Git Product home page Git Product logo

properties_scraper's Introduction

Properties scraper

This is a Python script to massively gather information about exposure limits and physical properties from different publicly-available sources:

Organization Data source Information Website
National Oceanic and Atmospheric Administration (NOAA) Computer-Aided Management of Emergency Operations (CAMEO) Database National Fire Protection Association (NFPA) 704 classification for hazardous chemicals https://cameochemicals.noaa.gov/search/simple
Occupational Safety and Health Administration (OSHA) Occupational Chemical Database Physcial properties and exposure limits https://www.osha.gov/chemicaldata
National Institute of Standards and Technology (NIST) Chemistry WebBook Physical properties https://webbook.nist.gov/
Environmental Protection Agency (EPA) CompTox Chemicals Dashboard Environmental fate, transport and physical properties https://comptox.epa.gov/dashboard
Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA) GESTIS Substance Database International limit values http://limitvalue.ifa.dguv.de

Requirements

In order to use this code you need the following requirements:

  1. Google Chrome installed in your computer. However, you can modify the code and use other selenium driver (e.g., Firefox)
  2. A .csv with a column named as CAS NUMBER (except for the OSHA database)
  3. Install:

How to use

To run the code from the Linux/Ubuntu terminal or Windows CMD:

  1. You must move to the folder where is main.py
  2. Run the following command:
   python main.py Option -FR file_path_to_read_CAS -FS file_path_to_save_infomartion

The inputs accompanying the flags represent:

  • file_path_to_read_CAS: path of the file where you have the CAS numbers for searching (except for OSHA database).
  • file_path_to_save_infomartion: path of the file where you will save the information.

The positional argument Option has the following values currently:

  • A: for running osha_scraper.py.
  • B: for running cameo_scraper.py.
  • C: for running comptox_scraper.py.
  • D: for running nist_scraper.py.
  • E: for running ifa_scraper.py

Additionally, you can use each scraper separately, for example:

   python cameo_scraper.py -FR file_path_to_read_CAS -FS file_path_to_save_infomartion

properties_scraper's People

Contributors

gruizmer avatar jodhernandezbe avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar

Forkers

tupshin

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.