**Login Email: '''admin@mcnaircenter.org'''
**Login Password: '''amount'''
*Eventbrite API is well-documented and its database readily accessible. In the python dev environment, I am using the http '''<code>requests''' </code> library to make queries to the database, to obtain json data containing event objects that in turn contain organizer objects, venue objects, start/end time values, longitude/latitude values specific to each event. The '''<code>requests''' </code> library has inbuilt <code>.json() </code> access methods, simplifying the json reading/writing process. Bang.
**In querying for events organized by techstar, one of the biggest startup programs organization in the U.S., I use the following. Note that the organizer ID of techstar is 2300226659.
import requests
verify = True,
)
**In each case, var <code>response</code> is a json object, that can be read/written in python using the requests method <code>response.json()</code>. Each endpoint used above are instances of e.g. <code>GET events/search/ </code> or <code>GET categories/:id</code> EventBrite API methods. There are different parameters each GET function can harness to get more specific results. To populate a comprehensive local database, the '''dream''' is to systematic queries from different endpoints and collecting all results, without repetition, in a centralized database. In order to do this, I'll have to familarize further with these GET functions and develop a systematic approach to automate queries to the eventbrite server. One way to do this is to import entrepreneurship buzzword libraries that are available on the web, and make queries by iterating through these search strings systematically.
*Eventbrite event objects in json are well-organized and consistent. There are many interesting fields such as the longitude/latitude decimals, apart from name/location/organizer/start-time/end-time data which are data we want to amass initially.
**For instance, the upcoming startup weekend event in Seville looks like the following.