transtractor 0.9.2

Universal PDF bank statement parsing library

The Transtractor

Universal PDF bank statement parsing

The Transaction Extractor, or 'Transtractor', aspires to be a universal library for extracting transaction data from PDF bank statements. Key features:

• Written in Rust (fast)
• Python API (user friendly)
• AI-free (lightweight)
• Rules-based extraction (100% predictable and accurate)

Installation

Install from PyPI

Transtractor is available on PyPI and can be installed with pip:

pip install transtractor

Requirements: Python 3.9 or higher

Compile from source

1. Install Rust: Download and install Rust from rustup.rs

2. Install Maturin: Install the Python build tool for Rust extensions

   pip install maturin
   

3. Build and install Transtractor: Clone the repository and build

   git clone https://github.com/gravytoast/transtractor.git
   cd transtractor
   maturin develop --release
   

Basic usage

1. Import and initialise the parser

   from transtractor import Parser
   
   parser = Parser()
   

2. Convert PDF to CSV: All CSV files are written in a standard format

   parser.parse('statement.pdf').to_csv('statement.csv')
   

3. Convert PDF to DataFrame: Load into a DataFrame for analysis

   import pandas as pd
   
   data = parser.parse('statement.pdf').to_pandas_dict()
   df = pd.DataFrame(data)
   

Advanced usage

See the documentation maintained on Read the Docs.

Supported statements

See the documentation for a current list of supported statements. You may also create your own parsing configuration files by following these instructions and loading it by:

from transtractor import Parser

parser = Parser()
parser.load('my_config.json')
parser.parse('statement.pdf').to_csv('statement.csv')

Contributions

New and well-tested configuration files are especially welcome. Please submit a pull request with them add to the python/transtractor/configs directory, or email to [e-mail].