The backend of the tool is written in Python3 and depends on the following libraries:
| Name | URL | Install |
|---|---|---|
| scikit-learn | https://scikit-learn.org/stable/index.html | pip install scikit-learn |
| Flask | https://flask.palletsprojects.com/en/1.1.x/ | pip install Flask |
| Jinja2 | https://jinja.palletsprojects.com/en/2.11.x/ | pip install Jinja2 |
| Pandas | https://pandas.pydata.org/ | pip install pandas |
| Unidecode | https://pypi.org/project/Unidecode/ | pip install Unidecode |
Make sure you have Python3 and pip installed with the dependencies in the table above.
- Go to data_cleaning/tables.txt and insert the absolute paths of the .csv-files that you want to clean. Do not move, rename or delete this file!
- Go to the root folder of this project and execute
python -m data_cleaning.start_server. This will start the server and process the data.- To run the program on a specific port, run
python -m data_cleaning.start_server -p PORTNUMBER, with PORTNUMBER any portnumber you want. By default, the program will run on port 5000. - Functional dependencies are disabled by default since version v1.1.0. Add
--enable-functional-dependenciesto the command to enable this functionality.
- To run the program on a specific port, run
- Go to http://127.0.0.1:5000/ (or to another port) to use the client and start your cleaning procedure.