This is a showcase for a fictional scenario that could be encountered in the context of investment banking operations.
The scenario is as follows: "The regulatory reporting team have to change their current reporting data format from CSV to XML and enrich their data with counterparty information. The volume is 5 transactions per day.".
This project showcases a potential solution to automate the process of converting a CSV of transaction(like) data into XML format, whilst intermittently enriching the data with additional information for each of the counterparties involved in the transaction, using publicly available information from the GLEIF API.
- Python 3.10 or higher
- Poetry for Python (can be installed using pip:
pip install poetry)
Follow these steps to get the install the project.
- Clone the repository
git clone [email protected]:harley-rm/transactions-report-xmliser.git
- Navigate to the project directory
cd transactions-report-xmlilser
- Install all dependencies using poetry (by default, poetry will create a venv)
poetry install
- Prepare your input. Place your input csv in a suitable location, and choose where you would like your output to go.
- Run the XMLiser Tool
poetry run xmlise --input-file-path <path/to/inputcsv.csv> --output-directory-path <path/to/outputdir>