kye 0.0.5

A Data Validation Framework

Kye Validation Tool

Kye is a validation tool in progress that allows you to define and validate models for your data.

Getting Started

Install

pip install kye

Define Models

Models can be defined in either a models.yaml file or a models.kye file. Create your models file in the same directory as your python scripts

Yaml Models

Here is an example of a models.yaml file:

# Define a model for each table
# using the table name as the key
models:
  User:
    # List of indexes means that
    # both `id` and `name` should both be able
    # to uniquely identify a `User`
    indexes:
      - id
      - username
    # Edges are the name and value type of each column
    edges:
      id: Number
      username: String
      name: String
      # Add a `?` to the end of the column name
      # if the value is allowed to be null
      age?: Number
  Post:
    # The `index` field is a shorthand for `indexes`
    # when there is only a single field used to identify a model
    index: id
    edges:
      id: Number
      # Coming soon is the ability to define relationships with other models
      author: User

Kye Models

Here is the same definitions as above, but as a kye script in models.kye

model User(id)(username) {
  id: Number
  username: String
  name: String
  age?: Number
}

model Post(id) {
  id: Number
  author: User
}

Usage in Python

Add the kye.validate('<Model Name>') decorator to your python loading functions and library will throw an error if the return value of your function does not match your defined model.

Right now the validation decorator only works with data that is returned as a list of dictionaries, but support for more data formats like pandas data frames will soon follow.

import requests

import kye

@kye.validate('User')
def get_users():
  return requests.get('/api/v1/users').json()