Metadata-Version: 2.1
Name: worldgeo
Version: 1.2.3
Summary: world geohash index
Author-email: Pavel Vorobyev <aquavitale@yandex.ru>
License: MIT
Project-URL: Source, https://github.com/viert/worldgeo
Keywords: geohash,world,index,geoindex
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: pycountry
Requires-Dist: python-geohash
Requires-Dist: requests
Requires-Dist: shapely

## worldgeo

### World geohash index

A simple, easy to use python package to get a country 
by a given geohash or raw coordinates.

### Getting started

#### Installation

```commandline
pip install worldgeo
```

#### Usage

Import the `Index` class and load an index file (we'll discuss
how to get one later on)

```python
from worldgeo import Index
i = Index.load("world5.idx")
```

Now you can resolve a geohash

```
In [3]: i.find_by_hash("9smk")
Out[3]: Country(name='Mexico', code='MEX')
```

or coordinates

```
In [4]: i.find_by_coord(49.2827, -123.1207) # Vancouver
Out[4]: Country(name='Canada', code='CAN')
```

#### Using a pre-built index

The indexes are based on https://github.com/johan/world.geo.json/blob/master/countries.geo.json
and this is the only GeoJSON source supported at the moment. Given that, you don't really
need to build indexes yourself, as there are ready to use files built by GitHub CI.

There are pre-built indexes with precision 4 to 6. Precision 6 means accuracy up to 1.2x1.2 km,
which must be enough given the source might be even less accurate. Since more accurate index take much more
disk and memory space, you might want to use precision 4 or 5 (39km or 5km correspondingly) as these take
only a few Mb.


#### Building a new index

In case you still want to build a more (or less) precise index, you can do so by running

```
build-geoidx -o <output filename> -p <precision> [-t <num threads>]
```

and load the resulting file later on with `Index.load(filename)`
