semvec/pypi-packages huggingface dataset:
ai-data-sdk 0.1.2
A comprehensive SDK for standardizing, processing, embedding, and retrieving data for AI applications
License: MIT
Requires Python: >=3.8
Keywords: ai, data, embeddings, vector database, pii

# AI Data SDK by Zeebee

A comprehensive SDK for standardizing, processing, embedding, and retrieving data for AI applications.

## Features

- Text embedding generation
- Semantic search with filtering and hybrid search
- PII detection and masking
- User feedback submission
- IP allowlist management (admin only)

## Installation

```bash
pip install ai-data-sdk-zeebee==0.1.2
```

## Usage

### Initialize Client

```python
from ai_data_sdk import AIDataClient

# Initialize with your API key
client = AIDataClient(api_key="your_api_key_here")
```

### Generate Embeddings

```python
# Generate embeddings for a list of texts
texts = [
    "AI Data SDK helps standardize data for AI applications.",
    "The embedding module converts text into vector representations."
]

result = client.create_embeddings(texts)
```

### Search for Similar Documents

```python
# Basic search
search_result = client.search(query_text="How do machines learn from data?")

# Advanced search with filters
filters = {
    "category": "technology",
    "rating": {"$gt": 4.5}
}

search_result = client.search(
    query_text="neural networks",
    filters=filters,
    hybrid_search_text="deep learning",
    hybrid_alpha=0.3
)
```

### Detect and Mask PII

```python
# Basic PII detection
text = "My email is john.doe@example.com and my phone is 555-123-4567."
result = client.detect_pii(text, pii_types=["email", "phone"], mask=True)

# Advanced anonymization
result = client.detect_pii(
    text,
    advanced_anonymize=True,
    consistent_replacements=True
)
```

### Submit Feedback

```python
feedback = client.submit_feedback(
    query_id="q_12345",
    result_id="doc_1",
    rating=4,
    comments="Very relevant result, but missing some details."
)
```

## Error Handling

```python
from ai_data_sdk import APIError, AuthenticationError, InvalidRequestError, RateLimitError

try:
    result = client.create_embeddings(texts)
except AuthenticationError:
    print("Authentication failed. Check your API key.")
except InvalidRequestError as e:
    print(f"Invalid request: {e}")
except RateLimitError:
    print("Rate limit exceeded. Please try again later.")
except APIError as e:
    print(f"API error: {e}")
```

## Documentation

For full documentation, visit [https://ai-data-sdk.readthedocs.io/](https://ai-data-sdk.readthedocs.io/)

## License

This project is licensed under the MIT License - see the LICENSE file for details.
can-isotp 2.0.7
Module enabling the IsoTP protocol defined by ISO-15765
License: MIT
Requires Python: >=3.7
Keywords: isotp, can, iso-15765, 15765, iso15765

python-can-isotp
################

.. image:: https://app.travis-ci.com/pylessard/python-can-isotp.svg?branch=master

This project is a Python package meant to provide support for IsoTP (ISO-15765) protocol written in Python 3. The code is published under MIT license on GitHub (`pylessard/python-can-isotp <https://github.com/pylessard/python-can-isotp>`_).

This package contains a Python implementation of the protocol that works in the user space that may or may not be coupled with `python-can <https://python-can.readthedocs.io>`_. It also contains a wrapper for a simplified usage of the `Linux SocketCAN IsoTP kernel module <https://github.com/hartkopp/can-isotp>`__

Documentation
-------------

The documentation is available here :   https://can-isotp.readthedocs.io

Requirements
------------

 - Python 3.7+

Installation
------------

using pip::

    pip install can-isotp
symbologyl2 0.1.6
A python wrapper for symbologyl2 (https://github.com/onechronos/symbologyl2)
License: MIT
Requires Python: <4.0,>=3.10

[![Build](https://github.com/onechronos/symbologyl2-py/actions/workflows/build.yml/badge.svg)](https://github.com/onechronos/symbologyl2-py/actions/workflows/build.yml)
[![Coverage Status](https://coveralls.io/repos/github/onechronos/symbologyl2-py/badge.svg)](https://coveralls.io/github/onechronos/symbologyl2-py)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit)](https://github.com/pre-commit/pre-commit)


[![PyPI](https://img.shields.io/pypi/v/symbologyl2)](https://pypi.org/project/symbologyl2/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/symbologyl2)](https://pypi.org/project/symbologyl2/)
[![PyPI - Format](https://img.shields.io/pypi/format/symbologyl2)](https://pypi.org/project/symbologyl2/)
[![PyPI - License](https://img.shields.io/pypi/l/symbologyl2)](https://pypi.org/project/symbologyl2/)
[![Documentation Status](https://readthedocs.org/projects/symbologyl2-py/badge/?version=latest)](https://symbologyl2-py.readthedocs.io/en/latest/?badge=latest)

# Symbology Normalization (symbologyl2-py)

## Introduction

Utility functions for parsing, normalizing, and translating between various capital market symbology types. This
library is a thin wrapper over the [symbologyl2](https://github.com/onechronos/symbologyl2) library, written in rust.

## Current Support

- [x] US equities
  - [x] CMS Concatenated/Suffix
  - [x] Nasdaq Integrated
  - [x] CQS (NYSE/CTA plan)

## Development

```
uv sync && uv sync --dev
source .venv/bin/activate
maturin develop
```

### Version Bumps

Given how [maturin](https://pyo3.rs/v0.17.3/index.html) operates, it's necessary to bump release versions in both
`pyproject.toml` and `Cargo.toml`.

```
pyproject.toml

[project]
version = "x.y.z"
```

```
Cargo.toml

[package]
version = "x.y.z"
```