semvec/pypi-packages huggingface dataset:
Total5 0.0.2
Total.js v5 integration (Pypeline) with Python
Requires Python: >=3.8

# Total.js integration

The Total.js Python library provides a predefined integration between the Total.js framework (Pypelines) and Python scripts.

- [Website](https://totaljs.com)

```python
import Total5
import sys

@Total5.on('data')
def data(payload):
	# @payload {JSON|String|Buffer} payload
	print("--->", payload)

@Total5.on('open')
def open():
	# Total.js is connected

@Total5.on('close')
def close():
	# Total.js is disconnected

@Total5.on('error')
def error(err):
	# Unexpected error
	print("ERROR", err)

# Total5.send(payload, [uid]);
# @payload {JSON|String|Buffer} payload
# @uid {Number} message identifier (optional)
# IMPORTANT: This method must be performed while Total.js is connected.
Total5.send({ "name": "Hello world!"})

# Total.listen(type, socket_path)
# @type {json|text|buffer} default "json"
# @socket_path {String} path to the socket (optional)
Total5.listen()
```

__Python on MacOS__:

```shell
python3 -m venv .venv
source .venv/bin/activate
```

## Release package

__Preinstallation__:

```shell
pip install build
pip install twine
```

```shell
rm -rf dist/ build/ total.egg-info
python3 -m build
twine upload dist/*
```
gripcd 0.1.2
Implementation of GRIP & FLAMES algorithms, for Fast & Global Point Cloud rigid registration.
Requires Python: >=3.7

# GRIP
Implementation of GRIP & FLAMES algorithms, for Fast & Global Point Cloud rigid registration.

## Installation

```
pip install grip
```


## Basic Usage


- **Pairwise**:

```python
from grip import PairwiseGRIP, icp

estimator = PairwiseGRIP(icp)
T_s2m_hat = estimator(sources, models)
# or
registered_sources, registered_models = estimator.register(sources, models)
```


- **Generative multiview**:

```python
from grip import GenerativeMultiviewsGRIP, ChamferJRMPC

estimator = GenerativeMultiviewsGRIP(ChamferJRMPC())
estimator(views)
T_hat = estimator.T_hat
```
pm-studio-mcp-nanyin 0.1.0
PM Studio MCP Server - A Model Context Protocol server for product managers
Requires Python: >=3.13

# PM Studio MCP

PM Studio MCP is a Model Context Protocol (MCP) server for product management tasks. It provides a suite of tools and utilities to help product managers analyze user feedback, perform competitive analysis, generate data visualizations, and access structured data sources.

## Getting Started
### Set up MCP Runtime - Install uv

For windows: please refers to the [uv official site]https://docs.astral.sh/uv/getting-started/installation/#__tabbed_1_2
For macOS: run `brew install uv` (If you don't have Homebrew [click here](https://github.com/ai-microsoft/fsd/blob/main/private/DEVELOPER.md#install-homebrew-on-macos))


### Set up MCP server in your config file
   ```bash
   {
      "mcpServers": {
         "pm-studio-mcp": {
               "command": "uvx",
               "args": [
                  "pm-studio-mcp"
               ],
               "env": {
                  "WORKING_PATH": "{PATH_TO_YOUR_WORKSPACE}/working_dir/",
                  "AZURE_KEY_VAULT_CLIENT_SECRET":"{AZURE_KEY_VAULT_CLIENT_SECRET}",  // optional,this is the key to access all API keys in PM Studio, reach out to us to get the key
               },
               "disabled": false
         }
      }
   }
   ```
##PM Studio MCP Package