Metadata-Version: 2.1
Name: yat_geo_db
Version: 1.1.2
Summary: A simple and effective Python wrapper around the Open Geo DB managed by YAT
Home-page: https://github.com/yat-co/yat-geo-db
Author: YAT, LLC
Author-email: Robert Goss <rgoss@yat.ai>, Jarod Hart <jhart@yat.ai>
License: The MIT License
        
        Copyright (c) 2022 YAT (https://yat.ai)
        
        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
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        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
        THE SOFTWARE.
Project-URL: Homepage, https://github.com/yat-co/yat-geo-db
Project-URL: Bug Tracker, https://github.com/yat-co/yat-geo-db/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests
Requires-Dist: numpy
Requires-Dist: jellyfish
Requires-Dist: pytz

# YAT Geo DB

An elegantly simple Geo Reference manager with managed database of US, Canada and Mexico. 
Quickly perform auto-complete style fuzzy search, fetch record details and search
a mile radius around a specific place.

Geo DB file lists available at `https://yat-geo-db.sfo3.digitaloceanspaces.com/`


## Install 

With Python 3.7 or greater install the package with simple pip command.

```
pip install yat-geo-db
```

## Usage

The manager utilizes two flat files maintained by YAT available at `<location>`.
On initial load those files will be downloaded to local machined and stored on 
machine as a form of cache.  You can specify a specific version denoted by date 
or utilize the current version.


Import and load data
```python
from yat_geo_db import GeoManager as GeoManagerImport

GeoManager = GeoManagerImport()

GeoManager.load_data(
    force_db_fetch= False, cache_local=True, compressed=True
)
```

Refresh local data (current version)

```python
from yat_geo_db import GeoManager as GeoManagerImport

GeoManager = GeoManagerImport()

GeoManager.load_data(force_db_fetch=True)
```

Perform Auto-complete style search
```python
search_param = "Nashvil"
filters = {"ref_data.state_prov": "TN", "ref_data.country": "US"}
fuzzy_res = GeoManager.fuzzy_search(
    search_param, num_results=2, filters=filters
)
print([(value["value"], value["id"]) for value in fuzzy_res])
>>> [('Nashville, TN', 'us__tn__nashville'), ('Nashville Metro Area, TN', 'nashville_tn_us_metro')]
```

Apply filters for any element in shape object including `geo_type` and `ref_data`,
latter allowing to refine search to specific country or state.

```python
search_param = "Nashvil"
filters = {"geo_type": "ZipCode", "ref_data.country": "US"}
fuzzy_res = GeoManager.fuzzy_search(
    search_param, num_results=2, filters=filters
)
print([(value["value"], value["id"]) for value in fuzzy_res])
>>> []
```

Fetch a shape object by the reference code.  All reference codes follow a hierarchical
structure, for below example `<country>__<state>__<name with _ seperator>`.

```python
reference_code = 'us__tn__nashville'

res = GeoManager.get_shape_by_ref_code(reference_code=reference_code)

print(res)

>>> {'value': 'Nashville, TN',
>>>  'clean_value': 'nashville tn',
>>>  'id': 6818,
>>>  'area': 0.0,
>>>  'bbox': {'ll_latitude': '36.165890',
>>>   'ur_latitude': '36.165890',
>>>   'll_longitude': '-86.784440',
>>>   'ur_longitude': '-86.784440'},
>>>  'geo_type': 'City',
>>>  'latitude': 36.16589,
>>>  'ref_data': {'city': 'Nashville',
>>>   'country': 'US',
>>>   'zip_code': '37222',
>>>   'state_prov': 'TN'},
>>>  'longitude': -86.78444,
>>>  'population': 530852,
>>>  'is_zip_code': False,
>>>  'is_aggregate': False,
>>>  'long_display': 'Nashville, TN 37222',
>>>  'short_display': 'Nashville, TN',
>>>  'primary_source': None,
>>>  'reference_code': 'us__tn__nashville',
>>>  'primary_timezone': 'America/Chicago',
>>>  'related_shape_id': 6718,
>>>  'primary_source_id': None,
>>>  'is_three_digit_zip_code': False}
```

Perform radius search around a Geo Object, utilizing a reference code, radius in
miles and indicator to return results within the same country.  Results returned 
are a list of Geo Shape IDs or with `full_results=True` a full list of Geo Objects 
returned.

```python
reference_code = 'us__tn__nashville'

res = GeoManager.radius_search(
    reference_code=reference_code, radius=10, country_exact=True
)

print(res)
>>> [6702, 6831, 142898, 142897, 142895, 142901, 142903, 142904, 142905, 142910, 142893, 119979, 104924, 258833, 259091, 118948, 
>>> 118950, 119199, 119208, 119565, 119569, 119570, 119978, 259331, 239701, 242429, 6764, 98, 6609, 6818, 242049, 6612, 6621, 
>>> 142899, 142900, 241027, 119206, 119572, 133787, 119196, 119567, 119977, 6622, 134214, 134217, 143024, 179468, 133797, 133808, 
>>> 119980, 119201, 119204, 119205, 119210, 142902, 142906, 142907, 142908, 142909]
```

### Example 

For an example microservice implementation with Flask check out this [repository](https://github.com/yat-co/yat_geo_db_api).

Of try out the free API with documentation here [YAT Demo](https://demo.yat.ai).
