hydrah 0.1.1

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Hydra Validator Library

Hydrah is a validation library for Python that provides a simple and easy way to validate inputs in your applications. With Hydrah, you can validate user inputs, command-line arguments, or configuration files with just a few lines of code.

Features

• Simple and easy to use
• Supports multiple data types (strings, integers, lists, objects, booleans, datetime)
• Can validate inputs and provide detailed error messages
• Provides a coerce method to automatically convert inputs to the desired data type

Installation

h can be installed using pip:

pip install hydrah

Usage

To validate an input, you need to first create a validator instance for the desired data type. For example, to validate a string input:

from hydrah import h

validator = h.string()

if validator.is_valid("hello"):
    print("Valid input")
else:
    print(validator.get_error_message("hello"))

To validate a list of strings:

from hydrah import h

list_validator = h.list()string()

if list_validator.is_valid(["hello", "world"]):
    print("Valid input")
else:
    print(list_validator.get_error_message(["hello", 1]))

To validate an object:

from hydrah import h

object_validator = h.object({
    "name": h.string(),
    "age": h.integer()
})

if object_validator.is_valid({"name": "John", "age": 30}):
    print("Valid input")
else:
    print(object_validator.get_error_message({"name": "John", "age": "30"}))

Custom Validators

Hydrah can also be extended to support custom data types. To create a custom validator, you need to inherit from the Validator class and implement the is_valid and get_error_message methods.

For example, to create a validator for boolean inputs:

from hydrah import Validator

class BooleanValidator(Validator):
    def is_valid(self, value):
        return isinstance(value, bool)

    def get_error_message(self, value):
        return f"Expected boolean, but got {type(value).__name__}"

Coercion

Hydrah also provides a coerce method to automatically convert inputs to the desired data type. For example:

from hydrah import h

validator = h.integer()

value = validator.coerce("10")

print(value) # 10
print(type(value)) # <class 'int'>

Creating Objects with Optional Schemas

In some cases, you may want to define a schema that is optional, meaning that it can either be present or absent in the data. To define an optional schema in Hydrah, you can either use hydrah.h.string().optional() or hydrah.h.optional(hydrah.h.string()).

Here's an example of how you could define an object with an optional string field using both methods:

from hydrah import h
# Using string().optional()
optional_string_validator = h.object({
    "optional_field": h.string().optional()
})

# Using optional(hydrah.h.string())
optional_string_validator = h.object({
    "optional_field": h.optional(hydrah.string())
})

# Both of these validators will accept the following data:
data = {
    "optional_field": "Hello, world!"
}

assert optional_string_validator.is_valid(data)

# And also this data:
data = {}

assert optional_string_validator.is_valid(data)