semvec/pypi-packages huggingface dataset:
pytest-toolkit 0.1.8
Useful utils for testing
Requires Python: >=3.10

# pytest_toolkit

pytest_toolkit - is an useful utils for testing applications

# how to use

1. Installation
    ```
    pip install pytest-toolkit
    ```
    ```
    pytest tests/
    ```
2. Get started 
    ```
    The advantage is in having clear understanding of difference between 
    response.json and static json. For example
    {
        'Значение или тип элемента изменены': 
        {"root['example1']": {'new_value': 'example2', 'old_value': 'example1'}}
    } == {}
    Its easy to see that value of key 'example1' changed from 'example1' to 'example2'.
    ```
    ```
    from pytest_toolkit import get_diff

    def test():
        response = client.get(url)
        assert get_diff(result_dict=response.json()) == {}
    ```
    OR
    ```
    from pytest_toolkit import get_file_json

    def test():
        response = client.get(url)
        assert get_file_json() == response.json()
    ```
3. Static files search
    ```
    1. You need to create static directory in tests/
    2. If you create filename test_a.py with test_b function, you need to 
    create "a" directory in static directory and "b.json" in directory "a". 
    Library will automatically find a file for get_diff function
    3. If you don't have directory "a" in static files, library will try
    to find file "b.json" in "default" directory first

    If you don't want compare responses manually, you can use get_file_json function:
    ```
    ```
    from pytest_toolkit import get_file_json

    def test():
        response = client.get(url)
        assert get_file_json() == {"test": "test"}
    ```
4. DOESNT_MATTER
    ```
    1. If you don't care about value of dictionary, but you need a key, you
    can write "DOESNT_MATTER" in value and library will skip checking of this field.
    2. If you need to have a constraint for value, you can write python code,
    for example "DOESNT_MATTER > 9" and library will check response.json() value is more than 9.
    ```
5. Check directory tests for more information and examples
6. Coverage
    ```
    ---------- coverage: platform darwin, python 3.12.1-final-0 ----------
    Name                          Stmts   Miss  Cover
    -------------------------------------------------
    pytest_toolkit/__init__.py        2      0   100%
    pytest_toolkit/configure.py       9      0   100%
    pytest_toolkit/constants.py       5      0   100%
    pytest_toolkit/errors.py          2      0   100%
    pytest_toolkit/json.py           83      0   100%
    -------------------------------------------------
    TOTAL                           101      0   100%
    ```
static-analysis-script 0.2.7
A utility to perform static analysis on files.


## Static-analysis-script 
Welcome to the Static Analysis Script! This Python tool is crafted to extract emails, paths, files, URLs, and IPs from the specified file for analysis.
## Purpose
This tool aids in the collection of data essential for static analysis, accelerating the detection of Indicators of Compromise (IOCs) and other potentially malicious activities executed by files.
## Installation

### option 1:
pip install from the pypi project
```bash
  python -m pip install static-analysis-script
```
please make sure to download the latest version, currently 0.2.3

### option 2:
git clone the project.
pip install local from the git directory
```bash
  git clone https://github.com/perzibel/static-analysis-script.git
  cd static-analysis-script
  python -m pip install .
```
    
## Usage

![image](https://github.com/perzibel/static-analysis-script/assets/58742092/2734c00a-3f4d-4f36-bed4-48e72e8656a9)


## Analysis of Executables and DLL Files
The tool employs strings.exe to pull strings from executable (EXE) and dynamic link library (DLL) files, analyzing these strings to pinpoint paths, files, IP addresses, and URLs.

NEW! extract WinApi commands in the file 

## Analysis of CSV Files
For Comma-Separated Values (CSV) files, the tool extracts relevant information by directly reading the contents of the files.

## Analysis of Word Documents
Utilizing the zipfile library, the tool processes Word documents, extracting embedded emails and URLs from various sections.

## Analysis of PDF Files
extract ALL visiable and hidden URIs
anonymizePy 0.1.6
A PII removal toolkit to help you anonymize your data.
Requires Python: >=3.8

# anonymizePy: *anonymize your data with ease*

[![PyPI version](https://img.shields.io/pypi/v/anonymizePy?color=0071B6)](https://pypi.org/project/anonymizePy/)

### 🤔 What is anonymizePy?
As part of a research project, I was working on developing methods to anonymize data for a local crisis response team. I quickly realized the greater potential for an easy (it's only three steps!) tool to allow people of all skill levels to leverage methods such as named entity recognition, regular expressions, and more to anonymize their data. anonymizePy is a tool that allows anyone to *anonymize their data* ✨.

### 🧑‍💻 How to install anonymizePy

1. Install anonymizePy: `pip install anonymizePy`
2. Install neccecary model: `pip install https://huggingface.co/beki/en_spacy_pii_distilbert/resolve/main/en_spacy_pii_distilbert-any-py3-none-any.whl`

### 🧑‍🔬 How to use anonymizePy
Once anonymizePy is installed, you can run [example.py](example.py) to get an idea on how anonymizePy works!

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A package by Aussie Frost. Last updated 6/6/2024. Thanks for viewing!