semvec/pypi-packages huggingface dataset:
tonic-fabricate 1.0.2
The official Fabricate client for Python
Requires Python: >=3.8

# Fabricate Client

The official [Fabricate](https://www.tonic.ai/products/fabricate) client package for Python.

## Installation

```bash
pip install tonic-fabricate
```

## Usage

To generate and download data from Fabricate:

```python
from tonic_fabricate import generate

generate(
    # The workspace to use
    workspace='Default',

    # The name of the database to generate
    database='ecommerce',

    # The format to generate. Should be one of:
    # - 'sql'
    # - 'sqlite'
    # - 'csv'
    # - 'jsonl'
    # - 'xml'
    format='sql',

    # The destination to save the data
    dest='./data',

    # Optional: Overwrite the destination if it exists
    overwrite=True,

    # Optional: Generate a single table
    # entity='Customers',
)
```

To push data to an existing database:

```python
from tonic_fabricate import generate
import os

generate(
    # The workspace to use
    workspace='Default',

    # The name of the database in Fabricate
    database='ecommerce',

    # The connection details for the target database
    connection={
        # The host of the target database
        'host': 'host.example.com',

        # The port of the target database
        'port': 5432,

        # The name of the target database
        'database_name': 'ecommerce',

        # The username for the target database
        'username': os.environ.get('FABRICATE_DATABASE_USERNAME'),

        # The password for the target database
        'password': os.environ.get('FABRICATE_DATABASE_PASSWORD'),

        # Whether to use TLS for the connection
        'tls': True,
    },
)
```

## Progress Tracking

You can track the progress of data generation using a callback function:

```python
from tonic_fabricate import generate

def on_progress(data):
    phase = data.get('phase', '')
    percent = data.get('percentComplete', 0)
    status = data.get('status', '')

    phase_text = f"[{phase}] " if phase else ""
    status_text = f", {status}" if status else ""
    print(f"{phase_text}{percent}% complete{status_text}...")

generate(
    workspace='Default',
    database='ecommerce',
    format='sql',
    dest='./data',
    on_progress=on_progress
)
```

## Environment Variables

The client will automatically use the following environment variables if they are set:

- `FABRICATE_API_KEY`: Your Fabricate API key
- `FABRICATE_API_URL`: The Fabricate API URL (defaults to https://fabricate.tonic.ai/api/v1)

## Error Handling

The client raises appropriate exceptions for various error conditions:

```python
from tonic_fabricate import generate

try:
    generate(
        workspace='Default',
        database='ecommerce',
        format='sql',
        dest='./data'
    )
except ValueError as e:
    print(f"Invalid parameters: {e}")
except Exception as e:
    print(f"Generation failed: {e}")
```
akari-textscout 0.1.0
A simple and lightweight Python library for basic text analysis.
Requires Python: >=3.7
Keywords: analysis, nlp, statistics, text

# TextScout

`textscout` is a simple and lightweight Python library for basic text analysis. It provides quick statistics like word count, character count, sentence count, and estimated reading time.

## Installation

You can install `textscout` via pip:

```bash
pip install textscout
mano-datahub-mcp 0.0.5
A Model Context Protocol (MCP) server for DataHub
Requires Python: >=3.10

# mcp-server-datahub

A [Model Context Protocol](https://modelcontextprotocol.io/) server implementation for [DataHub](https://datahubproject.io/).

## Features

Check out the [demo video](https://youtu.be/VXRvHIZ3Eww?t=1878), done in collaboration with the team at Block.

- Searching across all entity types and using arbitrary filters
- Fetching metadata for any entity
- Traversing the lineage graph, both upstream and downstream
- Listing SQL queries associated with a dataset

## Usage

See instructions in the [DataHub MCP server docs](https://docs.datahub.com/docs/features/feature-guides/mcp).

## Developing

See [DEVELOPING.md](DEVELOPING.md).
text2emoji 0.1.1
Convert words in text to emojis
Requires Python: >=3.7

# text2emoji

A simple Python package to convert words in text to emojis.

## Features
- Converts common words to emojis
- Handles punctuation and capitalization
- Easy to use in scripts, chat apps, or fun projects

## Installation

```bash
pip install text2emoji
```
## Usage

```bash
from text2emoji import text_to_emoji

print(text_to_emoji("I am happy"))
# Output: I am 😊
```