semvec/pypi-packages huggingface dataset:
pytweetql 1.0.0
Easy parsing of Twitter GraphQL API responses
License: MIT
Requires Python: >=3.12,<4.0

# pytweetql
pytweetql is a simple Python package designed for developers who work with the Twitter GraphQL API

Currently it is built to parse tweet, user, and list GET responses from the Twitter GraphQL API. The function to call is based on the GraphQL endpoint. So for the UserTweets endpoint, you would import the ```parsing``` module and use the ```parse_user_tweets()``` function.

## How it Works

```python
from pytweetql import parsing

# Given a response from GraphQL
response = {'data': {.....}}

# To pull data from a tweet response
tweets = parsing.parse_user_tweets(response=response)

# Will return a list of tweet classes, one for each tweet parsed
print(tweets.tweets)


# To pull data from a user response
users = parsing.parse_users_by_screen_name(response=response)

# Will return a list of user classes, one for each user parsed
print(users.users)


# To pull data from a list response
lists = parsing.parse_create_list(response=response)

# Will return a list of list classes, one for each list parsed
print(lists.lists)

```
audio-flamingo 0.0.3
Paper - Pytorch
License: MIT
Requires Python: >=3.6,<4.0
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# AudioFlamingo
Implementation of the model "AudioFlamingo" from the paper: "Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities". [PAPER LINK](https://arxiv.org/pdf/2402.01831.pdf)


## Install
`pip3 install audio-flamingo`

## Usage
```python
import torch
from audio_flamingo.model import AudioFlamingo

# Generate a random input sequence
text = torch.randint(0, 256, (1, 1024))
audio = torch.randn(1, 16000)

# Initialize AudioFlamingo model
model = AudioFlamingo(
    dim=512,
    num_tokens=256,
    max_seq_len=1024,
    heads=8,
    depth=6,
    dim_head=64,
    dropout=0.1,
    context_dim=512,
)

# Pass the input sequence through the model
output = model(text, audio)  # (1, 1024, 256)

# Print the output shape
print(output.shape)
# Path: audio_flamingo/model.py

```

# License
MIT
bulksmsmd 0.1.3
Python wrapper for Unifun BulkSMSAPI (bulksms.md)
License: MIT
Keywords: python api wrapper unifun bulksms bulksmsmd bulksmsapi

<div align="center">

# `bulksmsmd` - Python wrapper for Unifun BulkSMSAPI (bulksms.md)

![Python Versions](https://pypi-camo.freetls.fastly.net/663448f90f103babe3b8b9dc15965ec36915dd58/68747470733a2f2f696d672e736869656c64732e696f2f707970692f707976657273696f6e732f70796261646765732e737667)
![PyPI Version](https://img.shields.io/pypi/v/bulksmsmd.svg)
![License](https://img.shields.io/pypi/l/bulksmsmd.svg)

Condsider the official documentation before using this package or to understand the more advanced options __dlrurl__, __dlrmask__, __charset__ and __coding__.

[2021 Official documentation .DOCX](https://github.com/markmelnic/bulksmsmd/blob/main/res/docs_2021.docx)

[2021 Official documentation .PDF](https://github.com/markmelnic/bulksmsmd/blob/main/res/docs_2021.pdf)

</div>

## Installation

Installation is done using the following command:

    pip install bulksmsmd

## Usage

The `username` and `password` are the credentials for the API. The `sender` is the name of the sender.

    client = SMSClient(
        username = 'username',
        password = 'password',
        sender = 'sender',
        proxy = {
            'http': 'http://PROXY_URL,
            'https': 'https://PROXY_URL',
        }
    )

The `client` object is used to send messages and contains two methods: `send_sms_simple` & `send_sms_nde`.

    client.send_sms_simple(
        msisdn = '69123456',
        body = 'Test message.',
        prefix = '373',
    )

    client.send_sms_nde(
        msisdn = '69123456',
        body = 'Test message.',
        prefix = '373',
        dlr_url = 'https://example.com/dlr',
        dlr_mask = '31',
        charset = 'utf8',
        coding = '2',
    )


# History

## 0.1.0 (2021-10-03)

* First release on Github.

## 0.1.1 (2021-10-03)

* Uploaded wheel.

## 0.1.2 (2022-03-03)

* Multiple changes & documentation improved.

## 0.1.3 (2023-02-07)

* Proxy support added.
ashrio 0.1.0
Frontend web development, in python, for python.
License: MIT
Requires Python: >=3.12,<4.0

# Ashrio
_A frontend web-framework made in python, for python, with python in mind constantly_

Ashrio is the thing I've been looking for but could never find: a frontend-web framework in python that is easy to use ***and even easier to extend****. Right now it is JUST starting out, there are a grand total of 4 components, 5 if you count the grid system. It is simple and probably not useable at the moment, but hopefully it will be. 

## The Idea + How to customize
I wanted something I could EXTEND easily. To extend this, you only really need your class to be a subclass of pydantic BaseModel, to have a filepath parameter, and to define a get_html method and a recommended write_to_file method (which is basically 3 lines of code once youve defined the get_html method haha). 

The get_html method should do the following:
- take the "props" (pydantic items) and integrate them into the styles/content/whatever they do
- output html with styles, js, or whatever you want
  i. the only rule about the html is that it needs a style_extra parameter with a default set to "" that plugs into (usually) the top level div/whatever. This is how the grid system works, so it is a must

there is a write_to_file method defined in utils that handles the complex stuff, so really you just need to get the code from get_html and then use the write_to_file method.

If you have any questions, PLEASE ask.

## Plans/Future
- Move to react (not sure if this is even worth it, might make it harder to use..
- Add more styling options
- add a ton more components
- add an event handling system
- migrate to tailwind
- use Alpine for reactivity and better functionality (WIP)