typepy: Runtime Type Checker, Validator, and Converter

1.3.4 · active · verified Thu Apr 09

typepy is a Python library for variable type checking, validation, and conversion at runtime. As of version 1.3.4, it supports Python 3.9 and newer. It maintains an active release cadence, with several minor updates per year addressing compatibility, new Python versions, and bug fixes.

Warnings

breaking Support for Python 3.7 and 3.8 was dropped in version 1.3.3. Ensure your environment uses Python 3.9 or newer.
Fix: Upgrade your Python interpreter to version 3.9 or a later compatible version.
breaking The `Binary` type class was renamed to `Bytes` in version 1.1.0 to align with Python 3's `bytes` type. Usage of `Binary` will result in an `AttributeError`.
Fix: Replace all instances of `typepy.Binary` with `typepy.Bytes`.
breaking Support for Python 3.6 was dropped in version 1.3.1. `typepy` now requires Python 3.7 (or later, as of 1.3.3).
Fix: Upgrade your Python interpreter to version 3.7 or a later compatible version (preferably 3.9+ for current versions).
gotcha When performing type conversions, `convert()` will raise a `typepy.TypeConversionError` on failure, while `try_get()` allows specifying a `default_value` to return instead of raising an error.
Fix: Use `Type(...).try_get(Type.TARGET_TYPE, default_value=...)` when you want to gracefully handle conversion failures with a fallback. Use `Type(...).convert()` (or specific type class `.convert()`) when you expect strict conversion or want to catch and handle specific conversion errors.

Install

pip install typepy Install typepy

Imports

Type
```
import typepy
tc = typepy.Type(...)
```
The primary class for generic type handling and conversion with constants like Type.INTEGER.

String

from typepy import String
s = String(' value ')

Integer

from typepy import Integer
i = Integer('123')

DateTime
```
from typepy import DateTime
dt = DateTime('2023-01-01')
```
Specific type classes are available for direct use when precise type handling is needed.

Quickstart

This example demonstrates how to use the `typepy.Type` class for generic type handling and conversion, including providing default values for `None`. It also shows the usage of specific type classes like `typepy.String` and `typepy.Integer` for more focused operations and how to handle potential conversion errors.

import typepy

# Generic type checking and conversion
tc = typepy.Type('100')
print(f"Converted '100' to integer: {tc.try_get(typepy.Type.INTEGER)}")

tc_none = typepy.Type(None)
print(f"Converted None to string with default: {tc_none.try_get(typepy.Type.STRING, default_value='a')}")

# Using specific type classes
str_value = typepy.String('  hello  ').strip()
print(f"Stripped string: '{str_value}'")

int_value = typepy.Integer('1,234').convert()
print(f"Converted '1,234' to integer: {int_value}")

try:
    # Conversion without try_get will raise an error on failure
    invalid_int = typepy.Integer('abc').convert()
    print(f"Converted 'abc' to integer: {invalid_int}")
except typepy.TypeConversionError as e:
    print(f"Error converting 'abc' to integer: {e}")

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