Skip to main content

Agilisys Tender Alert is a data processing, web scraping, and classification tool focused on tender data. The project uses Playwright to automate web filtering and scraping, then processes and classifies the scraped data using various NLP techniques to retain only relevant tenders.

Project description

Agilisys Tender ALert

Agilisys Tender Alert is a data processing, web scraping, and classification tool focused on tender data. The project uses Playwright to automate web filtering and scraping, then processes and classifies the scraped data using various NLP techniques to retain only relevant tenders.

Project Overview

This project aims to streamline the tender selection process by:

  1. Scraping data from tender websites after applying specific filters via Playwright.
  2. Cleaning and preprocessing the scraped data.
  3. Classifying relevant tenders using various NLP methods.
  4. Exporting the relevant tenders to a new Excel file for review.

Installation

  1. Using pip (PyPI Release) To install the package from PyPI, run:

    pip install Agilisys_Daily_Tender

  2. Run a python file with the below code in it

    from AgilisysDailyTender import main

Output

The final Excel file (Shortlisted_Tenders_.xlsx) will contain only the tenders that passed the classification criteria, along with any relevant metadata and URLs. All the tenders are saved in case if there is a need of reference under the corresponding Excel files (extracted_data)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

AgilisysDailyTenders-1.0.3-py2.py3-none-any.whl (16.4 kB view details)

Uploaded Python 2Python 3

File details

Details for the file AgilisysDailyTenders-1.0.3-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for AgilisysDailyTenders-1.0.3-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 920454785aa9278359118b977548439143574c78de05944b885b898fe40a7ce6
MD5 00e55f16f55346e33384f70369e2f1ae
BLAKE2b-256 d876b144406cda843c5f0f8ede7f19dd1ae06229e9d7f6b3fdf90fb56eab82d6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page