view mercurial/profiling.py @ 31765:264baeef3588

show: new extension for displaying various repository data Currently, Mercurial has a number of commands to show information. And, there are features coming down the pipe that will introduce more commands for showing information. Currently, when introducing a new class of data or a view that we wish to expose to the user, the strategy is to introduce a new command or overload an existing command, sometimes both. For example, there is a desire to formalize the wip/smartlog/underway/mine functionality that many have devised. There is also a desire to introduce a "topics" concept. Others would like views of "the current stack." In the current model, we'd need a new command for wip/smartlog/etc (that behaves a lot like a pre-defined alias of `hg log`). For topics, we'd likely overload `hg topic[s]` to both display and manipulate topics. Adding new commands for every pre-defined query doesn't scale well and pollutes `hg help`. Overloading commands to perform read-only and write operations is arguably an UX anti-pattern: while having all functionality for a given concept in one command is nice, having a single command doing multiple discrete operations is not. Furthermore, a user may be surprised that a command they thought was read-only actually changes something. We discussed this at the Mercurial 4.0 Sprint in Paris and decided that having a single command where we could hang pre-defined views of various data would be a good idea. Having such a command would: * Help prevent an explosion of new query-related commands * Create a clear separation between read and write operations (mitigates footguns) * Avoids overloading the meaning of commands that manipulate data (bookmark, tag, branch, etc) (while we can't take away the existing behavior for BC reasons, we now won't introduce this behavior on new commands) * Allows users to discover informational views more easily by aggregating them in a single location * Lowers the barrier to creating the new views (since the barrier to creating a top-level command is relatively high) So, this commit introduces the `hg show` command via the "show" extension. This command accepts a positional argument of the "view" to show. New views can be registered with a decorator. To prove it works, we implement the "bookmarks" view, which shows a table of bookmarks and their associated nodes. We introduce a new style to hold everything used by `hg show`. For our initial bookmarks view, the output varies from `hg bookmarks`: * Padding is performed in the template itself as opposed to Python * Revision integers are not shown * shortest() is used to display a 5 character node by default (as opposed to static 12 characters) I chose to implement the "bookmarks" view first because it is simple and shouldn't invite too much bikeshedding that detracts from the evaluation of `hg show` itself. But there is an important point to consider: we now have 2 ways to show a list of bookmarks. I'm not a fan of introducing multiple ways to do very similar things. So it might be worth discussing how we wish to tackle this issue for bookmarks, tags, branches, MQ series, etc. I also made the choice of explicitly declaring the default show template not part of the standard BC guarantees. History has shown that we make mistakes and poor choices with output formatting but can't fix these mistakes later because random tools are parsing output and we don't want to break these tools. Optimizing for human consumption is one of my goals for `hg show`. So, by not covering the formatting as part of BC, the barrier to future change is much lower and humans benefit. There are some improvements that can be made to formatting. For example, we don't yet use label() in the templates. We obviously want this for color. But I'm not sure if we should reuse the existing log.* labels or invent new ones. I figure we can punt that to a follow-up. At the aforementioned Sprint, we discussed and discarded various alternatives to `hg show`. We considered making `hg log <view>` perform this behavior. The main reason we can't do this is because a positional argument to `hg log` can be a file path and if there is a conflict between a path name and a view name, behavior is ambiguous. We could have introduced `hg log --view` or similar, but we felt that required too much typing (we don't want to require a command flag to show a view) and wasn't very discoverable. Furthermore, `hg log` is optimized for showing changelog data and there are things that `hg display` could display that aren't changelog centric. There were concerns about using "show" as the command name. Some users already have a "show" alias that is similar to `hg export`. There were also concerns that Git users adapted to `git show` would be confused by `hg show`'s different behavior. The main difference here is `git show` prints an `hg export` like view of the current commit by default and `hg show` requires an argument. `git show` can also display any Git object. `git show` does not support displaying more complex views: just single objects. If we implemented `hg show <hash>` or `hg show <identifier>`, `hg show` would be a superset of `git show`. Although, I'm hesitant to do that at this time because I view `hg show` as a higher-level querying command and there are namespace collisions between valid identifiers and registered views. There is also a prefix collision with `hg showconfig`, which is an alias of `hg config`. We also considered `hg view`, but that is already used by the "hgk" extension. `hg display` was also proposed at one point. It has a prefix collision with `hg diff`. General consensus was "show" or "view" are the best verbs. And since "view" was taken, "show" was chosen. There are a number of inline TODOs in this patch. Some of these represent decisions yet to be made. Others represent features requiring non-trivial complexity. Rather than bloat the patch or invite additional bikeshedding, I figured I'd document future enhancements via TODO so we can get a minimal implmentation landed. Something is better than nothing.
author Gregory Szorc <gregory.szorc@gmail.com>
date Fri, 24 Mar 2017 19:19:00 -0700
parents 22fbca1d11ed
children f40dc6f7c12f
line wrap: on
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# profiling.py - profiling functions
#
# Copyright 2016 Gregory Szorc <gregory.szorc@gmail.com>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.

from __future__ import absolute_import, print_function

import contextlib

from .i18n import _
from . import (
    encoding,
    error,
    util,
)

@contextlib.contextmanager
def lsprofile(ui, fp):
    format = ui.config('profiling', 'format', default='text')
    field = ui.config('profiling', 'sort', default='inlinetime')
    limit = ui.configint('profiling', 'limit', default=30)
    climit = ui.configint('profiling', 'nested', default=0)

    if format not in ['text', 'kcachegrind']:
        ui.warn(_("unrecognized profiling format '%s'"
                    " - Ignored\n") % format)
        format = 'text'

    try:
        from . import lsprof
    except ImportError:
        raise error.Abort(_(
            'lsprof not available - install from '
            'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/'))
    p = lsprof.Profiler()
    p.enable(subcalls=True)
    try:
        yield
    finally:
        p.disable()

        if format == 'kcachegrind':
            from . import lsprofcalltree
            calltree = lsprofcalltree.KCacheGrind(p)
            calltree.output(fp)
        else:
            # format == 'text'
            stats = lsprof.Stats(p.getstats())
            stats.sort(field)
            stats.pprint(limit=limit, file=fp, climit=climit)

@contextlib.contextmanager
def flameprofile(ui, fp):
    try:
        from flamegraph import flamegraph
    except ImportError:
        raise error.Abort(_(
            'flamegraph not available - install from '
            'https://github.com/evanhempel/python-flamegraph'))
    # developer config: profiling.freq
    freq = ui.configint('profiling', 'freq', default=1000)
    filter_ = None
    collapse_recursion = True
    thread = flamegraph.ProfileThread(fp, 1.0 / freq,
                                      filter_, collapse_recursion)
    start_time = util.timer()
    try:
        thread.start()
        yield
    finally:
        thread.stop()
        thread.join()
        print('Collected %d stack frames (%d unique) in %2.2f seconds.' % (
            util.timer() - start_time, thread.num_frames(),
            thread.num_frames(unique=True)))

@contextlib.contextmanager
def statprofile(ui, fp):
    from . import statprof

    freq = ui.configint('profiling', 'freq', default=1000)
    if freq > 0:
        # Cannot reset when profiler is already active. So silently no-op.
        if statprof.state.profile_level == 0:
            statprof.reset(freq)
    else:
        ui.warn(_("invalid sampling frequency '%s' - ignoring\n") % freq)

    statprof.start(mechanism='thread')

    try:
        yield
    finally:
        data = statprof.stop()

        profformat = ui.config('profiling', 'statformat', 'hotpath')

        formats = {
            'byline': statprof.DisplayFormats.ByLine,
            'bymethod': statprof.DisplayFormats.ByMethod,
            'hotpath': statprof.DisplayFormats.Hotpath,
            'json': statprof.DisplayFormats.Json,
            'chrome': statprof.DisplayFormats.Chrome,
        }

        if profformat in formats:
            displayformat = formats[profformat]
        else:
            ui.warn(_('unknown profiler output format: %s\n') % profformat)
            displayformat = statprof.DisplayFormats.Hotpath

        kwargs = {}

        def fraction(s):
            if s.endswith('%'):
                v = float(s[:-1]) / 100
            else:
                v = float(s)
            if 0 <= v <= 1:
                return v
            raise ValueError(s)

        if profformat == 'chrome':
            showmin = ui.configwith(fraction, 'profiling', 'showmin', 0.005)
            showmax = ui.configwith(fraction, 'profiling', 'showmax', 0.999)
            kwargs.update(minthreshold=showmin, maxthreshold=showmax)

        statprof.display(fp, data=data, format=displayformat, **kwargs)

@contextlib.contextmanager
def profile(ui):
    """Start profiling.

    Profiling is active when the context manager is active. When the context
    manager exits, profiling results will be written to the configured output.
    """
    profiler = encoding.environ.get('HGPROF')
    if profiler is None:
        profiler = ui.config('profiling', 'type', default='stat')
    if profiler not in ('ls', 'stat', 'flame'):
        ui.warn(_("unrecognized profiler '%s' - ignored\n") % profiler)
        profiler = 'stat'

    output = ui.config('profiling', 'output')

    if output == 'blackbox':
        fp = util.stringio()
    elif output:
        path = ui.expandpath(output)
        fp = open(path, 'wb')
    else:
        fp = ui.ferr

    try:
        if profiler == 'ls':
            proffn = lsprofile
        elif profiler == 'flame':
            proffn = flameprofile
        else:
            proffn = statprofile

        with proffn(ui, fp):
            yield

    finally:
        if output:
            if output == 'blackbox':
                val = 'Profile:\n%s' % fp.getvalue()
                # ui.log treats the input as a format string,
                # so we need to escape any % signs.
                val = val.replace('%', '%%')
                ui.log('profile', val)
            fp.close()

@contextlib.contextmanager
def maybeprofile(ui):
    """Profile if enabled, else do nothing.

    This context manager can be used to optionally profile if profiling
    is enabled. Otherwise, it does nothing.

    The purpose of this context manager is to make calling code simpler:
    just use a single code path for calling into code you may want to profile
    and this function determines whether to start profiling.
    """
    if ui.configbool('profiling', 'enabled'):
        with profile(ui):
            yield
    else:
        yield