This project is a (work in progress) tool to take the Ordnance Survey 'Address Base Premium' data and mangle it into a more usable form.
The data is then loaded into a database and provided as an API (Using FastAPI). Finally, a Frontend web app (written in React JS) will allow searching this data by address and return the UPRN and links for Google maps and OpenStreetMap.
The entire project has just had a major rewrite. The original project was started in 2022 and was a bit of a mess. I have learned a lot since then and can improve the codebase significantly.
For a start, the UPRN import process was VERY memory intensive and slow. It took over 12-15Gb of memory and many hours to import the full Scotland data. I have now reduced this to around 2Gb, though I still need to check the timing changes, it is still pretty slow but that is a lot of data.
Dependency management and virtual-environment control is now taken care of by
Poetry
which is a much better fit for the project. I have also added
pre-commit
hooks to ensure code quality and formatting. The latter two are now
handled completely by Ruff
, while Mypy
is used for type checking.
I have also replaced the original Django
and Django Rest Framework
with
FastAPI
and SQLAlchemy 2
. This is a much better fit for the project.
Database access is Async, and the pagination is blindingly fast.
The Frontend has been updated to use Vite
instead of Create React App
. This
is a much faster and more modern build tool.
You will need a PostgreSQL database set up, with a user, password, and dedicated database. The user should have full access to the specified database; It is good practice to create a specific Postgresql user that only has access to this database.
All setup for this project is done in the config.toml
file in the root folder.
An example-config.toml
file is provided. Copy this to config.toml
and edit
the values to match your setup. Make sure to put the correct database details
in.
You can change the api_prefix
to place the API at a different URL. The default
is /api/v2/
so the API will be available at http://localhost:8000/api/v2/
.
Note
The frontend is currently hard-coded to look for the API at the above URL. If you change this, you will need to update the frontend code.
[uprn_mangle]
api_base_url = "http://localhost"
api_port = 8000
api_prefix = "/api/v2"
db_user = "addressbase"
db_password = "mysecurepassword"
db_name = "addressbase"
db_host = "localhost"
db_port = "5432"
db_table = "addressbase"
On your local machine, you need a working copy of Python and Nodejs. I recommend you use Pyenv to manage your Python versions.
Use Poetry
to manage the Python dependencies and Yarn
or npm
for the
JavaScript dependencies.
The data used for this project comes from the AddressBase Premium
( noted as
ABP
from now on) by Ordnance Survey. APB is a commercial product, but
you can apply for a Data Exploration License here. The DEL allows
you to test and use the data in a limited way.
I will assume you have a copy of ABP in CSV format for this App. Copy all
the individual CSV files into the backend/data/raw-csv/
folder.
The data provided by Ordnance Survey is a bit of a mess; that was the original inspiration for this project - to merge/prune/tidy them into a usable format for development.
We also need several other data files that are provided for free by OS on their OpenData pages :
- We need the 'BLPU UPRN Street USRN 11' data from the
OS Open Linked Identifiers
dataset. Download this, unzip and place the CSV file in thebackend/data/cross-ref-csv/
folder. - We need the header files for the ABP data; this allows us to parse the
data automatically. The project already contains the latest header files as
of June 2022, but if any changes cause the scripts to fail, you can
download the latest from OS here. Download this file and replace
all the existing CVS files in the
backend/data/header-files/
folder with those in the zip file
From the root folder, run the following commands:
poetry install
poetry shell
This will install all the required Python dependencies and switch to the virtual environment.
Now, run the following command to set up the database and import the UPRN data:
python uprn_mangle/backend/import_uprn.py
This last part can take a good long time and memory to complete. It is recommended to run this on a machine with a good amount of memory and a fast CPU.
Finally, if this completes successfully, you can start the backend server:
python uprn_mangle/backend/api/main.py
Change to the uprn_mangle/frontend
folder and run the following commands:
yarn install
yarn dev
You can also use npm
if you prefer. This will install all the required
JavaScript dependencies and start the frontend server. You should leave this
running too.
You can now access the Front-end at http://localhost:5173
Important
The above is only useful for development and testing purposes. For production use, you should use a proper web server and reverse proxy setup.
While this is currently just a personal project and at a very early stage, contributions, especially Bug Reports, are very welcome.
- Fork it
- Create your feature branch (
git checkout -b my-new-feature
) - Commit your changes (
git commit -am 'Add some feature'
) - Push to the branch (
git push origin my-new-feature
) - Create a new Pull Request
This project is under the MIT license.
Copyright (c) 2022-2024 Grant Ramsay
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
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copies of the Software, and to permit persons to whom the Software is
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The above copyright notice and this permission notice shall be included in all
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