Metadata-Version: 2.1
Name: pymwp
Version: 0.1.2
Summary: Implementation of MWP analysis on C code in Python
Home-page: https://github.com/seiller/pymwp
Author: Clément Aubert, Thomas Rubiano, Neea Rusch, Thomas Seiller
Author-email: nrusch@augusta.edu
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/seiller/pymwp/issues
Project-URL: Documentation, https://seiller.github.io/pymwp/
Platform: UNKNOWN
Classifier: Natural Language :: English
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Classifier: Environment :: Console
Classifier: Typing :: Typed
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENCE.md

# pymwp: MWP analysis in Python

[![build](https://github.com/seiller/pymwp/actions/workflows/build.yaml/badge.svg)](https://github.com/seiller/pymwp/actions/workflows/build.yaml)
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[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pymwp)](https://pypi.org/project/pymwp/)
[![PyPI](https://img.shields.io/pypi/v/pymwp)](https://pypi.org/project/pymwp/)

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pymwp is a tool for automatically performing static analysis on programs written in C, inspired by [_"A Flow Calculus of mwp-Bounds for Complexity Analysis"_](https://doi.org/10.1145/1555746.1555752).
It analyzes resource usage and determines if a program's variables growth rates are no more than polynomially related to their inputs sizes.
You can run our [many examples](https://seiller.github.io/pymwp/examples/) on-line [in our demo](https://seiller.github.io/pymwp/demo/) before [installing it](https://seiller.github.io/pymwp/), or consult our list of [supported C language features](https://seiller.github.io/pymwp/features/).

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## Documentation and Demo

Refer to **[seiller.github.io/pymwp](https://seiller.github.io/pymwp/)** for a documentation of our modules, an [on-line demo](https://seiller.github.io/pymwp/demo/) as well as a presentation of [our examples](https://seiller.github.io/pymwp/examples/).

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## Installation

Install latest release from PyPI

```
pip install pymwp
```

## How to Use

To analyze a C file, run:

```
pymwp path/to_some_file.c
```

For all available options and help, run:

```
pymwp
```


You can also use pymwp in a Python script:

```python
from pymwp import Polynomial
from pymwp.matrix import identity_matrix, show

matrix = identity_matrix(3)
matrix[0][1] = Polynomial('m')
matrix[1][0] = Polynomial('w')
matrix[2][1] = Polynomial('p')

show(matrix)
```

See [documentation](https://seiller.github.io/pymwp/analysis) for available modules and methods.

## Running from source

If you want to use the latest stable version (possibly ahead of 
latest release), use the version from source following these steps.

1. Clone the repository

    ```bash
    git clone https://github.com/seiller/pymwp.git
    ``` 

2. Set up Python environment

    install required packages

    ```bash
    pip install -q -r requirements.txt
    ``` 

3. Run the analysis

    From project root run:
    
    ```bash
    python -m pymwp path/to_some_file.c
    ```

    for example:
    
    ```bash
    python -m pymwp c_files/basics/if.c
    ```
    
    for all available options and help, run:
    
    ```bash
    python -m pymwp
    ```

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