semvec/pypi-packages huggingface dataset:
sscstu 0.0.3
Super Simple Cloud Storage Transfer Utilities
Requires Python: >=3.6

Super Simple Cloud Storage Transfer Utilities
========

This project is designed to be a *super* high level interface
for transferring files to and from various cloud storage solutions.

For example, copying a single folder from one S3 bucket to another:
```python3
from sscstu.storage.s3 import S3Storage, S3StorageItem
from sscstu.transfer import transfer

src = S3Storage(bucket_name='my-bucket')
dest = src = S3Storage(bucket_name='my-other-bucket')
transfer(src, dest, source_basepath="Foldername", destination_prefix="Foldername")

```

Installation
------------

    python3 -m pip install sscstu

Contribute
----------

- Issue Tracker: https://github.com/16awala/py-sscstu/issues
- Source Code: https://github.com/16awala/py-sscstu

License
-------

The project is licensed under the LGPLv3 license.
adguard-sync 1.0
Sync dns rewrites on multiple adguards
Requires Python: >=3.9

# AdguardSync

This script syncs the DNS-Rewrite list with the given config file.

Example:
```python
>>> from adguard_sync import AdguardSync
>>> AdguardSync('config.yml')
```

Configuration File:
```yaml
---

adguards:
  - hostname: https://10.0.0.3
    username: adguard
    password: adguard_pass
    verify_ssl: False # (Optional, default = True)
  - hostname: https://10.0.0.4
    username: adguard
    password: adguard_pass

dns_records:
  - domain: adguard.test
    address: 10.0.0.3
  - domain: adguard2.test
    address: 10.0.0.4
```
digipale 2.3.4
Generate harmonious colors freely.
Keywords: Color-Editor

# DigitalPalette
![DigitalPalette](https://raw.githubusercontent.com/liujiacode/DigitalPalette/master/src/main/icons/full/icon_full_256.png)

DigitalPalette is a free software for generating a set of harmonious colors from a color wheel or an existed image, or deriving a gradual board from current color set, and applying these colors into your creative works.

# Repository
[Source Code](https://github.com/liujiacode/DigitalPalette)

# Version
[2.3.4 Preview](https://github.com/liujiacode/DigitalPalette/releases/tag/v2.3.4-pre)

# Author
[Eigenmiao](mailto:eigenmiao@outlook.com)

# Copyright
Copyright (c) 2019-2021 [Eigenmiao](mailto:eigenmiao@outlook.com). All Rights Reserved.

# License
DigitalPalette is a free software, which is distributed in the hope that it will be useful, but without any warranty. You can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation. See the [GNU General Public License 3.0 (GPL 3.0)](https://www.gnu.org/licenses/) for more details.

All images (including logo and sample images, etc.), documents and translations in DigitalPalette [code repository](https://github.com/liujiacode/DigitalPalette) are licensed under [Creative Commons Attribution-NonCommercial-ShareAlike License 4.0 (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/) unless stating additionally.

DigitalPalette default uses [Noto Serif](https://fonts.google.com/specimen/Noto+Serif) ([SC](https://fonts.google.com/specimen/Noto+Serif+SC)) fonts and [Noto Sans](https://fonts.google.com/specimen/Noto+Sans) ([SC](https://fonts.google.com/specimen/Noto+Sans+SC)) fonts for interface display, which are designed by Google and published in website [Google Fonts](https://fonts.google.com/). These fonts are open-sourced under [Apache 2.0](http://www.apache.org/licenses/) and [SIL Open Font License 1.1](http://scripts.sil.org/OFL), respectively.

# Update
| Version   | Tag    | Category | Date       |
| --------- | ------ | -------- | ---------- |
| 2.2.10    | x1d1s1 | Preview  | 2020/08/23 |
| 2.3.4     | x2d2s2 | Preview  | 2021/03/21 |
digipale-startup 2.3.4
Generate harmonious colors freely.
Keywords: Color-Editor

# DigitalPalette
![DigitalPalette](https://raw.githubusercontent.com/liujiacode/DigitalPalette/master/src/main/icons/full/icon_full_256.png)

DigitalPalette is a free software for generating a set of harmonious colors from a color wheel or an existed image, or deriving a gradual board from current color set, and applying these colors into your creative works.

# Repository
[Source Code](https://github.com/liujiacode/DigitalPalette)

# Version
[2.3.4 Preview](https://github.com/liujiacode/DigitalPalette/releases/tag/v2.3.4-pre)

# Author
[Eigenmiao](mailto:eigenmiao@outlook.com)

# Copyright
Copyright (c) 2019-2021 [Eigenmiao](mailto:eigenmiao@outlook.com). All Rights Reserved.

# License
DigitalPalette is a free software, which is distributed in the hope that it will be useful, but without any warranty. You can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation. See the [GNU General Public License 3.0 (GPL 3.0)](https://www.gnu.org/licenses/) for more details.

All images (including logo and sample images, etc.), documents and translations in DigitalPalette [code repository](https://github.com/liujiacode/DigitalPalette) are licensed under [Creative Commons Attribution-NonCommercial-ShareAlike License 4.0 (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/) unless stating additionally.

DigitalPalette default uses [Noto Serif](https://fonts.google.com/specimen/Noto+Serif) ([SC](https://fonts.google.com/specimen/Noto+Serif+SC)) fonts and [Noto Sans](https://fonts.google.com/specimen/Noto+Sans) ([SC](https://fonts.google.com/specimen/Noto+Sans+SC)) fonts for interface display, which are designed by Google and published in website [Google Fonts](https://fonts.google.com/). These fonts are open-sourced under [Apache 2.0](http://www.apache.org/licenses/) and [SIL Open Font License 1.1](http://scripts.sil.org/OFL), respectively.

# Update
| Version   | Tag    | Category | Date       |
| --------- | ------ | -------- | ---------- |
| 2.2.10    | x1d1s1 | Preview  | 2020/08/23 |
| 2.3.4     | x2d2s2 | Preview  | 2021/03/21 |
matrixb 0.0.2.0
An extensible package to automate and enhance the manipulation of tabular/matrix data without giving up performance.

[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

# matrixb

matrixb is a Python library to provide a single interface to handle common data input, cleaning, and analysis features for data science datasets. The name MatrixB arise from a play on several interpretations - *Matrix, Beta* (Experimental tools to use with matrices) and *Matrix, Version B* (Enhancements on 2-D matrix processing).

In general, you might consider matrixb as occupying a middlespace between the speed and efficiency of using native 2-D array matrices in Python and sophisticated statistical datastructures such as dataframes in Pandas and R. It provides a singular interface to load in csv, xls, xlsx, and ods files, automatically cleans common mistakes (accidentally adding a space to the end of a text string, or changing the capitalization structure of column names between two different data files) and allows tremendous flexibility in programmer-assisted cleaning and analysis, in part by leveraging the tools in the *[pydatacleaner](https://libraries.io/pypi/pydatacleaner)* package. If you need more functionality than matrixb, you likely should be using Pandas. There isn't a lot of overhead in matrixb (at least that can't be eliminated with a switch passed into the constructor), and so if it is too heavy for you, you probably need to custom write your own processing.

## Distribution
* [GitLab Project](https://gitlab.com/krcrouse/matrixb)
* [PyPI Distribution Page](https://pypi.org/project/matrixb)
* [Read the Docs Full API Documentation](https://matrixb.readthedocs.io)


## Project Status

Currently, matrixb is functional but shallowly vetted condition and should be considered **alpha** software. Some features that were implemented in the past may have been broken with more recent refactoring, and test coverage is still limited. Your mileage may vary.

Code comments of *NOTE* and *TODO* indicate known shortcomings that may be useful to you. The interface will likely change in future versions.

If you wish to rely on features of this package, I am likely more than willing to accommodate and to incorporate sensible design improvements or, in some cases, changes.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install matrixb.

```bash
pip install matrixb
```

## Usage

Many examples of usage are available in the main test files included in the t/ subdirectory.

```python
import matrixb

**EXAMPLES coming soon**
```

## Contributing
Contributions are collaboration is welcome. For major changes, please contact me in advance to discuss.

Please make sure to update tests for any contribution, as appropriate.

## Author

[Kevin Crouse](mailto:krcrouse@gmail.com). Copyright, 2019.

## License
[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
napalm-control 0.0.6
Nonlinear Algebraic Approximation in Control systems
Requires Python: >=3.6

# Nonlinear Algebraic Approximation of Control Systems

A Python implementation of an algorithm for construction homogeneous 
approximations of nonlinear control systems. For description of the algoritm refer to ...

## Installation

You can install the package using pip

```
pip install napalm-control
```

## How to use

The main part of the package is implemented in a single class called ControlSystem. This class describes a control system and its methods implement the algorithm of approximation of given system.

```python
from napalm_control.approximation_tools import ControlSystem
```

Given a system ![equation](https://latex.codecogs.com/gif.latex?%5Cdot%7Bx%7D%3Da%28t%2Cx%29%20&plus;%20b%28t%2Cx%29u)
you can initialize it the following way

```python
system = ControlSystem(a, b)
```

where _a_ and _b_ are corresponding vectors.

__Note__: the vectors __must__ be composed out of sympy symbols or numbers.
For example, consider a system:


![equation](https://latex.codecogs.com/gif.latex?%5Cleft%5C%7B%20%5Cbegin%7Baligned%7D%20%5Cdot%20x_1%20%26%3D%20-u%20%5C%5C%20%5Cdot%20x_2%20%26%3D%20-%5Cfrac12x_1%5E2-4tx_1-3t%5E2x_1%20%5C%5C%20%5Cdot%20x_3%20%26%3D%20-x_1%5E2-2tx_1-3t%5E2x_1%20%5Cend%7Baligned%7D%20%5Cright.)

Then the implementation using the package would be as follows:
```python
import sympy as sym
from napalm_control.approximation_tools import ControlSystem

x1, t = sym.symbols('x_1 t')
a = sym.Matrix([0, -sym.Rational(1, 2)*x1**2 - 4*t*x1 - 3*t**2*x1, -x1**2 - 2*t*x1 - 3*t**2*x1])
b = sym.Matrix([-1, 0, 0])
system = ControlSystem(a, b)
```