places-geocode 0.5.8

Description:

placesgeocode 0.5.8

Places API Geocoding!
There are a many geocoding APIs out there to choose from. However, Places API tops them
all with the most accurate, affordable, and effective solution!
Our package focuses on a pythonic and accessible way to geocode POIs (Places of Interest) in Python.

SUPPORT
We have multiple support channels that you can contact us on:

Slack


NOTE
Places is a commercial product created for the purpose of geocoding with simplicity and speed. Authorization
API tokens are necessary for using the API endpoints. Registering such API tokens is possible through
our website subscription page.
→ Check out our official documentation!

QUICK START
The places module:
The places(token: str) module allows you to register your access tokens into the Places API which
provides the base functionality for geocoding, density, convex, and radius calls.
→ Note: The Places API package undergoes constant development so consider that endpoint changes may occur.
To import the Places API package:
from places_geocoding import places_api as pa


TABLE OF CONTENTS



Endpoint
Function




load_properties_api
load_radius()


convex_search
convex()


density_search
density()


reverse_geocode
reverse()


batch_reverse
batch_reverse()


geocode
forward()


batch_geocode
batch_forward()




API EXAMPLES
To use the Places API for free leave "token" argument blank
Note: Free usage has a rate limit of 2 requests / second
All example code to the Places API package can be found below:

load_radius()

coordinate: required, indicates center of search
radius: required, indicates radius of search
reverse_param: option, (bool indicating the order of the input coordinates)

Example(1)
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.load_properties(
coordinates=[43.0961466, -77.6337776],
radius=100,
reverse_param=False
)



convex()

coordinate_array: required, edges of polygon
reverse_param: optional, (bool indicating the order of the input coordinates)

Example(2)
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.convex(
coordinates=[[43.0961466, -77.6337776],
[43.1018722, -77.6334654],
[43.1010339, -77.6342459]],
reverse_param=False
)



density()
Radius Load Density:

unit_input: required, str

options: [km, mi, m, ft, yd]


unit_output: required, str

options: [km, mi, m, ft, yd]


coordinates: optional, list
reverse_param: optional, (bool indicating the order of the input coordinates)

Example(3)
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.density(
unit_in='ft',
unit_out='ft',
coordinates=[43.1010339, -77.6342459],
radius=100
)


Custom Density:

unit_input: required, str

options: [km, mi, m, ft, yd]


unit_output: required, str

options: [km, mi, m, ft, yd]


custom_option: optional, str

city
postcode
region/state


custom_utility: optional, int/str,

custom_utility specifies the input of custom_option



Example(4)
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.density(
unit_in='ft',
unit_out='ft',
custom_option='postcode',
custom_utility=10980
)



reverse()

coordinate: required, geographic location of POI
radius: optional, radius of error

Default error radius is 10 ft


reverse_param: optional, (bool indicating the reversal of the input coordinates)

Example(5)
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.reverse(
coordinate=[43.1017283, -77.6338936],
radius=10,
reverse_param=False
)



batch_reverse()

coordinates: required, geographic location(s) of POI
radius: optional, radius of error

Default error radius is 10 ft


reverse_param: optional, (bool indicating the reversal of the input coordinate)

Example(6)
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.batch_reverse(
coordinates=[[43.1017283, -77.6338985],
[43.0936914, -77.6349024],
[43.0937299, -77.6350315],
[43.0930091, -77.6354702],
[43.09245, -77.6353749]],
radius=10,
reverse_param=False
)



forward()
Full Address Geocoding

full address: optional, user-defined1 address of the POI


Places flex-formatting AI allows for multiple address formats

Example(7)
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.forward(
full_address="94 Crittenden Way, Brighton, NY, 14623",
)

Parsed Address Geocoding

street: optional, street on which the POI is located
number: optional, number of the POI's street
postcode: optional, zip code or microregion of the POI
region: optional, state in the USA1 or region internationally
city: optional, city where the POI is located
unit: optional, unit if the POI is non-singular (ex. apartment)


If the POI is within USA borders, the region must be the state's 2-letter abbreviation

Example (8.1) without unit
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.forward(
street="Crittenden Way",
number=94,
postcode=14623,
region="NY",
city="Brighton",
)

Example (8.2) with unit
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.forward(
street="Crittenden Way",
number=88,
postcode=14623,
region="NY",
city="Brighton",
unit='Unit 2'
)



batch_forward()

addresses: optional, list of formatted addresses
address_file: optional, JSON or XML file of formatted addresses1


Note: Check our documentation for formatting details

Example(9.1) array of addresses
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.batch_forward(addresses=["88 Crittenden Way, Brighton, NY, 14623, Unit 2",
"140 Centre Drive, Brighton, NY, 14623",
"94 Crittenden Way, Brighton, NY, 14623",
"104 Crittenden Way, Brighton, NY, 14623, Unit 6"
])

Example(9.2) file of addresses
pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.batch_forward(address_file=address_file.json)

pg = pa.Places(token)
# pg = pa.Places() for free plan

result = pg.batch_forward(address_file=address_file.xml)

→ Download the XML or JSON file as "address_file" to test the examples


INSTALLATION
Install the Places API on pip:
$ pip install places_geocoding

OR
Install the Places API on conda:
$ conda install -c Martin Mashalov places_geocoding


REQUIREMENTS

Python3 >= 3.6
pymongo >= 3.7.0
numpy
pandas


BUSINESS CONTACT
Our business email contact is: [email protected]. Please feel free to reach out
regarding any product feedback or support.