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Copy Spotter

PyPI - Version PyPI - License Python

GIF demo

About

This program will process pdf, txt, docx, and odt files that can be found in the given input directory, find similar sentences, calculate similarity percentage, display a similarity table with links to side by side comparison where similar sentences are highlighted.

Usage

$ pip install copy-spotter
$ copy-spotter [-s] [-o] [-h] input_directory

Positional Arguments:

  • input_directory: One directory that contains all files (pdf, txt, docx, odt) (see data/pdf/plagiarism for example)
input_directory/
│
├── file_1.docx
├── file_2.pdf
└── file_3.pdf

Optional Arguments:

  • -s, --block-size: Set minimum number of consecutive and similar words detected. (Default is 2)
  • -o, --out_dir: Set the output directory for html files. (Default is creating a new directory called results)
  • -h, --help: Show this message and exit.

Examples

# Analyze documents in 'data/pdf/plagiarism', with default settings
$ copy-spotter data/pdf/plagiarism

# Analyze with custom block size and specify output directory
$ copy-spotter data/pdf/plagiarism -s 5 -o results/output

Development Setup:

# Clone this repository
$ git clone https://github.com/Wazzabeee/copy_spotter

# Go into the repository
$ cd copy_spotter

# Install requirements
$ pip install -r requirements.txt
$ pip install -r requirements_lint.txt

# Install precommit
$ pip install pre-commit
$ pre-commit install

# Run tests
$ pip install pytest
$ pytest tests/

# Run package locally
$ python -m scripts.main [-s] [-o] [-h] input_directory

Recommandations

  • Please make sure that all text files are closed before running the program.
  • In order to get the best results please provide text files of the same languages.
  • Pdf files that are made from scanned images won't be processed correctly.
  • Ensure you have writing access when using the package
  • If a specific file is not processed correctly feel free to contact me so that I can address the issue.

TODO

  • Add more tests on existing functions
  • Implement OCR with tesseract for scanned documents
  • Add custom naming option for pdf files