semvec/pypi-packages huggingface dataset:
batch-please 0.3.1
A package for batch processing with sync and async capabilities
Requires Python: >=3.8

# batch_please

A flexible and efficient Python library for processing large datasets in batches, with support for both synchronous and asynchronous operations.

## Features

- Process large datasets in customizable batch sizes
- Support for both synchronous and asynchronous processing
- Flexible input handling - accepts iterables or dictionaries of keyword arguments
- Checkpoint functionality to resume processing from where it left off
- Optional progress bar using tqdm
- Configurable concurrency limit for asynchronous processing
- Logging support

## Installation

```bash
pip install batch_please  
```

## Quick Start

### Synchronous Processing

```python
from batch_please import BatchProcessor

# Simple iterable input
def process_func(item):
    return f"Processed: {item}"

processor = BatchProcessor(
    process_func=process_func,
    batch_size=100,
    use_tqdm=True
)

input_data = range(1000)
processed_items = processor.process_items_in_batches(input_data)

# Dictionary input with keyword arguments
def process_with_params(name, value):
    return f"{name}: {value}"

processor = BatchProcessor(
    process_func=process_with_params,
    batch_size=100,
    use_tqdm=True
)

input_data_dict = {
    f"item_{i}": {"name": f"Item {i}", "value": i * 10} 
    for i in range(100)
}
processed_items = processor.process_items_in_batches(input_data_dict)
```

### Asynchronous Processing

```python
import asyncio
from batch_please import AsyncBatchProcessor

# Simple iterable input
async def async_process_func(item):
    await asyncio.sleep(0.1)
    return f"Processed: {item}"

async def main():
    processor = AsyncBatchProcessor(
        process_func=async_process_func,
        batch_size=100,
        max_concurrent=10,
        use_tqdm=True
    )

    input_data = range(1000)
    processed_items = await processor.process_items_in_batches(input_data)
    
    # Dictionary input with keyword arguments
    async def process_with_params(name, value):
        await asyncio.sleep(0.1)
        return f"{name}: {value}"
    
    processor = AsyncBatchProcessor(
        process_func=process_with_params,
        batch_size=100,
        max_concurrent=10,
        use_tqdm=True
    )
    
    input_data_dict = {
        f"item_{i}": {"name": f"Item {i}", "value": i * 10} 
        for i in range(100)
    }
    processed_items = await processor.process_items_in_batches(input_data_dict)

asyncio.run(main())
```

## Advanced Usage

### Checkpoint Recovery

```python
processor = BatchProcessor(
    process_func=process_func,
    batch_size=100,
    pickle_file="checkpoint.pkl",
    recover_from_checkpoint=True
)
```

### Logging

```python
processor = BatchProcessor(
    process_func=process_func,
    batch_size=100,
    logfile="processing.log"
)
```

Further [Documentation](https://gillespied.github.io/batch_please/)
bitbox02 7.0.0
Python library for bitbox02 communication
Requires Python: >=3.6
Keywords: digitalbitbox BitBoxSwiss bitbox bitbox02 bitcoin litecoin ethereum erc20 u2f

# BitBox02 python API

This repository contains two packages

* u2fhid
* bitbox02

## u2fhid

This is a small package that contains read/write primitives for u2fhid devices such as the
bitbox02.

## bitbox02

In this folder is the Python API for communicating with the BitBox02 device.

The folder `generated` contains files generated by `python-protobuf`. Regenerate with `make`.


### Development environment

It is highly recommended that you use the dockerized setup while developing, guide for setting it up
can be found in [BUILD.md](../../BUILD.md).

If you intended to develop instead on your local environment be vary that some development procedures
such as regenerating files have their libraries NOT in requirements.txt as they are not necessary for the bitbox02 
Python package.

It is highly advisable to use same version that is used in the [Dockerfile](../../Dockerfile) that is used in dockerized
setup.
aws-ec2-pricing-tool 0.1.6
CLI tool to compare AWS EC2 on-demand pricing and AMIs across regions
Requires Python: >=3.7

# AWS EC2 Instance Pricing Tool

A Python CLI tool to fetch and compare **AWS EC2 hourly on-demand pricing** and the latest **AMI IDs** across all available AWS regions.  
Supports Linux distributions (Ubuntu, Amazon Linux, RHEL, SUSE) and Windows instances.

[![PyPI version](https://img.shields.io/pypi/v/aws-ec2-pricing-tool)](https://pypi.org/project/aws-ec2-pricing-tool/)
[![Python version](https://img.shields.io/pypi/pyversions/aws-ec2-pricing-tool)](https://pypi.org/project/aws-ec2-pricing-tool/)
[![License](https://img.shields.io/pypi/l/aws-ec2-pricing-tool)](https://github.com/spithash/AWS-EC2-Instance-Pricing-Tool/blob/main/LICENSE)
[![GitHub stars](https://img.shields.io/github/stars/spithash/AWS-EC2-Instance-Pricing-Tool?style=social)](https://github.com/spithash/AWS-EC2-Instance-Pricing-Tool/stargazers)

💡 Ideal for DevOps engineers, cloud architects, and infrastructure teams looking to optimize EC2 costs or automate cloud image selection.

> 🔖 This tool focuses on **on-demand EC2 pricing**, making it perfect for dynamic or short-term workloads where flexibility matters.

![AWS-EC2 Instance Pricing Tool](https://raw.githubusercontent.com/spithash/trunk/refs/heads/master/ec2pricing/AWS-EC2-Instance-Pricing-Tool.png)

## Requirements

- **Python 3.7+**  
  The package is compatible with Python 3.7 and above.

- **AWS Credentials Configured**  
  It uses `boto3` to interact with AWS APIs. Make sure your AWS CLI or environment variables are configured with appropriate credentials and permissions to access EC2 and Pricing APIs.  
  _Note: You don't need to set a default region in your environment._

## Installation

Install from PyPI:

```bash
pip install aws-ec2-pricing-tool
```

Or clone from GitHub and install manually:

```bash
git clone https://github.com/spithash/AWS-EC2-Instance-Pricing-Tool.git
cd AWS-EC2-Instance-Pricing-Tool
pip install .
```

## Usage

Run the tool from the command line by specifying the EC2 instance type, operating system, and optionally the distro:

```bash
ec2pricing <instance_type> --os <linux|windows> [--distro <distro_name>]
```

### Examples

Fetch pricing and AMI info for a Linux Ubuntu t2.micro instance:

```bash
ec2pricing t2.micro --os linux --distro ubuntu
```

Fetch pricing and AMI info for a Windows t3.medium instance (Microsoft publisher):

```bash
ec2pricing t3.medium --os windows --distro microsoft
```

Fetch pricing and AMI info for a Linux instance across all distros (no distro specified):

```bash
ec2pricing t2.micro --os linux
```

## Linux Instances Demo

![EC2 Pricing Linux](https://raw.githubusercontent.com/spithash/trunk/refs/heads/master/ec2pricing/ec2pricing-linux.gif)

## Windows Instances Demo

![EC2 Pricing Windows](https://raw.githubusercontent.com/spithash/trunk/refs/heads/master/ec2pricing/ec2pricing-windows.gif)