semvec/pypi-packages huggingface dataset:
motalk 0.1.0
A Python package
License: MIT
Requires Python: >=3.8

# motalk

Widgets for talking to/with Python from a notebook.

## Overview

motalk provides interactive speech-to-text widgets for Jupyter notebooks, built on top of [anywidget](https://anywidget.dev/). It enables voice input capabilities directly in your notebook environment, making it easy to capture spoken text and use it in your Python code. It uses the Webkit Speech API from your browser too, which means you don't have to worry about API keys. Be ware though: different browsers may have different levels of support for this feature.

## Installation

```bash
pip install motalk
```

## Quick Start

```python
import motalk

# Create a speech-to-text widget
widget = motalk.WebkitSpeechToTextWidget()

# Display the widget
widget
```
snomed-neo4j-client 0.1.1
A client library for interacting with SNOMED CT data in Neo4j
License: MIT
Requires Python: >=3.9

# SNOMED CT Neo4j Client

A Python client library for interacting with SNOMED CT data stored in a Neo4j database.

## Installation

```bash
pip install snomed-neo4j-client
```

## Features

- Connect to a Neo4j database containing SNOMED CT data
- Retrieve concepts, descriptions, and relationships
- Navigate the SNOMED CT hierarchy (parents, children, ancestors, descendants)
- Search for concepts by term
- Check subsumption relationships between concepts
- Full Pydantic model support for type safety

## Usage

```python
from snomed_neo4j_client import SnomedClient

# Initialize the client
client = SnomedClient(
    uri="bolt://localhost:7687",
    user="neo4j",
    password="password"
)

# Get a concept by ID
concept = client.get_concept("138875005")  # SNOMED CT Concept (root)
print(concept)

# Get a concept with all its details
concept_details = client.get_concept_with_details("73211009")  # Diabetes mellitus
print(f"Concept: {concept_details.id}")
print(f"Descriptions: {len(concept_details.descriptions)}")
print(f"Relationships: {len(concept_details.relationships)}")

# Get the preferred term for a concept
term = client.get_preferred_term("73211009")
print(f"Preferred term: {term}")

# Check if one concept is a subtype of another
is_subtype = client.is_a("73211009", "64572001")  # Is diabetes a disease?
print(f"Is subtype: {is_subtype}")

# Find concepts by term
results = client.find_concepts("diabetes")
for result in results:
    print(f"{result['id']}: {result['term']}")

# Close the connection when done
client.close()
```

## Requirements

- Python 3.9+
- Neo4j database with SNOMED CT data
- Neo4j Python driver
- Pydantic 2.0+

## License

MIT