gig_scraper (Legacy code; currently updating)

A python script that scrapes concert data from both https://www.alttickets.com/ and https://www.seetickets.com/ for any artist(s). Now includes fuzzy matching location filter and Flask UI!
NOTE: The geocoder used might not be able to recognise some venues which may result in misplotted pins or none at all.

What is this repository for?

Finding concerts for the artists you love across multiple sites. Saves results as a csv file.

• Developed and tested with Python 3.7, should work for 3.6+.

Setup

• Download Python3+ from https://www.python.org/downloads/release/python-370/
• Download or clone the repository
• Install requirements using pip install -r requirements.txt

Running the gig_scanner.py script as a stand-alone module

• Populate the gigs.txt file with artists you want to scan!
• Run script with or without optional location flag python gig_scanner.py --artist-file <path_to_file> --location <optional_location_here>

Example

python .\gig_scanner.py --artist-file "C:\Users\EJones820\Desktop\Projects\scraping\concert_scanner\src\gigs.txt" --location "Bristol" 

Note: gigs.txt only contains one artists - The Night Cafe

Should expect an output of a dataframe along these lines

            Artist          Venue           Date/Time   Price         Gig Status
6   The Night Cafe  SWX - Bristol  6:30 PM Tue 18 May  £15.52  Tickets available
20  The Night Cafe  Bristol - SWX      18:30 18/05/21  £15.19  Tickets available

Note: Two entries from both sites - both are kept in case tickets are available on one site and not the other etc.

Running the gig_flask.py flask application

• Create file for your Bing Maps API key called bing_api_key.txt in src folder
• Add user_agent in gig_flask.py script (near the top) - any identifying string i.e. <your_email_and_project_name>
• Launch flask using python gig_flask.py OR launch_gig_ui.ps1 - if using powershell
• Navigate to http://localhost:5000/ (Chrome recommended)

To Do

1. Add location filter for gigs
2. Flask application with map displaying gigs - Still needs testing
3. Rewrite coords so venue names can be labelled to pushpins on map
4. Add location filter for Flask UI