gh-88500: Reduce memory use of `urllib.unquote` (#96763)

`urllib.unquote_to_bytes` and `urllib.unquote` could both potentially generate `O(len(string))` intermediate `bytes` or `str` objects while computing the unquoted final result depending on the input provided. As Python objects are relatively large, this could consume a lot of ram.

This switches the implementation to using an expanding `bytearray` and a generator internally instead of precomputed `split()` style operations.

Microbenchmarks with some antagonistic inputs like `mess = "\u0141%%%20a%fe"*1000` show this is 10-20% slower for unquote and unquote_to_bytes and no different for typical inputs that are short or lack much unicode or % escaping. But the functions are already quite fast anyways so not a big deal.  The slowdown scales consistently linear with input size as expected.

Memory usage observed manually using `/usr/bin/time -v` on `python -m timeit` runs of larger inputs. Unittesting memory consumption is difficult and does not seem worthwhile.

Observed memory usage is ~1/2 for `unquote()` and <1/3 for `unquote_to_bytes()` using `python -m timeit -s 'from urllib.parse import unquote, unquote_to_bytes; v="\u0141%01\u0161%20"*500_000' 'unquote_to_bytes(v)'` as a test.
This commit is contained in:
Gregory P. Smith 2022-12-10 16:17:39 -08:00 committed by GitHub
parent 1bb68ba6d9
commit 2e279e85fe
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3 changed files with 23 additions and 11 deletions

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@ -1104,6 +1104,8 @@ class UnquotingTests(unittest.TestCase):
self.assertEqual(result.count('%'), 1,
"using unquote(): not all characters escaped: "
"%s" % result)
def test_unquote_rejects_none_and_tuple(self):
self.assertRaises((TypeError, AttributeError), urllib.parse.unquote, None)
self.assertRaises((TypeError, AttributeError), urllib.parse.unquote, ())

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@ -600,6 +600,9 @@ _hextobyte = None
def unquote_to_bytes(string):
"""unquote_to_bytes('abc%20def') -> b'abc def'."""
return bytes(_unquote_impl(string))
def _unquote_impl(string: bytes | bytearray | str) -> bytes | bytearray:
# Note: strings are encoded as UTF-8. This is only an issue if it contains
# unescaped non-ASCII characters, which URIs should not.
if not string:
@ -611,8 +614,8 @@ def unquote_to_bytes(string):
bits = string.split(b'%')
if len(bits) == 1:
return string
res = [bits[0]]
append = res.append
res = bytearray(bits[0])
append = res.extend
# Delay the initialization of the table to not waste memory
# if the function is never called
global _hextobyte
@ -626,10 +629,20 @@ def unquote_to_bytes(string):
except KeyError:
append(b'%')
append(item)
return b''.join(res)
return res
_asciire = re.compile('([\x00-\x7f]+)')
def _generate_unquoted_parts(string, encoding, errors):
previous_match_end = 0
for ascii_match in _asciire.finditer(string):
start, end = ascii_match.span()
yield string[previous_match_end:start] # Non-ASCII
# The ascii_match[1] group == string[start:end].
yield _unquote_impl(ascii_match[1]).decode(encoding, errors)
previous_match_end = end
yield string[previous_match_end:] # Non-ASCII tail
def unquote(string, encoding='utf-8', errors='replace'):
"""Replace %xx escapes by their single-character equivalent. The optional
encoding and errors parameters specify how to decode percent-encoded
@ -641,21 +654,16 @@ def unquote(string, encoding='utf-8', errors='replace'):
unquote('abc%20def') -> 'abc def'.
"""
if isinstance(string, bytes):
return unquote_to_bytes(string).decode(encoding, errors)
return _unquote_impl(string).decode(encoding, errors)
if '%' not in string:
# Is it a string-like object?
string.split
return string
if encoding is None:
encoding = 'utf-8'
if errors is None:
errors = 'replace'
bits = _asciire.split(string)
res = [bits[0]]
append = res.append
for i in range(1, len(bits), 2):
append(unquote_to_bytes(bits[i]).decode(encoding, errors))
append(bits[i + 1])
return ''.join(res)
return ''.join(_generate_unquoted_parts(string, encoding, errors))
def parse_qs(qs, keep_blank_values=False, strict_parsing=False,

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@ -0,0 +1,2 @@
Reduced the memory usage of :func:`urllib.parse.unquote` and
:func:`urllib.parse.unquote_to_bytes` on large values.