Metadata-Version: 2.1
Name: geoiter
Version: 0.1.1
Summary: A simple tool to iterate circles within given boundaries:
Home-page: https://github.com/cloasdata/geoiter
Author: Simon Bauer
Author-email: code@seimenadventure.de
License: MIT
Keywords: iter,geo,scraping,data
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Provides-Extra: gpx
Provides-Extra: plot
Provides-Extra: overpass
Provides-Extra: test
License-File: LICENSE.md

# geoiter
iterates the planet.

A simple tool to iterate coordinates within given boundaries.
The usage is mostly for querying/searching by location. 
Geoiter provides many locations within a boundary, like a country. 
Let's say Germany has in sum 5000 houses to sell. Then most platforms will only allow you to visit the first 200 houses. 
Now to get the others, you need to dissect the big boundary area into smaller ones.
And this is where geoiter provides you with coordinates

<img src="https://user-images.githubusercontent.com/84661606/159549731-44de6016-0582-4ef2-94ba-646b6277aec3.png" width="300" />


**geoiter** can be used for web scraping to utilize geo/location queries:

<img src="https://user-images.githubusercontent.com/84661606/159549754-470fa19f-a826-44ad-b76c-6c338ae72b1b.png" width="300"/>

In many cases the web page restrict the result items to a fixed number. 
With geoiter you can now dissect this one query to a many location queries to relax 
the result density under the restriction limit.

geoiter has only one additional dependency called [haversine](https://pypi.org/project/haversine/).

## install
    pip install geoiter

## usage
```python
import pickle

from geoiter.util.ressource_example import germany
from geoiter import GeoIter

# get you boundary for example
with open(germany, "rb") as file:
    germany = pickle.load(file)

# prepare
gi = GeoIter(
    boundary=germany,
    radius=100,
    comp_rate=20
    )

if __name__ == "__main__":
    # plot them as example
    for coordinate in gi:
        print(coordinate)
```
## speed
one may consider that geo data have megabytes of coordinates. Which may make the iteration very slow,
because it needs to look up coordinates in the boundary often.
To accelerate the **geoiter** provides a very simple compressor and uses bisect instead of list iteration.
However, it still can be slow.

## extensions
There two extensions which give additional help

    pip install geoiter["gpx]

provides you with an gpx exporter.

    pip install geoiter["plot"]

provides a plotting function to visualize the grid.

## data
get boundaries from osm or others sources like
* https://www.geoboundaries.org/
* https://osm-boundaries.com/
* ...

## todo
* SRP for compressor
* Make own haversine calculation for fixed directions.

## Homepage
* <a href="https://github.com/cloasdata/geoiter">on github </a>
* <a href="https://pypi.org/project/geoiter">on pypi </a>
Copyright © 2022 Simon Bauer

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

