https://github.com/okp4/detection-of-personal-data
📟 CLI tool to detect sensitive personal data
https://github.com/okp4/detection-of-personal-data
sensitive-data-discovery
Last synced: 25 days ago
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📟 CLI tool to detect sensitive personal data
- Host: GitHub
- URL: https://github.com/okp4/detection-of-personal-data
- Owner: okp4
- License: bsd-3-clause
- Archived: true
- Created: 2022-03-03T15:41:42.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-21T03:37:09.000Z (11 months ago)
- Last Synced: 2024-11-04T19:42:32.325Z (6 months ago)
- Topics: sensitive-data-discovery
- Language: Python
- Homepage:
- Size: 4.3 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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- awesome-ccamel - okp4/detection-of-personal-data - 📟 CLI tool to detect sensitive personal data (Python)
README
# Detection Of Personal data
[](https://github.com/okp4/detection-of-personal-data/releases)[](https://github.com/okp4/detection-of-personal-data/actions/workflows/lint.yml)[](https://github.com/okp4/detection-of-personal-data/actions/workflows/build.yml)[](https://github.com/okp4/detection-of-personal-data/actions/workflows/test.yml)
[](https://codecov.io/gh/okp4/detection-of-personal-data)
[](https://conventionalcommits.org)
[](https://github.com/okp4/.github/blob/main/CODE_OF_CONDUCT.md)
[](https://opensource.org/licenses/BSD-3-Clause)
## Purpose
`detection-of-personal-data` is a CLI tool to detect sensitive personal data, including names, contact information, health details, identification numbers, and financial details.
Users can input a variety of text files (e.g., `.txt`, `.csv`) which the service then processes, returning a JSON. The JSON not only indicates the presence of personal information but also provides tags for the detected data.
## Technology
### Nltk
NLTK is a leading platform for building Python programs to work with human language data. It provides easy - to - use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial - strength NLP libraries, and an active discussion forum.
### RE (Regular Expression)
A regular expression is a method used in programming for pattern matching. Regular expressions provide a flexible and concise means to match strings of text.
### [Transformers](https://huggingface.co/docs/transformers/index)
State-of-the-art Machine Learning for PyTorch, TensorFlow and JAX.
Transformers provides APIs to easily download and train state-of-the-art pretrained models.
### Usage
Retrieve command help with:
```sh
poetry run detection-of-personal-data pii-detect --help
```
```console
Usage: detection-of-personal-data pii-detect [OPTIONS]
Represents cli 'pii_detect' command
Options:
-i, --input TEXT path to text file [required]
-o, --output TEXT output directory where json file will be
written [default: .]
-tr, --thresh ... the minimum probability of private data for
labels
-f, --force overwrite existing file
--dry-run passthrough, will not write anything
--help Show this message and exit.
```
Example:
```sh
poetry run detection-of-personal-data pii-detect \
-tr person 0.3 \
-tr passport 0.3 \
-i ./tests/data/inputs_test/text \
-o ./tests/data/outputs -f
```
## System requirements
### Python
The repository targets python `3.9` and higher.
### Poetry
The repository uses [Poetry](https://python-poetry.org) as python packaging and dependency management. Be sure to have it properly installed before.
```sh
curl -sSL https://install.python-poetry.org | python3
```
#### Docker
You can follow the link below on how to install and configure **Docker** on your local machine:
- [Docker Install Documentation](https://docs.docker.com/install/)
## Everyday activity
### Build
Project is built by [poetry](https://python-poetry.org). Initialize the project using:
```sh
poetry install
```
### Quality Assurance
> ⚠️ Ensure your code complies with our linters to pass CI checks.
**Code linting** is performed by [flake8](https://flake8.pycqa.org).
```sh
poetry run flake8 --count --show-source --statistics
```
**Static type check** is performed by [mypy](http://mypy-lang.org/).
```sh
poetry run mypy .
```
To improve code quality, we use other linters in our workflows, if you want them to succeed in the CI,
please check these additional linters.
**Markdown linting** is performed by [markdownlint-cli](https://github.com/igorshubovych/markdownlint-cli).
```sh
markdownlint "**/*.md"
```
**Docker linting** is performed [hadolint](https://github.com/hadolint/hadolint).
```sh
hadolint Dockerfile
```
#### Unit Testing
> ⚠️ Be sure to write tests that succeed to pass CI checks.
Unit testing is performed by the [pytest](https://docs.pytest.org) testing framework.
```sh
poetry run pytest -v
```
### Build & run docker image (locally)
Build a local docker image using the following command line:
```sh
docker build -t detection-of-personal-data .
```
Once built, you can run the container locally with the following command line:
```sh
docker run -ti --rm detection-of-personal-data
```
## You want to get involved? 😍
Please check out OKP4 health files :
- [Contributing](https://github.com/okp4/.github/blob/main/CONTRIBUTING.md)
- [Code of conduct](https://github.com/okp4/.github/blob/main/CODE_OF_CONDUCT.md)