semvec/pypi-packages huggingface dataset:
ni.datamonikers.v1.client 1.0.0
gRPC Client for NI Data Moniker Service
License: MIT
Requires Python: <4.0,>=3.10
Keywords: data-moniker, client

# Table of Contents

- [Table of Contents](#table-of-contents)
- [About](#about)
  - [Operating System Support](#operating-system-support)
  - [Python Version Support](#python-version-support)
  - [Installation](#installation)

# About

`ni.datamonikers.v1.client` is a Python package that provides a gRPC client for the
NI Data Moniker Service, version 1. The corresponding service is defined in the
[ni.datamonikers.v1 package](https://github.com/ni/ni-apis/tree/main/ni/datamonikers/v1).

NI created and supports this package.

## Operating System Support

`ni.datamonikers.v1.client` supports Windows operating systems.

## Python Version Support

`ni.datamonikers.v1.client` supports CPython 3.10+.

## Installation

You can directly install the `ni.datamonikers.v1.client` package using `pip` or by listing it as a
dependency in your project's `pyproject.toml` file.
ni.measurements.data.v1.client 1.0.0
gRPC Client for NI Data Store Service
License: MIT
Requires Python: <4.0,>=3.10
Keywords: data-store, client

# Table of Contents

- [Table of Contents](#table-of-contents)
- [About](#about)
  - [Operating System Support](#operating-system-support)
  - [Python Version Support](#python-version-support)

# About

`ni.measurements.data.v1.client` is a Python package that provides a gRPC client for the
NI Data Store Service, version 1. The corresponding service is defined in the
[ni.measurements.data.v1 package](https://github.com/ni/ni-apis/tree/main/ni/measurements/data/v1).

NI created and supports this package.

## Operating System Support

`ni.measurements.data.v1.client` supports Windows operating systems.

## Python Version Support

`ni.measurements.data.v1.client` supports CPython 3.10+.

## Installation

You can directly install the `ni.measurements.data.v1.client` package using `pip` or by listing it as a
dependency in your project's `pyproject.toml` file.
docslicer 0.1.1
SDK for the DocSlicer document processing API - transform HTML documents into structured chunks for RAG applications
License: MIT
Requires Python: >=3.8
Keywords: chunking, docslicer, document-processing, html, llm, rag, sec-filings

# DocSlicer SDK

Python SDK for the DocSlicer document processing API.

## Installation

```bash
pip install docslicer
```

## Quick Start

```python
from docslicer import run

# Process a URL
chunks = run("https://sec.gov/filing.html", api_key="sk_live_...")

# Process a local file
chunks = run("./document.html", api_key="sk_live_...")

# Process all HTML files in a directory
chunks = run("./docs/", api_key="sk_live_...")

# Process multiple files
chunks = run(["file1.html", "file2.html"], api_key="sk_live_...")

# Process URLs from a CSV
chunks = run("./urls.csv", api_key="sk_live_...")
```

## Options

```python
chunks = run(
    "./docs/",
    api_url="https://www.docslicer.ai/api/v1/run",  # Custom API URL
    api_key="sk_live_...",                           # API key for auth
    format="json",                                   # Output format: json, csv, jsonl, parquet
    timeout=300,                                     # Request timeout
)
```

## Output Formats

```python
# JSON (default) - list of dictionaries
chunks = run("./doc.html", api_key="sk_live_...", format="json")

# CSV - string with header row  
csv_data = run("./doc.html", api_key="sk_live_...", format="csv")

# JSON Lines - one JSON object per line
jsonl_data = run("./doc.html", api_key="sk_live_...", format="jsonl")

# Parquet - binary bytes
parquet_bytes = run("./doc.html", api_key="sk_live_...", format="parquet")
```

## Async Support

```python
from docslicer import run_async

chunks = await run_async("./docs/", api_key="sk_live_...")
```

## Client Class

For multiple calls, use the client class to reuse configuration:

```python
from docslicer import DocSlicerClient

client = DocSlicerClient(
    api_url="https://www.docslicer.ai/api/v1/run",
    api_key="sk_live_...",
)

chunks1 = client.run("./doc1.html")
chunks2 = client.run("./doc2.html")
```

## Environment Variables

You can set the API URL via environment variable:

```bash
export DOCSLICER_API_URL="https://www.docslicer.ai/api/v1/run"
```

## Get an API Key

Sign up at [docslicer.ai](https://www.docslicer.ai) to get your API key.