validate data stored in CSV, PRN, ODS or Excel files
Cutplace is a tool and API to validate that tabular data stored in CSV, Excel, ODS and PRN files conform to a cutplace interface definition (CID).
As an example, consider the following customers.csv file that stores data about customers:
customer_id,surname,first_name,born,gender 1,Beck,Tyler,1995-11-15,male 2,Gibson,Martin,1969-08-18,male 3,Hopkins,Chester,1982-12-19,male 4,Lopez,Tyler,1930-10-13,male 5,James,Ana,1943-08-10,female 6,Martin,Jon,1932-09-27,male 7,Knight,Carolyn,1977-05-25,female 8,Rose,Tammy,2004-01-12,female 9,Gutierrez,Reginald,2010-05-18,male 10,Phillips,Pauline,1960-11-09,female
A CID can describe such a file in an easy to read way. It consists of three sections. First, there is the general data format:
Next there are the fields stored in the data file:
Optionally you can describe conditions that must be met across the whole file:
|C||customer must be unique||IsUnique||customer_id|
The CID can be stored in common spreadsheet formats, in particular Excel and ODS, for example cid_customers.ods.
Cutplace can validate that the data file conforms to the CID:
$ cutplace cid_customers.ods customers.csv
Now add a new line with a broken date_of_birth:
Cutplace rejects this file with the error message:
customers.csv (R12C4): cannot accept field ‘date_of_birth’: date must match format YYYY-MM-DD (%Y-%m-%d) but is: ‘04.08.1953’
Additionally, cutplace provides an easy to use API to read and write tabular data files using a common interface without having to deal with the intrinsic of data format specific modules. To read and validate the above example:
import cutplace import cutplace.errors cid_path = 'cid_customers.ods' data_path = 'customers.csv' try: for row in cutplace.rows(cid_path, data_path): pass # We could also do something useful with the data in ``row`` here. except cutplace.errors.DataError as error: print(error)
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