semvec/pypi-packages huggingface dataset:
fileboxes 0.1.4
Simplifies the creation of custom formats.
Requires Python: >=3.10

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  <img width="100" src="https://github.com/user-attachments/assets/08d8ef52-9c58-41a3-b9b8-ef53be0ee1b7" alt="ExpiraBot Logo" align="center">
</div>
<h1 align="center" style="margin-top: 20px;"> Fileboxes </h1>

# Overview
Have you ever wondered how is the internal structure of files like `.docx`, `.pptx` or `.xlsx`?
It is actually just a ZIP with a bunch of `.xml` files inside it, following the Office Open XML file formats.

I like the idea, but I do not like XML.

This project is a way to write your custom file formats with zips and using a pythonic api.
skellyforge 2024.12.1009
Basic template of a python repository
Requires Python: <3.13,>=3.9
Keywords: basic, template, python, repository

# postprocessing_gui

# INSTALLING the GUI
 1. Create a 3.9 or 3.10 conda environment environment 
   -have tested this successfully on 3.9.16 (latest 3.9 version) and 3.10.11 (latest 3.10 version)
 2. Navigate to this github repo and use the command `pip install -e.` to install the dependencies from the pyproject.toml

# STARTING the GUI:
 1. Open up `postprocess_GUI.py`
 2. Scroll down to the `if __name__ == '__main__'` section at the bottom
 3. Change the `path_to_data_folder` variable to the path to your recording
   -NOTE: The GUI is set up to take file paths and file names corresponding to the 
          FreeMoCap 1.0 release. If you need to change these file paths, you can do so
          from the `FileManager` class at the top of `postprocess_GUI.py`
 4. After changing the path, run the `postprocess_GUI.py` script, and the GUI will pop up

# OPERATING the GUI 
 - When the GUI pops up you'll see the main menu, from which you can alter and apply
   various postprocessing parameters (currently mostly for interpolation/filtering)
 - Press the 'Process Data and View Results' button to run the postprocessing on the skeleton,
   and the postprocessed skeleton should appear in the 'post-processed data' skeleton viewer
 - You can move between the Filtering and Interpolation tabs at the top to more closely look
   at how the different processing options affect your data 
 - When finished, press the 'Save Out Data' button on the main menu to save the post_processed data
   and a .toml file of your processing parameters into the 'output_data' folder
 - Default processed data file name is 'mediapipe_processed_xyz.npy' and the parameter summary name
   is 'postprocessing_settings.toml'
langgraph-dynamodb-saver 0.2.1
DynamoDB checkpoint saver implementation for LangGraph
Requires Python: >=3.9

# LangGraph DynamoDB Saver

A DynamoDB-based checkpoint saver implementation for LangGraph applications.

## Installation

bash
pip install langgraph-dynamodb-saver


## Prerequisites

- AWS credentials configured (either through environment variables, AWS CLI, or IAM roles)
- Appropriate permissions to create and access DynamoDB tables

## Usage

python
from langgraph_dynamodb_saver import DynamoDBSaver

# Create a new saver instance with a table name
saver = DynamoDBSaver(table_name="my-checkpoints")

# Using context manager
with DynamoDBSaver.from_conn_info(table_name="my-checkpoints") as saver:
    # Use the saver in your LangGraph application
    pass


## Configuration

The DynamoDB saver automatically creates a table if it doesn't exist with the following structure:

- Partition Key (PK): String
- Sort Key (SK): String
- On-demand billing mode
- Default throughput limits:
  - Max Read Request Units: 100
  - Max Write Request Units: 100

## Environment Variables

Ensure your AWS credentials are properly configured using one of these methods:

bash
# Option 1: Environment variables
export AWS_ACCESS_KEY_ID="your_access_key"
export AWS_SECRET_ACCESS_KEY="your_secret_key"
export AWS_REGION="your_region"

## Error Handling

The saver will:
- Automatically create the DynamoDB table if it doesn't exist
- Handle connection and operation retries
- Raise appropriate exceptions for permission issues or AWS service problems

## Limitations

- DynamoDB item size limit of 400KB applies to individual checkpoints
- Queries are eventually consistent by default
- Table names must be unique within an AWS region