_ignore functions included
  • automatically creates index
  • pass sql functions on 'On Conflict' keys (see example)
  • option to upsert/insert_ignore without creating index (future)
• Copy functions to follow postgres COPY protocol (today only csv is avail)

Setup

Dependencies:

• python 3.10+
• psycopg[binary]>=3.0.11
• pandas>=1.4.2

Usage

• TODO: add more examples later

Before you get started is is recommended to create .env file with below connection parameters. Wrapg will auto-import default connectionn parameters and make all functions ready to be executed.
The .env file should contain below specific name variables

# Database config
PG_HOST = "localhost"
PG_USER = "postgres"
PG_PASSWORD = "mypass"
PG_PORT = 1234
PG_DBNAME = "sales"

Any connection variable can be overwritten in each function call if needed per postgres connection parameter key words.

Below will overide connection dbname for specific function call.

qry="SELECT * FROM customer" 
wrapg.query(raw_sql=qry, conn_kwargs: {'dbname': 'anotherdb'})

Easily call sql upsert or insert_ignore.
The 'keys' parameter represents the on conflict target.

record = {'name': 'Dave', 'email': '[e-mail]'}
wrapg.upsert(data=record, table="customer", keys=["email"])

Todo

• Add delete_row, delete funtionality
• Handle JSON, ITERATOR?
• Add more tests
• Optimize code after it is all working

Acknowledgements

This project built on great work by psycopg 3 and was inspired by dataset

Contact

Created by jturnercode - hope package is helps.

License

• MIT