[Python-Dev] PEP 564: Add new time functions with nanosecond resolution

Ben Hoyt benhoyt at gmail.com
Mon Oct 16 11:37:37 EDT 2017

I've read the examples you wrote here, but I'm struggling to see what the
real-life use cases are for this. When would you care about *both* very
long-running servers (104 days+) and nanosecond precision? I'm not saying
it could never happen, but would want to see real "experience reports" of
when this is needed.


On Mon, Oct 16, 2017 at 9:50 AM, Victor Stinner <victor.stinner at gmail.com>

> I read again the discussions on python-ideas and noticed that I forgot
> to mention the "time_ns module" idea. I also added a section to give
> concrete examples of the precision loss.
> https://github.com/python/peps/commit/a4828def403913dbae7452b4f9b9d6
> 2a0c83a278
> Issues caused by precision loss
> -------------------------------
> Example 1: measure time delta
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> A server is running for longer than 104 days. A clock is read before
> and after running a function to measure its performance. This benchmark
> lose precision only because the float type used by clocks, not because
> of the clock resolution.
> On Python microbenchmarks, it is common to see function calls taking
> less than 100 ns. A difference of a single nanosecond becomes
> significant.
> Example 2: compare time with different resolution
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> Two programs "A" and "B" are runing on the same system, so use the system
> block. The program A reads the system clock with nanosecond resolution
> and writes the timestamp with nanosecond resolution. The program B reads
> the timestamp with nanosecond resolution, but compares it to the system
> clock read with a worse resolution. To simplify the example, let's say
> that it reads the clock with second resolution. If that case, there is a
> window of 1 second while the program B can see the timestamp written by A
> as "in the future".
> Nowadays, more and more databases and filesystems support storing time
> with nanosecond resolution.
> .. note::
>    This issue was already fixed for file modification time by adding the
>    ``st_mtime_ns`` field to the ``os.stat()`` result, and by accepting
>    nanoseconds in ``os.utime()``. This PEP proposes to generalize the
>    fix.
> (...)
> Modify time.time() result type
> ------------------------------
> It was proposed to modify ``time.time()`` to return a different float
> type with better precision.
> The PEP 410 proposed to use ``decimal.Decimal`` which already exists and
> supports arbitray precision, but it was rejected.  Apart
> ``decimal.Decimal``, no portable ``float`` type with better precision is
> currently available in Python.
> Changing the builtin Python ``float`` type is out of the scope of this
> PEP.
> Moreover, changing existing functions to return a new type introduces a
> risk of breaking the backward compatibility even the new type is
> designed carefully.
> (...)
> New time_ns module
> ------------------
> Add a new ``time_ns`` module which contains the five new functions:
> * ``time_ns.clock_gettime(clock_id)``
> * ``time_ns.clock_settime(clock_id, time: int)``
> * ``time_ns.perf_counter()``
> * ``time_ns.monotonic()``
> * ``time_ns.time()``
> The first question is if the ``time_ns`` should expose exactly the same
> API (constants, functions, etc.) than the ``time`` module. It can be
> painful to maintain two flavors of the ``time`` module. How users use
> suppose to make a choice between these two modules?
> If tomorrow, other nanosecond variant are needed in the ``os`` module,
> will we have to add a new ``os_ns`` module as well? There are functions
> related to time in many modules: ``time``, ``os``, ``signal``,
> ``resource``, ``select``, etc.
> Another idea is to add a ``time.ns`` submodule or a nested-namespace to
> get the ``time.ns.time()`` syntax.
> Victor
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