Prepare 2.0.1 release

Author: dunkelstern

LICENSE.txt

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2018, Johannes Schriewer
+Copyright (c) 2018-2019, Johannes Schriewer
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

README.md

@@ -31,6 +31,17 @@ See `README.md` in the [repository](https://github.com/dunkelstern/osmgeocoder)
 - Restored compatability with older PostgreSQL DB versions (9.5+ if you do no use openaddresses.io)
 - Switched to `pipenv`
 
+### v2.0.1
+
+- Fix missing import for structured forward geocoding
+- Fix Copy and Paste error in forward geocoding SQL
+
+If you're coming from `2.0.0`, re-run the finalize step to update the SQL functions:
+
+```bash
+$ pipenv run bin/finalize_geocoder.py --db postgresql://geocoder:password@localhost/osmgeocoder
+```
+
 ## TODO
 
 - Return Attribution in API and in webservices

setup.py

@@ -6,22 +6,22 @@
 
 setup(
         name='osmgeocoder',
-        version='2.0.0',
+        version='2.0.1',
         description='OpenStreetMap and OpenAddresses.io based geocoder',
         long_description='''
-            Python implementation for a OSM / Openaddresses.io Geocoder.
+Python implementation for a OSM / Openaddresses.io Geocoder.
 
-            This geocoder is implemented in PostgreSQL DB functions as much as possible, there is a simple API and an example flask app included.
+This geocoder is implemented in PostgreSQL DB functions as much as possible, there is a simple API and an example flask app included.
 
-            You will need PostgreSQL 9.5+ (or 11.0+ for Openaddresses.io) with PostGIS installed as well as some disk space and data-files from OpenStreetMap and (optionally) OpenAddresses.io.
+You will need PostgreSQL 9.5+ (or 11.0+ for Openaddresses.io) with PostGIS installed as well as some disk space and data-files from OpenStreetMap and (optionally) OpenAddresses.io.
 
-            Data import will be done via [Omniscale's imposm3](https://github.com/omniscale/imposm3) and a supplied python script to import the openaddresses.io data.
+Data import will be done via [Omniscale's imposm3](https://github.com/omniscale/imposm3) and a supplied python script to import the openaddresses.io data.
 
-            Optionally you can use the [libpostal machine learning address classifier](https://github.com/openvenues/libpostal) to parse addresses supplied as input to the forward geocoder.
+Optionally you can use the [libpostal machine learning address classifier](https://github.com/openvenues/libpostal) to parse addresses supplied as input to the forward geocoder.
 
-            For formatting the addresses from the reverse geocoder the `worldwide.yml` from [OpenCageData address-formatting repository](https://github.com/OpenCageData/address-formatting) is used to format the address according to customs in the country that is been encoded.
+For formatting the addresses from the reverse geocoder the `worldwide.yml` from [OpenCageData address-formatting repository](https://github.com/OpenCageData/address-formatting) is used to format the address according to customs in the country that is been encoded.
 
-            See `README.md` in the [repository](https://github.com/dunkelstern/osmgeocoder) for more information.
+See `README.md` in the [repository](https://github.com/dunkelstern/osmgeocoder) for more information.
         ''',
         long_description_content_type='text/markdown',
         url='https://github.com/dunkelstern/osmgeocoder',