Generate fake data conforming to a Table Schema
Project description
Generate tabular fake data conforming to a Table Schema
Usage
# Installation
$ pip3 install tsfaker
# Usage
$ tsfaker https://gitlab.com/healthdatahub/tsfaker/raw/master/tests/schemas/implemented_types.json --nrows 3 --pretty
string number integer date datetime year yearmonth
0 QZluRNRoaJ 8524064526.189381 5603365028 1918-06-09 1963-02-25T15:27:14 1927 1968-03
1 OAXCFryYDVMWmRTnP 8084094810.096195 -9782888534 1995-06-06 1924-06-14T07:41:59 1928 1929-02
2 -6416720321.04726 -1060427558 2006-12-11 2002-12-25T07:41:47 1999 1914-11
Goals
We aim to generate fake data conforming to a schema.
We do not aim to generate realistic data with statistical information (see related work).
Implementation steps
Generate data conforming to types
Generate data conforming to formats and constraints, such as min/max, enum, missing values, unique, length, and regex
Generate multiple tables conforming to foreign key references, with optional tables’ data provided through csv
API
We want to provide both a Python API and a command line API
Development methodology
We will conform to Test Driven Development methodology, hence writing test before writing implementation.
We want generated data to be valid when using goodtables.
We could go by conforming to more and more content checks, which are included in table-schema specification.
Project details
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