In the following example the prefilter of esy-osmfilter is used to extract all pipelines from Liechtenstein. The easiest way to run esy-osmfilter is to download the from and run it. It is quite similar to the more detailed desription below.

In this example, we start by importing all necessary libraries and methods.

>>> import configparser, contextlib
>>> import os, sys
>>> from esy.osmfilter import osm_colors as CC
>>> from esy.osmfilter import run_filter 
>>> from esy.osmfilter import Node, Way, Relation

Thereafter, the IO filepaths are defined, assuming the osm-pbf file is already downloaded.

>>> PBF_inputfile = os.path.join(os.getcwd(),
...                              'tests/input/liechtenstein-191101.osm.pbf')
>>> JSON_outputfile = os.path.join(os.getcwd(),
...                              'tests/output/LI/liechtenstein-191101.json')

Alternatively, you could also make use of urllib library to retrieve a OSM file:

>>> import urllib.request
>>> if not os.path.exists('tests/input/liechtenstein-191101.osm.pbf'):
...    filename, headers = urllib.request.urlretrieve(
...        '',
...        filename='liechtenstein-191101.osm.pbf'
...    )
...    PBF_inputfile = filename

In the next step, a prefilter for all pipeline objects is defined. With the prefilter, we accept all way-items that have “man_made” as key and “pipeline” as value in their taglist. The white and black filter are left empty for the moment.

>>> prefilter   = {Node: {}, Way: {"man_made":["pipeline",],}, Relation: {}}
>>> whitefilter = []
>>> blackfilter = []

The run_filter function will allow to filter for OSM items from a pbf-file. We confirm the prefilter phase by setting the boolean variable NewPreFilterData=True.

>>> [Data,Elements]=run_filter('noname',
...                     PBF_inputfile, 
...                     JSON_outputfile, 
...                     prefilter,
...                     whitefilter, 
...                     blackfilter, 
...                     NewPreFilterData=True, 
...                     CreateElements=False, 
...                     LoadElements=False,
...                     verbose=True)

The prefilter returns the filter results to the Data dictionary. This means all OSM way-items with the tag “man_made”=”pipeline” are stored there. But not enough, additionally, all referenced node items of these pipelines are stored there too.

>>> len(Data['Node'])
>>> len(Data['Relation'])
>>> len(Data['Way'])

In this example, we have only found two pipelines and their correspondent 13 nodes.

You can also set “man_made”:True to accept items independently of a key value.

In the next step we use run_filter to load the Data dictionary and specify the main filtering results. In this example, we use the blackfilter to exclude possible pipelines substations from our prefiltering results.

>>> blackfilter = [("pipeline","substation"),]

We further only accept the drain pipelines that have the really great name “Wäschgräbli”.

>>> whitefilter =[(("waterway","drain"),("name","Wäschgräble")), ]

We initiate the mainfilter phase by setting CreateElements=True.

>>> [Data,Elements]=run_filter('funny-waterway-pipelines',
...                            PBF_inputfile, 
...                            JSON_outputfile, 
...                            prefilter,
...                            whitefilter, 
...                            blackfilter, 
...                            NewPreFilterData=False, 
...                            CreateElements=True, 
...                            LoadElements=False,
...                            verbose=True)
>>> len(Elements['funny-waterway-pipelines']['Node'])
>>> len(Elements['funny-waterway-pipelines']['Relation'])
>>> len(Elements['funny-waterway-pipelines']['Way'])

We see, that there is only one way-item left in the Elements dictionary, the other has been filtered out. There are no referenced nodes (or relation members) of the remaining way-item passed to the Elements dictionary.

esy-osmfilter comes with an export function for GeoJSON files (not implemented for relations yet) which will make thinks a lot easier:

>>> from esy.osmfilter import export_geojson
>>> export_geojson(Elements['funny-waterway-pipelines']['Way'],Data,
... filename='test.geojson',jsontype='Line')

If you want to convert the ‘Node’ dictionary from Elements, you can set jsontype=’Point’.

To visualize the output-file just open and drag it on the screen.

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