semvec/pypi-packages huggingface dataset:
golftrainer 1.0.2
Analyze a golf swing looking at critical points.

# Introdction
This package provides a utility for analyzing a golf swing. The input data is represented as a json file
generated by [GolfTracker](https://pypi.org/project/golftracker/). 

The json file structure is represented by a data class "GolfData". A factory method is used to create it from the json filename.

The structure of the *GolfData* class is shown below.

![GolfData](docs/images/golf_data.png)

## Installation
Install the package in your virtual env.

```
pip install golftrainer
```

## Demo
For this purpose we will use **data/demo.json** as an example. This file is same as "00001.json" from the below google drive.

### Setup Jupyter Notebook
To make the notebook run under my virtual env (say 'venv'), follow the following steps.

```

pip install jupyter

```

Or for existing install create a new kernel.

```
ipython kernel install --user --name=venv

```

```
cd notebooks/demo

jupyter notebook demo1.ipynb 
```

Once we have the notebook the following commands we can use the GolfData object to access the parameters.


## Generated Data
Various sample golf swing videos shot down the line on a right handed golf player with the corresponding json file are stored in this [GoogleDrive](https://drive.google.com/drive/folders/1TDUnGjP1wh1gZeN1EZdJOO4AeYuMLnkO?usp=sharing). Each video file (either a mp4 or mov) has 2 output files. The ".pkl" is the pickle database and ".json" is the file that we will use for this package to measure the various metrics associated with the swing.
linkeds 1.0.0
LinkeDS is a versatile Python project with linked data structures — stack, queue, and list — offering adaptability in bounded and dynamic sizes.
Requires Python: >=3.6

# LinkeDS

This project introduces a versatile implementation of linked data structures, encompassing stacks, queues, and linked lists. The structures are designed for 
adaptability, available in both bounded and dynamic size variations. Single and doubly linked nodes facilitate flexible element connections.

Incorporating advanced features, the project includes a Jsonifier class, which acts as an Abstract Base Class (ABC) for JSON serialization and deserialization. 
This comprehensive toolkit empowers developers with efficient and flexible linked data structures, suitable for diverse programming needs.

> [!NOTE]  
> This project has been developed based on Python 3.6 or above.

<br />



## Features

1. **Bounded and Dynamic Sizes**: Choose between bounded and dynamic sizes for each structure, offering flexibility in managing element capacity.
2. **Single and Doubly Linked Nodes**: Utilize both single and doubly linked nodes to facilitate versatile connections between elements.
3. **Efficient Stack Operations**: Execute all standard operations for each data structure, including bounded and dynamic sizes.
4. **Serialization of List**: Serialize the entire list effortlessly to JSON format, enabling easy persistence and interchangeability.

<br />



## License

This project adopts the **MIT License**, which allows you to use and make modifications to the code as you wish. The only thing I ask is that proper credit is given, acknowledging the effort and time I invested in building it.
bumpAPI 1.5
Python library for interacting with the site's external API.


    BumpAPI - A Python Library for Website Interaction
-------------------------------------------------

BumpAPI is a Python library developed by BumpAPI Labs to facilitate interaction with external APIs of websites. It empowers users to interact with the content and functionalities of various websites through a range of methods and commands.

Features:
- Fetch content from a specified URL.
- Retrieve text content from the page, removing HTML tags.
- Search for specific text occurrences on a page.
- Display HTML code from a webpage.
- Refresh or reload a web page.
- Retrieve links or images from a webpage.
- Generate a summary of the page content.
- Gather statistics about HTML tags used on the page.
- Fetch header information of the webpage.
- Compare two web pages for differences.
- Extract specific elements based on their titles.
- Simulate wait time between commands.
- Click on elements using their IDs.
- Send text inputs to the targeted webpage.

Usage:
The library offers a set of methods to interact with web content. Users can specify a target URL and perform various operations to extract, analyze, or interact with elements on the webpage. It's important to understand and adhere to the terms of service of the websites being accessed using this library.

Note:
BumpAPI is currently in a testing phase, and although efforts are being made to enhance its reliability and stability, users should expect potential bugs or errors during usage.

Contributions:
BumpAPI welcomes contributions and feedback from the community. Feel free to contribute to the project or report any issues encountered during usage.

Disclaimer:
Usage of this library to interact with websites should comply with ethical and legal standards. The developers assume no liability for the usage of BumpAPI beyond its intended functionality.

Support:
For any inquiries, suggestions, or issues, please reach out to BumpAPI Labs via ecomatedev@gmail.com

Thank you for considering BumpAPI for your web interaction needs!
flex-object 1.0.0
FlexObject is a Python class that provides dynamic attribute management, runtime attribute addition/removal, JSON serialization, and JSON file/str reading.
Requires Python: >=3.6

# FlexObject

The FlexObject redefines your Python programming experience with its versatile base class, offering an array of dynamic attribute management capabilities, seamless runtime attribute manipulation, effortless JSON serialization, and streamlined JSON file/string handling. This library serves as a cornerstone for simplified data interaction, catering to a wide spectrum of scenarios.

> **Note**
> This project has been developed based on Python 3.6 or above.

<br />



## Features

1. **Dynamic Attribute Management**: Enjoy the freedom to effortlessly manage object attributes on-the-fly, enhancing adaptability to evolving requirements.
2. **Runtime Attribute Addition/Removal**: Streamline your workflow by dynamically adding or removing attributes during execution, minimizing disruptions.
3. **JSON Serialization**: Seamlessly transform object attributes into the JSON format, facilitating convenient storage, sharing, or communication with external systems.
4. **JSON File/String Reading**: Effortlessly load object attributes from JSON files or strings, expediting data retrieval and utilization.

<br />



## Usage

After incorporating FlexObject into your project, the usage will follow the steps outlined below.

```Python
from flex_object import FlexObject

# Create a FlexObject instance
flex_obj = FlexObject()

# Set attributes dynamically
flex_obj.set(name='David Santana', github='davidsantana06', age=21)

# Serialize attributes to JSON string
json_str = flex_obj.dumps_json()

# Deserialize attributes from JSON string
flex_obj.loads_json(json_str)

# Store attributes in a JSON file
flex_obj.dump_json('data.json')

# Load attributes from a JSON file
flex_obj.load_json('data.json')
```

<br />



## License

This project adopts the **MIT License**, which allows you to use and make modifications to the code as you wish. The only thing I ask is that proper credit is given, acknowledging the effort and time I invested in building it.