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Geocaching.com site crawler. Provides tools for searching, fetching caches and geocoding.

Project description

Complete documentation can be found at Read the Docs.

Features

  • login to Geocaching.com

  • search caches

    • normal search (unlimited number of caches from any point)

    • quick search (all caches inside some area)

  • get cache and its details

    • normal loading (can load all details)

    • quick loading (can load just basic info but very quickly)

    • load logbook for given cache

  • get trackable details by tracking code

  • post log for a cache or a trackable

  • geocode given location

Installation

Stable version - using pip:

pip install pycaching

Dev version - manually from GIT:

git clone https://github.com/tomasbedrich/pycaching.git
cd pycaching
pip install .

Pycaching has following requirements:

Python>=3.4
requests>=2.8
beautifulsoup4>=4.4
geopy>=1.11

Examples

Login

Simly call pycaching.login() method and it will do everything for you.

import pycaching
geocaching = pycaching.login("user", "pass")

If you won’t provide an username or password, pycaching will try to load .gc_credentials file from current directory or home folder. It will try to parse it as JSON and use the keys username and password from that file as login credentials.

# sample .gc_credentials JSON file
{ "username": "myusername", "password": "mypassword" }
import pycaching
geocaching = pycaching.login()  # assume the .gc_credentials file is presented

Load a cache details

cache = geocaching.get_cache("GC1PAR2")
print(cache.name)  # cache.load() is automatically called
print(cache.location)  # stored in cache, printed immediately

This uses lazy loading, so the Cache object is created immediately and the page is loaded when needed (accessing the name).

You can use different method of loading cache details. It will be much faster, but it will load less details:

cache = geocaching.get_cache("GC1PAR2")
cache.load_quick()  # takes a small while
print(cache.name)  # stored in cache, printed immediately
print(cache.location)  # NOT stored in cache, will trigger full loading

You can also load a logbook for cache:

for log in cache.load_logbook(limit=200):
    print(log.visited, log.type, log.author, log.text)

Or its trackables:

for trackable in cache.load_trackables(limit=5):
    print(trackable.name)

Post a log to cache

geocaching.post_log("GC1PAR2", "Found cache in the rain. Nice place, TFTC!")

It is also possible to call post_log on Cache object, but you would have to create Log object manually and pass it to this method.

Search for all traditional caches around

from pycaching import Point
from pycaching.cache import Type

point = Point(56.25263, 15.26738)

for cache in geocaching.search(point, limit=50):
    if cache.type == Type.traditional:
        print(cache.name)

Notice the limit in the search function. It is because geocaching.search() returns a generator object, which would fetch the caches forever in case of simple loop.

Geocode adress and search around

point = geocaching.geocode("Prague")

for cache in geocaching.search(point, limit=10):
    print(cache.name)

Find caches with their approximate locations in some area

from pycaching import Point, Rectangle

rect = Rectangle(Point(60.15, 24.95), Point(60.17, 25.00))

for cache in geocaching.search_quick(rect, strict=True):
    print(cache.name, cache.location.precision)

Load a trackable details

trackable = geocaching.get_trackable("TB3ZGT2")
print(trackable.name, trackable.goal, trackable.description, trackable.location)

Post a log for trackable

from pycaching.log import Log, Type as LogType
import datetime

log = Log(type=LogType.discovered_it, text="Nice TB!", visited=datetime.date.today())
tracking_code = "ABCDEF"
trackable.post_log(log, tracking_code)

Appendix

Inspiration

Original version was inspired by these packages:

Although the new version was massively rewritten, I’d like to thank to their authors.

Authors

Authors of this project are all contributors. Maintainer is Tomáš Bedřich.

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