An API client (usable as a command-line script or as a Python library) for exporting dataset metadata from CKAN sites to Excel-compatible CSV files.
To install run:
pip install ckanapi-exporter
ckanapi-exporter --url 'http://demo.ckan.org' \
--column "Title" --pattern '^title$' > output.csv
This searches each dataset on demo.ckan.org for fields matching the
regular expression
^title$
(the --pattern
argument) and puts the values into a
column called "Title" in the CSV file (the --column
argument). It'll create
an output.csv
file something like this:
Title |
---|
Senior Salaries Information |
Demo Data for Open Data in 1 Day - Spending Over £500 |
UK Cat Burglaries |
... |
You can add as many columns as you want: just add a --column
and a
--pattern
argument for each column. The title of the column in the CSV file
can be anything you want - it doesn't have to match the name of the field in
CKAN. Let's add a second column titled "Rights" that contains the
license_title
fields from the datasets:
ckanapi-exporter --url 'http://demo.ckan.org' \
--column "Title" --pattern '^title$' \
--column "Rights" --pattern '^license_title$' > output.csv
Title | Rights |
---|---|
Senior Salaries Information | Creative Commons Attribution |
Demo Data for Open Data in 1 Day - Spending Over £500 | Creative Commons CCZero |
UK Cat Burglaries | UK Open Government Licence (OGL) |
... | ... |
You can apply certain transformations to the values from the datasets.
For example, let's add a third column with the first 50 characters of each
dataset's description (the notes
field in the CKAN API):
ckanapi-exporter --url 'http://demo.ckan.org' \
--column "Title" --pattern '^title$' \
--column "Rights" --pattern '^license_title$' \
--column "Description" --pattern '^notes$' --max-length 50 > output.csv
Title | Rights | Description |
---|---|---|
Senior Salaries Information | Creative Commons Attribution | Demo information about senior salaries from 11/04/ |
Demo Data for Open Data in 1 Day - Spending Over £500 | Creative Commons CCZero | Data on spending over £500 generated for Open Data |
UK Cat Burglaries | UK Open Government Licence (OGL) | A record of cat burgalries, listing the cat names, |
... | ... | ... |
Let's add a column containing the formats of each datasets' resources:
ckanapi-exporter --url 'http://demo.ckan.org' \
--column "Title" --pattern '^title$' \
--column "Rights" --pattern '^license_title$' \
--column "Description" --pattern '^notes$' --max-length 50 \
--column Formats --pattern '^resources$' '^format$' > output.csv
This time the pattern has two arguments: --pattern '^resources$' '^format$'
.
This means find the "resources" field of each dataset and then find the
"format" field of each resource. When a dataset has more than one resource
the formats will be combined into a quoted, comma-separated list in a single
table cell. It'll create a CSV file something like this:
Title | Rights | Description | Formats |
---|---|---|---|
Senior Salaries Information | Creative Commons Attribution | Demo information about senior salaries from 11/04/ | XLSX, CSV |
Demo Data for Open Data in 1 Day - Spending Over £500 | Creative Commons CCZero | Data on spending over £500 generated for Open Data | CSV, CSV, CSV, CSV |
UK Cat Burglaries | UK Open Government Licence (OGL) | A record of cat burgalries, listing the cat names, | JPEG, CSV, CSV |
... | ... | ... | ... |
CSV is repeated a lot because lots of the datasets have multiple CSV resources.
You can add the --deduplicate
option to the column to remove the duplication:
ckanapi-exporter --url 'http://demo.ckan.org' \
--column "Title" --pattern '^title$' \
--column "Rights" --pattern '^license_title$' \
--column "Description" --pattern '^notes$' --max-length 50 \
--column Formats --pattern '^resources$' '^format$' --deduplicate \
> output.csv
Title | Rights | Description | Formats |
---|---|---|---|
Senior Salaries Information | Creative Commons Attribution | Demo information about senior salaries from 11/04/ | XLSX, CSV |
Demo Data for Open Data in 1 Day - Spending Over £500 | Creative Commons CCZero | Data on spending over £500 generated for Open Data | CSV |
UK Cat Burglaries | UK Open Government Licence (OGL) | A record of cat burgalries, listing the cat names, | JPEG, CSV |
... | ... | ... | ... |
Let's add a column with the values of the "Next Update" extra from each dataset. Dataset publishers have been inconsistent with naming this column, it's sometimes "Next Update" and sometimes "next update", "Next update day", "Next Update Time" etc. We'll use a regular expression that matches all of these possible names and combine them into a single "Next Update" column:
ckanapi-exporter --url 'http://demo.ckan.org' \
--column "Title" --pattern '^title$' \
--column "Rights" --pattern '^license_title$' \
--column "Description" --pattern '^notes$' --max-length 50 \
--column Formats --pattern '^resources$' '^format$' --deduplicate \
--column "Next Update" --pattern '^extras$' '^next update.*' --unique \
> output.csv
The two-part pattern '^extras$' '^next update.*'
means to look in the
"extras" field of each dataset for extras whose name matches
^next update.*
. We're expecting each dataset to have only one matching
extra so we add the --unique
argument which will crash if a dataset has more
than one extra matching the pattern.
By default patterns are matched case-insensitively and whitespace is stripped
from field names before matching. To match case-sensitively and without
stripping whitespace add --case-sensitive --strip false
to the column.
We can also find multiple extras and combine them into a single column. For example, let's say our datasets have a "contributor" extra (sometimes spelled "contributor", sometimes "Contributor"). Some datasets have multiple extras named "Contributor 1", "Contributor 2" etc. We can find all of these contributor extras and combine them into a single quoted, comma-separated list with a pattern like this:
--column Contributors --pattern '^extras$' '^contributor.*'
You can specify your columns in a columns.json
file instead of on the command
line. Here's an example of the format:
{
"Data Owner": {
"pattern": "^author$",
"unique": true,
"case_sensitive": true
},
"Delivery Unit": {
"pattern": ["^extras$", "^Delivery Unit$"],
"unique": true
},
"Contributor": {
"pattern": ["^extras$", "^Contributor.*"]
},
"Description": {
"pattern": "^notes$",
"unique": true,
"case_sensitive": true,
"max_length": 255
},
"Format": {
"pattern": ["^resources$", "^format$"],
"case_sensitive": true,
"deduplicate": true
}
}
Then tell ckanapi-exporter to read the column options from this file instead of giving them on the command line:
ckanapi-exporter --url 'http://demo.ckan.org' --columns columns.json > output.csv
For a working example columns.json
file that you can use against demo.ckan.org,
see test_columns.json.
ckanapi-exporter is a thin wrapper around
losser, hooking it up to the CKAN API.
For more documentation of the filtering and transforming options run
ckanapi-exporter --help
or read losser's docs.
You can also import ckanapi-exporter in Python and use it from your CKAN API client or plugin:
import ckanapi_exporter.exporter as exporter
csv_string = exporter.export('http://demo.ckan.org', 'columns.json')
Returns a UTF8-encoded string.
The second argument can be either the filename of the columns.json file as a string, or a list of dictionaries (equivalent to the contents of columns.json file after loading the JSON).
To install for development, create and activate a Python virtual environment then do:
git clone https://github.com/ckan/ckanapi-exporter.git
cd ckanapi-exporter
python setup.py develop
pip install -r dev-requirements.txt
To run the tests do:
nosetests