semvec/pypi-packages huggingface dataset:
pudo 1.6.1
Python version of linux sudo command without password prompt

**Pudo Package**

This is an Python Package for running Linux commands with root permission.
We can see this as an alternative to Linux sudo command without password prompt.
This is very handy when you are writing python automation scripts and need to deal with root privileges.
You can use this as an python module or an Linux command.

Before using the pudo, please accept the Disclaimer:

    user$ sudo /usr/local/bin/pudo --accept-disclamer
	We trust you have received the usual lecture from the local System
	Administrator. It usually boils down to these three things:

		#1) Respect the privacy of others.
		#2) Think before you type.
		#3) With great power comes great responsibility.

	PLEASE NOTE:
		Pudo Developers are not responsible for any misuse of Root Privileges

	Thank You for Accepting the Disclaimer:
	    It is great quality of you to respect other's privacy

Below is the code snippet for using in python automation for running commands under root privilege:

    user$ python3 # or python2
    >>> from pudo import pudo
    >>> (ret, out) = pudo.run(('ls', '/root')) # or pudo.run('ls /root')
    >>> print(ret)
    0
    >>> print(out)
    b'Desktop\nDownloads\nPictures\nMusic\n'

Below is the cmd example for running commands under root privilege:

    user$ pudo ls /root
    Desktop  Downloads  Pictures  Music
ItIf 0.10
ItIf provides a convenient and interactive way to transform time signal to frequncy spectra via FFT
Requires Python: >=3.7
Keywords: FFT, Spectroscopy

# I(t) to I(f)

This package provides an graphical user interface to convert a timesignel (I(t)) to a frequency spectrum (I(f)) via Fast Fourier transform (FFT).
Different window functions can be applied, the window position and duration can be changed interactively and zeropadding can be applied.

The default options are chosen to fit our usecase in the [Labastro Group Cologne](https://astro.uni-koeln.de/schlemmer).
If your dataformats are different, please modify the default options file accordingly.
To do this, start the program and save the default values via *File > Save as default*. This creates the file "~/.itif./default.json".

This file is in simple json format and can be edited with your editor of choice.

Find the project on [PyPi](https://pypi.org/project/ItIf/) or install via
```
pip install itif
```
sax-ts 1.2
Symbolic Aggregate approXimation (SAX)
Requires Python: >=3.9

# Symbolic Aggregate approXimation #

This package implements the Symbolic Aggregate approXimation (SAX) algorithm in C++ with Python bindings using pybind11. SAX is a time series discretization method that represents a continuous-valued time series as a (sliding window of) symbolic representation(s). 

[Jessica Lin's SAX page](http://cs.gmu.edu/~jessica/sax.htm)

[Eamonn Keogh's SAX page](http://www.cs.ucr.edu/~eamonn/SAX.htm)

# Installation
The easiest way to install `sax-ts` is via pip:
```
pip install sax-ts
```

If you want to run the tests locally, install the optional dependencies:
```
pip install "sax-ts[test]"
```

You can then import the `sax` and `paa` functions as follows:
```Python
from sax_ts import sax, paa
```
# References

P. Patel, E. Keogh, J. Lin and S. Lonardi, "Mining motifs in massive time series databases," 2002 IEEE International Conference on Data Mining, 2002. Proceedings., Maebashi City, Japan, 2002, pp. 370-377, doi: 10.1109/ICDM.2002.1183925.

J. Lin, E. Keogh, S. Lonardi, and B. Chiu, "A symbolic representation of time series, with implications for streaming algorithms," In Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery, 2003, pp. 2-11, doi: 10.1145/882082.882086.

J. Lin, E. Keogh, L. Wei, and S. Lonardi, "Experiencing SAX: a novel symbolic representation of time series," Data Min Knowl Disc, vol. 15, pp. 107–144, Apr. 2007, doi: 10.1007/s10618-007-0064-z.
coloraiz 1.0.3
Simple way to add color to your terminal text output
Requires Python: >=3.6

# coloraiz

coloraiz is a Python library that provides a simple way to add color to your terminal text output. This library is a copy of the popular `colorama` library, created for educational purposes to help users understand how terminal text coloring works in Python.

## Installation

You can install coloraiz using pip. Run the following command in your terminal:

```bash
pip install coloraiz
```

## Usage

To use coloraiz, simply import it in your Python script and use the provided functions to color your text. Here’s a quick example:

```python
from coloraiz import Fore, Back, Style

print(Fore.RED + 'This text is red!')
print(Back.GREEN + 'This background is green!')
print(Style.RESET_ALL + 'Back to normal text.')
```

### Available Colors

#### Foreground Colors
- `Fore.BLACK`
- `Fore.RED`
- `Fore.GREEN`
- `Fore.YELLOW`
- `Fore.BLUE`
- `Fore.MAGENTA`
- `Fore.CYAN`
- `Fore.WHITE`

#### Background Colors
- `Back.BLACK`
- `Back.RED`
- `Back.GREEN`
- `Back.YELLOW`
- `Back.BLUE`
- `Back.MAGENTA`
- `Back.CYAN`
- `Back.WHITE`

#### Styles
- `Style.DIM`
- `Style.NORMAL`
- `Style.BRIGHT`
- `Style.RESET_ALL`

## Example

Here’s a more comprehensive example demonstrating the use of coloraiz:

```python
from coloraiz import Fore, Back, Style

print(Fore.GREEN + 'Success: Operation completed successfully!' + Style.RESET_ALL)
print(Back.RED + Fore.WHITE + 'Error: Something went wrong!' + Style.RESET_ALL)
print(Fore.YELLOW + 'Warning: Check your input.' + Style.RESET_ALL)
```

## Compatibility

coloraiz is compatible with Windows, macOS, and Linux. It automatically detects the operating system and applies the appropriate settings for terminal color support.

## Contributing

Contributions are welcome! If you would like to contribute to coloraiz, please fork the repository and submit a pull request.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Disclaimer

coloraiz is intended for educational purposes only. It is a copy of the `colorama` library and should not be used in production environments. For production use, please refer to the original `colorama` library.

## Acknowledgments

- [Colorama](https://pypi.org/project/colorama/) - The original library that inspired this educational project.