pyqupa 0.1.1

PYthon Qualdich.de mountain PAss data processor.

PYQUPA: PYthon wrapper for QUaeldich.de mountain PAss data

A Python interface to access data in quaeldich.de.

Quaeldich.de owns all rights to the data. I am therefore willing to give up the repository upon request from quaeldich.de.

Installation

You can use either poetry or pip.

pip install pyqupa
# or
poetry add pyqupa

How it works

Quaeldich.de stores all mountain pass data in json files with unique data-ids. For example, Mont Ventoux approaching from Bédoin has geopositioning data (latitude, longitude, elevation, and distance) identified by data-id=127_189. Therefore, data can be accessed via the URL https://www.quaeldich.de/qdtp/anfahrten/127_189.json. We scraped all pass data URLs from the website and saved them in pypass/db/passes.json. Whenever you attempt to search for pass information, the code will first look for the URL and process data for you.

Basic usage

Below shows basic search options you can use with pypass.

>>> from pypass.passees import PassDB
>>> passdb = PassDB()
>>> passdb.search("Mont Ventoux", "name")
# List of a Pass with length == 1
[Pass(name="Mont Ventoux", coord=[44.1736, 5.27879], ...)]
>>> passdb.search("alpen", "region") # Only works for german names
# List of Passes matching criteria
[Pass(name="Stilfser Joch", ...), Pass(...), ...]
# Below commands returns similar return type shown above
>>> passdb.search("italien", "country") # Only works for german name
>>> passdb.search([1800, 2000], "height")
>>> passdb.search([10.0, 15.0], "distance")
>>> passdb.search([500, 1000], "elevation")

Features

Extract data

• You can use cli command to extract data from quaeldich.de.

  • You need two arguments -e and -d.
  • If you set give 0 for -e, it will extract all data registered in quaeldich.de.
  • If you don't set -d option, it will save db to pypass/db/.
  • DB doesn't contain geopositioning data. Only relevant URLs to be processed later on.

• Mac OS or Linux

  python -m pypass -e NUMBER_OF_PASS_TO_BE_EXTRACTED -d DIRECTORY_TO_BE_SAVE_DB
  

• Windows

  py -m pypass -e NUMBER_OF_PASS_TO_BE_EXTRACTED -d DIRECTORY_TO_BE_SAVE_DB
  

DB structure

pypass has two different DBs.

• pypass/db/passes.json: DB contains all scraped Pass data from quaeldic.de. And the DB looks like:

// pypass/db/passes.json
{
    "_default":
    {
        "1":
        {
            "name": ..., // name of Pass
            "coord": ..., // coordinate of the summit
            "country": ...,
            "region": ...,
            "height": ...,
            "total_distance": ..., // distances of all paths to the summit
            "total_elevation": ..., // elevation gain of all paths to the summit
            "avg_grad": ..., // average gradient of each paths
            "max_distance": ...,
            "min_distance": ...,
            "max_elevation": ...,
            "min_elevation": ...,
            "url": ..., // Pass url at quaeldich.de
            "gpts": ..., // geopositioning data. No actual data, only links.
            "status": ..., // HTTP reponse code. Always 200.
        },
        ...
    }
}

• pypass/db/pass_names.json: DB only contains all Pass names, regions, and country. If Pass has alternative name, it also stored as alt.

Search and access Pass data

• You can search Pass data by region, name, height, distance, and elevation gain.

• Each Pass class contains all paths to the top including information regarding distance, elevation, and gradient.

>>> from pypass.passees import PassDB
>>> passdb = PassDB()
>>> Pass = passdb.search("Mont Ventoux", "name")  # Always return list[Pass]
>>> Pass[0].path_names
['South Side from Bédoin', 'West Side from Malaucène', 'East Side from Sault']
# Mont Ventoux has 3 access points.
>>> Pass[0].total_distance
[21169.514785722, 20846.819408688, 25365.999999999996]  # in meter
>>> Pass[0].total_elevation
[1592.295991259, 1572.2721899565, 1152.0] # in meter
>>> Pass[0].avg_grad
[7.521646137742093, 7.5420243209918585, 4.54151226050619] # in %
>>> Pass[0].elevation
[array([ 313, ..., 1905.29599126]), ...]
# GPT log data for the elevation in meter (from start to end)

• Name suggestion for a typo when searching the pass.

>>> from pypass.passees import PassDB
>>> passdb = PassDB()
>>> Pass = passdb.search("Mont Venoux", "name") # Wrong input name
...
NameError: The given name (Mont Ventox) is not in our database. Did you mean ['Mont Ventoux']?
# Raise `NameError` and will give name suggestion for the close match.

Running GUI

We created GUI using steamlit.

• You can run GUI by typing following command in the file directory (git cloned directory):

python -m streamlit run pypass/app.py

• Or you can simply run

python -m pypass --gui # -g also works

It is possible to access via URL

Demos:

• Search by name:
  • Pass can be searched by its name (supports drop-down menu).
  • Visual representation of paths in 2D (Folium) and 3D (Deck.gl) map.
  • Plots for the gradient profiles.

• Search by distance/elevation/height:
  • Passes are searched from the given range (using slider).
  • If a number of searched data is larger than 10, display statistics (histogram).
  • List of all searched data.

• Search by region/country:
  • Passes are searched from the given region/country.
  • Only works with German. However, you can search with drop-down menu.

Current issues/WIPs

Below is the list of issues or WIPs.

DBs

• Function to update DB data efficiently.

GUI

• Sorting table properly.

MISC

• Proper translation (German - English).
• Fix all broken Pass names.
• Make proper test files