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esy-osmfilter-1.0.9
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مشاهده بیشترتوضیحات
Filtering of OSM pbf-files and exporting to geojson
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | esy-osmfilter-1.0.9 |
| نام | esy-osmfilter |
| نسخه کتابخانه | 1.0.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Adam Pluta |
| ایمیل نویسنده | Adam.Pluta@dlr.de |
| آدرس صفحه اصلی | https://github.com/pypa/osmfilter |
| آدرس اینترنتی | https://pypi.org/project/esy-osmfilter/ |
| مجوز | - |
# esy-osmfilter
`esy-osmfilter` is a Python library to read and filter [OpenStreetMap](https://www.openstreetmap.org) data files in the [Protocol
Buffers (PBF)](https://developers.google.com/protocol-buffers/) format and export them to a Python dictionary and/or JSON file.
## Install
```console
foo@bar:~$ pip install esy-osmfilter
```
## Usage
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 sample.py
from https://gitlab.com/dlr-ve-esy/esy-osmfilter 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.
```python
>>> 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.
```python
>>> 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:
```python
>>> import urllib.request
>>> if not os.path.exists('tests/input/liechtenstein-191101.osm.pbf'):
... filename, headers = urllib.request.urlretrieve(
... 'https://download.geofabrik.de/europe/liechtenstein-191101.osm.pbf',
... 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.
```python
>>> 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.
```python
>>> [Data,_]=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.
```python
>>> len(Data['Node'])
13
>>> len(Data['Relation'])
0
>>> len(Data['Way'])
2
```
In this example, we have only found two pipelines and their correspondent 13 nodes.
***PLEASE NOTICE:***
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.
```python
>>> blackfilter = [("pipeline","substation"),]
```
We further only accept the drain pipelines that have the really great name "Wäschgräbli".
```python
>>> whitefilter =[(("waterway","drain"),("name","Wäschgräble")), ]
```
We initiate the mainfilter phase by setting CreateElements=True.
```python
>>> [_,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'])
0
>>> len(Elements['funny-waterway-pipelines']['Relation'])
0
>>> len(Elements['funny-waterway-pipelines']['Way'])
1
```
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.
However, these are still accessible in the `Data` dictionary.
Esy-osmfilter comes with an export function for GeoJSON files (not implemented for relations yet) which will
make thinks a lot easier:
```python
>>> from esy.osmfilter import export_geojson
>>> export_geojson(Elements['funny-waterway-pipelines']['Way'],Data,
... filename='test.geojson',jsontype='Line')
```
To visualize the output-file just open http://geojson.io and drag it on the screen.
For more details, jump to the
[documentation](https://dlr-ve-esy.gitlab.io/esy-osmfilter/).
نیازمندی
| مقدار | نام |
|---|---|
| <4,>=3 | protobuf |
| >=0 | esy-osm-pbf |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl esy-osmfilter-1.0.9:
pip install esy-osmfilter-1.0.9.whl
نصب پکیج tar.gz esy-osmfilter-1.0.9:
pip install esy-osmfilter-1.0.9.tar.gz