--- myst: html_meta: description: >- Handling whenever's DST and footgun warnings: turning them into errors, suppressing specific calls, pytest configuration, and choosing an approach. --- (warnings)= # Handling warnings `whenever` emits warnings when operations may produce incorrect results, for example due to DST transitions, missing context, or field-wise composition of calendar units. This is intentional: the operations are classic "footguns", but forbidding them entirely would be too strict. Warnings are an ideal mechanism to ensure the potential issues don't pass unnoticed. All `whenever` warnings are subclasses of {class}`~whenever.WheneverWarning`, which is itself a subclass of Python's built-in {class}`UserWarning `. DST-related warnings are grouped under {class}`~whenever.PotentialDstBugWarning`. They fit into Python's standard [`warnings` infrastructure](https://docs.python.org/3/library/warnings.html) fully, giving you several levels of control. ```text UserWarning (stdlib) └── WheneverWarning ├── CalendarUnitCompositionWarning ├── PotentialDstBugWarning │ ├── DaysAssumed24HoursWarning │ ├── NaiveArithmeticWarning │ └── StaleOffsetWarning └── WheneverDeprecationWarning ``` ## Turn warnings into errors For production code, **turn whenever's warnings into exceptions** as early as possible — typically in your module's setup or at the top of your application entry point: ```python import warnings import whenever warnings.filterwarnings("error", category=whenever.WheneverWarning) ``` If you only want to target DST-related warnings: ```python warnings.filterwarnings("error", category=whenever.PotentialDstBugWarning) ``` Any code that triggers a matching warning now raises an exception immediately, forcing you (or your CI) to address it. This is the same principle as `PYTHONWARNINGS=error` but scoped to `whenever`'s warning hierarchy only. To target a specific warning type instead: ```python # Only error on timezone-unaware arithmetic (PlainDateTime): warnings.filterwarnings("error", category=whenever.NaiveArithmeticWarning) # Only error on potentially stale offset operations (OffsetDateTime): warnings.filterwarnings("error", category=whenever.StaleOffsetWarning) ``` ### In pytest When running tests, it's highly recommended to turn `whenever` warnings into errors so tests catch potential issues. Add this to your `pytest.ini` (or the `[tool.pytest.ini_options]` table in `pyproject.toml`): ```ini [pytest] filterwarnings = error::whenever.WheneverWarning ``` Or to target only one module of your project (leaving third-party libraries unaffected): ```ini [pytest] filterwarnings = error::whenever.WheneverWarning:mymodule.* ``` ```{admonition} Command-line filter not supported :class: warning Unfortunately, passing `PYTHONWARNINGS=error::whenever.WheneverWarning` on the command line does **not** work, due to a [limitation in CPython](https://github.com/python/cpython/issues/66733): the command-line filter only accepts built-in warning classes by name, not third-party ones. Use `pytest.ini`, `pyproject.toml`, or a call to `warnings.filterwarnings()` in your code instead. ``` ### In a specific module You can also apply a filter at the top of a module, so it applies to all code in that module without touching other modules: ```python # mymodule/scheduling.py import warnings import whenever warnings.filterwarnings( "error", category=whenever.WheneverWarning, module=r"mymodule\.scheduling" # or re.escape(__name__) ) ``` ## Suppress specific calls Sometimes an operation is deliberately imprecise — and that's fine, as long as the decision is conscious and documented. Each method that may emit a DST-related warning accepts a boolean keyword argument that suppresses it: | Keyword argument | Suppresses | Used on | |---|---|---| | `days_assumed_24h_ok=True` | {class}`~whenever.DaysAssumed24HoursWarning` | {class}`~whenever.TimeDelta` methods, {class}`~whenever.Instant` `add`/`subtract` | | `stale_offset_ok=True` | {class}`~whenever.StaleOffsetWarning` | {class}`~whenever.OffsetDateTime` methods | | `naive_arithmetic_ok=True` | {class}`~whenever.NaiveArithmeticWarning` | {class}`~whenever.PlainDateTime` methods | | `cal_unit_composition_ok=True` | {class}`~whenever.CalendarUnitCompositionWarning` | {class}`~whenever.ItemizedDelta` and {class}`~whenever.ItemizedDateDelta` `add`/`subtract` | For example: ```python from whenever import PlainDateTime # Naive arithmetic is acceptable here because next_departure = scheduled.add(hours=1, naive_arithmetic_ok=True) ``` The keyword argument documents the decision at the call site while keeping the suppression limited to exactly one operation. ```{note} These keyword arguments supersede the ``ignore_dst`` keyword argument (deprecated in 0.10). ``` ### Operators The `+` and `-` operators always emit warnings when applicable, because operators cannot accept keyword arguments. Use the method equivalents instead: - `dt + delta` → `dt.add(delta, ...)` - `dt - delta` → `dt.subtract(delta, ...)` - `dt_a - dt_b` → `dt_a.difference(dt_b)` (for {class}`~whenever.PlainDateTime`, pass `naive_arithmetic_ok=True`) For itemized-delta composition, operators emit {class}`~whenever.CalendarUnitCompositionWarning` when either operand contains nonzero calendar units. Exact-only composition does not warn. Use the method form if you want to pass `cal_unit_composition_ok=True` instead of relying on a global warning filter. Alternatively, suppress operator warnings with Python's standard {func}`warnings.filterwarnings`. ## Using Python's warnings infrastructure Since `whenever` warnings are standard Python warnings, you can also suppress them with {class}`warnings.catch_warnings`: ```python import warnings import whenever with warnings.catch_warnings(): warnings.simplefilter("ignore", whenever.StaleOffsetWarning) # ... all stale-offset warnings suppressed inside this block ``` This is useful when you want to blanket-suppress warnings for a block of code or for operators (which can't take keyword arguments). ```{admonition} Limitation before Python 3.14 :class: warning Before Python 3.14, {class}`warnings.catch_warnings` is **not context-safe**: in concurrent code (threads or async tasks) the suppression filter may leak to other contexts, or other contexts may interfere with yours. This is a [known CPython limitation](https://docs.python.org/3/library/warnings.html#warning-filter) addressed by the ``PYTHON_CONTEXT_AWARE_WARNINGS`` flag introduced in Python 3.14. The per-method keyword arguments described above don't have this limitation — they suppress the warning for exactly one call, regardless of concurrency. ``` ## Exploratory use and scripts When hacking around or writing a quick script, you may simply want to silence all `whenever` warnings globally and move on: ```python import warnings import whenever warnings.filterwarnings("ignore", category=whenever.WheneverWarning) ``` This is fine for exploration. If you later promote the code to production, revisit the suppressed warnings and decide for each one whether to fix the underlying issue or suppress it explicitly with the appropriate keyword argument. ## Choosing the right approach | Situation | Recommended approach | |---|---| | Production code | `filterwarnings("error", ...)` at startup | | CI / test suite | `filterwarnings = error::whenever.WheneverWarning` in `pytest.ini` | | One intentional imprecision | Per-method kwarg (e.g. `naive_arithmetic_ok=True`) + a comment | | Suppress operator warnings | `warnings.catch_warnings()` block (Python ≥ 3.14 for concurrency safety) | | Entire module intentionally imprecise | `filterwarnings("ignore", ..., module=r"mymodule\.*")` | | Exploratory scripts | `filterwarnings("ignore", ...)` globally |