semvec/pypi-packages huggingface dataset:
solugen.env-manager 0.1.0
A Python library to manage environment variables
License: MIT
Requires Python: >=3.6

# Environment Setup for `env_manager`

To properly use this library, ensure your project contains the following files in its root directory:

1. **`.env.dev`**

   - Used for development environment variables.
   - **Important**: Add this file to `.gitignore` to avoid committing sensitive data.

2. **`.env.prod`**

   - Used for production environment variables.
   - **Important**: Add this file to `.gitignore` to avoid committing sensitive data.

3. **`.env.example`**
   - A template file that details the required environment variables and their structure.
   - **Do not add this file to `.gitignore`**, as it serves as documentation for other developers, and more importantly - it's necessary for the funtionality, as it loads the key names.

---

## Key Guidelines

- **Never use quotes** (`"` or `'`) in environment variable values. This ensures compatibility and avoids parsing issues.

---

## Running in Development Mode

To run the application in development mode:

- Explicitly set the environment variable `FLASK_DEV_ENV`.
- The value of `FLASK_DEV_ENV` can be arbitrary (any value is acceptable).

```bash
export FLASK_DEV_ENV=true
```
pvanalytics 0.2.2
PVAnalytics is a python library for the analysis of photovoltaic system-level data.
License: MIT


PVAnalytics is a collection of functions for working with data
from photovoltaic power systems. The library includes functions for
general data quality tests such as outlier detection, validation that
data is physically plausible, filtering data for specific conditions,
and labeling specific features in the data.

Documentation: https://pvanalytics.readthedocs.io

Source code: https://github.com/pvlib/pvanalytics
libtsm 1.1.2
Python Package for Time-Scale Modification and Pitch-Shifting
License: MIT
Requires Python: >=3.6
Keywords: audio, music, tsm, pitch-shifting

# libtsm

A Python toolbox for Time-Scale Modification (TSM) and Pitch-Shifting.

Details and example application:

https://www.audiolabs-erlangen.de/resources/MIR/2021-DAFX-AdaptivePitchShifting

`libtsm` is based on a re-implementation of the Matlab TSM Toolbox by Jonathan Driedger and Meinard Müller:

https://www.audiolabs-erlangen.de/resources/MIR/TSMtoolbox/

If you use the libtsm in your research, please consider the following references.

## References

Sebastian Rosenzweig, Simon Schwär, Jonathan Driedger, and Meinard Müller:
Adaptive Pitch-Shifting with Applications to Intonation Adjustment in A Cappella Recordings
Proceedings of the International Conference on Digital Audio Effects (DAFx), 2021.

Jonathan Driedger and Meinard Müller:
[TSM Toolbox: MATLAB Implementations of Time-Scale Modification Algorithms.](https://www.audiolabs-erlangen.de/fau/professor/mueller/publications/2014_DriedgerMueller_TSM-Toolbox_DAFX.pdf)
In Proceedings of the International Conference on Digital Audio Effects (DAFx): 249–256, 2014.

Jonathan Driedger and Meinard Müller:
[A Review on Time-Scale Modification of Music Signals.](https://www.mdpi.com/2076-3417/6/2/57)
Applied Sciences, 6(2): 57–82, 2016.

Jonathan Driedger, Meinard Müller, and Sebastian Ewert:
[Improving Time-Scale Modification of Music Signals using Harmonic-Percussive Separation.](https://ieeexplore.ieee.org/abstract/document/6678724)
IEEE Signal Processing Letters, 21(1): 105–109, 2014.

## Installation

With Python >= 3.6, you can install libtsm using the Python package manager pip:

```
pip install libtsm
```

## Documentation

The API documentation of `libtsm` is hosted here:

https://meinardmueller.github.io/libtsm

## Contributing

We are happy for suggestions and contributions. However, to facilitate the synchronization, we would be grateful for either directly contacting us via email (meinard.mueller@audiolabs-erlangen.de) or for creating [an issue](https://github.com/meinardmueller/libtsm/issues) in our GitHub repository. Please do not submit a pull request without prior consultation with us.

If you want to report an issue with libtsm or seek support, please use the same communication channels (email or GitHub issue).

## Tests

Central to our tests is the comparison of `libtsm` with the MATLAB TSM Toolbox.
To this end, please execute `tests/test_matlab.m` in MATLAB to create the MATLAB output.
Then, you can use [pytest](https://pytest.org) for executing our Python test scripts. `pytest` is available when installing libtsm with the extra requirements for testing.

```
pip install 'libtsm[tests]'
pytest
```

## Acknowledgements

This project is supported by the German Research Foundation (DFG MU 2686/12-1, MU 2686/13-1).
The International Audio Laboratories Erlangen are a joint institution of the Friedrich-Alexander Universität Erlangen-Nürnberg (FAU) and Fraunhofer Institute for Integrated Circuits IIS. We thank Edgar Suarez, El Mehdi Lemnaouar and Miguel Gonzales for implementation support.