semvec/pypi-packages huggingface dataset:
stratpy 0.0.4
Rust based Game Theory package
Requires Python: >=3.7

<p align="center">
    <picture>
    <source media="(prefers-color-scheme: dark)" srcset="https://github.com/fredrikofstad/stratpy/blob/main/res/stratpy-dark.png?raw=true">
    <source media="(prefers-color-scheme: light)" srcset="https://github.com/fredrikofstad/stratpy/blob/main/res/stratpy-light.png?raw=true">
    <img alt="stratpy logo" src="https://github.com/fredrikofstad/stratpy/blob/main/res/stratpy-light.png?raw=true">
    </picture>
</p>

## Stratpy - A python library for Game Theory written in rust

Read the documentation [here!](https://stratpy-docs.readthedocs.io/en/latest/)

 <!-- start info -->
### Motivation:
- Create an easy to use python package for game theory catering to alternate disciplines like polisci.
- Backend created in rust offering a modern fast and memory-safe language, while python allows for an easy api for 
the scientific community.

### Features:

- Normal form and Extensive form games (including incomplete information)
- Solve games using user-ordered preferences (unknown but orderable variables)
- Easily export games to latex and other formats
 <!-- end info -->

 <!-- start quickstart -->
### Installation

```bash
$ pip install stratpy
```

### Usage

```python
>>> from stratpy import *
>>> 
>>> game1 = Game("Title")

```
 <!-- end quickstart -->
Read more about how to use the library [here!](https://stratpy-docs.readthedocs.io/en/latest/)
roborecipe 0.1.3
generate robot build instruction from scripts
Requires Python: >=3.7

# Roborecipe

## Abstruct
Roborecipe generate robot build instructions automatically.  
See [Generated html file](https://eriac.github.io/roborecipe/docs/sample_out).

## framework
roborecipe is based on Ubuntu20.4 and Python3

# source file reference
see [xml document](https://github.com/eriac/roborecipe/blob/master/docs/xml_reference.md)

# usage

## how to install

### from PyPl (pip)
```code
pip install roborecipe

```

### from source
```code
$ git clone https://github.com/eriac/roborecipe.git  
$ cd roborecipe
$ pip install ./ (add -e for develope mode)
```

## how to use
```code
$ roborecipe # dispaly help
```

## get list of component with sample 
```code
$ roborecipe list -d ~/roborecipe/sample/ 
### package ###
...
### component ###
...
```

## generate instruction with sample
```code
$ roborecipe generate sample_project main_asm -d roborecipe/sample/ -o out
```

## how to uninstall
```code
pip uninstall roborecipe
```
audio-normalizer 1.3.1
Audio Normalizer for MP3 and WAV files
Requires Python: >=3.7

# ![plot](https://raw.githubusercontent.com/MatthiasSchmid93/AudioNormalizer/main/audio_normalizer/assets/nor.png) AudioNormalizer
<p align="center">
 <img src="https://raw.githubusercontent.com/MatthiasSchmid93/AudioNormalizer/main/audio_normalizer/assets/UI.png">
</p>
<br/>
<p align="center">
This is a normalizer for mp3 and wav files. Its a final project for Havard CS50P.

The approach in this program to normalize audio differs in comparison to most other programs that implement this task. Most normalizers amplify an audio signal  until the highest transient reaches 0 dB. The downside of this approach is that the audio signal can only be amplified based on a single maximum transient.     In other words, the whole normalizing process depends on one transient, which is inefficient.

This program, however, doesn't depend on a single transient. It rather splits the original signal into four separate signals (left positive, left negative,     right positive, and right negative). Then it uses an algorithm that finds several transients that exceed a calculated value based on the audio file's           duration and actual volume. For each split signal, a copy is being created, a dummy signal. In the dummy signals, the found transients are turned into the       value of zero. The next task is to find the new maximum transient in each modified dummy signal like any other simple normalizer. The new maximum value is       then saved for the final amplification.

At this stage, the program finds all amplitudes in the original split signals where the previously found transients are sitting. The split audio signals are     then amplified based on the new maximum transient. All amplitudes that exceed (clip) above 0 dB are lowered to 0 dB without manipulating the original signal     except for the volume.

Finally, all the amplified split signals are merged together and are saved as the original file name and type. All the ID3 tags, including the album cover,     are also maintained in the new normalized file.

As a result, the user gets an audiofile normalized to 0 dB without losing noticeable dynamic range or the overall audio quality.


## Installation

```bash
pip install audio_normalizer
```

## Usage

```python
import audio_normalizer

audio_normalizer.open_window()
```
NSAencrypt 1.0.0
A package for encryption and decryption of images, video, text, and audio

# NSAencrypt

**NSAencrypt** is a Python package that provides functionalities for encryption and decryption of images, video, text, and audio.

## Installation

You can install NSAencrypt using pip:

```bash
pip install NSAencrypt
```

## Usage

Here's an example of how to use different functionalities provided by NSAencrypt:

### Image Encryption and Decryption

```python
from NSAencrypt.image import encrypt_image, decrypt_image

# Encrypt an image
encrypted_image_path = encrypt_image(r'path\to\your\image.png', 'your_key')

# Decrypt the encrypted image
decrypted_image_path = decrypt_image(encrypted_image_path, 'your_key')
```

### Video Encryption and Decryption

```python
from NSAencrypt.video import encrypt_video, decrypt_video

# Encrypt a video
encrypted_video_path = encrypt_video(r'path\to\your\video.mp4', 'your_key')

# Decrypt the encrypted video
decrypted_video_path = decrypt_video(encrypted_video_path, 'your_key')
```

### Text Encryption and Decryption

```python
from NSAencrypt.text import encrypt_text, decrypt_text

# Encrypt text
encrypted_text = encrypt_text("Your secret message")

# Decrypt the encrypted text
decrypted_text = decrypt_text(encrypted_text)
```

### Audio Encryption and Decryption

```python
from NSAencrypt.audio import encrypt_audio, decrypt_audio

# Encrypt an audio file
encrypted_audio_path = encrypt_audio(r'path\to\your\audio.mp3', 'your_key')

# Decrypt the encrypted audio file
decrypted_audio_path = decrypt_audio(encrypted_audio_path, 'your_key')
```
ANSEncrypt 1.0.0
A package for encryption and decryption of images, video, text, and audio

# ANSEncrypt

**ANSEncrypt** is a Python package that provides functionalities for encryption and decryption of images, video, text, and audio.

## Installation

You can install ANSEncrypt using pip:

```bash
pip install ANSEncrypt
```

## Usage

Here's an example of how to use different functionalities provided by ANSEncrypt:

### Image Encryption and Decryption

```python
from ANSEncrypt.image import encrypt_image, decrypt_image

# Encrypt an image
encrypted_image_path = encrypt_image(r'path\to\your\image.png', 'your_key')

# Decrypt the encrypted image
decrypted_image_path = decrypt_image(encrypted_image_path, 'your_key')
```

### Video Encryption and Decryption

```python
from ANSEncrypt.video import encrypt_video, decrypt_video

# Encrypt a video
encrypted_video_path = encrypt_video(r'path\to\your\video.mp4', 'your_key')

# Decrypt the encrypted video
decrypted_video_path = decrypt_video(encrypted_video_path, 'your_key')
```

### Text Encryption and Decryption

```python
from ANSEncrypt.text import encrypt_text, decrypt_text

# Encrypt text
encrypted_text = encrypt_text("Your secret message")

# Decrypt the encrypted text
decrypted_text = decrypt_text(encrypted_text)
```

### Audio Encryption and Decryption

```python
from ANSEncrypt.audio import encrypt_audio, decrypt_audio

# Encrypt an audio file
encrypted_audio_path = encrypt_audio(r'path\to\your\audio.mp3', 'your_key')

# Decrypt the encrypted audio file
decrypted_audio_path = decrypt_audio(encrypted_audio_path, 'your_key')
```
ANSencrypt 1.0.0
A package for encryption and decryption of images, video, text, and audio

# ANSencrypt

**ANSencrypt** is a Python package that provides functionalities for encryption and decryption of images, video, text, and audio.

## Installation

You can install ANSencrypt using pip:

```bash
pip install ANSencrypt
```

## Usage

Here's an example of how to use different functionalities provided by ANSencrypt:

### Image Encryption and Decryption

```python
from ANSencrypt.image import encrypt_image, decrypt_image

# Encrypt an image
encrypted_image_path = encrypt_image(r'path\to\your\image.png', 'your_key')

# Decrypt the encrypted image
decrypted_image_path = decrypt_image(encrypted_image_path, 'your_key')
```

### Video Encryption and Decryption

```python
from ANSencrypt.video import encrypt_video, decrypt_video

# Encrypt a video
encrypted_video_path = encrypt_video(r'path\to\your\video.mp4', 'your_key')

# Decrypt the encrypted video
decrypted_video_path = decrypt_video(encrypted_video_path, 'your_key')
```

### Text Encryption and Decryption

```python
from ANSencrypt.text import text, decrypt_text

# Encrypt text
encrypted_text = text("Your secret message")

# Decrypt the encrypted text
decrypted_text = decrypt_text(encrypted_text)
```

### Audio Encryption and Decryption

```python
from ANSencrypt.audio import encrypt_audio, decrypt_audio

# Encrypt an audio file
encrypted_audio_path = encrypt_audio(r'path\to\your\audio.mp3', 'your_key')

# Decrypt the encrypted audio file
decrypted_audio_path = decrypt_audio(encrypted_audio_path, 'your_key')
```
api-geoguessr 1.0.0
An asynchronous API integrator for Geoguessr
Requires Python: >=3.9

This is a Geoguessr API client written in Python. It allows you to interact with the Geoguessr API, such as getting information about users, challenges, maps, and scores.

To install the package, run the following command:

```
pip install geoguessr-api
```

Once the package is installed, you can create a client object by passing your NCFA cookie to the constructor:

```Python
from geoguessr_async import Geoguessr

client = Geoguessr("your_ncfa_cookie")
```

*To get your NCFA cookie, login to geoguessr, open your dev tools (`Ctrl+Shift+I`), go to Storage/Cookies and copy the value of `_ncfa`.*

You can then use the client object to get information about users, challenges, maps, and scores. For example, to get information about an user with his ID, you can use the following code:

```Python
user = client.get_user_infos(userId)
```

The `Profile` object will contain information such as your username, country, and number of games played.

To get information about a challenge, you can use the following code:

```Python
challenge = client.get_challenge_infos("https://geoguessr.com/challenge/xxxx")
```

The `Challenge` object will contain information such as the challenge name, description, and time limit.

To get information about a map, you can use the following code:

```Python
map = client.get_map_infos("https://geoguessr.com/maps/xxxx")
```

The `Map` object will contain information such as the map name, size, and location.

To get information about a score, you can use the following code:

```Python
score = client.get_challenge_score("https://geoguessr.com/challenge/xxxx")
```

The `Score` object will contain information such as the players' name, score, and time.
*When getting the score of a challenge, it automatically plays it, pinging (0, 0) each round.*

### Example: Get results of a challenge as a list of dictionnaries
```Python
score = client.get_challenge_score("https://geoguessr.com/challenge/xxxx")
scores = []
for s in score:
    d_player = {
        "userId": s.userId,
        "userName":s.playerName,
        "total": s.totalScore,
        "roundPoints": s.gamePlayerGuessesRoundScoreInPoints,
        "roundTimes": s.gamePlayerGuessesTime
    }
    scores.append(d_player)
print(scores)
```

I hope you find this package useful! Please let me know if you have any questions or feedback.