esy-osmfilter 0.1.2

filtering of OSM pbf-files

esy-osmfilter

esy-osmfilter is a Python library to read and filter OpenStreetMap data files in the Protocol Buffers (PBF) format and export them to a dictionary and/or JSON file.

Usage

In the usage

>>> 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

The prefilter will return the Data-dictionary. With the prefilter, we accept all way-items that have man_made as key and pipeline as value in their taglist.

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

Additionally, all corresponent nodes that are refered in these way-items will be stored as Nodes. You can also set "man_made":True to accept items independently of a key value. In this example, we have only found two pipelines "Wäschgräbli" and "Wäschgräble" and their correspondent Nodes. The Element dictionary will be constructed from the Data dictionary by the usage of the whitefilter and the blackfilter. The blackfilter is a list of tuples. It ignores items if one tuple is present as tag. The whitefilter is a list of list of tuples. It accepts entries if a list of tuples is present in the taglist of an OSM item. By the way, in case of conflict, the blackfilter wins. In this example, we blackfilter the prefiltered items for pipeline substation.

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

We further only accept the drain pipelines that have really funny name "Wäschgräbli".

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

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

Filtered elements are given a name:

>>> elementname='funny-waterway-pipelines'

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

>>> len(Data['Node'])
13
>>> len(Data['Relation'])
0
>>> len(Data['Way'])
2

Only one way left after the blackfilter and whitefiler

>>> len(Elements['funny-waterway-pipelines']['Node'])
0
>>> len(Elements['funny-waterway-pipelines']['Relation'])
0
>>> len(Elements['funny-waterway-pipelines']['Way'])
1

One can access the referenced nodes from the Data dictionary.

>>> elementlist=list(Elements['funny-waterway-pipelines']['Way'].keys())
>>> first_element=elementlist.pop()
>>> first_item_refs=list(Elements['funny-waterway-pipelines']['Way'][first_element]['refs'])
>>> first_ref_id=str(first_item_refs[0])
>>> first_ref_item=Data['Node'][first_ref_id]
>>> first_ref_item['lonlat']
[9.502233600000002, 47.153427400000005]

This pipeline has 3 node references. The first referenced node of the first element was selected via its id-string from the Data-dictionary: Data['Node'][id-string].

for more details, jump to the documentation.