gh-130167: Optimise textwrap.dedent()

[AA-Turner]

Alternative to #131792, created as a new PR as I don't want to push commits to @Marius-Juston's main branch, which that PR is created from.

A

• Issue: Improve speed of stdlib functions by replacing re uses #130167

[AA-Turner]

Open question: by switching to str.isspace() over the regular expression approach, we now strip '\v'. '\f', and '\r'. The documentation notes that the function Remove[s] any common leading whitespace from every line in text, so this could be seen as a bugfix, but is an observable change in behaviour.

Do we want to restrict the removed whitespace to just tabs and spaces, and update the documentation as appropriate, or is this change acceptable? Previously, there was inconsistent behaviour around Windows-style newlines, which this PR does resolve.

Benchmark	dedent_textwrap	dedent_newer
raw_text: no prefix	12.1 ms	4.81 ms: 2.52x faster
raw_text: "abc \t"	12.7 ms	4.81 ms: 2.63x faster
raw_text: " "	19.4 ms	5.77 ms: 3.37x faster
raw_text: "\t"	18.4 ms	5.66 ms: 3.25x faster
raw_text: "\t abc"	21.0 ms	5.75 ms: 3.65x faster
raw_text: "\t abc \t "	24.1 ms	6.12 ms: 3.94x faster
raw_text: 1000 spaces	338 ms	43.5 ms: 7.76x faster
Basic indented text with empty lines	4.66 us	2.92 us: 1.60x faster
Text with mixed indentation and blank lines	4.28 us	2.99 us: 1.43x faster
No indentation (edge case)	2.66 us	1.95 us: 1.37x faster
Only blank lines	1.09 us	299 ns: 3.64x faster
Edge case: No common prefix to remove	1.79 us	1.71 us: 1.05x faster
Edge case: Single indented line	2.90 us	1.67 us: 1.74x faster
Edge case: Single indented line only	704 ns	260 ns: 2.71x faster
Edge case: Empty text	478 ns	130 ns: 3.67x faster
no_indent	10.4 us	3.68 us: 2.81x faster
spaces	18.2 us	4.76 us: 3.81x faster
mixed	27.5 us	18.0 us: 1.53x faster
large_text	379 us	109 us: 3.47x faster
whitespace_only	1.23 us	299 ns: 4.12x faster
Geometric mean	(ref)	2.69x faster

A

[picnixz]

Can you use python -m pyperf compare_to dedent_textwrap.json dedent_new.json --table so that we have a markdown table (I think that's the option)

[AA-Turner]

Can you use python -m pyperf compare_to dedent_textwrap.json dedent_new.json --table so that we have a markdown table (I think that's the option)

Done, and I reran the benchmarks, now showing a 2.7x improvement.

[eendebakpt]

Open question: by switching to str.isspace() over the regular expression approach, we now strip '\v'. '\f', and '\r'. The documentation notes that the function Remove[s] any common leading whitespace from every line in text, so this could be seen as a bugfix, but is an observable change in behaviour.

This behaviour change is also in the PR by @Marius-Juston. I have no strong opinion on whether the behaviour change is acceptable or not, but it should be in the news entry (and perhaps even in the whats new?).

[eendebakpt]

The paths are here because otherwise non_blank_lines is empty (not for performance I would say, the cases are rare).

It is possible though to get rid of these cases by writing

def dedent(text): lines = text.split('\n') # Get length of leading whitespace, inspired by ``os.path.commonprefix()``. non_blank_lines = [l for l in lines if l and not l.isspace()] l1 = min(non_blank_lines, default='hello') l2 = max(non_blank_lines, default='world') for margin, c in enumerate(l1): if c != l2[margin] or c not in ' \t': break return '\n'.join([l[margin:] if not l.isspace() else '' for l in lines]) 

Not sure whether this makes the code nice and small, or part of some obfuscated code contest :-)

[AA-Turner]

Using:

defdedent(text): lines=text.split('\n') non_blank_lines= [lforlinlinesiflandnotl.isspace()] l1=min(non_blank_lines, default='') l2=max(non_blank_lines, default='') margin=0formargin, cinenumerate(l1): ifc!=l2[margin] orcnotin' \t': breakreturn'\n'.join([l[margin:] ifnotl.isspace() else''forlinlines])

I get the following benchmark results:

Benchmark	textwrap	with whitespace checks	proposed (no branches)
raw_text: no prefix	12.1 ms	4.81 ms: 2.52x faster	4.71 ms: 2.58x faster
raw_text: "abc \t"	12.7 ms	4.81 ms: 2.63x faster	4.50 ms: 2.81x faster
raw_text: " "	19.4 ms	5.77 ms: 3.37x faster	5.67 ms: 3.43x faster
raw_text: "\t"	18.4 ms	5.66 ms: 3.25x faster	5.54 ms: 3.32x faster
raw_text: " \t abc"	21.0 ms	5.75 ms: 3.65x faster	5.42 ms: 3.88x faster
raw_text: " \t abc \t "	24.1 ms	6.12 ms: 3.94x faster	5.76 ms: 4.18x faster
raw_text: 1000 spaces	338 ms	43.5 ms: 7.76x faster	42.7 ms: 7.91x faster
Basic indented text with empty lines	4.66 us	2.92 us: 1.60x faster	3.08 us: 1.52x faster
Text with mixed indentation and blank lines	4.28 us	2.99 us: 1.43x faster	3.07 us: 1.39x faster
No indentation (edge case)	2.66 us	1.95 us: 1.37x faster	2.05 us: 1.30x faster
Only blank lines	1.09 us	299 ns: 3.64x faster	1.56 us: 1.43x slower
Edge case: No common prefix to remove	1.79 us	1.71 us: 1.05x faster	not significant
Edge case: Single indented line	2.90 us	1.67 us: 1.74x faster	1.68 us: 1.73x faster
Edge case: Single indented line only	704 ns	260 ns: 2.71x faster	1.00 us: 1.42x slower
Edge case: Empty text	478 ns	130 ns: 3.67x faster	1.01 us: 2.11x slower
no_indent	10.4 us	3.68 us: 2.81x faster	3.97 us: 2.61x faster
spaces	18.2 us	4.76 us: 3.81x faster	4.57 us: 3.98x faster
mixed	27.5 us	18.0 us: 1.53x faster	16.9 us: 1.63x faster
large_text	379 us	109 us: 3.47x faster	117 us: 3.23x faster
whitespace_only	1.23 us	299 ns: 4.12x faster	1.40 us: 1.14x slower
Geometric mean	(ref)	2.69x faster	1.94x faster

Notably, the synthetic benchmarks contain quite a lot of whitespace-only cases: Only blank lines, Edge case: Single indented line only, Edge case: Empty text, and whitespace_only. The text-heavy benchmarks don't seem to change, and some have slight improvements.

[Marius-Juston]

This is looking really good! I am having a lot of difficulties improving this further. The only possible other optimizations I can think of are optimizing the min / max computation to maybe perform the computation as it is computing the non_blank_lines and maybe cache the computation of not l.isspace() since that is done twice. I was trying to implement something like that but did not have much success there since the list comprehension is C optimized as well as the min and max operations.

[picnixz]

Caching would only make sense for lines that are very very long and for which we need to iterate multiple times over the same line. Now, for caching, we could either use a custom str class to cache the call or cache the results themselves in an other list and use it as a mask (as for numpy arrays) but I don't know if we're gaining something (we need to test that).

isspace= [l.isspace() forlinlines] non_blank_lines= [lines[i] fori, vinenumerate(isspace) ifv] ... return'\n'.join([l[margin:] ifnotisspace[i] else''fori, linenumerate(lines)])

I'm almost certain we can compute isspace and non_blank_lines simultaneously using some itertools recipes but I don't know how much we gain. In the worst case, we need to iterate over all the lines at least 3 + 3 (min/max + compute margin). Currently, we already iterate over the lines at least 1 + 2 + 1 + 1 times (1 for non_blank_lines, 2 for min/max, 1 for margin, and 1 for the final merge) so we're already doing lots of passes.

[AA-Turner]

I benchmarked a version using itertools.compress, and found it was slower overall (1.1x):

# Get length of leading whitespace, inspired by ``os.path.commonprefix()``.non_blank_idx= [landnotl.isspace() forlinlines] non_blank_lines=list(compress(lines, non_blank_idx)) l1=min(non_blank_lines, default='') l2=max(non_blank_lines, default='') margin=0formargin, cinenumerate(l1): ifc!=l2[margin] orcnotin' \t': breakreturn'\n'.join([l[margin:] ifnon_blank_idx[i] else''fori, linenumerate(lines)])

I suspect that the isspace() calls are quite cheap, as I assume they exit on the first non-space character. I also prefer the simplicity of the current implementation. What would help is a C-level min-max function that returns both the min and max from one iteration, but that's out of scope for this PR.

[picnixz]

they exit on the first non-space character

yes

[Marius-Juston]

What would help is a C-level min-max function that returns both the min and max from one iteration, but that's out of scope for this PR.

Agreed! I was just thinking about potentially creating this function. If I were to try this do you happen to know where the min and max implementation is in this repo? Should be pretty simple to implement the min-max version from that.

[Marius-Juston]

@AA-Turner, would it be possible to get your benchmarking script, please, so that I can use that as a comparison?

[AA-Turner]

$ python bm_dedent.py --fast --quiet --warmups 3 --output <filename>.json --quiet $ python -m pyperf compare_to <old>.json <new>.json --table --table-format md

bm_dedent.py

fromtextwrapimportindent, dedentastextwrap_dedentimportpyperfdefsetup_cases(): withopen("Objects/unicodeobject.c") asf: raw_text=f.read() return [ ('raw_text: no prefix', raw_text), (r'raw_text: "abc \t"', indent(raw_text, 'abc \t')), ('raw_text: " "', indent(raw_text, ' ')), (r'raw_text: "\t"', indent(raw_text, '\t')), (r'raw_text: " \t abc"', indent(raw_text, ' \t abc')), (r'raw_text: " \t abc \t "', indent(raw_text, ' \t abc \t ')), ("raw_text: 1000 spaces", indent(raw_text, ' '*1000)), ( 'Basic indented text with empty lines', """ def hello(): print("Hello, world!") """, ), ( 'Text with mixed indentation and blank lines', """ This is a test. Another line. """, ), ( 'No indentation (edge case)', """No indents here. Just normal text. With empty lines.""", ), ( 'Only blank lines', """ """, ), ( 'Edge case: No common prefix to remove', """hello world """, ), ( 'Edge case: Single indented line', """ Only one indented line""", ), ( 'Edge case: Single indented line only', """ """, ), ( 'Edge case: Empty text', """""", ), ('no_indent',textwrap_dedent(textwrap_dedent.__doc__)), ('spaces','\n'.join([' '+lforlintextwrap_dedent(textwrap_dedent.__doc__).split('\n')])), ('mixed','\n'.join([' Hello space', '\tHello tab', 'Hello'] *20)), ('large_text','\n'.join([textwrap_dedent.__doc__] *40)), ('whitespace_only','\n'.join([' ', '\t', ''])), ] if__name__=='__main__': runner=pyperf.Runner() args=runner.parse_args() forname, textinsetup_cases(): runner.bench_func(nameor'default', textwrap_dedent, text)

[AA-Turner]

Thanks all!

A

[bedevere-bot]

⚠️⚠️⚠️ Buildbot failure ⚠️⚠️⚠️

Hi! The buildbot AMD64 CentOS9 NoGIL Refleaks 3.x (tier-1) has failed when building commit 6aa88a2.

What do you need to do:

1. Don't panic.
2. Check the buildbot page in the devguide if you don't know what the buildbots are or how they work.
3. Go to the page of the buildbot that failed (https://buildbot.python.org/#/builders/1610/builds/1118) and take a look at the build logs.
4. Check if the failure is related to this commit (6aa88a2) or if it is a false positive.
5. If the failure is related to this commit, please, reflect that on the issue and make a new Pull Request with a fix.

You can take a look at the buildbot page here:

https://buildbot.python.org/#/builders/1610/builds/1118

Failed tests:

• test_free_threading

Summary of the results of the build (if available):

==

Click to see traceback logs

remote: Enumerating objects: 20, done. remote: Counting objects: 5% (1/20) remote: Counting objects: 10% (2/20) remote: Counting objects: 15% (3/20) remote: Counting objects: 20% (4/20) remote: Counting objects: 25% (5/20) remote: Counting objects: 30% (6/20) remote: Counting objects: 35% (7/20) remote: Counting objects: 40% (8/20) remote: Counting objects: 45% (9/20) remote: Counting objects: 50% (10/20) remote: Counting objects: 55% (11/20) remote: Counting objects: 60% (12/20) remote: Counting objects: 65% (13/20) remote: Counting objects: 70% (14/20) remote: Counting objects: 75% (15/20) remote: Counting objects: 80% (16/20) remote: Counting objects: 85% (17/20) remote: Counting objects: 90% (18/20) remote: Counting objects: 95% (19/20) remote: Counting objects: 100% (20/20) remote: Counting objects: 100% (20/20), done. remote: Compressing objects: 9% (1/11) remote: Compressing objects: 18% (2/11) remote: Compressing objects: 27% (3/11) remote: Compressing objects: 36% (4/11) remote: Compressing objects: 45% (5/11) remote: Compressing objects: 54% (6/11) remote: Compressing objects: 63% (7/11) remote: Compressing objects: 72% (8/11) remote: Compressing objects: 81% (9/11) remote: Compressing objects: 90% (10/11) remote: Compressing objects: 100% (11/11) remote: Compressing objects: 100% (11/11), done. remote: Total 11 (delta 9), reused 0 (delta 0), pack-reused 0 (from 0)  From https://github.com/python/cpython * branch main -> FETCH_HEAD Note: switching to '6aa88a2cb36240fe2b587f2e82043873270a27cf'. You are in 'detached HEAD' state. You can look around, make experimental changes and commit them, and you can discard any commits you make in this state without impacting any branches by switching back to a branch. If you want to create a new branch to retain commits you create, you may do so (now or later) by using -c with the switch command. Example: git switch -c <new-branch-name> Or undo this operation with: git switch - Turn off this advice by setting config variable advice.detachedHead to false HEAD is now at 6aa88a2cb36 gh-130167: Optimise ``textwrap.dedent()`` (#131919) Switched to and reset branch 'main' configure: WARNING: no system libmpdecimal found; falling back to bundled libmpdecimal (deprecated and scheduled for removal in Python 3.15)make: *** [Makefile:2334: buildbottest] Error 2

[hroncok]

This changes the exception type when bad type is passed:

Before:

>>> import textwrap >>> textwrap.dedent(5) Traceback (most recent call last): File "<python-input-1>", line 1, in <module> textwrap.dedent(5) ~~~~~~~~~~~~~~~^^^ File "/usr/lib64/python3.14/textwrap.py", line 435, in dedent text = _whitespace_only_re.sub('', text) TypeError: expected string or bytes-like object, got 'int'

After:

>>> import textwrap >>> textwrap.dedent(5) Traceback (most recent call last): File "<python-input-1>", line 1, in <module> textwrap.dedent(5) ~~~~~~~~~~~~~~~^^^ File "/usr/lib64/python3.14/textwrap.py", line 432, in dedent lines = text.split('\n') ^^^^^^^^^^ AttributeError: 'int' object has no attribute 'split'

The exception context itself could be better in both cases, but arguably, TypeError is better here. This breaks tests assumption in https://github.com/laurent-laporte-pro/deprecated/blob/3f67ca71143479ef7ce71786538b2bc0ef9ee4b4/tests/test_deprecated.py#L201

(Originally from #107369 (comment))

[picnixz]

Oh that's indeed an oversight. TypeError is a better error so let's wrap the call and reraise a TypeError instead if we catch an AttributeError

cc @AA-Turner

[AA-Turner]

I'll prepare a PR.