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Description:
address extractor 0.1.0.post1
A script to extract US-style street addresses from a text file
$ address_extractor
1600 Pennsylvania Ave NW, Washington, DC 20500 ^D
1 lines in input
,1600 Pennsylvania Ave NW,Washington DC 20500
$ address_extractor -o output.csv input.csv
4361 lines in input
*snip*
11 lines unable to be parsed
$ ls
output.csv
address_extractor takes text or a text file containing address-like data, one address per line, and parses it into a uniform format with the usaddress package.
Installation
This package is available from PyPi via pip:
pip install address_extractor
This will install the module as well as the command-line script as address_extractor.
Command-line Usage
address_extractor [-h] [-o OUTPUT] [--remove-post-zip] [input]
positional arguments:
input the input file. Defaults to stdin.
optional arguments:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
the output file. Defaults to stdout.
--remove-post-zip, -r
when scanning the input lines, remove everything after
a sequence of 5 digits followed by a comma. The
parsing library used by this script chokes on
addresses containing this kind of information, often a
county name.
Lines that could not be parsed will be printed to STDERR. They can be saved to a file with standard bash redirection techniques:
$ address_extractor -o good_addresses.csv has_some_bad_addresses.txt 2> bad_addresses.txt
Usage as a Module
address_extractor can be used as a Python module:
>>> import address_extractor
>>> address_extractor.main(input=input_file_object, output=output_file_object, remove_post_zip=a_bool)
There are some small issues with this implementation:
If using sys.stdin or sys.stdout for input or output, respectively, the file objects will still be closed. This presents issues trying to use these in the future.
Errored lines are still printed to sys.stderr which may not be expected.
Versions and Stability
This package is uploaded as a 0.1.0 release. There are no tests and little error checking–it originated as a quick-‘n-dirty script and I decided to release it as a package to gain familiarity with that process.
Issues, comments, and pull requests are welcome at the GitHub page!
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Files In This Product:
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