semvec/pypi-packages huggingface dataset:
microtest-framework 1.0.1
Simple but powerful testing framework for Python
Requires Python: >=3.7

# microtest
Simple but powerful testing framework for Python.

<br>

## Installation

    python -m pip install microtest-framework

On Mac and Linux microtest doesn't require any external dependencies.
On Windows [colorama](https://github.com/tartley/colorama) is used to translate ANSI escape sequences to win32 calls.

Microtest currently requires Python version 3.7 or higher.

<br>

## Usage

Here's the simplest testing program you can create with microtest:
```python
import microtest


@microtest.test
def function():
    x = 10
    assert x < 0
    

if __name__ == '__main__':
    microtest.run()
```
You can run this script normally via the command line:

    python test.py

The script will produce the following output:

```
======================================================================
Started testing...
======================================================================
function ..................................................... FAILED

AssertionError on line 7:
assert 10 < 0 


----------------------------------------------------------------------
Ran 1 tests in 0.001s.

ERRORS: 0
FAILED: 1
```

<br>

## Documentation

Full source code refrence and user guide can be found [here](https://varajala.github.io/microtest/docs/).

<br>

## Contributing

To contribute new features to this project do the following steps:

  - Open a new issue explaining the new feature
  - Wait for approval
  - Fork and clone the repository to your local machine and code up the feature in a **new branch**
  - Pull request

The *wait for approval* step is there so that you don't end up coding up some feature that might
not be included into microtest. This could happen if the proposed feature is redundant, changes the
existing api too radically, or simply just is not the *right thing* to be added into microtest.

The goal is to keep this project simple and small.

**Bug fixes, documentation improvements and other minor tweaks are always welcome, no need for approval.** Just leave a pull request with the fixes done in a separate branch.
pylpsd 0.1.4
Method for calulating power spectrum on logarithmic frequency axis.
Requires Python: >=3.5

# py-lpsd

 Python implementation of the pylpsd algorithm for computing power spectral density with logarithmically spaced points. 

## Installation

This package can be installed via pip:

```
pip install pylpsd
```

In case you want to edit this, clone this repository and install it in editable mode:

```
git clone https://github.com/bleykauf/py-lpsd
cd py-lpsd
pip install -e .
```

## Usage
See the Jupyter notebook in the examples folder and the docstring.

 ## Implementation in other languages

 [Matlab](https://github.com/tobin/lpsd): py-lpsd is based on this implementation.