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Every task is made easy with tons of help
& debug
commands!
>>> import geocoder # pip install geocoder
>>> g = geocoder.google('<address>')
>>> g.lat, g.lng
45.413140 -75.656703
...
A place to get you started on how to use this module and set up your work station.
Install from PyPi
$ pip install geocoder
Using iPython with Geocoder
$ pip install ipython
$ ipython
Using the TAB key after entering '.' you will see all the available providers.
>>> import geocoder
>>> g = geocoder.
geocoder.api geocoder.geolytica geocoder.mapquest
geocoder.arcgis geocoder.geonames geocoder.nokia
geocoder.base geocoder.get geocoder.osm
geocoder.bing geocoder.google geocoder.timezone
geocoder.canadapost geocoder.ip geocoder.yahoo
geocoder.cli geocoder.keys geocoder.tomtom
geocoder.elevation geocoder.location
...
Using the TAB key again, you can see all the available attributes.
>>> g = geocoder.google('Ottawa')
>>> g.
g.accuracy g.latlng g.south
g.address g.lng g.southeast
g.api g.locality g.southwest
g.attributes g.location g.state
g.bbox g.neighborhood g.status
g.content g.north g.status_code
g.country g.northeast g.status_description
g.county g.northwest g.street_number
g.debug g.ok g.sublocality
g.east g.params g.subpremise
g.error g.parse g.url
g.geometry g.postal g.west
g.headers g.provider g.wkt
g.help g.quality g.x
g.json g.route g.y
g.lat g.short_name
...
The command line tool allows you to geocode one or many strings, either passed as an argument, passed via STDIN, or contained in a referenced file.
$ geocode "Ottawa"
{
"accuracy": "Rooftop",
"quality": "PopulatedPlace",
"lng": -75.68800354003906,
"status": "OK",
"locality": "Ottawa",
"country": "Canada",
"provider": "bing",
"state": "ON",
"location": "Ottawa",
"address": "Ottawa, ON",
"lat": 45.389198303222656
}
Now, suppose you have a file with two lines, which you want to geocode.
$ geocode `textfile.txt`
{"status": "OK", "locality": "Ottawa", ...}
{"status": "OK", "locality": "Boston", ...}
The output is, by default, sent to stdout, so it can be conveniently parsed
by json parsing tools like jq
.
$ geocode `textfile.txt` | jq [.lat,.lng,.country] -c
[45.389198303222656,-75.68800354003906,"Canada"]
[42.35866165161133,-71.0567398071289,"United States"]
Parsing a batch geocode to CSV can also be done with jq
. Build your headers first then run the geocode
application.
$ echo 'lat,lng,locality' > test.csv
$ geocode cities.txt | jq [.lat,.lng,.locality] -c | jq -r '@csv' >> test.csv
For more development requests for the CLI, please provide your input in the Github Issues Page.
The term geocoding generally refers to translating a human-readable address into a location on a map. The process of doing the opposite, translating a location on the map into a human-readable address, is known as reverse geocoding. Using Geocoder you can retrieve Reverse's geocoded data from Google Geocoding API.
At the moment the two providers that have the functionality of Reverse geocoding are Google & Bing. Simply include the reverse=True
parameter.
>>> import geocoder
>>> g = geocoder.bing(['lat','lng'], reverse=True)
>>> g.address
'453 Booth Street, Ottawa'
...
Visit the Wiki
Please look at the following pages on the wiki for more information about a certain topic.
Here is a list of providers that are available for use with FREE or limited restrictions.
The fun extra stuff I added to enjoy some cool features the web has to offer.
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[IP Address](https://github.com/DenisCarriere/geocoder/wiki/IP Address)
If you cannot find a topic you are looking for, please feel free to ask me @DenisCarriere or post them on the Github Issues Page.
This project is free & open source, it would help greatly for you guys reading this to contribute, here are some of the ways that you can help make this Python Geocoder better.
Please feel free to give any feedback on this module. If you find any bugs or any enhancements to recommend please send some of your comments/suggestions to the Github Issues Page.
Speak up on Twitter @DenisCarriere and tell me how you use this Python Geocoder. New updates will be pushed to Twitter Hashtags #geocoder.
A big thanks to all the people that help contribute: