an elegant datasets factory
Project description
an elegant datasets factory
Free software: MIT license
Documentation: https://rawbuilder.readthedocs.io.
Features
Schema oriented datasets builder
How to Use it
Terminal:
# Import the package into any python app import rawbuilder
# Init the dataset object as ds ds = rawbuilder.DataSet(size=1000,task=’user’)
# Build the dataset ds.build()
# Get the schema location to edit with any IDE ds.schema_location
Schema
The Schema is a JSON object that describes three main components.
The model names, the column names, and the data source per column.
Note the below code-block, The model name is “Student”, and it contain 4 properties [id,first_name,email,math_test_results].
Each property of the model “student” has its data source description.
The builder will use all the information in the schema to build the required tasks or data sets.
Student data model example:
- “student”: {
“id”: “int”, “first_name”: “first_name”, “last_name”: “last_name”, “email”: “email”, “math_test_results”: “random_int between,0,30”}
Data types to can use in the schema
int: build a list of integers between 1 and requested dataset size.
decrement: build a list of decremented integers between the requested size and 1.
random_int: build a list of random integers between 0 and 100 by default.
first_name: build a list of first names.
last_name: build a list of last names.
email: build a list of fake emails.
Data Modifiers
Combine Data Modifiers to the above data types, it can adjust values, change the data nature, and gives more control over the final output.
Modifiers syntax is simple:
“modifier,argument_1,arg_2,arg_*”
Use the modifier between to generate random integer column between 0 and 30:
“math_test_results”: “random_int between,0,30”
All Modifiers
1) ranges
Use this modifier to set the high-end and low-end for a specific data type
Syntax:
“between,10,1000”
Supported with
random_int:
“math_test_results”: “random_int between,0,30”
History
0.0.4 (2021-11-13)
Data modifiers
0.0.3 (2021-11-05)
Migrate to JSON
Generate simple datasets
0.0.2 (2021-11-05)
Proof of concept
0.0.1 (2021-10-24)
First release on PyPI.
Project details
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