typepy
typepy is a Python library for variable type checker/validator/converter at a run time.
Decision gist · record as of 2026-08-14
Yes. Typepy is actively maintained, has no known vulnerabilities, carries a permissive MIT license, and installs with minimal friction. It's a focused tool for a common problem—runtime type validation and conversion—and ranks in the top 5000 PyPI packages by download volume. Install it if your code needs to safely check or coerce types at runtime.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later.
- Optional: install typepy[datetime] for DateTime class support.
- Low friction: pure Python wheel with a single runtime dependency (mbstrdecoder).
License · maintenance · safety
MIT License (permissive) — MIT License permits unrestricted use, modification, and distribution with only attribution required—no restrictions on commercial or proprietary use.
last release 2026-05-09 (97 days) · last repo commit 2026-07-20 · 17 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 9,663,651 downloads/mo, #1,510 on PyPI
Alternatives
Verify before relying
pip install typepy
from typepy import Integer, String
# Type check
print(Integer(1).is_type()) # True
print(Integer(1.1).is_type()) # False
# Type conversion
print(Integer("1").convert()) # 1- Whether the package handles edge cases in type coercion (e.g., leading/trailing whitespace in string conversions).
- Performance characteristics when validating large collections or nested structures.
- Behavior of strict_level parameter and how it affects validation across different type classes.
What it is and what it does
Typepy is a runtime type-checking and conversion library that wraps Python's built-in types and adds specialized validators for domains like IP addresses and null strings. It provides three main operations: is_type() to check if a value matches a type class, validate() to raise an exception on mismatch, and convert()/try_convert()/force_convert() to coerce values between types with varying strictness.
The library is useful when you need to enforce or transform types in data pipelines, user input validation, or configuration parsing. It depends only on mbstrdecoder and works across Python 3.9 through 3.14, making it a lightweight addition to projects that handle mixed or uncertain input types.
Use it for
- Validate user input in web forms or APIs before processing (e.g., ensure a field is a valid integer or IP address).
- Convert CSV or JSON data fields to the correct Python type with clear error handling.
- Check and coerce configuration values at application startup.
- Build data pipelines that need to handle heterogeneous input types safely.
- Implement strict type contracts in data validation layers without external schema libraries.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Typepy is actively maintained, has no known vulnerabilities, carries a permissive MIT license, and installs with minimal friction. It's a focused tool for a common problem—runtime type validation and conversion—and ranks in the top 5000 PyPI packages by download volume. Install it if your code needs to safely check or coerce types at runtime.
Install
typepy on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (mbstrdecoder). Actively maintained with a recent release and current Python version support through 3.14.
Requires Python 3.9 or later. Optional: install typepy[datetime] for DateTime class support.
License in practice
MIT License permits unrestricted use, modification, and distribution with only attribution required—no restrictions on commercial or proprietary use.
Quickstart
pip install typepy
from typepy import Integer, String
# Type check
print(Integer(1).is_type()) # True
print(Integer(1.1).is_type()) # False
# Type conversion
print(Integer("1").convert()) # 1Verify before relying
- Whether the package handles edge cases in type coercion (e.g., leading/trailing whitespace in string conversions).
- Performance characteristics when validating large collections or nested structures.
- Behavior of strict_level parameter and how it affects validation across different type classes.
Package facts
| License | MIT License permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagembstrdecoder |
| Maintenance | Actively maintained 97 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 9,663,651 / month, #1,510 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Information TechnologyLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python Modules |
Evidence: typepy-2.0.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “validate variable types at runtime”
- typepyTypepy checks, validates, and converts Python variable types at…
- phantom-typesPhantom types enable you to create type-safe wrappers around base…
- pydantic-settingsLoads and validates application settings from environment variables,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Libraries packages
urllib3 is an HTTP client library that provides thread-safe connection pooling, SSL/TLS verification, multipart file uploads, request retries, compression support, and proxy handling for Python applications.
Requests is a Python HTTP library that simplifies sending HTTP/1.1 requests with automatic handling of headers, authentication, cookies, and response parsing.
Pluggy provides a plugin system that lets you define hook specifications and register implementations to be called in sequence, enabling extensible Python applications without tight coupling.
Install it if you're building an extensible application or framework.
Provides parsing, arithmetic, and recurrence rule computation for dates and times, with timezone support and iCalendar RFC compliance.
Install it if you need to parse flexible date strings, compute relative dates, handle timezones, or work with recurrence rules—it's the de facto choice for these tasks.
Six provides utility functions to write Python code that runs on both Python 2.7 and Python 3.3+, smoothing over language differences between the two versions.
pytest is a testing framework that lets you write test functions using plain assert statements and automatically discovers and runs them, with detailed failure reporting.
See also DataProperty · fastnumbers · typing-validation · validator-collection · phantom-types · msgfy · infinity · type-enforced · types-ipaddress · strongtyping