The Hack For LA Data Science team is a Community of Practice within the LA brigade seeking to make analytical and machine learning services available to local communities and organizations.
This issue contains resources to help community members learn more about web scraping in Python, including the use of APIs.
Action Items
[ ] Gather resources, including relevant Hack for LA content (i.e. our tutorials and projects that have used web scraping), online courses, and tutorial/how-to web content.
[ ] Once done, remove the "Guide: Research" label and add the "Guide: Draft Guide" label
[ ] Create a draft template, either in markdown format in this issue or a google doc in the Data Science google drive
[ ] Once done, remove the "Guide: Draft Guide" label and add the "Guide: Create Guide" label
[ ] Create a guide on how to use the resources contained, including steps on how to get started for volunteers new to web scraping
[ ] Once done, remove the "Guide: Create Guide" label and add the "Guide: Review Guide" label
[ ] Review the guide with Data Science Communities of Practice
[ ] Once done, remove the "Guide: Review Guide" label and add the "Guide: Leadership Review" label
[ ] Present to Hack for LA leadership team for sign off
[ ] Once approved, remove the "Guide: Leadership Review" label and add the "Guide: Place Guide" label
[ ] Include link to guide under Resources if you add it as a template in .github
Overview
This issue contains resources to help community members learn more about web scraping in Python, including the use of APIs.
Action Items
Resources/Instructions
Hack for LA Web Scraping Tutorial with Selenium/Docker/Python