The Bank Statement Parser is an essential Python library for financial data management. Developed for the busy finance and treasury professional, it simplifies the task of parsing bank statements.
This tool simplifies the process of analysing CAMT and SEPA transaction files. Its streamlined design removes cumbersome manual data review and provides you with a concise, accurate report to facilitate further analysis.
Bank Statement Parser helps you save time by quickly and accurately processing data, allowing you to focus on your financial insights and decisions. Its reliable precision is powered by Python, making it the smarter, more efficient way to manage bank statements.
- Versatile Parsing: Easily handle formats like CAMT (ISO 20022) and beyond.
- Financial Insights: Unlock detailed analysis with powerful calculation utilities.
- Simple CLI: Automate and integrate with a straightforward command-line interface.
- Designed for Finance: Tailored features for the finance sector's needs.
- Efficiency at Heart: Transform complex data tasks into simple ones.
- Community First: Built and enhanced by experts, for experts.
- CamtParser: Parse CAMT format files with ease.
- Pain001Parser: Handle SEPA PAIN.001 files effortlessly.
We recommend creating a virtual environment to install the Bank Statement Parser. This will ensure that the package is installed in an isolated environment and will not affect other projects.
python3 -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
Install bankstatementparser
with just one command:
pip install bankstatementparser
from bankstatementparser import CamtParser
# Initialize the parser with the CAMT file path
camt_parser = CamtParser('path/to/camt/file.xml')
# Parse the file and get the results
results = camt_parser.parse()
from bankstatementparser import Pain001Parser
# Initialize the parser with the PAIN.001 file path
pain_parser = Pain001Parser('path/to/pain/file.xml')
# Parse the file and get the results
results = pain_parser.parse()
Leverage the CLI for quick parsing tasks:
python cli.py --type <file_type> --input <input_file> [--output <output_file>]
--type
: Type of the bank statement file. Currently supported types are "camt" and "pain001".--input
: Path to the bank statement file.--output
: (Optional) Path to save the parsed data. If not provided, data is printed to the console.
-
Parse a CAMT file and print the results to the console:
python cli.py --type camt --input path/to/camt/camt_file.xml
Using the test data:
python ./bankstatementparser/cli.py --type camt --input ./tests/test_data/camt.053.001.02.xml
-
Parse a CAMT file and save the results to a CSV file:
python cli.py --type camt --input path/to/camt/file.xml --output path/to/output/file.csv
Using the test data:
python ./bankstatementparser/cli.py --type camt --input ./tests/test_data/camt.053.001.02.xml --output ./tests/test_data/camt_file.csv
- Parse a PAIN.001.001.03 file and print the results to the console:
python cli.py --type pain001 --input path/to/pain.001.001.03.xml
Using the test data:
python ./bankstatementparser/cli.py --type pain001 --input ./tests/test_data/pain.001.001.03.xml
- Parse a PAIN.001.001.03 file and save the results to a CSV file:
python cli.py --type pain001 --input path/to/pain.001.001.03.xml --output path/to/output/file.csv
Using the test data:
python ./bankstatementparser/cli.py --type pain001 --input ./tests/test_data/pain.001.001.03.xml --output ./tests/test_data/pain_file.csv
The project is licensed under the terms of both the MIT license and the Apache License (Version 2.0).
We welcome contributions to bankstatementparser. Please see the contributing instructions for more information.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.
We would like to extend a big thank you to all the awesome contributors of bankstatementparser for their help and support.
This repo was inspired by khorevkp/KK_Tools's innovative use of data structures and algorithms, and was forked to build upon its foundation. Thank you to Konstantin Khorev