moj-analytical-services / uk_address_matcher
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Repository Overview (README excerpt)
Crawler viewHigh performance UK addresses matcher (geocoder) Fast, simple address matching (geocoding) in Python. For full documentation, see our main documentation site. Why use this library • **Simple.** Setup in seconds, runs on a laptop. No separate infrastructure of services needed. • **Fast.** Match 100,000 addresses in ~30 seconds. • **Proven accuracy.** We use public, labelled datasets to measure and document accuracy. • **Support for Ordnance Survey data.** We provide a automated build pipeline for users wishing to match to Ordnance Survey data. Matching to any other canonical dataset is also supported. The end-to-end process of matching 100,000 addresses to Ordnance Survey data, including all software downloads and data processing takes: • Less than a minute if you are matching to a small area such as a local council region. • If matching to the whole UK, there's a one-time preprocessing step that takes around 10 minutes. Subsequent matching of 100k records takes less than a minute. Installation What does it do? Given the following data: • a "messy" dataset of addresses that you want to match • a "canonical" dataset of known addresses, often an Ordnance Survey dataset such as AddressBase or NGD. this package will find the best matching canonical address for each messy address. Example: Your address files need, at minimum, two columns: and . is optional by recommended. If not provided an attempt is made to parse them out of Given the following data: Messy data | unique_id | address_concat | postcode | |----------|----------------|----------| | m_1 | Flat A Example Court, 10 Demo Road, Townton | AB1 2BC | | ...more rows | Canonical data | unique_id | address_concat | postcode | |----------|----------------|----------| | c_1 | Flat A, 10 Demo Road, Townton | AB1 2BC | | c_2 | Flat B, 10 Demo Road, Townton | AB1 2BC | | c_3 | Basement Flat, 10 Demo Road, Townton | AB1 2BC | | ...more rows | You can match it as follows: Example output: | unique_id | resolved_canonical_id | original_address_concat | original_address_concat_canonical | match_reason | match_weight | distinguishability | |----------|------------------------|-------------------------|-----------------------------------|--------------|--------------|--------------------| | m_1 | c_2 | Flat A Example Court, 10 Demo Road, Townton | Flat A, 10 Demo Road, Townton | splink: probabilistic match | 13.5885 | 11.5033 | Development The scripts and tests will run better if you create .vscode/settings.json with the following: