semvec/pypi-packages huggingface dataset:
json-profiler 0.1.0
A tool for exploring and analyzing JSON structure with aggregated statistics
License: MIT
Requires Python: >=3.7

# JSON Profiler

A Python tool for exploring and analyzing JSON structure with aggregated statistics. This package helps you understand the structure of complex JSON data by providing detailed insights into field types, presence percentages, and nested structures.

## Installation

```bash
pip install json-profiler
```

## Usage

```python
from json_profiler import explore_json_aggregated
import json

# Example JSON data
data = {
    "users": [
        {"id": 1, "name": "Alice", "email": "alice@example.com", "tags": ["admin", "user"]},
        {"id": 2, "name": "Bob", "email": "bob@example.com", "tags": []},
        {"id": 3, "name": "Charlie", "tags": ["user"]}
    ],
    "metadata": {
        "total": 3,
        "active": True
    }
}

# Analyze the JSON structure
result = explore_json_aggregated(data)
```

This will output:
```
=== AGGREGATED STRUCTURE ===
users[] (total items: 3 across 1 list instances):
  email: str (66.7% present)
  id: int (100.0% present)  
  name: str (100.0% present)
  tags: list (100.0% present) [WARNING: 1/3 lists empty (33.3%)]

ROOT[] (total items: 1 across 1 list instances):
  active: bool (100.0% present)
  total: int (100.0% present)
```

## Features

- **Field Analysis**: Shows data types and presence percentages for each field
- **Nested Structure Support**: Handles deeply nested JSON objects and arrays
- **Empty List Detection**: Warns about empty lists in your data
- **Aggregated Statistics**: Provides comprehensive statistics across all instances
- **Type Information**: Shows all data types encountered for each field

## Return Value

The function returns a dictionary containing all unique values found for each field across the entire JSON structure.

## License

MIT License
geogals 0.1.8
A publicly available repository for using geostatistical methods on real and simulated galaxy data.
License: MIT
Requires Python: >=3.7

=======
GeoGals
=======


.. image:: https://img.shields.io/pypi/v/geogals.svg
        :target: https://pypi.python.org/pypi/geogals

.. image:: https://img.shields.io/travis/astrobenji/geogals.svg
        :target: https://travis-ci.com/astrobenji/geogals

.. image:: https://readthedocs.org/projects/geogals/badge/?version=latest
        :target: https://geogals.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status




A publicly available repository for using geostatistical methods on real and simulated galaxy data.


* Free software: MIT license
* Tutorials: https://github.com/astrobenji/GeoGals/tree/main/docs/tutorials
* Further documentation: https://geogals.readthedocs.io/


Features
--------

This package contains functions that enable a user to:

 * Create a semivariogram for real or simulated spatial galaxy data
 * Fit geostatistical models to galaxy data that accounts for a spatially-varying mean, as well as small-scale fluctuations
 * Use kriging to predict values of random fields at observed/unobserved locations

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
kynex 0.2.5
A Python package to get data from different llm's
License: MIT
Requires Python: >=3.7

# 🔷 Kynex

**Kynex** is a modular, pluggable Python framework that simplifies integrating multiple LLM providers such as **Google Gemini**, **Groq**, and **Ollama** through a unified, flexible interface.

Whether you're building AI workflows, chatbots, or prompt-based tools, Kynex allows seamless integration with different LLMs — all through a single API.

---

## 🚀 Features

- **Multi-LLM Support**: Easily switch between Gemini, Groq, and Ollama with a single interface.
- **Dynamic Inputs**: Accept LLM type, model name, API keys, and host dynamically at runtime.
- **LangChain Prompt Templates**: Built-in LangChain `PromptTemplate` for clean prompt formatting.
- **Pluggable Architecture**: Easily extend to new LLMs in the future.
- **Ready for Local & Remote Deployments**: Supports local Ollama and remote LLM services.

---

## 📦 Installation

```bash
pip install kynex

Example Usage:

Create it:

Create a Python file and add the following:

 from kynex.LLMTools import LLMConnector

Google Gemini Example:


if __name__ == "__main__":
    # Simulated input from frontend
    request = {
        "prompt": "what is fast api",
        "model_name": "your_model",   #gemini-1.5-flash
        "api_key": "your_api_key",
        "llm_type": "LLMConnector.LLM_GEMINI"
    }

    response = LLMConnector.get_llm_response(
        prompt=request["prompt"],
        model_name=request["model_name"],
        api_key=request["api_key"],
        llm_type=request.get("llm_type")  # Can be None — will default to gemini
    )

    print("\n🔹 Response:\n")
    print(response)



Groq Example:

from kynex.LLMTools import LLMConnector


 if __name__ == "__main__":
     request = {
         "prompt": "your_prompt",
         "model_name": "your_model",  # ✅ Groq model
         "api_key": "your_api_key",
         "llm_type": "groq"
     }

     response =LLMConnector.get_llm_response(
         prompt=request["prompt"],
         model_name=request["model_name"],
         api_key=request["api_key"],
         llm_type=request.get("llm_type")
     )

     print("\n🔹 Groq LLaMA-4 Response:\n")
     print(response)

Ollama Example (Local or Remote):

from kynex.LLMTools import LLMConnector

response = LLMConnector.get_llm_response(
    prompt="your_prompt",
    model_name="your_model",  #EX:llama3
    llm_type=LLMConnector.LLM_OLLAMA,
    host="your_host"  # or remote URL if exposed via proxy
)

print(response)
treewalker 0.2.2
A simple package to walk a directory tree and collect files and sizes into a SQLite DB.
License: MIT
Keywords: system, tool, database

# Treewalker

A simple package to walk a directory tree and collect files and sizes into a SQLite DB.

## Usage

For simple (and most) use cases, simply install the package from PyPI:
```commandline
pip install treewalker
```
And run it from the command line:
```commandline
treewalker --help
treewalker --db test.sqlite --walk C:/temp
```
This is the preferred and recommended way to run Treewalker.

## Usage and development

Get started (change directory to where you want the project first):
```commandline
pip install treewalker
```

Run the script with your own .json configuration:
```commandline
python treewalker.py --cfg my_config.json
```

```my_config.json
{
    "database": "test.sqlite",
    "walk": "c:/temp"
}
```

Or run the script entirely from the command line:
```commandline
python treewalker.py --db test.sqlite --walk c:\temp
```

Or build a single file executable if you need this to run on Windows systems that won't have Python pre-installed:
```commandline
scripts/build_pyinstaller.bat c:/target/folder
scripts/build_pyinstaller_xp.bat c:/target/folder

```
This creates a `treewalker.exe`, which can be run 'anywhere':
```commandline
.\treewalker.exe --db test.sqlite --walk c:\temp
```

Note that the executable will be limited to running on systems that support the version of Python you're using to build it. I.e. for Windows XP (32-bit or 64-bit), the very latest version of Python you can use is 3.4.4.

## Getting at the data

You can easily access the contents of any of the sqlite files:
```python
from sqlite3 import connect

conn = connect('test.sqlite')
c = conn.cursor()
# show all the root directories
print(c.execute('SELECT * FROM dirs WHERE parent_dir<0').fetchall())
# show all files that have "test" in their name (case-insensitive)
print(c.execute('SELECT * FROM files WHERE name LIKE "%test%"').fetchall())
```
Look at the documentation of the Python standard sqlite3 library for more examples. https://docs.python.org/3/library/sqlite3.html and at the documentation of Treewalker at https://treewalker.readthedocs.io