ugrc-sweeper 2.0.2

CLI tool for making good data

ugrc-sweeper

The data cleaning service.

Available Sweepers

Addresses

Checks that addresses have minimum required parts and optionally normalizes them.

Duplicates

Checks for duplicate features.

Empties

Checks for empty geometries.

Metadata

Checks to make sure that the metadata meets the Basic SGID Metadata Requirements.

Tags

Checks to make sure that existing tags are cased appropriately. This mean that the are title-cased other than known abbreviations (e.g. UGRC, BLM) and articles (e.g. a, the, of).

This check also verifies that the data set contains a tag that matches the database name (e.g. SGID) and the schema (e.g. Cadastre).

--try-fix adds missing required tags and title-cases any existing tags.

Summary

Checks to make sure that the summary is less than 2048 characters (a limitation of AGOL) and that it is shorter than the description.

Description

Checks to make sure that the description contains a link to a data page on gis.utah.gov.

Use Limitations

Checks to make sure that the text in this section matches the official text for UGRC.

--try-fix updates the text to match the official text.

Parsing Addresses

This project contains a module that can be used as a standalone address parser, sweeper.address_parser. This allows developer to take advantage of sweepers advanced address parsing and normalization without having to run the entire sweeper process.

Usage Example

from sweeper.address_parser import Address

address = Address('123 South Main Street')
print(address)

'''
--> Parsed Address:
{'address_number': '123',
 'normalized': '123 S MAIN ST',
 'prefix_direction': 'S',
 'street_name': 'MAIN',
 'street_type': 'ST'}
'''

Available Address class properties

All properties default to None if there is no parsed value.

address_number

address_number_suffix

prefix_direction

street_name

street_direction

street_type

unit_type

unit_id If no unit_type is found, this property is prefixed with # (e.g. # 3). If unit_type is found, # is stripped from this property.

city

zip_code

po_box The PO Box if a po-box-type address was entered (e.g. po_box would be 1 for p.o. box 1).

normalized A normalized string representing the entire address that was passed into the constructor. PO Boxes are normalized in this format PO BOX <number>.

Installation (requires Pro 2.7+)

1. clone arcgis conda environment
   • conda create --name sweeper --clone arcgispro-py3
2. activate environment
   • activate sweeper
3. install sweeper
   • pip install ugrc-sweeper
4. Optionally duplicate config.sample.json as config.json in the folder where you will run sweeper.

[!CAUTION] This is required for the following functions:

• --scheduled argument (required for sending emails)
• --change-detect argument
• using user-specific connection files via the CONNECTIONS_FOLDER config value

Exclusions

Tables can be skipped by adding values to the EXCLUSIONS.<sweeper_key> config array. These values are matched against table names using fnmatch. Note that these do not apply when using the --table-name argument.

Development

1. clone arcgis conda environment
   • conda create --name sweeper --clone arcgispro-py3
2. activate environment
   • activate sweeper
3. install required dependencies to work on sweeper
   • pip install -e ".[tests]"
4. test_metadata.py uses a SQL database that needs to be restored via src/sweeper/tests/data/Sweeper.bak to your local SQL Server.
5. run sweeper: sweeper
6. test: pytest
7. lint: ruff check .
8. format: ruff format .