The Enhanced Transparency Framework (ETF) is a set of reporting and review requirements under the Paris Agreement to enhance the transparency of climate action and support.
Parties can submit their ETF GHG inventory data in the electronic format of a CRT Data Exchange JSON file.
The structure and requirements of the CRT Data Exchange JSON format are described in detail at the UNFCCC ETF reporting tools help page.
This repository contains the source code of a command line tool for processing CRT Data Exchange JSON files before importing them into ETF GHG inventory.
The tool supports the following functionality:
- Splitting reports into subsets, filtered by GHG inventory sectors.
- Adding missing metadata required by the ETF Reporting Tools.
To install and set up the CLI tool, follow these steps:
- Prepare and activate a Python virtual environment:
python -m venv venv
source venv/bin/activate # On Windows use: venv\Scripts\activate
pip install build wheel- Clone the GitHub repository and build the package:
git clone https://github.com/unfccc/etf-cli
cd etf-cli
python -m build- Install the resulting package:
pip install dist/unfccc_etf_cli-1.0.0-py3-none-any.whlLocate the root node for LULUCF sector of medatata:
etf metadata find LULUCF
Locate lower level node in the Agriculture sector of medatata:
etf metadata find "3.F.1.b. Barley"
Filter out all country data, leaving only related to energy sector, print result to standard output:
etf data filter -s energy country_data.json
Apply all known fixes to satisfy import requirements:
etf data fix -r ALL country_data.json
Only insert missing template grids into the country data:
etf data fix -r GRIDS country_data.json
Print statistic of country data:
etf data stats country_data.json
The tool contains built-in help on commands, available by calling with --help parameter.
Please submit any issues directly into this repository and not via ETF reporting tools ServiceNow portal.
That will ensure proper routing and faster processing.
Special thanks to Pallets Projects, creators of excellent Click Python package.
This project is licensed under the MIT License. See the LICENSE file for details.