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Add Control Passing Of Time In Tests as a Python TIL

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jbranchaud
2026-03-14 16:18:36 -05:00
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@@ -10,7 +10,7 @@ working across different projects via [VisualMode](https://www.visualmode.dev/).
For a steady stream of TILs, [sign up for my newsletter](https://visualmode.kit.com/newsletter). For a steady stream of TILs, [sign up for my newsletter](https://visualmode.kit.com/newsletter).
_1756 TILs and counting..._ _1757 TILs and counting..._
See some of the other learning resources I work on: See some of the other learning resources I work on:
@@ -1044,6 +1044,7 @@ If you've learned something here, support my efforts writing daily TILs by
- [Access Most Recent Return Value In REPL](python/access-most-recent-return-value-in-repl.md) - [Access Most Recent Return Value In REPL](python/access-most-recent-return-value-in-repl.md)
- [Break Debugger On First Line Of Program](python/break-debugger-on-first-line-of-program.md) - [Break Debugger On First Line Of Program](python/break-debugger-on-first-line-of-program.md)
- [Check If Package Is Installed With Pip](python/check-if-package-is-installed-with-pip.md) - [Check If Package Is Installed With Pip](python/check-if-package-is-installed-with-pip.md)
- [Control Passing Of Time In Tests](python/control-passing-of-time-in-tests.md)
- [Create A Dummy DataFrame In Pandas](python/create-a-dummy-dataframe-in-pandas.md) - [Create A Dummy DataFrame In Pandas](python/create-a-dummy-dataframe-in-pandas.md)
- [Dunder Methods](python/dunder-methods.md) - [Dunder Methods](python/dunder-methods.md)
- [Easy Key-Value Aggregates With defaultdict](python/easy-key-value-aggregates-with-defaultdict.md) - [Easy Key-Value Aggregates With defaultdict](python/easy-key-value-aggregates-with-defaultdict.md)
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# Control Passing Of Time In Tests
While it is nice to be able to write pure functional code, our software still
lives in the real world and may have to relate to or depend on the passing of
time. In order to test this kind of code, we need time to behave in a reliable,
deterministic way. One of the best ways to create a testing environment where
that is true is to bring in tooling that hijacks time.
The [`freezegun` module](https://github.com/spulec/freezegun) is a great tool
for that job. We can use it to freeze time at a specific testable point, advance
time a specific amount, and much more.
Here is an example from the tests for [my CLI-based time tracking
app](https://github.com/jbranchaud/py-vmt/blob/acb26e4840279d936a12f16c505ca7e75e9a6d20/tests/src/py_vmt/test_cli.py#L21)
where I freeze time before starting a session. That gives me a chance to assert
about the exact start time that is output by the command. Then I can advance
time a little and assert that the `status` command outputs the correct thing.
```python
import datetime
from freezegun import freeze_time
# some other test setup omitted ...
initial_datetime = datetime.datetime(
2026, 3, 14, 15, 5, 11, 0, datetime.timezone.utc
)
with freeze_time(initial_datetime) as frozen_datetime:
# start a session
start_result = runner.invoke(cli, ["start", "my-project"])
output = "Started tracking 'my-project' at 10:05AM"
assert output in start_result.output
frozen_datetime.tick(delta=datetime.timedelta(minutes=30))
# check status
status_result = runner.invoke(cli, ["status"])
output = "Tracking 'my-project' for 30m (since 10:05AM)"
assert output in status_result.output
```