README.md

kohi

A powerfull schema validator

Instalation

Via Poetry:

poetry add kohi

Via PIP:

pip install kohi

Via GitHub (recommended only in dev env):

git clone https://github.com/natanfeitosa/kohi.git && cd kohi && pip install .

Quickstart

To validate a type you can import your schema validator from kohi or from kohi.<type> import <type>Schema

e.g.

Let's check if a person's date of birth is a positive integer less than the current date — 2023 — and greater than or equal to 2005

from kohi import NumberSchema
# from kohi.number import NumberSchema

n = NumberSchema().int().positive().lt(2023).gte(2005)

print(n.validate(2005)) # True
print(n.validate(2022)) # True
print(n.validate(2004)) # False
print(n.validate(2023)) # False

# You can see the errors generated in the last `validate` call just by accessing the `errors` property
# print(n.errors) # ['number must be less than 2022']

Validators

• kohi.base.BaseSchema

Only one base class for all schema validators

• kohi.number.NumberSchema

or kohi.NumberSchema

• kohi.string.StringSchema

or kohi.StringSchema

• kohi.enum.EnumSchema

or kohi.EnumSchema

• kohi.dictionary.DictSchema

or kohi.DictSchema

Methods

BaseSchema

• add_validator(name, func): Self

  Add a custom data validator

• validate(data): bool

  The method to be called when we validate the schema

• reset(): None

  Reset error list

• throw(): Self

  By default no errors are thrown, but when this method is chained a ValidationError will be thrown

• add_mutation(): Self

  Add a mutation function than will run after the validate method. P.S. Will only be executed in the parse method

• parse(data): typeof data

  Run the validate method, the mutations and return a deep clone of data

• default(data): Self

  Set a default value for when the validator receives None and you don't want to generate an error

• optional(): Self

  Allow values None

• required(error_message=None): Self

  Mark the schema as required. Does not allow values None

NumberSchema

inherits from BaseSchema

By default validates int and float

• float(): Self

  Validate only float

• int(): Self

  Validate only int

• lt(num): Self

  Validates if the data is less than num

• gt(num): Self

  Validates if the data is greater than num

• lte(num): Self

  Validates if the data is less than or equal to num

• gte(num): Self

  Validates if the data is greater than or equal to num

• min(num): Self

  Just an alias for gte(num)

• max(num): Self

  Just an alias for lte(nun)

• positive(): Self

  Just an alias for gt(0)

• negative(): Self

  Just an alias for lt(0)

• nonpositive(): Self

  Just an alias for lte(0)

• nonnegative(): Self

  Just an alias for gte(0)

StringSchema

inherits from BaseSchema

• min(min_length): Self

  Validate if the data len is greater than or equal to min_length

• length(length): Self

  Validate if the data len equal to length

• max(max_length): Self

  Validate if the data len is less than or equal to max_length

• url(): Self

  Validate if the data is an url

• uuid(): Self

  Validate if the data is a valid uuid

• starts_with(text): Self

  Validate if the data starts with text

• ends_with(text): Self

  Validate if the data ends with text

EnumSchema

inherits from BaseSchema

• one_of(opts): Self

  Validate if the data is in opts

• not_one_of(opts): Self

  Validate that data is different from the values in opts

DictSchema

inherits from BaseSchema

• props(**props): Self

  Defines the structure of the dictionary in the format [key]: ClassValidator

Dev env

• install development dependencies
• check types using mypy
• run all tests using pytest