semvec/pypi-packages huggingface dataset:
apisani-test-project-25070208 0.0.1
A short description of the project
Requires Python: <4.0,>=3.10

# apisani-test-project-25070208

A short description of the project

## Overview

This documentation covers the apisani-test-project-25070208 library..

## Installation

```bash
pip install apisani-test-project-25070208
```

Or, if you use Poetry:

```bash
poetry add apisani-test-project-25070208
```

## Quick Start

```python
from apisani_test_project_25070208 import Example

# Initialize
example = Example()

# Use the library
result = example.run()
print(result)
```
TDAtaframe 0.5.0
A package to handle shape-matching for meshes
Requires Python: >=3.12

# TDAtaframe
TDA brought to dataframes.

# Install
TDAtaframe is available on pypi as a source distribution.
The backend requires that you have the appropriate libtorch 2.6.0 libraries 
installed on your system in the standard location.

On Linux/macOS, this is typically /usr/lib, /usr/include, /usr/share for 
library, include, and share files respectively. Sym-linking the files will not 
work.

After ensuring that these libraries are present, all that is needed is

```pip install tdataframe```.

On first install, it is normal for compilation to take a few minutes.

## Manual libtorch install instructions
It is recommended to use your package manager to install libtorch.
If not readily available for your system, follow the below instructions 
as a workaround.

Download libtorch from [here](https://pytorch.org/).
Then, unzip the files.

`unzip libtorch-*.zip && cd libtorch`

Next, copy all the files to the system. Make sure
you understand what these commands do as they are difficult to undo.
You will likely need to run these commands with `sudo`.

`cp -r lib/* /usr/lib && cp -r include/* /usr/include && cp -r share /usr/share`

Finally, update your linker cache with

`ldconfig`.

## Alternative libtorch locations
todo. see tch-rs docs