Metadata-Version: 2.1
Name: lor_gdp_tools
Version: 0.1.10
Summary: This is a utility package designed to enable data scientitists and analysts to easily access GDP data within a python environment
Home-page: https://github.com/laingorourke/lor-gdp-tools
Author: Damian Rumble <DRumble@laingorourke.com>
Description-Content-Type: text/markdown

# Gdp Tools Package

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This is a utility package designed to enable data scientists and analysts to easily access GDP data within a python environment

Requirements:
- The data professional should be able to clone the package at the start of new project and when in production
- The package will contain a number of support functions serving the following objectives:
-- Accessing data on GDP Base/CIM/Warehouse 
-- Accessing data in temp storage (LAB)
-- Querying that data in SQL
-- utlising that data as a Python/PySpark DataFrame
-- Storing processed data to the temp storage space (LAB)
- any data access configs should available to be used 

### Credentials

See .env file for credentials. Contact a member of the Laing O'Rourke Data Science team to access these

### Functionality

**validate_odbc_drivers** - check if the correct ODBC connectors are installed, install them as necessary automatically [**check_odbc_driver**, **install_odbc_driver**] 

**setup_odbc_connection** - set up the ODBC with your credentials. Happens when class is initalised

**query_gdp_to_pd** - enter a SQL query as a string, return the data as a pandas dataframe

**search_tables** - will return a list of all table in the GDP. give it the argument 'source_system' = '[COINS]' to narrow your search for any table with the term 'COINS' in it (for example)  






