datetype
A type wrapper for the standard library `datetime` that supplies stricter checks, such as making 'datetime' not substitutable for 'date', and separating out Naive and Aware datetimes into separate, mutually-incompatible types.
Decision gist · record as of 2026-08-14
Yes, if you use a type checker (mypy, pyright) and want stricter datetime type safety. The package is actively maintained, has no known vulnerabilities, and adds minimal friction. It's most valuable in codebases where datetime/date confusion or naive/aware mixing has been a source of bugs. If you don't use static type checking or haven't encountered these issues, it offers no runtime benefit.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction with a single lightweight dependency (typing_extensions).
- The package is actively maintained with recent commits and has been in production status since its first release.
License · maintenance · safety
(unclear) — Licensed under Apache 2.0 with portions under MIT (inherited from typeshed). Both are permissive licenses suitable for most use cases, though the dual-license structure should be reviewed if you have specific compliance requirements.
last release 2025-12-01 (256 days) · last repo commit 2026-02-21 · 97 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 89,530 downloads/mo, #13,653 on PyPI
Alternatives
Verify before relying
pip install datetype
from datetype import Naive, Aware
from datetime import timezone
naive_dt = Naive.now()
aware_dt = Aware.now(timezone.utc)- Whether the type-checking fixes apply to all major type checkers (mypy, pyright, etc.) or only mypy
- Runtime performance impact of the wrapper compared to stdlib datetime
- Compatibility with third-party libraries that expect stdlib datetime instances
What it is and what it does
DateType is a type-checking wrapper for Python's `datetime` module designed to address limitations in how the standard library's datetime types interact with static type checkers. The core issue it solves is that `datetime` objects inherit from `date` at runtime but should not be treated as interchangeable with `date` in type-checked code—a distinction that standard type stubs don't enforce. Additionally, it separates naive (timezone-unaware) and aware (timezone-aware) datetimes into distinct, mutually-incompatible types at the type-checking level, preventing accidental mixing of these fundamentally different datetime representations.
The implementation preserves the runtime behavior of stdlib datetime (instances still inherit as before) while providing separate `Naive` and `Aware` type wrappers and construction methods. It depends only on typing_extensions and supports Python versions from 3.7 through 3.14, making it suitable for projects that need stricter datetime type safety without major runtime overhead or compatibility concerns.
Use it for
- Enforce type-checker rejection of code that passes a datetime where a date is expected, catching a common source of type errors
- Prevent mixing of naive and aware datetimes in the same codebase by making them incompatible at type-check time
- Migrate a large codebase to stricter datetime typing without rewriting datetime construction logic
- Build libraries that need to document and enforce whether they accept only naive or only aware datetimes
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you use a type checker (mypy, pyright) and want stricter datetime type safety.
The package is actively maintained, has no known vulnerabilities, and adds minimal friction. It's most valuable in codebases where datetime/date confusion or naive/aware mixing has been a source of bugs. If you don't use static type checking or haven't encountered these issues, it offers no runtime benefit.
Install
datetype on PyPI
Before you install
Low install friction with a single lightweight dependency (typing_extensions). The package is actively maintained with recent commits and has been in production status since its first release.
License in practice
Licensed under Apache 2.0 with portions under MIT (inherited from typeshed). Both are permissive licenses suitable for most use cases, though the dual-license structure should be reviewed if you have specific compliance requirements.
Quickstart
pip install datetype
from datetype import Naive, Aware
from datetime import timezone
naive_dt = Naive.now()
aware_dt = Aware.now(timezone.utc)Verify before relying
- Whether the type-checking fixes apply to all major type checkers (mypy, pyright, etc.) or only mypy
- Runtime performance impact of the wrapper compared to stdlib datetime
- Compatibility with third-party libraries that expect stdlib datetime instances
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagetyping_extensions |
| Maintenance | Actively maintained 256 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 89,530 / month, #13,653 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 :: DevelopersProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: datetype-2025.11.30-py3-none-any.whl
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See also whenever · phantom-types · SQLAlchemy-Utc · iso8601 · aniso8601 · DateTime · types-DateTimeRange · types-dataclasses · freezegun · delorean