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$ egrep 'a.*e.*i.*o.*u' /usr/share/dict/words
abietineous
abstemious
abstemiously
abstemiousness
abstentious
acetabuliferous
acetarious
acheilous
acheirous

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Location Data Importer

Location Data Importer is a scala application that imports Ordinance Survey data into a mongo database. Primarily it is used to back the locate-api which provides address and local authority lookups from postcode / GSS Code.

The code is under an MIT license, see LICENSE.

Data

This is backed by two Ordinance Survey products:

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Metadata

• https://github.com/openregister/registry-data/blob/master/data/register/location.yaml
• https://github.com/openregister/registry-data/blob/master/data/field/location.yaml
• https://github.com/openregister/registry-data/blob/master/data/field/point.yaml
• https://github.com/openregister/registry-data/blob/master/data/datatype/point.yaml

Data

• https://raw.githubusercontent.com/openregister/food-data/master/ratings/data/location.tsv

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Verifying that +psd is my blockchain ID. https://onename.com/psd

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Hack script to convert a PDF of Tiers 2 and 5 sponsors into a tab-separated value format file, reproduced here under the terms of the Open Government Licence and loaded as a Google Doc.

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$ tiddlywiki test --init server

.. created test/tiddlers/$__sidebar.tid

$ tiddlywiki test --server

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9715c9715
< "{AFC934E1-B31A-473B-960C-0309094FE2E3}","106000","1995-01-09 00:00","SW11 3BL","F","N","F","533","FLAT ABOVE SHOP","BATTERSEA PARK ROAD","LONDON","LONDON","WANDSWORTH","GREATER LONDON","A"
---
> "{AFC934E1-B31A-473B-960C-0309094FE2E3}","106000","1995-01-09 00:00","SW11 3BL","F","N","F","533A","","BATTERSEA PARK ROAD","","LONDON","WANDSWORTH","GREATER LONDON","A"
25601c25601
< "{1FB96B78-6395-4C6F-9A7C-F1D8ABC78EB6}","65000","1995-01-20 00:00","NR14 7SX","S","N","F","22","","CAWSTONS MEADOW","PORINGLAND","NORWICH","SOUTH NORFOLK","NORFOLK","A"
---
> "{1FB96B78-6395-4C6F-9A7C-F1D8ABC78EB6}","65000","1995-01-20 00:00","NR14 7SX","D","N","F","22","","CAWSTONS MEADOW","PORINGLAND","NORWICH","SOUTH NORFOLK","NORFOLK","A"
44146a44147
> "{CEB111BB-7F11-49D6-BE3A-61998E3B084F}","37500","1995-01-31 00:00","CB7 4TQ","S","N","F","2","","MILE END CROSSING","PRICKWILLOW","ELY","EAST CAMBRIDGESHIRE","CAMBRIDGESHIRE","A"

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One CSV, thirty stories

I hit something of an impasse blogging here of late. A number of colleagues in a similar position have used the 30 days song challenge to unblock their blogs with some success, and I thought I’d try to do something similar, but different.

So I’ve picked out a single CSV file, the list of price paid for property from The Land Registry, and each day over the next month I’ll use it to tell small stories about open data and visualisations. Thirty is a nice round number and at this point seems almost unachievable and definitely a challenge.

The code for these articles are open source, natch, and I’ll build a portfolio site as we go along.

_Something of a disclaim

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### Keybase proof

I hereby claim:

  * I am psd on github.
  * I am psd (https://keybase.io/psd) on keybase.
  * I have a public key whose fingerprint is 1C76 88BC 706A 353B 0CAD  D260 C78B 6F27 E1EE 3052

To claim this, I am signing this object:

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#!/usr/bin/env python
from bs4 import BeautifulSoup
from json import JSONEncoder

def xml2json(text):
    xml = BeautifulSoup(text, 'xml')
    #print xml.prettify()

    title = {
        'title_number': xml.TitleNumber.string