CLIMT (CLI for Modular Text data mining) is a modular data engineering CLI tool for easily producing text mining reports in portable formats.

First, create a virtual environment to manage the project's dependencies.

Using uv:

uv init         # Initialize the project with uv
uv run          # The first run generates the .venv directory

Second, activate the virtual environment:

• On Windows:

.\.venv\Scripts\activate

• On macOS and Linux:

source .venv/bin/activate

Third, install the required dependencies:

uv add -r requirements.txt

Finally, install this project in editable mode so that the climt command is available:

uv pip install -e .

Now you can run the tool from the command line:

climt "This is a sample text." --analyze text words

The software is designed to analyze a text or a text file and generate reports in various formats. The user can interact with the software via the command line using several options for customization.

climt [input] [options]

It is possible to type the command directly in the command line, or type it in the run.sh file and then run it via

./run.sh

• input (Optional): A string representing the raw text to analyze. If not provided, you must specify a file using the --file option.
• --files (Optional): This specifies the path to one or more text files containing the content to analyze. It is an alternative to providing raw text directly.
• --output (Optional): This option allows you to specify the format of the output report. You can choose from the following:
  • stream (default): The output is printed directly to the command line.
  • txt or md: The output is saved as a plain text file or in a Markdown file.
• --outfile (Optional): If you select any option other than stream as the output format, you can provide a file name for the output file. If not specified, the file will be named according to the format (e.g., output.txt or output.md).
• --analyze (Optional): This option allows you to specify the focus of the analysis. The available choices are:
  • text (default): Performs a general statistical analysis on the text.
  • words: Performs a statistical analysis on each word in the text. Also allows generating visualizations for word frequencies.
  • pos: Performs a statistical Part-of-Speech (PoS) analysis on the text. Also allows generating visualizations for PoS frequencies.
  • read: Performs a readability analysis on the text.
  • sent: Performs a sentiment analysis on the text.

You can provide multiple analysis focuses by separating them with space (e.g. --analyze text words read).

climt "This is a sample text."

climt "This is a sample text." --output txt --outfile report.txt

climt --files "input.txt" "other.txt" --output md --outfile report.md

Run the following command in the terminal:

chmod +x test.sh

./test.sh

• Add more analysis modules;
• Implement better CLI UX design;
• Add other formats for report generation (JSON, XML, HTML);
• Add RDF conversion;
• Add visual graphs generation;
• Add research bundle generation.

Barzaghi, Sebastian (https://orcid.org/0000-0002-0799-1527).

@software{barzaghi_2025_14994045,
  author       = {Barzaghi, Sebastian},
  title        = {CLIMT},
  month        = mar,
  year         = 2025,
  publisher    = {Zenodo},
  version      = {v1.0.0},
  doi          = {10.5281/zenodo.14994045},
  url          = {https://doi.org/10.5281/zenodo.14994045},
  swhid        = {swh:1:dir:3ed76b26799f6c467462694f3fb559a7d6157fb4
                   ;origin=https://doi.org/10.5281/zenodo.14994044;vi
                   sit=swh:1:snp:6f73683da2edea4d58c9d324592251ddf66b
                   5a96;anchor=swh:1:rel:924dee9e6fa7d3674e5417ac593d
                   e2a32ac9701b;path=sbrzt-lodot-8ea7eb0
                  },
}