semvec/pypi-packages huggingface dataset:
PandaPrimes 0.0.6
A Python extension module for finding primes using C

# PandaPrimes

PandaPrimes is a CPython extension under active development, leveraging the powerful [primesieve](https://github.com/kimwalisch/primesieve) library to significantly enhance prime number generation performance.

## Usage

### Iterating Over Primes
Iterating through primes is a common practice, providing a memory-efficient way to work with prime numbers. PandaPrimes introduces two main functionalities for iterating through primes.

#### `primes_range`

The `primes_range` function enables seamless iteration through prime numbers within a specified range.

```python
from PandaPrimes import primes_range

primes_count = 0

# Example 1: Iterate through primes less than or equal to one million
for prime in primes_range(10**6):
    primes_count += 1
```

```python
primes_count = 0

# Example 2: Iterate through primes in the range between one million and five million
for prime in primes_range(10**6, 5*10**6):
    primes_count += 1
```

### Prime Generation

#### `generate_primes`

The `generate_primes` function creates a NumPy array containing prime numbers within a specified range.

```python
from PandaPrimes import generate_primes

# Example: Generate an array of primes from 2 to 1e10
primes_array = generate_primes(10**10)
```

#### `generate_n_primes`

The `generate_n_primes` function generates a NumPy array of the first `n` prime numbers.

```python
from PandaPrimes import generate_n_primes

# Example: Generate an array containing the first million prime numbers
primes_array = generate_n_primes(10**6)
```

## Installation

As of now, PandaPrimes is still under development.

- for now you can try it by installing primesieve library on you machine first. [install primesieve](https://github.com/kimwalisch/primesieve#installation)

- after that you can simply install PandaPrimes using pip.
```bash
pip install PandaPrimes
```

## Contributing

We welcome contributions from the community! Feel free to contribute by opening issues, submitting pull requests, or providing feedback.

Please note that the README usage section is a work in progress, and further details will be added as development progresses.
compress-comics 1.0.0
Compress images in cbz/cbr files with jpegxl, fast.
Requires Python: >=3.11

## compress\_comics

Find all the cbz/cbr files in the current directory and subdirectories and compress all the jpg/png/gif images inside with jpeg xl.  
Output files preserve the folder structure.  
Repacks cbr into cbz.  

By default, compresses with:
```
-d / --distance 0 (lossless)
-j / --lossless_jpeg 1
```

Compresses as many images in parallel as there are threads.  
Because of that, it may run out of memory on bigger resolutions.  
Adjust with:  
```
-t / --threads
```

Basic usage:  
`compress_comics -O output_directory`  

To check all program options:  
`compress_comics -h`

Needs `cjxl` installed and in PATH.
scistringparser 0.1.7
A python module that converts strings in the metric scientific notation to numerical data types.
Requires Python: >=3.6

# PyScientificStringParser
A python module that converts strings in the metric scientific notation to numerical data types.

This package is available at [PyPI](https://pypi.org/project/scistringparser/).

It is a very simple module that contains one function, made for a specific application, but i think that it can be useful for other people since i couldn't find anywhere a similar package.

## Usage
You can import the module by calling the function `parse_str`.
The input is a string that contains the number in the metric scientific notation, like `1u` -> _1e-6_.

Example:

`parse_str('1.2k')`

Outuput: `1.2e3`

It is compatible with all the metric system prefixes.

## Installation
You can install this package by calling `pip install scistringparser`.
younotyou 0.1.1
Filter a list of strings and/or paths based on include and exclude patterns.
Requires Python: >=3.10
Keywords: filter,filtering,fnmatch,match,path,patternmatching,string

# younotyou

Filter a list of strings and/or paths based on include and exclude patterns.

## Installation

Install with:

<pre>
pip install younotyou
</pre>

Convenient one stop shop to include and exclude strings using glob style pattern matching.<br>


## Usage

Patterns can be literals or glob style wildcard strings.<br>
Exclusion patterns override include patterns,
i.e. if an item matches an include pattern but also matches an exclude pattern, it will be excluded.

<pre>
>>> from younotyou import younotyou
>>> strings = ["thispattern", "aPaTtErN", "mypatterns"]
>>> younotyou(strings, ["*pattern"])
['thispattern']
>>> younotyou(strings, ["*pattern*"])
['thispattern', 'mypatterns']
>>> younotyou(strings, ["*pattern*"], case_sensitive=False)
['thispattern', 'aPaTtErN', 'mypatterns']
>>> younotyou(strings, ["*pattern*"], ["my*", "*is*"], case_sensitive=False)
['aPaTtErN']
>>> younotyou(strings, exclude_patterns=["*PaT*"])
['thispattern', 'mypatterns']
>>> younotyou(strings, exclude_patterns=["*PaT*"], case_sensitive=False)
[]
>>> younotyou(strings, include_patterns=["*PaT*"], exclude_patterns=["*PaT*"], case_sensitive=False)
[]
</pre>
protonne 1.0.0
Python bindings for proton vpn's cli.
Requires Python: >=3.10
Keywords: autorotate,proton,protonvpn,rotate,vpn

# protonne

Python bindings for proton vpn's linux cli.

## Installation

Install with:

<pre>
pip install protonne
</pre>

### **NOTE**: This package requires that you have a Proton VPN account and that you've installed and set up the [Proton VPN Linux CLI](https://protonvpn.com/support/linux-vpn-tool/).

## Usage

<pre>
from protonne import Proton
proton = Proton()
proton.connect_fastest()
proton.enable_permanent_killswitch()

# If you want to execute the commands "silently", you can set 'capture_output' to True in the class constructor or after creation through the 'capture_output' property
proton.capture_output = True
proton.capture_output = False
# Almost every function returns an 'Output' object that contains 3 fields: 'return_code', 'stdout', and 'stderr'.
# When 'capture_output' is True, 'stdout' and 'stderr' can be accessed through the 'Output' object, otherwise they are empty strings.
# The 'capturing_output()' context manager can also be used.
with proton.capturing_output():
    output = proton.connect_random()
    print(output.stdout)

# Once you're connected, info about the connection is available through the 'connection' property.
# Accessing this property invokes the cli's 'status' command and parses the output into a 'Connection' object.
# For performance, it's best to store this property in a local variable for repeated access until you need an updated 'Connection' object.
ip_history = []
connection = proton.connection
ip_history.append((connection.IP, connection.server.name))
proton.connect_random()
connection = proton.connection
ip_history.append((connection.IP, connection.server.name))
proton.connect(server=ip_history[0][1])

# Full 'Connection' annotation:
connection.IP: str
connection.killswitch.active: bool
connection.killswitch.on: bool
connection.killswitch.permanent: bool
connection.raw: str # The raw output string of the 'status' cli command
connection.server.name: str
connection.server.country: str
connection.server.protocol: str
connection.server.load: str
connection.server.plan: str
connection.server.features: str | None
connection.time: str
</pre>
ai-stream-interact 0.0.9
An model agnostic extensible package that allows for AI & LLM interactions on a video stream
Keywords: python,ai,llm,artificial intelligence,large language models,nlp,natural language processing,video,video stream

# AI Stream Interact🧠🎞️ - LLM interaction capabilities on live USB camera video stream.
This package can easily be extended to accommodate different LLMs, but for this first version interactions were implemented only for [Google's Gemini Pro & Vision Pro Models](https://ai.google.dev/tutorials)

**Note: This is a basic Alpha version that's been written & tested in Ubuntu Linux only so it may have unexpected behavior with other operating systems.**

<br>
<br>

## Installation:
- `pip install ai-stream-interact`

Note that pip install might take a while as it will also install [coqui-ai](https://github.com/coqui-ai/TTS) for Text to Speech. Although TTS is partially implemented it is not turned on by default due to some glitchy behavior. (This will be fixed in future releases.)

## Example Usage:

1. You need a Gemini API key. (if you don't already have one you can get one [here](https://ai.google.dev/tutorials/setup)).
2. Have a USB camera connected.
3. run `aisi --llm gemini` to enter the AI Stream Interact🧠🎞️ main menu. _(note that you can always go back to the main menu from the video stream by press "**m**" while having the video stream focused.)_
4. Enter the API key or press enter if you've added it to .env.
5. You will be asked to enter your camera index. Currently there is no straight forward way to identify the exact index for your camera's name due to how open-cv enumerates such indicies so you'll have to just try a few times till you get the right one if you have multiple camers connected. If you have one camera connected you can try passing "**-1**" as in most cases it'll just pick that one.
   
Now you're in!. You have access to 3 types of interactions as of today.

### Detect Default:
This fires up a window with your camera stream and whenever you press "**d**" will identify the object the camera is looking at. (Make sure to press "**d**" with the camera window focused and not your terminal).
![](https://github.com/The0mar/ai_stream_interact/blob/main/gifs/detect.gif)


### Detect with Custom Prompt:
Use this to write up a custom prompt before showing the model an object for custom interactions beyond just identifying objects.
![](https://github.com/The0mar/ai_stream_interact/blob/main/gifs/detect_custom.gif)

### Interactions:
This just allows for back & forth chat with the model.

## Troubleshooting:

### Errors:

- `google.api_core.exceptions.FailedPrecondition: 400 User location is not supported for the API use.`: **This is specific to Gemini as they currently do not provide general availability to all regions, so you need to make sure your region is supported [here](https://ai.google.dev/available_regions#available_regions)**
tmd-editor 0.0.10
A Node Editor Library using PyQt5 Specialized in TMD
Keywords: python,node,tmd_nodeeditor,editor,edges,sockets

tmd_nodeeditor
==============

A Node Editor Library using PyQt5 Specialized in TMD
-----------------------------------------------------

A package that allows building simple nodes, sockets, and edges.

Installation
------------

::

    pip install tmd_nodeeditor

Usage
-----

[Include any usage instructions or examples here.]