- What is this?
- Assumptions
- What's in here?
- Bootstrap the project
- Geocode unstructured data
- Geocode structured data
- Geocode mixed data
- Advanced configuration
Geocode addresses using Nominatim geocode service.
It uses a simple cache file to optimize the need for redundant geolocation.
If you plan to do a big geocoding batch, please contact Nominatim geocode service to let them know that you are planning to do so. They will point you to the right time to execute or give you some recommendations over what frequency to use, etc.
The following things are assumed to be true in this documentation.
- You are running OSX.
- You are using Python 2.7. (Probably the version that came OSX.)
- You have virtualenv and virtualenvwrapper installed and working.
- You have postgres installed and running
For more details on the technology stack used with the app-template, see our development environment blog post.
This code should work fine in most recent versions of Linux, but package installation and system dependencies may vary.
The project contains the following folders and important files:
code-- Where are lambda function code livestest-- test csv files with some examples of allowed formatsgeocode.py-- Main Python scriptrequirements.txt-- Python requirements.
To bootstrap the project:
git clone [email protected]:nprapps/geocode-nominatim.git
cd geocode-nominatim
mkvirtualenv geocode-nominatim
pip install -r requirements.txt
In order to geocode an unstructured address, create a csv file with the following headers:
- address -- unstructured format, wrap in quotes if it contains commas
$python geocode.py $CSVFILE
Where $CSVFILE is the path to the csv file on your hard drive
The results will be stored in the output folder
In order to geocode an unstructure address, create a csv file with the following headers:
- street -- [street number] [steetname]
- city
- state
- country
- postalcode
Fill one or as many as the fields as you need to specify the location that you want to geocode. Then run the script
$python geocode.py $CSVFILE
Where $CSVFILE is the path to the csv file on your hard drive
The results will be stored in the output folder
If you have a mix of unstructured and structured location then create a csv file with the following headers:
- address -- use this for the unstructured locations
- street -- [street number] [steetname] for structured locations
- city -- for structured locations
- state -- for structured locations
- country -- for structured locations
- postalcode -- for structured locations
Fill either the address for the unstructured locations and one or as many as the fields as you need to specify the location that you want to geocode for structured locations. Then run the script
$python geocode.py $CSVFILE
Where $CSVFILE is the path to the csv file on your hard drive
The results will be stored in the output folder
The geocode.py scripts can be customized with some advanced behaviors
You can add a debug flag to the script to have a more verbose execution
$python geocode.py $CSVFILE -d
If you want to test the execution on a sample of the data prior to launching the full dataset then:
$python geocode.py $CSVFILE -s $SAMPLE_SIZE
Where $SAMPLE_SIZE is the number of lines to be used for the sample from the beginning of the csv
The script uses a file based cache to optimize the number of requests to the Nominatim service.
If you do not want to use the file cache at all add the no-cache flag like this:
$python geocode.py $CSVFILE -C
You can customize the number of seconds to wait between consecutive executions of the geocoding service:
$python geocode.py $CSVFILE -w $WAIT_SECONDS
Where $WAIT_SECONDS is the number of seconds to wait until the next execution
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent