semvec/pypi-packages huggingface dataset:
easymdm 0.1.2
easymdm is an open source mdm system, usefull for user data consolidation.
Requires Python: >=3.13

![pylint](https://img.shields.io/badge/pylint-5.61-red)
[![PyPi Deployment](https://github.com/ankit48365/easymdm/actions/workflows/deployy_cicd.yml/badge.svg)](https://github.com/ankit48365/easymdm/actions/workflows/deployy_cicd.yml)

#### Prerequisite
Define a yaml file for configuration details like below, Need to pass its name and location to CLI as shown below

#### YAML Construct Readme

```
priority_rule:
  conditions:
    - column: priority_score
      value: 5  # Selects records with exactly priority_score = 5
    - column: confidence_level
      value: 100  # If multiple records have priority_score=5, picks those with confidence_level=100

survivorship:
  rules:
    - column: last_updated
      strategy: most_recent  
    - column: source_id
      strategy: source_priority 
      source_order: ["erp", "crm"]
    - column: address
      strategy: longest_string 
    - column: priority_score
      strategy: highest_value
    - column: confidence_level
      strategy: lowest_value
    - column: quality_rating
      strategy: greater_than_threshold
      threshold: 75
    - column: quality_rating
      strategy: less_than_threshold
```

#### Sample YAML
```
sqlite:
  - DB_PATH: 'D:\path	o\database\'
    DB_NAME: 'mydatabase.db'

blocking:
  columns:
    - first_name
    - last_name
similarity:
  - column: first_name
    method: jarowinkler
  - column: middle_name
    method: jarowinkler
  - column: last_name
    method: jarowinkler
  - column: address
    method: levenshtein
  - column: city
    method: jarowinkler
  - column: zip_code
    method: exact

thresholds:
  review: 0.6
  auto_merge: 0.8

survivorship:
  rules:
    - column: Last_Updated_On
      strategy: most_recent # longest_string

priority_rule:
  conditions:
    - column: original
      value: 1
    - column: Address
      value: *STREET*

```
### CLI Run

```
uv run roar --help

For flat file
> uv run roar --source file --name D:\path	o_your_file\123.csv --config D:\path	o_your_config
```

### Local Test Run

```
uv run .\src\easymdm\cli.py --source file --name .\sample\testdata.csv --config .\sample\testdata.yaml --outpath .\sample\
uv run .\src\easymdm\cli.py --source duckdb --name .\sample\testdata.csv --config .\sample\testdata.yaml --outpath .\sample\
```

### Pylint Action

```
    if: contains(github.event.head_commit.message, 'CheckCodeQuality')
```
recipescraper-cli-tool-er 0.1.1
Add your description here
Requires Python: >=3.13

RecipeScraper CLI Tool

Version: 0.1.1
Python: >= 3.13

RecipeScraper is a Python command-line tool that extracts recipe information from a given recipe URL. It supports most popular recipe websites that use structured data (JSON-LD) and saves the results in a structured text format.

Features:
CLI prompts for a recipe URL, or pass it as an argument
Scrapes and extracts:
Recipe title
Ingredients
Instructions (including nested sections)
Optional: Equipment list, nutrition info if available
Saves the recipe in a formatted .txt file in the current directory
Works with most websites that provide recipe metadata in structured formats

Requirements:
Python >= 3.13

Dependencies (managed automatically with uv):
argparse>=1.4.0
bs4>=0.0.2
requests>=2.32.5
validators>=0.35.0

Installation:
Clone this repository:
git clone https://github.com/yourusername/RecipeScraper.git
cd RecipeScraper

Create and sync the virtual environment:
uv sync

Activate the environment:
Linux / macOS:
source .venv/bin/activate
Windows:
.venv\Scripts\activate

Or install the package directly with pip:
pip install recipescraper-cli-tool-er==0.1.0

Usage:
Run the program by passing a URL as an argument:
recipescraper https://example.com/recipe-url

Or interactively:
python main.py

This will scrape the recipe and save a .txt file in the current directory.

Example Output File:
Recipe Title: Polenta Fries
Ingredients:
1 cup cornmeal
4 cups water
Salt
Olive oil
Instructions:
Preheat the oven to 425°F.
Bring water to a boil, add salt.
Slowly whisk in cornmeal.
Cook until thickened...
Planned Features:
Support exporting recipes in JSON or Markdown
Improved error handling and validation
Optional web interface for easier scraping
Automatic detection of recipe metadata across more websites

License:

MIT License
cffi 2.0.0
Foreign Function Interface for Python calling C code.
Requires Python: >=3.9

[![GitHub Actions Status](https://github.com/python-cffi/cffi/actions/workflows/ci.yaml/badge.svg?branch=main)](https://github.com/python-cffi/cffi/actions/workflows/ci.yaml?query=branch%3Amain++)
[![PyPI version](https://img.shields.io/pypi/v/cffi.svg)](https://pypi.org/project/cffi)
[![Read the Docs](https://img.shields.io/badge/docs-latest-blue.svg)][Documentation]


CFFI
====

Foreign Function Interface for Python calling C code.

Please see the [Documentation] or uncompiled in the `doc/` subdirectory.

Download
--------

[Download page](https://github.com/python-cffi/cffi/releases)

Source Code
-----------

Source code is publicly available on
[GitHub](https://github.com/python-cffi/cffi).

Contact
-------

[Mailing list](https://groups.google.com/forum/#!forum/python-cffi)

Testing/development tips
------------------------

After `git clone` or `wget && tar`, we will get a directory called `cffi` or `cffi-x.x.x`. we call it `repo-directory`. To run tests under CPython, run the following in the `repo-directory`:

    pip install pytest
    pip install -e .  # editable install of CFFI for local development
    pytest src/c/ testing/

[Documentation]: http://cffi.readthedocs.org/