Data Parsing and Database Insertion Script

Overview

This script parses data from CSV files and inserts it into a PostgreSQL database. The data includes information about entities, officers, roles, addresses, intermediaries, and relationships between them.

Contact me for the sample CSV files i used.

Prerequisites

Python 3
PostgreSQL database
Python virtual enviroment

Installation

Install the required Python packages:
```
pip install -r requirements.txt
```

Usage

Ensure that your CSV files are placed in the same folder as the script.
Create a PostgreSQL database with the necessary credentials.
Run the script with the following command:
```
python parser.py -H <hostname> -p <port> -U <username> -P <password> -d <database>
```
Replace <hostname>, <port>, <username>, <password>, and <database> with your PostgreSQL database connection details.

Files in the Same Folder

queries.sql: SQL script for creating the database schema.
csv_panama_papers/: Place your CSV files in this folder.

Notes

This repository provides two methods for using the parser:
1. Automated Setup:
  - Run the parser_automated.py script after initializing the PostgreSQL database. Refer to the usage instructions for the code snippet.
  - This automated process will create the necessary database schema and parse the data automatically.
2. Manual Setup:
  - Execute the schema.sql script to manually create the database schema.
  - Run the parser.py script (as described in the usage section).
  - This will generate a substantial .sql file named data.sql (approximately 400MB).
  - Execute the generated data.sql file to insert the parsed data into the database.

Choose the method that best fits your requirements and workflow. If you opt for the automated setup, the entire process, including schema creation and data parsing, is handled in a single step. For manual setup, you have more control over the individual steps, allowing for customization or troubleshooting as needed.

dimcel / Panama_papers_SQL