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pokeminer

Pokemon Go scraper. Based on an early version of AHAAAAAAA/PokemonGo-Map.

Oh great, another map?

This is not just a map. Apart from much cleaner codebase that suits my needs better, the example.py has been split into two entities: worker.py and web.py.

So what's this for?

This tool (or more importantly, worker.py) gets rectangle as a start..end coordinates (configured in config.py) and spawns n workers. Each of the worker uses different Google/PTC account to scan its surrounding area for Pokemon. To put it simply: you can scan entire city for Pokemon. All gathered information is put into a database for further processing (since servers are unstable, accounts may get banned, Pokemon disappear etc.). worker.py is fully threaded, waits a bit before rescanning, and logins again after 10 scans just to make sure connection with server is in good state.

And web.py? It's just a simple interface for gathered data that displays active Pokemon on a map.

Here it is in action:

In action!

Bulletpoint list of features

  • multithreaded
  • multiple accounts at the same time
  • able to map entire city in real time
  • data gathering for further analysis
  • visualization

ELI5: setting up

/u/gprez made a great tutorial on Reddit. Check it out if you're confused after reading this readme.

Running

The only parameter worker accepts is step limit, just as in example.py.

python worker.py -st 8

To run interface:

python web.py --host 127.0.0.1 --port 8000

Configuration

You need to have at least rows x columns accounts. So for below example, you need to have 20 accounts.

DB_ENGINE = 'sqlite:///db.sqlite'  # anything SQLAlchemy accepts
MAP_START = (12.3456, 14.5)  # top left corner
MAP_END = (13.4567, 15.321)  # bottom right corner
GRID = (4, 5)  # row, column
# LAT_GAIN and LON_GAIN can be configured to tell how big a space between
# points visited by worker should be. LAT_GAIN should also compensate for
# differences in distance between degrees as you go north/south.
LAT_GAIN = 0.0015
LON_GAIN = 0.0025

ACCOUNTS = [
    # username, password, service (google/ptc)
    ('trainer1', 'secret', 'google'),
    ('trainer2', 'secret', 'ptc'),
    ('trainer3', 'secret', 'google'),
    # ...
]

# Trash Pokemon won't be shown on the live map.
# Their data will still be collected to the database.
TRASH_IDS = [16, 19, 41, 96]

# List of stage 2 & rare evolutions to show in the report
STAGE2 = [
    3, 6, 9, 12, 15, 18, 31, 34, 45, 62, 65, 68, 71, 76, 94, 139, 141, 149
]

Setting up database

Run python REPL and:

import db
db.Base.metadata.create_all(db.get_engine())

License

See LICENSE.