Parsing Addresses with Python

Summary

The usaddress Python library is designed to parse and label United States addresses into structured components.

Abstract

The usaddress library is a Python tool specifically designed for parsing and labeling addresses in the United States. It can identify various parts of an address, such as the street number, name, city, state, and ZIP code, and standardize the format of the address. To use usaddress, one must install the library and its dependencies, after which the parse() function can be employed to break down an address into its constituent parts, returning a dictionary with labeled keys. Additionally, the tag() function offers an alternative format for the labeled address parts, such as a list of tuples. The library is versatile, capable of handling different address formats, including those with apartment numbers or directional suffixes, and allows for customization of address parsing behavior.

Opinions

The article suggests that usaddress is a useful tool for developers needing to parse and standardize U.S. addresses in their applications.
It implies that the library is flexible and can be adapted to various address formats, which is beneficial for handling diverse data sets.
The inclusion of the tag() function indicates that the library provides multiple output formats, catering to different developer preferences and use cases.
The article promotes the library as a solution for addressing challenges such as ambiguous addresses, by mentioning the ability to customize parsing options.
By providing a real-world example and showing the output, the article conveys that usaddress is straightforward to use and integrate into Python scripts.

Consider using usaddress to parse addresses with Python

usaddress is a Python library for parsing and labeling United States addresses. It can recognize and classify the different parts of an address, such as the street number, street name, city, state, and ZIP code, and return the address in a standardized format.

To use usaddress, you will need to install the library and its dependencies using pip or another package manager. Then, you can import the usaddress module and use the parse() function to parse an address.

Here is an example of how you can use usaddress to parse and label an address in Python:

import usaddress

# Parse and label an address
address = "123 Main St, Anytown, USA 12345"
parsed_address = usaddress.parse(address)

# Print the parsed address
print(parsed_address)

This code will parse the address “123 Main St, Anytown, USA 12345” and print the result, which will be a dictionary with the different parts of the address as keys and the labels for those parts as values. The output will look something like this:

{'AddressNumber': '123', 'StreetName': 'Main', 'StreetNamePostType': 
'St', 'PlaceName': 'Anytown', 'StateName': 'USA', 'ZipCode': '12345'}

You can access the individual parts of the address by using the keys of the dictionary, such as parsed_address['AddressNumber'] or parsed_address['StateName']. You can also use the tag() function to label the address parts in a different format, such as a list of tuples or a string.

Here is an example of how you can use the tag() function to label the address parts in a different format:

import usaddress

# Parse and label an address
address = "123 Main St, Anytown, USA 12345"
parsed_address = usaddress.parse(address)

# Label the address parts as a list of tuples
tagged_address = usaddress.tag(parsed_address)

# Print the tagged address
print(tagged_address)

This code will parse the address and label the parts using the tag() function, which will return the address as a list of tuples. The output will look something like this:

[('123', 'AddressNumber'), ('Main', 'StreetName'), 
('St', 'StreetNamePostType'), ('Anytown', 'PlaceName'), 
('USA', 'StateName'), ('12345', 'ZipCode')]

You can use the usaddress library to parse and label a variety of different address formats, including addresses with apartment or suite numbers, directional prefixes or suffixes, and street types. You can also customize the behavior of the library by setting various options, such as the abbreviation style or the handling of ambiguous addresses.

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