kmvahini 1.1.0

A Python package to scrape agricultural data from Karnataka's market website.

kmvahini

Download Market Data from Krishi Marata Vahini!

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Important Legal Disclaimer

Krishi Marata Vahini is the registered trademark of the Karnataka State Agricultural Marketing Board (KSAMB) and the Department of Agricultural Marketing, Govt. of Karnataka.

kmvahini is not affiliated, endorsed, or vetted by KSAMB or the Government of Karnataka. It is an open-source tool designed for research and educational purposes using publicly available data from KSAMB.

The data is intended for personal and research use only. Refer to KSAMB's Terms of Use for more details.

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About kmvahini

kmvahini is a Python library that enables users to scrape and analyze market data for agricultural commodities available on Krishi Marata Vahini.

Key Features

• Scrape market data for over 264 commodities from 164 markets across Karnataka.
• Retrieve data from 2002 onwards.
• Filter by month, year, commodity, and market.
• Multithreading support for faster data retrieval.
• Outputs clean and structured data for research and analysis.

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Installation

To install the latest version of kmvahini:

pip install kmvahini

Upgrade to the latest version:

pip install --upgrade kmvahini

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Quick Start

Example Usage

import kmvahini.scraper as scraper

# Define parameters for scraping
months = ['JANUARY', 'FEBRUARY', 'MARCH']  # Specify months
years = ["2010"]  # Specify year(s)
commodities = ["BENGALGRAM"]  # Choose a commodity
markets = ["AllMarkets"]  # Select all or specific markets

# Scrape the data
df = scraper.scrape_website(months, years, commodities, markets)

# Preview the data
print(df.head())

Output

The resulting DataFrame contains structured columns, such as:

• Date
• Market
• Commodity
• Price Details (Min, Max, Modal)

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Requirements

This package depends on:

• Python 3.7+
• selenium
• pandas
• tqdm
• lxml

For full details, check:

• Requirements
• setup.py

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Legal Notes

kmvahini is licensed under the MIT License. See the LICENSE file for more details.

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Feedback & Contributions

We welcome your feedback and contributions! Here's how you can contribute:

• Raise an Issue: Report bugs or suggest new features via the Issues section of the GitHub repository.
• Contribute: Fork the repository, make your changes, and submit a pull request.
• Contact: For direct feedback or queries, email [e-mail].

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P.S.

Thank you for using kmvahini! Your feedback is invaluable in making it better. 😊

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