semvec/pypi-packages huggingface dataset:
simple-gpu-queue 0.1.1
Simple GPU Queue: For running lots of smaller experiments on your handful of GPUs, designed for JAX

# Simple GPU Queue
> Simple GPU Queue: For running lots of smaller experiments on your handful of GPUs
> 

Functional, minimal.

## Quickstart

```
pip install simple_gpu_queue
simpleq_start 4 --memfrac-per-proc=0.45 # Start 2 processes per gpu, each taking 0.45 the total amount of GPU RAM available
```

Example python launch script

```python
from simple_gpu_queue.simple_gpu_queue import GPUQueueClient
queue = GPUQueueClient(git_commit_id="most_recent")

# Send commands as a list of (command, stdout_file) tuples. Stdoutfile can be "" for no saving of stdout logging.
commands = [
    ("python -c 'import time; import jax.numpy as jnp; a=jnp.ones(5); time.sleep(1); print(\"I SLEPT HAPPY 1\")'", "testlogs/v1.txt"),
    ("python -c 'import time; import jax.numpy as jnp; a=jnp.ones(5); time.sleep(2); print(\"I SLEPT HAPPY 2\")'", ""),
    ("python -c 'import time; import jax.numpy as jnp; a=jnp.ones(5); time.sleep(3); print(\"I SLEPT HAPPY 3\")'", "testlogs/v3.txt"),
]

if queue.git_repo.is_dirty():
    user_input = input("Repo has uncommitted changes: continue? [Y/n] ").strip().lower()
    if user_input == 'n':
        raise ValueError("Aborting due to uncommitted changes in the repository.") 

queue.send_command_list(commands)
```


## For Development
```
conda env create -f environment.yml
conda activate simple-gpu-queue
pip install -r requirements.txt
# pip install -r requirements-dev.txt
```

Check the server is running, navigate to `http://localhost:5034/docs`, test the routes

## Upload to pypi (reference)
```
rm -rf dist/
python setup.py sdist bdist_wheel
twine upload dist/*
```
twoblock 0.0.1
A Scikit-Learn Compatible Library for Simultaneous Two-Block Sufficient Dimension Reduction Methods

# twoblock
Two-block simultaneous dimension reduction 

A scikitlearn compatible implementation of simultaneous two-block dimension reduction as proposed in [1]. 

References
----------
[1] Cook, R. Dennis, Liliana Forzani, and Lan Liu.
    "Partial least squares for simultaneous reduction of response and predictor
    vectors in regression." Journal of Multivariate Analysis 196 (2023): 105163.
APIUnifier 0.1.0
Python package for integrating with various APIs.

# IntegrationAPI

IntegrationAPI is a Python package that simplifies the integration of multiple APIs, including social media, payment gateways, and geolocation services. With this package, you can seamlessly connect to various APIs and streamline your application's functionality.

## Features

- **Social Media Integration:** Easily connect to popular social media platforms like Twitter

- **Payment Handling:** Simplify online transactions with support for payment gateways like PayPal.

- **Geolocation Services:** Access geolocation data and integrate maps using the power of Google Maps.

- **User-Friendly:** Provides a straightforward and consistent interface for working with multiple APIs.

## Installation

To install the IntegrationAPI package, use `pip`:

```bash
pip install integrationapi
```

## Usage
Here's how you can use the IntegrationAPI package in your Python project:
```bash
from integrationapi.social_media import TwitterAPI
```

## Replace with your Twitter API credentials

api_key = "your_api_key"
api_secret = "your_api_secret"
access_token = "your_access_token"
access_token_secret = "your_access_token_secret"

## Create an instance of the TwitterAPI class
twitter_client = TwitterAPI(api_key, api_secret, access_token, access_token_secret)

## Use the class to fetch user tweets
username = "some_twitter_user"
tweets = twitter_client.get_user_tweets(username)

for tweet in tweets:
    print(tweet)

# Limitations 

In the initial release, version 1.0, we have successfully integrated essential APIs, namely Twitter, PayPal, and Google Maps. This strategic selection of APIs empowers our application with social media engagement, secure payment processing, and geolocation services. These integrations enable us to provide a comprehensive user experience by incorporating functionalities from these prominent service providers. However, it is crucial to acknowledge that, in this version, our system is designed with a specific constraint in mind, limiting our API portfolio. Future releases are planned to expand the scope and capabilities by incorporating additional APIs to diversify the range of features and services we can offer to our users. This iterative approach aligns with our commitment to delivering a robust and versatile software solution by harnessing the power of various APIs as we continue to evolve and meet the evolving demands of our user base.

## License
This package is open-source and is available under the Apache License Version 2.0.
sensitive-data-validator 0.2.3
A package to validate sensitive data in various file formats.
Requires Python: >=3.6

# Sensitive Data Validator

A package to validate sensitive data in various file formats.

## Installation

You can install the package using pip:

```bash
pip install sensitive_data_validator


```

Example code:

```bash

from sensitive_data_validator import SensitiveAPI

# Exemplo de uso com personalização de campos
api = SensitiveAPI(fields_to_check=['BRAZIL_PERSONAL_ID', 'EMAIL'])
result = api.file_check('example.json', filetype='json')
print(result)

# Exemplo de uso sem personalização de campos (verificando todos os campos)
api = SensitiveAPI()
result = api.file_check('example.json', filetype='json')
print(result)
minidag 0.1.1
Small decorator based DAG to orchestrate jobs
Requires Python: >=3.8

# minidag

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/minidag)

Bare minimum DAG implementation for in-process sorting of jobs with
dependency injection. Runs jobs in topological order.

Install:
`pip install minidag`

Usage:
```python
from minidag import MiniDAG

dag = MiniDAG()

@dag.job()
def job1():
    return 1

@dag.job()
def job2(job1):
    return job1 + 1

@dag.job()
def job3(job1, job2):
    return job1 + job2

@dag.job()
def job4(some_external_value, job3)
    return some_external_value + job3

dag.run(some_external_value=10)
# > {'job1': 1, 'job2': 2, 'job3': 3, 'job4': 13, 'some_external_value': 10}
```
API-Integration 0.1.0
Python package for integrating with various APIs.

# IntegrationAPI

IntegrationAPI is a Python package that simplifies the integration of multiple APIs, including social media, payment gateways, and geolocation services. With this package, you can seamlessly connect to various APIs and streamline your application's functionality.

## Features

- **Social Media Integration:** Easily connect to popular social media platforms like Twitter

- **Payment Handling:** Simplify online transactions with support for payment gateways like PayPal.

- **Geolocation Services:** Access geolocation data and integrate maps using the power of Google Maps.

- **User-Friendly:** Provides a straightforward and consistent interface for working with multiple APIs.

## Installation

To install the IntegrationAPI package, use `pip`:

```bash
pip install integrationapi
```

## Usage
Here's how you can use the IntegrationAPI package in your Python project:
```bash
from integrationapi.social_media import TwitterAPI
```

## Replace with your Twitter API credentials

api_key = "your_api_key"
api_secret = "your_api_secret"
access_token = "your_access_token"
access_token_secret = "your_access_token_secret"

## Create an instance of the TwitterAPI class
twitter_client = TwitterAPI(api_key, api_secret, access_token, access_token_secret)

## Use the class to fetch user tweets
username = "some_twitter_user"
tweets = twitter_client.get_user_tweets(username)

for tweet in tweets:
    print(tweet)

# Limitations 

In the initial release, version 1.0, we have successfully integrated essential APIs, namely Twitter, PayPal, and Google Maps. This strategic selection of APIs empowers our application with social media engagement, secure payment processing, and geolocation services. These integrations enable us to provide a comprehensive user experience by incorporating functionalities from these prominent service providers. However, it is crucial to acknowledge that, in this version, our system is designed with a specific constraint in mind, limiting our API portfolio. Future releases are planned to expand the scope and capabilities by incorporating additional APIs to diversify the range of features and services we can offer to our users. This iterative approach aligns with our commitment to delivering a robust and versatile software solution by harnessing the power of various APIs as we continue to evolve and meet the evolving demands of our user base.

## License
This package is open-source and is available under the Apache License Version 2.0.