Integrate Line Profiler in Codeflash CF-470 #35
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Failed to generate code suggestions for PR |
you won't want to use line-profiler with coverage run, it won't profile what we need to profile correctly |
.env
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| @@ -0,0 +1,2 @@ | |||
| CODEFLASH_AIS_SERVER=local | |||
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Never commit.env files.
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that's right, reason i'm doing it right now is that I usually call git clean for removing concolic test dirs which accidentally deletes the env file/s. it won't be in the final pr of course.
alvin-r
reviewed
Mar 19, 2025
alvin-r
reviewed
Mar 19, 2025
alvin-r
reviewed
Mar 19, 2025
alvin-r
reviewed
Mar 19, 2025
codeflash-ai bot
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Apr 1, 2025
…-profiler`) To make the given Python program faster, we can improve the performance of the `_pipe_line_with_colons` function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version. ### Explanation of Changes. 1. **Reduce Function Calls within Loops**: By directly including the logic from `_pipe_segment_with_colons` within the loop in `_pipe_line_with_colons`, we avoid the overhead of repeatedly calling the `_pipe_segment_with_colons` function. 2. **Optimize List Construction**: We merged the list comprehension into a standard `for` loop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. 3. **Optimize Condition Check**: Simplified the alignment checks by directly comparing the `align` variable instead of storing and passing it around. This reduces the memory overhead. This will result in decreased execution time particularly when processing larger tables.
![codeflash-ai[bot]](https://avatars.githubusercontent.com/in/413177?s=60&v=4){kind=small}
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| return fmt.format(s) | ||
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| def _padnone(ignore_width, s): | ||
| return s | ||
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| def _strip_ansi(s): | ||
| if isinstance(s, str): | ||
| return _ansi_codes.sub(r"\4", s) | ||
| else: # a bytestring | ||
| return _ansi_codes_bytes.sub(r"\4", s) |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| return fmt.format(s) | |
| def _padnone(ignore_width, s): | |
| return s | |
| def _strip_ansi(s): | |
| if isinstance(s, str): | |
| return _ansi_codes.sub(r"\4", s) | |
| else: # a bytestring | |
| return _ansi_codes_bytes.sub(r"\4", s) | |
| # a bytestring | |
| return _ansi_codes_bytes.sub(r"\4", s) | |
| def _strip_ansi(s): | |
| if isinstance(s, str): | |
| return _ansi_codes.sub(r"\4", s) |
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| return _ansi_codes_bytes.sub(r"\4", s) | ||
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| def _visible_width(s): | ||
| if wcwidth is not None and WIDE_CHARS_MODE: | ||
| len_fn = wcwidth.wcswidth | ||
| else: | ||
| len_fn = len | ||
| if isinstance(s, (str, bytes)): | ||
| return len_fn(_strip_ansi(s)) | ||
| else: | ||
| return len_fn(str(s)) | ||
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| def _is_multiline(s): | ||
| if isinstance(s, str): | ||
| return bool(re.search(_multiline_codes, s)) | ||
| else: # a bytestring | ||
| return bool(re.search(_multiline_codes_bytes, s)) |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| return _ansi_codes_bytes.sub(r"\4", s) | |
| def _visible_width(s): | |
| if wcwidth is not None and WIDE_CHARS_MODE: | |
| len_fn = wcwidth.wcswidth | |
| else: | |
| len_fn = len | |
| if isinstance(s, (str, bytes)): | |
| return len_fn(_strip_ansi(s)) | |
| else: | |
| return len_fn(str(s)) | |
| def _is_multiline(s): | |
| if isinstance(s, str): | |
| return bool(re.search(_multiline_codes, s)) | |
| else: # a bytestring | |
| return bool(re.search(_multiline_codes_bytes, s)) | |
| return len_fn(str(s)) | |
| # a bytestring | |
| return bool(re.search(_multiline_codes_bytes, s)) | |
| if isinstance(s, (str, bytes)): | |
| return len_fn(_strip_ansi(s)) | |
| def _is_multiline(s): | |
| if isinstance(s, str): | |
| return bool(re.search(_multiline_codes, s)) |
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| def _align_column( | ||
| strings, | ||
| alignment, | ||
| minwidth=0, | ||
| has_invisible=True, | ||
| enable_widechars=False, | ||
| is_multiline=False, | ||
| preserve_whitespace=False, | ||
| ): | ||
| strings, padfn = _align_column_choose_padfn( | ||
| strings, alignment, has_invisible, preserve_whitespace | ||
| ) | ||
| width_fn = _align_column_choose_width_fn( | ||
| has_invisible, enable_widechars, is_multiline | ||
| ) | ||
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| s_widths = list(map(width_fn, strings)) | ||
| maxwidth = max(max(_flat_list(s_widths)), minwidth) | ||
| # TODO: refactor column alignment in single-line and multiline modes | ||
| if is_multiline: | ||
| if not enable_widechars and not has_invisible: | ||
| padded_strings = [ | ||
| "\n".join([padfn(maxwidth, s) for s in ms.splitlines()]) | ||
| for ms in strings | ||
| ] | ||
| else: | ||
| # enable wide-character width corrections | ||
| s_lens = [[len(s) for s in re.split("[\r\n]", ms)] for ms in strings] | ||
| visible_widths = [ | ||
| [maxwidth - (w - l) for w, l in zip(mw, ml)] | ||
| for mw, ml in zip(s_widths, s_lens) | ||
| ] | ||
| # wcswidth and _visible_width don't count invisible characters; | ||
| # padfn doesn't need to apply another correction | ||
| padded_strings = [ | ||
| "\n".join([padfn(w, s) for s, w in zip((ms.splitlines() or ms), mw)]) | ||
| for ms, mw in zip(strings, visible_widths) | ||
| ] | ||
| else: # single-line cell values | ||
| if not enable_widechars and not has_invisible: | ||
| padded_strings = [padfn(maxwidth, s) for s in strings] | ||
| else: | ||
| # enable wide-character width corrections | ||
| s_lens = list(map(len, strings)) | ||
| visible_widths = [maxwidth - (w - l) for w, l in zip(s_widths, s_lens)] | ||
| # wcswidth and _visible_width don't count invisible characters; | ||
| # padfn doesn't need to apply another correction | ||
| padded_strings = [padfn(w, s) for s, w in zip(strings, visible_widths)] | ||
| return padded_strings | ||
|
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| def _more_generic(type1, type2): | ||
| types = { | ||
| type(None): 0, | ||
| bool: 1, | ||
| int: 2, | ||
| float: 3, | ||
| bytes: 4, | ||
| str: 5, | ||
| } | ||
| invtypes = { | ||
| 5: str, | ||
| 4: bytes, | ||
| 3: float, | ||
| 2: int, | ||
| 1: bool, | ||
| 0: type(None), | ||
| } |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| def _align_column( | |
| strings, | |
| alignment, | |
| minwidth=0, | |
| has_invisible=True, | |
| enable_widechars=False, | |
| is_multiline=False, | |
| preserve_whitespace=False, | |
| ): | |
| strings, padfn = _align_column_choose_padfn( | |
| strings, alignment, has_invisible, preserve_whitespace | |
| ) | |
| width_fn = _align_column_choose_width_fn( | |
| has_invisible, enable_widechars, is_multiline | |
| ) | |
| s_widths = list(map(width_fn, strings)) | |
| maxwidth = max(max(_flat_list(s_widths)), minwidth) | |
| # TODO: refactor column alignment in single-line and multiline modes | |
| if is_multiline: | |
| if not enable_widechars and not has_invisible: | |
| padded_strings = [ | |
| "\n".join([padfn(maxwidth, s) for s in ms.splitlines()]) | |
| for ms in strings | |
| ] | |
| else: | |
| # enable wide-character width corrections | |
| s_lens = [[len(s) for s in re.split("[\r\n]", ms)] for ms in strings] | |
| visible_widths = [ | |
| [maxwidth - (w - l) for w, l in zip(mw, ml)] | |
| for mw, ml in zip(s_widths, s_lens) | |
| ] | |
| # wcswidth and _visible_width don't count invisible characters; | |
| # padfn doesn't need to apply another correction | |
| padded_strings = [ | |
| "\n".join([padfn(w, s) for s, w in zip((ms.splitlines() or ms), mw)]) | |
| for ms, mw in zip(strings, visible_widths) | |
| ] | |
| else: # single-line cell values | |
| if not enable_widechars and not has_invisible: | |
| padded_strings = [padfn(maxwidth, s) for s in strings] | |
| else: | |
| # enable wide-character width corrections | |
| s_lens = list(map(len, strings)) | |
| visible_widths = [maxwidth - (w - l) for w, l in zip(s_widths, s_lens)] | |
| # wcswidth and _visible_width don't count invisible characters; | |
| # padfn doesn't need to apply another correction | |
| padded_strings = [padfn(w, s) for s, w in zip(strings, visible_widths)] | |
| return padded_strings | |
| def _more_generic(type1, type2): | |
| types = { | |
| type(None): 0, | |
| bool: 1, | |
| int: 2, | |
| float: 3, | |
| bytes: 4, | |
| str: 5, | |
| } | |
| invtypes = { | |
| 5: str, | |
| 4: bytes, | |
| 3: float, | |
| 2: int, | |
| 1: bool, | |
| 0: type(None), | |
| } | |
| strings, padfn = _align_column_choose_padfn(strings, alignment, has_invisible, preserve_whitespace) | |
| width_fn = _align_column_choose_width_fn(has_invisible, enable_widechars, is_multiline) | |
| enable_widechars=False, | |
| padded_strings = [2025-03-31T20:57:26.923907489Z "\n".join([padfn(maxwidth, s) for s in ms.splitlines()]) for ms in strings] | |
| preserve_whitespace=False, | |
| ): | |
| visible_widths = [[maxwidth - (w - l) for w, l in zip(mw, ml)] for mw, ml in zip(s_widths, s_lens)] | |
| s_widths = list(map(width_fn, strings)) | |
| elif not enable_widechars and not has_invisible: | |
| padded_strings = [padfn(maxwidth, s) for s in strings] | |
| else: | |
| # enable wide-character width corrections | |
| s_lens = list(map(len, strings)) | |
| visible_widths = [maxwidth - (w - l) for w, l in zip(s_widths, s_lens)] | |
| # wcswidth and _visible_width don't count invisible characters; | |
| # padfn doesn't need to apply another correction | |
| padded_strings = [padfn(w, s) for s, w in zip(strings, visible_widths)] | |
| # enable wide-character width corrections | |
| s_lens = [[len(s) for s in re.split("[\r\n]", ms)] for ms in strings] | |
| types = {type(None): 0, bool: 1, int: 2, float: 3, bytes: 4, str: 5} | |
| invtypes = {5: str, 4: bytes, 3: float, 2: int, 1: bool, 0: type(None)} | |
| # wcswidth and _visible_width don't count invisible characters; | |
| # padfn doesn't need to apply another correction | |
| padded_strings = [ | |
| "\n".join([padfn(w, s) for s, w in zip((ms.splitlines() or ms), mw)]) | |
| for ms, mw in zip(strings, visible_widths) | |
| ] | |
| return padded_strings | |
| def _more_generic(type1, type2): |
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|
|
||
|
|
||
| def _more_generic(type1, type2): | ||
| types = { | ||
| type(None): 0, | ||
| bool: 1, | ||
| int: 2, | ||
| float: 3, | ||
| bytes: 4, | ||
| str: 5, | ||
| } | ||
| invtypes = { | ||
| 5: str, | ||
| 4: bytes, | ||
| 3: float, | ||
| 2: int, | ||
| 1: bool, | ||
| 0: type(None), | ||
| } | ||
| moregeneric = max(types.get(type1, 5), types.get(type2, 5)) | ||
| return invtypes[moregeneric] | ||
|
|
||
|
|
||
| def _column_type(strings, has_invisible=True, numparse=True): | ||
| types = [_type(s, has_invisible, numparse) for s in strings] | ||
| return reduce(_more_generic, types, bool) | ||
|
|
||
|
|
||
| def _format(val, valtype, floatfmt, intfmt, missingval="", has_invisible=True): | ||
| if val is None: | ||
| return missingval | ||
| if isinstance(val, (bytes, str)) and not val: | ||
| return "" | ||
|
|
||
| if valtype is str: | ||
| return f"{val}" | ||
| elif valtype is int: | ||
| if isinstance(val, str): | ||
| val_striped = val.encode("unicode_escape").decode("utf-8") | ||
| colored = re.search( | ||
| r"(\\[xX]+[0-9a-fA-F]+\[\d+[mM]+)([0-9.]+)(\\.*)$", val_striped | ||
| ) | ||
| if colored: | ||
| total_groups = len(colored.groups()) | ||
| if total_groups == 3: | ||
| digits = colored.group(2) | ||
| if digits.isdigit(): | ||
| val_new = ( | ||
| colored.group(1) | ||
| + format(int(digits), intfmt) | ||
| + colored.group(3) | ||
| ) | ||
| val = val_new.encode("utf-8").decode("unicode_escape") | ||
| intfmt = "" | ||
| return format(val, intfmt) | ||
| elif valtype is bytes: |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| def _more_generic(type1, type2): | |
| types = { | |
| type(None): 0, | |
| bool: 1, | |
| int: 2, | |
| float: 3, | |
| bytes: 4, | |
| str: 5, | |
| } | |
| invtypes = { | |
| 5: str, | |
| 4: bytes, | |
| 3: float, | |
| 2: int, | |
| 1: bool, | |
| 0: type(None), | |
| } | |
| moregeneric = max(types.get(type1, 5), types.get(type2, 5)) | |
| return invtypes[moregeneric] | |
| def _column_type(strings, has_invisible=True, numparse=True): | |
| types = [_type(s, has_invisible, numparse) for s in strings] | |
| return reduce(_more_generic, types, bool) | |
| def _format(val, valtype, floatfmt, intfmt, missingval="", has_invisible=True): | |
| if val is None: | |
| return missingval | |
| if isinstance(val, (bytes, str)) and not val: | |
| return "" | |
| if valtype is str: | |
| return f"{val}" | |
| elif valtype is int: | |
| if isinstance(val, str): | |
| val_striped = val.encode("unicode_escape").decode("utf-8") | |
| colored = re.search( | |
| r"(\\[xX]+[0-9a-fA-F]+\[\d+[mM]+)([0-9.]+)(\\.*)$", val_striped | |
| ) | |
| if colored: | |
| total_groups = len(colored.groups()) | |
| if total_groups == 3: | |
| digits = colored.group(2) | |
| if digits.isdigit(): | |
| val_new = ( | |
| colored.group(1) | |
| + format(int(digits), intfmt) | |
| + colored.group(3) | |
| ) | |
| val = val_new.encode("utf-8").decode("unicode_escape") | |
| intfmt = "" | |
| return format(val, intfmt) | |
| elif valtype is bytes: | |
| if valtype is int: | |
| colored = re.search(r"(\\[xX]+[0-9a-fA-F]+\[\d+[mM]+)([0-9.]+)(\\.*)$", val_striped) | |
| val_new = colored.group(1) + format(int(digits), intfmt) + colored.group(3) | |
| if valtype is bytes: | |
| return "" | |
| if valtype is str: | |
| return f"{val}" | |
| if isinstance(val, str): | |
| val_striped = val.encode("unicode_escape").decode("utf-8") | |
| if colored: | |
| total_groups = len(colored.groups()) | |
| if total_groups == 3: | |
| digits = colored.group(2) | |
| if digits.isdigit(): | |
| val = val_new.encode("utf-8").decode("unicode_escape") | |
| intfmt = "" | |
| return format(val, intfmt) |
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| types = [_type(s, has_invisible, numparse) for s in strings] | ||
| return reduce(_more_generic, types, bool) | ||
|
|
||
|
|
||
| def _format(val, valtype, floatfmt, intfmt, missingval="", has_invisible=True): | ||
| if val is None: | ||
| return missingval | ||
| if isinstance(val, (bytes, str)) and not val: | ||
| return "" | ||
|
|
||
| if valtype is str: | ||
| return f"{val}" | ||
| elif valtype is int: | ||
| if isinstance(val, str): | ||
| val_striped = val.encode("unicode_escape").decode("utf-8") | ||
| colored = re.search( | ||
| r"(\\[xX]+[0-9a-fA-F]+\[\d+[mM]+)([0-9.]+)(\\.*)$", val_striped | ||
| ) | ||
| if colored: | ||
| total_groups = len(colored.groups()) | ||
| if total_groups == 3: | ||
| digits = colored.group(2) | ||
| if digits.isdigit(): | ||
| val_new = ( | ||
| colored.group(1) | ||
| + format(int(digits), intfmt) | ||
| + colored.group(3) | ||
| ) | ||
| val = val_new.encode("utf-8").decode("unicode_escape") | ||
| intfmt = "" | ||
| return format(val, intfmt) | ||
| elif valtype is bytes: | ||
| try: | ||
| return str(val, "ascii") | ||
| except (TypeError, UnicodeDecodeError): | ||
| return str(val) | ||
| elif valtype is float: | ||
| is_a_colored_number = has_invisible and isinstance(val, (str, bytes)) | ||
| if is_a_colored_number: | ||
| raw_val = _strip_ansi(val) | ||
| formatted_val = format(float(raw_val), floatfmt) | ||
| return val.replace(raw_val, formatted_val) | ||
| else: | ||
| if isinstance(val, str) and "," in val: | ||
| val = val.replace(",", "") # handle thousands-separators | ||
| return format(float(val), floatfmt) | ||
| else: | ||
| return f"{val}" | ||
|
|
||
|
|
||
| def _align_header( | ||
| header, alignment, width, visible_width, is_multiline=False, width_fn=None | ||
| ): | ||
| "Pad string header to width chars given known visible_width of the header." | ||
| if is_multiline: | ||
| header_lines = re.split(_multiline_codes, header) | ||
| padded_lines = [ | ||
| _align_header(h, alignment, width, width_fn(h)) for h in header_lines | ||
| ] | ||
| return "\n".join(padded_lines) | ||
| # else: not multiline | ||
| ninvisible = len(header) - visible_width | ||
| width += ninvisible | ||
| if alignment == "left": | ||
| return _padright(width, header) | ||
| elif alignment == "center": | ||
| return _padboth(width, header) | ||
| elif not alignment: | ||
| return f"{header}" | ||
| else: | ||
| return _padleft(width, header) |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| types = [_type(s, has_invisible, numparse) for s in strings] | |
| return reduce(_more_generic, types, bool) | |
| def _format(val, valtype, floatfmt, intfmt, missingval="", has_invisible=True): | |
| if val is None: | |
| return missingval | |
| if isinstance(val, (bytes, str)) and not val: | |
| return "" | |
| if valtype is str: | |
| return f"{val}" | |
| elif valtype is int: | |
| if isinstance(val, str): | |
| val_striped = val.encode("unicode_escape").decode("utf-8") | |
| colored = re.search( | |
| r"(\\[xX]+[0-9a-fA-F]+\[\d+[mM]+)([0-9.]+)(\\.*)$", val_striped | |
| ) | |
| if colored: | |
| total_groups = len(colored.groups()) | |
| if total_groups == 3: | |
| digits = colored.group(2) | |
| if digits.isdigit(): | |
| val_new = ( | |
| colored.group(1) | |
| + format(int(digits), intfmt) | |
| + colored.group(3) | |
| ) | |
| val = val_new.encode("utf-8").decode("unicode_escape") | |
| intfmt = "" | |
| return format(val, intfmt) | |
| elif valtype is bytes: | |
| try: | |
| return str(val, "ascii") | |
| except (TypeError, UnicodeDecodeError): | |
| return str(val) | |
| elif valtype is float: | |
| is_a_colored_number = has_invisible and isinstance(val, (str, bytes)) | |
| if is_a_colored_number: | |
| raw_val = _strip_ansi(val) | |
| formatted_val = format(float(raw_val), floatfmt) | |
| return val.replace(raw_val, formatted_val) | |
| else: | |
| if isinstance(val, str) and "," in val: | |
| val = val.replace(",", "") # handle thousands-separators | |
| return format(float(val), floatfmt) | |
| else: | |
| return f"{val}" | |
| def _align_header( | |
| header, alignment, width, visible_width, is_multiline=False, width_fn=None | |
| ): | |
| "Pad string header to width chars given known visible_width of the header." | |
| if is_multiline: | |
| header_lines = re.split(_multiline_codes, header) | |
| padded_lines = [ | |
| _align_header(h, alignment, width, width_fn(h)) for h in header_lines | |
| ] | |
| return "\n".join(padded_lines) | |
| # else: not multiline | |
| ninvisible = len(header) - visible_width | |
| width += ninvisible | |
| if alignment == "left": | |
| return _padright(width, header) | |
| elif alignment == "center": | |
| return _padboth(width, header) | |
| elif not alignment: | |
| return f"{header}" | |
| else: | |
| return _padleft(width, header) | |
| if isinstance(val, str) and "," in val: | |
| val = val.replace(",", "") # handle thousands-separators | |
| return format(float(val), floatfmt) | |
| def _align_header(header, alignment, width, visible_width, is_multiline=False, width_fn=None): | |
| """Pad string header to width chars given known visible_width of the header.""" | |
| padded_lines = [_align_header(h, alignment, width, width_fn(h)) for h in header_lines] | |
| if alignment == "center": | |
| if not alignment: | |
| return _padleft(width, header) | |
| if is_a_colored_number: | |
| raw_val = _strip_ansi(val) | |
| formatted_val = format(float(raw_val), floatfmt) | |
| return val.replace(raw_val, formatted_val) | |
| else: | |
| return f"{val}" | |
| if is_multiline: | |
| header_lines = re.split(_multiline_codes, header) | |
| return "\n".join(padded_lines) | |
| # else: not multiline | |
| ninvisible = len(header) - visible_width | |
| width += ninvisible | |
| if alignment == "left": | |
| return _padright(width, header) | |
| return _padboth(width, header) | |
| return f"{header}" |
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| field_names = [field.name for field in dataclasses.fields(rows[0])] | ||
| if headers == "keys": | ||
| headers = field_names | ||
| rows = [[getattr(row, f) for f in field_names] for row in rows] | ||
|
|
||
| elif headers == "keys" and len(rows) > 0: | ||
| # keys are column indices | ||
| headers = list(map(str, range(len(rows[0])))) | ||
|
|
||
| # take headers from the first row if necessary | ||
| if headers == "firstrow" and len(rows) > 0: | ||
| if index is not None: | ||
| headers = [index[0]] + list(rows[0]) | ||
| index = index[1:] | ||
| else: | ||
| headers = rows[0] | ||
| headers = list(map(str, headers)) # headers should be strings | ||
| rows = rows[1:] | ||
| elif headers == "firstrow": | ||
| headers = [] | ||
|
|
||
| headers = list(map(str, headers)) | ||
| # rows = list(map(list, rows)) | ||
| rows = list(map(lambda r: r if _is_separating_line(r) else list(r), rows)) | ||
|
|
||
| # add or remove an index column | ||
| showindex_is_a_str = type(showindex) in [str, bytes] | ||
| if showindex == "never" or (not _bool(showindex) and not showindex_is_a_str): | ||
| pass | ||
|
|
||
| # pad with empty headers for initial columns if necessary | ||
| headers_pad = 0 | ||
| if headers and len(rows) > 0: | ||
| headers_pad = max(0, len(rows[0]) - len(headers)) | ||
| headers = [""] * headers_pad + headers | ||
|
|
||
| return rows, headers, headers_pad | ||
|
|
||
| def _to_str(s, encoding="utf8", errors="ignore"): | ||
| if isinstance(s, bytes): | ||
| return s.decode(encoding=encoding, errors=errors) | ||
| return str(s) | ||
|
|
||
|
|
||
| def tabulate( | ||
| tabular_data, | ||
| headers=(), | ||
| tablefmt="simple", | ||
| floatfmt=_DEFAULT_FLOATFMT, | ||
| intfmt=_DEFAULT_INTFMT, | ||
| numalign=_DEFAULT_ALIGN, | ||
| stralign=_DEFAULT_ALIGN, | ||
| missingval=_DEFAULT_MISSINGVAL, | ||
| showindex="default", | ||
| disable_numparse=False, | ||
| colglobalalign=None, | ||
| colalign=None, | ||
| preserve_whitespace=False, | ||
| maxcolwidths=None, | ||
| headersglobalalign=None, | ||
| headersalign=None, | ||
| rowalign=None, | ||
| maxheadercolwidths=None, | ||
| ): | ||
| if tabular_data is None: | ||
| tabular_data = [] | ||
|
|
||
| list_of_lists, headers, headers_pad = _normalize_tabular_data( | ||
| tabular_data, headers, showindex=showindex | ||
| ) |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| field_names = [field.name for field in dataclasses.fields(rows[0])] | |
| if headers == "keys": | |
| headers = field_names | |
| rows = [[getattr(row, f) for f in field_names] for row in rows] | |
| elif headers == "keys" and len(rows) > 0: | |
| # keys are column indices | |
| headers = list(map(str, range(len(rows[0])))) | |
| # take headers from the first row if necessary | |
| if headers == "firstrow" and len(rows) > 0: | |
| if index is not None: | |
| headers = [index[0]] + list(rows[0]) | |
| index = index[1:] | |
| else: | |
| headers = rows[0] | |
| headers = list(map(str, headers)) # headers should be strings | |
| rows = rows[1:] | |
| elif headers == "firstrow": | |
| headers = [] | |
| headers = list(map(str, headers)) | |
| # rows = list(map(list, rows)) | |
| rows = list(map(lambda r: r if _is_separating_line(r) else list(r), rows)) | |
| # add or remove an index column | |
| showindex_is_a_str = type(showindex) in [str, bytes] | |
| if showindex == "never" or (not _bool(showindex) and not showindex_is_a_str): | |
| pass | |
| # pad with empty headers for initial columns if necessary | |
| headers_pad = 0 | |
| if headers and len(rows) > 0: | |
| headers_pad = max(0, len(rows[0]) - len(headers)) | |
| headers = [""] * headers_pad + headers | |
| return rows, headers, headers_pad | |
| def _to_str(s, encoding="utf8", errors="ignore"): | |
| if isinstance(s, bytes): | |
| return s.decode(encoding=encoding, errors=errors) | |
| return str(s) | |
| def tabulate( | |
| tabular_data, | |
| headers=(), | |
| tablefmt="simple", | |
| floatfmt=_DEFAULT_FLOATFMT, | |
| intfmt=_DEFAULT_INTFMT, | |
| numalign=_DEFAULT_ALIGN, | |
| stralign=_DEFAULT_ALIGN, | |
| missingval=_DEFAULT_MISSINGVAL, | |
| showindex="default", | |
| disable_numparse=False, | |
| colglobalalign=None, | |
| colalign=None, | |
| preserve_whitespace=False, | |
| maxcolwidths=None, | |
| headersglobalalign=None, | |
| headersalign=None, | |
| rowalign=None, | |
| maxheadercolwidths=None, | |
| ): | |
| if tabular_data is None: | |
| tabular_data = [] | |
| list_of_lists, headers, headers_pad = _normalize_tabular_data( | |
| tabular_data, headers, showindex=showindex | |
| ) | |
| list_of_lists, headers, headers_pad = _normalize_tabular_data(tabular_data, headers, showindex=showindex) | |
| ): | |
| if tabular_data is None: | |
| tabular_data = [] |
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|
|
||
|
|
||
| def tabulate( | ||
| tabular_data, | ||
| headers=(), | ||
| tablefmt="simple", | ||
| floatfmt=_DEFAULT_FLOATFMT, | ||
| intfmt=_DEFAULT_INTFMT, | ||
| numalign=_DEFAULT_ALIGN, | ||
| stralign=_DEFAULT_ALIGN, | ||
| missingval=_DEFAULT_MISSINGVAL, | ||
| showindex="default", | ||
| disable_numparse=False, | ||
| colglobalalign=None, | ||
| colalign=None, | ||
| preserve_whitespace=False, | ||
| maxcolwidths=None, | ||
| headersglobalalign=None, | ||
| headersalign=None, | ||
| rowalign=None, | ||
| maxheadercolwidths=None, | ||
| ): | ||
| if tabular_data is None: | ||
| tabular_data = [] | ||
|
|
||
| list_of_lists, headers, headers_pad = _normalize_tabular_data( | ||
| tabular_data, headers, showindex=showindex | ||
| ) | ||
| list_of_lists, separating_lines = _remove_separating_lines(list_of_lists) | ||
|
|
||
| # PrettyTable formatting does not use any extra padding. | ||
| # Numbers are not parsed and are treated the same as strings for alignment. | ||
| # Check if pretty is the format being used and override the defaults so it | ||
| # does not impact other formats. | ||
| min_padding = MIN_PADDING | ||
| if tablefmt == "pretty": | ||
| min_padding = 0 | ||
| disable_numparse = True | ||
| numalign = "center" if numalign == _DEFAULT_ALIGN else numalign | ||
| stralign = "center" if stralign == _DEFAULT_ALIGN else stralign | ||
| else: | ||
| numalign = "decimal" if numalign == _DEFAULT_ALIGN else numalign | ||
| stralign = "left" if stralign == _DEFAULT_ALIGN else stralign | ||
|
|
||
| # 'colon_grid' uses colons in the line beneath the header to represent a column's | ||
| # alignment instead of literally aligning the text differently. Hence, | ||
| # left alignment of the data in the text output is enforced. | ||
| if tablefmt == "colon_grid": | ||
| colglobalalign = "left" | ||
| headersglobalalign = "left" | ||
|
|
||
| # optimization: look for ANSI control codes once, | ||
| # enable smart width functions only if a control code is found | ||
| # | ||
| # convert the headers and rows into a single, tab-delimited string ensuring | ||
| # that any bytestrings are decoded safely (i.e. errors ignored) | ||
| plain_text = "\t".join( | ||
| chain( | ||
| # headers | ||
| map(_to_str, headers), | ||
| # rows: chain the rows together into a single iterable after mapping | ||
| # the bytestring conversino to each cell value | ||
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | ||
| ) | ||
| ) | ||
|
|
||
| has_invisible = _ansi_codes.search(plain_text) is not None | ||
|
|
||
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | ||
| if ( | ||
| not isinstance(tablefmt, TableFormat) | ||
| and tablefmt in multiline_formats | ||
| and _is_multiline(plain_text) | ||
| ): |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| def tabulate( | |
| tabular_data, | |
| headers=(), | |
| tablefmt="simple", | |
| floatfmt=_DEFAULT_FLOATFMT, | |
| intfmt=_DEFAULT_INTFMT, | |
| numalign=_DEFAULT_ALIGN, | |
| stralign=_DEFAULT_ALIGN, | |
| missingval=_DEFAULT_MISSINGVAL, | |
| showindex="default", | |
| disable_numparse=False, | |
| colglobalalign=None, | |
| colalign=None, | |
| preserve_whitespace=False, | |
| maxcolwidths=None, | |
| headersglobalalign=None, | |
| headersalign=None, | |
| rowalign=None, | |
| maxheadercolwidths=None, | |
| ): | |
| if tabular_data is None: | |
| tabular_data = [] | |
| list_of_lists, headers, headers_pad = _normalize_tabular_data( | |
| tabular_data, headers, showindex=showindex | |
| ) | |
| list_of_lists, separating_lines = _remove_separating_lines(list_of_lists) | |
| # PrettyTable formatting does not use any extra padding. | |
| # Numbers are not parsed and are treated the same as strings for alignment. | |
| # Check if pretty is the format being used and override the defaults so it | |
| # does not impact other formats. | |
| min_padding = MIN_PADDING | |
| if tablefmt == "pretty": | |
| min_padding = 0 | |
| disable_numparse = True | |
| numalign = "center" if numalign == _DEFAULT_ALIGN else numalign | |
| stralign = "center" if stralign == _DEFAULT_ALIGN else stralign | |
| else: | |
| numalign = "decimal" if numalign == _DEFAULT_ALIGN else numalign | |
| stralign = "left" if stralign == _DEFAULT_ALIGN else stralign | |
| # 'colon_grid' uses colons in the line beneath the header to represent a column's | |
| # alignment instead of literally aligning the text differently. Hence, | |
| # left alignment of the data in the text output is enforced. | |
| if tablefmt == "colon_grid": | |
| colglobalalign = "left" | |
| headersglobalalign = "left" | |
| # optimization: look for ANSI control codes once, | |
| # enable smart width functions only if a control code is found | |
| # | |
| # convert the headers and rows into a single, tab-delimited string ensuring | |
| # that any bytestrings are decoded safely (i.e. errors ignored) | |
| plain_text = "\t".join( | |
| chain( | |
| # headers | |
| map(_to_str, headers), | |
| # rows: chain the rows together into a single iterable after mapping | |
| # the bytestring conversino to each cell value | |
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | |
| ) | |
| ) | |
| has_invisible = _ansi_codes.search(plain_text) is not None | |
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | |
| if ( | |
| not isinstance(tablefmt, TableFormat) | |
| and tablefmt in multiline_formats | |
| and _is_multiline(plain_text) | |
| ): | |
| if not isinstance(tablefmt, TableFormat) and tablefmt in multiline_formats and _is_multiline(plain_text): | |
| has_invisible = _ansi_codes.search(plain_text) is not None | |
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE |
Comment on lines
+717
to
+800
| disable_numparse=False, | ||
| colglobalalign=None, | ||
| colalign=None, | ||
| preserve_whitespace=False, | ||
| maxcolwidths=None, | ||
| headersglobalalign=None, | ||
| headersalign=None, | ||
| rowalign=None, | ||
| maxheadercolwidths=None, | ||
| ): | ||
| if tabular_data is None: | ||
| tabular_data = [] | ||
|
|
||
| list_of_lists, headers, headers_pad = _normalize_tabular_data( | ||
| tabular_data, headers, showindex=showindex | ||
| ) | ||
| list_of_lists, separating_lines = _remove_separating_lines(list_of_lists) | ||
|
|
||
| # PrettyTable formatting does not use any extra padding. | ||
| # Numbers are not parsed and are treated the same as strings for alignment. | ||
| # Check if pretty is the format being used and override the defaults so it | ||
| # does not impact other formats. | ||
| min_padding = MIN_PADDING | ||
| if tablefmt == "pretty": | ||
| min_padding = 0 | ||
| disable_numparse = True | ||
| numalign = "center" if numalign == _DEFAULT_ALIGN else numalign | ||
| stralign = "center" if stralign == _DEFAULT_ALIGN else stralign | ||
| else: | ||
| numalign = "decimal" if numalign == _DEFAULT_ALIGN else numalign | ||
| stralign = "left" if stralign == _DEFAULT_ALIGN else stralign | ||
|
|
||
| # 'colon_grid' uses colons in the line beneath the header to represent a column's | ||
| # alignment instead of literally aligning the text differently. Hence, | ||
| # left alignment of the data in the text output is enforced. | ||
| if tablefmt == "colon_grid": | ||
| colglobalalign = "left" | ||
| headersglobalalign = "left" | ||
|
|
||
| # optimization: look for ANSI control codes once, | ||
| # enable smart width functions only if a control code is found | ||
| # | ||
| # convert the headers and rows into a single, tab-delimited string ensuring | ||
| # that any bytestrings are decoded safely (i.e. errors ignored) | ||
| plain_text = "\t".join( | ||
| chain( | ||
| # headers | ||
| map(_to_str, headers), | ||
| # rows: chain the rows together into a single iterable after mapping | ||
| # the bytestring conversino to each cell value | ||
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | ||
| ) | ||
| ) | ||
|
|
||
| has_invisible = _ansi_codes.search(plain_text) is not None | ||
|
|
||
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | ||
| if ( | ||
| not isinstance(tablefmt, TableFormat) | ||
| and tablefmt in multiline_formats | ||
| and _is_multiline(plain_text) | ||
| ): | ||
| tablefmt = multiline_formats.get(tablefmt, tablefmt) | ||
| is_multiline = True | ||
| else: | ||
| is_multiline = False | ||
| width_fn = _choose_width_fn(has_invisible, enable_widechars, is_multiline) | ||
|
|
||
| # format rows and columns, convert numeric values to strings | ||
| cols = list(izip_longest(*list_of_lists)) | ||
| numparses = _expand_numparse(disable_numparse, len(cols)) | ||
| coltypes = [_column_type(col, numparse=np) for col, np in zip(cols, numparses)] | ||
| if isinstance(floatfmt, str): # old version | ||
| float_formats = len(cols) * [ | ||
| floatfmt | ||
| ] # just duplicate the string to use in each column | ||
| else: # if floatfmt is list, tuple etc we have one per column | ||
| float_formats = list(floatfmt) | ||
| if len(float_formats) < len(cols): | ||
| float_formats.extend((len(cols) - len(float_formats)) * [_DEFAULT_FLOATFMT]) | ||
| if isinstance(intfmt, str): # old version | ||
| int_formats = len(cols) * [ | ||
| intfmt | ||
| ] # just duplicate the string to use in each column |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| disable_numparse=False, | |
| colglobalalign=None, | |
| colalign=None, | |
| preserve_whitespace=False, | |
| maxcolwidths=None, | |
| headersglobalalign=None, | |
| headersalign=None, | |
| rowalign=None, | |
| maxheadercolwidths=None, | |
| ): | |
| if tabular_data is None: | |
| tabular_data = [] | |
| list_of_lists, headers, headers_pad = _normalize_tabular_data( | |
| tabular_data, headers, showindex=showindex | |
| ) | |
| list_of_lists, separating_lines = _remove_separating_lines(list_of_lists) | |
| # PrettyTable formatting does not use any extra padding. | |
| # Numbers are not parsed and are treated the same as strings for alignment. | |
| # Check if pretty is the format being used and override the defaults so it | |
| # does not impact other formats. | |
| min_padding = MIN_PADDING | |
| if tablefmt == "pretty": | |
| min_padding = 0 | |
| disable_numparse = True | |
| numalign = "center" if numalign == _DEFAULT_ALIGN else numalign | |
| stralign = "center" if stralign == _DEFAULT_ALIGN else stralign | |
| else: | |
| numalign = "decimal" if numalign == _DEFAULT_ALIGN else numalign | |
| stralign = "left" if stralign == _DEFAULT_ALIGN else stralign | |
| # 'colon_grid' uses colons in the line beneath the header to represent a column's | |
| # alignment instead of literally aligning the text differently. Hence, | |
| # left alignment of the data in the text output is enforced. | |
| if tablefmt == "colon_grid": | |
| colglobalalign = "left" | |
| headersglobalalign = "left" | |
| # optimization: look for ANSI control codes once, | |
| # enable smart width functions only if a control code is found | |
| # | |
| # convert the headers and rows into a single, tab-delimited string ensuring | |
| # that any bytestrings are decoded safely (i.e. errors ignored) | |
| plain_text = "\t".join( | |
| chain( | |
| # headers | |
| map(_to_str, headers), | |
| # rows: chain the rows together into a single iterable after mapping | |
| # the bytestring conversino to each cell value | |
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | |
| ) | |
| ) | |
| has_invisible = _ansi_codes.search(plain_text) is not None | |
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | |
| if ( | |
| not isinstance(tablefmt, TableFormat) | |
| and tablefmt in multiline_formats | |
| and _is_multiline(plain_text) | |
| ): | |
| tablefmt = multiline_formats.get(tablefmt, tablefmt) | |
| is_multiline = True | |
| else: | |
| is_multiline = False | |
| width_fn = _choose_width_fn(has_invisible, enable_widechars, is_multiline) | |
| # format rows and columns, convert numeric values to strings | |
| cols = list(izip_longest(*list_of_lists)) | |
| numparses = _expand_numparse(disable_numparse, len(cols)) | |
| coltypes = [_column_type(col, numparse=np) for col, np in zip(cols, numparses)] | |
| if isinstance(floatfmt, str): # old version | |
| float_formats = len(cols) * [ | |
| floatfmt | |
| ] # just duplicate the string to use in each column | |
| else: # if floatfmt is list, tuple etc we have one per column | |
| float_formats = list(floatfmt) | |
| if len(float_formats) < len(cols): | |
| float_formats.extend((len(cols) - len(float_formats)) * [_DEFAULT_FLOATFMT]) | |
| if isinstance(intfmt, str): # old version | |
| int_formats = len(cols) * [ | |
| intfmt | |
| ] # just duplicate the string to use in each column | |
| float_formats = len(cols) * [floatfmt] # just duplicate the string to use in each column | |
| int_formats = len(cols) * [intfmt] # just duplicate the string to use in each column | |
| cols = list(izip_longest(*list_of_lists)) | |
| numparses = _expand_numparse(disable_numparse, len(cols)) | |
| coltypes = [_column_type(col, numparse=np) for col, np in zip(cols, numparses)] | |
| if isinstance(floatfmt, str): # old version | |
| else: # if floatfmt is list, tuple etc we have one per column | |
| float_formats = list(floatfmt) | |
| if len(float_formats) < len(cols): | |
| float_formats.extend((len(cols) - len(float_formats)) * [_DEFAULT_FLOATFMT]) | |
| if isinstance(intfmt, str): # old version |
Comment on lines
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+815
| # Numbers are not parsed and are treated the same as strings for alignment. | ||
| # Check if pretty is the format being used and override the defaults so it | ||
| # does not impact other formats. | ||
| min_padding = MIN_PADDING | ||
| if tablefmt == "pretty": | ||
| min_padding = 0 | ||
| disable_numparse = True | ||
| numalign = "center" if numalign == _DEFAULT_ALIGN else numalign | ||
| stralign = "center" if stralign == _DEFAULT_ALIGN else stralign | ||
| else: | ||
| numalign = "decimal" if numalign == _DEFAULT_ALIGN else numalign | ||
| stralign = "left" if stralign == _DEFAULT_ALIGN else stralign | ||
|
|
||
| # 'colon_grid' uses colons in the line beneath the header to represent a column's | ||
| # alignment instead of literally aligning the text differently. Hence, | ||
| # left alignment of the data in the text output is enforced. | ||
| if tablefmt == "colon_grid": | ||
| colglobalalign = "left" | ||
| headersglobalalign = "left" | ||
|
|
||
| # optimization: look for ANSI control codes once, | ||
| # enable smart width functions only if a control code is found | ||
| # | ||
| # convert the headers and rows into a single, tab-delimited string ensuring | ||
| # that any bytestrings are decoded safely (i.e. errors ignored) | ||
| plain_text = "\t".join( | ||
| chain( | ||
| # headers | ||
| map(_to_str, headers), | ||
| # rows: chain the rows together into a single iterable after mapping | ||
| # the bytestring conversino to each cell value | ||
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | ||
| ) | ||
| ) | ||
|
|
||
| has_invisible = _ansi_codes.search(plain_text) is not None | ||
|
|
||
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | ||
| if ( | ||
| not isinstance(tablefmt, TableFormat) | ||
| and tablefmt in multiline_formats | ||
| and _is_multiline(plain_text) | ||
| ): | ||
| tablefmt = multiline_formats.get(tablefmt, tablefmt) | ||
| is_multiline = True | ||
| else: | ||
| is_multiline = False | ||
| width_fn = _choose_width_fn(has_invisible, enable_widechars, is_multiline) | ||
|
|
||
| # format rows and columns, convert numeric values to strings | ||
| cols = list(izip_longest(*list_of_lists)) | ||
| numparses = _expand_numparse(disable_numparse, len(cols)) | ||
| coltypes = [_column_type(col, numparse=np) for col, np in zip(cols, numparses)] | ||
| if isinstance(floatfmt, str): # old version | ||
| float_formats = len(cols) * [ | ||
| floatfmt | ||
| ] # just duplicate the string to use in each column | ||
| else: # if floatfmt is list, tuple etc we have one per column | ||
| float_formats = list(floatfmt) | ||
| if len(float_formats) < len(cols): | ||
| float_formats.extend((len(cols) - len(float_formats)) * [_DEFAULT_FLOATFMT]) | ||
| if isinstance(intfmt, str): # old version | ||
| int_formats = len(cols) * [ | ||
| intfmt | ||
| ] # just duplicate the string to use in each column | ||
| else: # if intfmt is list, tuple etc we have one per column | ||
| int_formats = list(intfmt) | ||
| if len(int_formats) < len(cols): | ||
| int_formats.extend((len(cols) - len(int_formats)) * [_DEFAULT_INTFMT]) | ||
| if isinstance(missingval, str): | ||
| missing_vals = len(cols) * [missingval] | ||
| else: | ||
| missing_vals = list(missingval) | ||
| if len(missing_vals) < len(cols): | ||
| missing_vals.extend((len(cols) - len(missing_vals)) * [_DEFAULT_MISSINGVAL]) | ||
| cols = [ | ||
| [_format(v, ct, fl_fmt, int_fmt, miss_v, has_invisible) for v in c] | ||
| for c, ct, fl_fmt, int_fmt, miss_v in zip( | ||
| cols, coltypes, float_formats, int_formats, missing_vals | ||
| ) |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| # Numbers are not parsed and are treated the same as strings for alignment. | |
| # Check if pretty is the format being used and override the defaults so it | |
| # does not impact other formats. | |
| min_padding = MIN_PADDING | |
| if tablefmt == "pretty": | |
| min_padding = 0 | |
| disable_numparse = True | |
| numalign = "center" if numalign == _DEFAULT_ALIGN else numalign | |
| stralign = "center" if stralign == _DEFAULT_ALIGN else stralign | |
| else: | |
| numalign = "decimal" if numalign == _DEFAULT_ALIGN else numalign | |
| stralign = "left" if stralign == _DEFAULT_ALIGN else stralign | |
| # 'colon_grid' uses colons in the line beneath the header to represent a column's | |
| # alignment instead of literally aligning the text differently. Hence, | |
| # left alignment of the data in the text output is enforced. | |
| if tablefmt == "colon_grid": | |
| colglobalalign = "left" | |
| headersglobalalign = "left" | |
| # optimization: look for ANSI control codes once, | |
| # enable smart width functions only if a control code is found | |
| # | |
| # convert the headers and rows into a single, tab-delimited string ensuring | |
| # that any bytestrings are decoded safely (i.e. errors ignored) | |
| plain_text = "\t".join( | |
| chain( | |
| # headers | |
| map(_to_str, headers), | |
| # rows: chain the rows together into a single iterable after mapping | |
| # the bytestring conversino to each cell value | |
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | |
| ) | |
| ) | |
| has_invisible = _ansi_codes.search(plain_text) is not None | |
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | |
| if ( | |
| not isinstance(tablefmt, TableFormat) | |
| and tablefmt in multiline_formats | |
| and _is_multiline(plain_text) | |
| ): | |
| tablefmt = multiline_formats.get(tablefmt, tablefmt) | |
| is_multiline = True | |
| else: | |
| is_multiline = False | |
| width_fn = _choose_width_fn(has_invisible, enable_widechars, is_multiline) | |
| # format rows and columns, convert numeric values to strings | |
| cols = list(izip_longest(*list_of_lists)) | |
| numparses = _expand_numparse(disable_numparse, len(cols)) | |
| coltypes = [_column_type(col, numparse=np) for col, np in zip(cols, numparses)] | |
| if isinstance(floatfmt, str): # old version | |
| float_formats = len(cols) * [ | |
| floatfmt | |
| ] # just duplicate the string to use in each column | |
| else: # if floatfmt is list, tuple etc we have one per column | |
| float_formats = list(floatfmt) | |
| if len(float_formats) < len(cols): | |
| float_formats.extend((len(cols) - len(float_formats)) * [_DEFAULT_FLOATFMT]) | |
| if isinstance(intfmt, str): # old version | |
| int_formats = len(cols) * [ | |
| intfmt | |
| ] # just duplicate the string to use in each column | |
| else: # if intfmt is list, tuple etc we have one per column | |
| int_formats = list(intfmt) | |
| if len(int_formats) < len(cols): | |
| int_formats.extend((len(cols) - len(int_formats)) * [_DEFAULT_INTFMT]) | |
| if isinstance(missingval, str): | |
| missing_vals = len(cols) * [missingval] | |
| else: | |
| missing_vals = list(missingval) | |
| if len(missing_vals) < len(cols): | |
| missing_vals.extend((len(cols) - len(missing_vals)) * [_DEFAULT_MISSINGVAL]) | |
| cols = [ | |
| [_format(v, ct, fl_fmt, int_fmt, miss_v, has_invisible) for v in c] | |
| for c, ct, fl_fmt, int_fmt, miss_v in zip( | |
| cols, coltypes, float_formats, int_formats, missing_vals | |
| ) | |
| for c, ct, fl_fmt, int_fmt, miss_v in zip(cols, coltypes, float_formats, int_formats, missing_vals) | |
| if len(missing_vals) < len(cols): | |
| missing_vals.extend((len(cols) - len(missing_vals)) * [_DEFAULT_MISSINGVAL]) | |
| cols = [ | |
| [_format(v, ct, fl_fmt, int_fmt, miss_v, has_invisible) for v in c] |
Comment on lines
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+855
| # enable smart width functions only if a control code is found | ||
| # | ||
| # convert the headers and rows into a single, tab-delimited string ensuring | ||
| # that any bytestrings are decoded safely (i.e. errors ignored) | ||
| plain_text = "\t".join( | ||
| chain( | ||
| # headers | ||
| map(_to_str, headers), | ||
| # rows: chain the rows together into a single iterable after mapping | ||
| # the bytestring conversino to each cell value | ||
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | ||
| ) | ||
| ) | ||
|
|
||
| has_invisible = _ansi_codes.search(plain_text) is not None | ||
|
|
||
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | ||
| if ( | ||
| not isinstance(tablefmt, TableFormat) | ||
| and tablefmt in multiline_formats | ||
| and _is_multiline(plain_text) | ||
| ): | ||
| tablefmt = multiline_formats.get(tablefmt, tablefmt) | ||
| is_multiline = True | ||
| else: | ||
| is_multiline = False | ||
| width_fn = _choose_width_fn(has_invisible, enable_widechars, is_multiline) | ||
|
|
||
| # format rows and columns, convert numeric values to strings | ||
| cols = list(izip_longest(*list_of_lists)) | ||
| numparses = _expand_numparse(disable_numparse, len(cols)) | ||
| coltypes = [_column_type(col, numparse=np) for col, np in zip(cols, numparses)] | ||
| if isinstance(floatfmt, str): # old version | ||
| float_formats = len(cols) * [ | ||
| floatfmt | ||
| ] # just duplicate the string to use in each column | ||
| else: # if floatfmt is list, tuple etc we have one per column | ||
| float_formats = list(floatfmt) | ||
| if len(float_formats) < len(cols): | ||
| float_formats.extend((len(cols) - len(float_formats)) * [_DEFAULT_FLOATFMT]) | ||
| if isinstance(intfmt, str): # old version | ||
| int_formats = len(cols) * [ | ||
| intfmt | ||
| ] # just duplicate the string to use in each column | ||
| else: # if intfmt is list, tuple etc we have one per column | ||
| int_formats = list(intfmt) | ||
| if len(int_formats) < len(cols): | ||
| int_formats.extend((len(cols) - len(int_formats)) * [_DEFAULT_INTFMT]) | ||
| if isinstance(missingval, str): | ||
| missing_vals = len(cols) * [missingval] | ||
| else: | ||
| missing_vals = list(missingval) | ||
| if len(missing_vals) < len(cols): | ||
| missing_vals.extend((len(cols) - len(missing_vals)) * [_DEFAULT_MISSINGVAL]) | ||
| cols = [ | ||
| [_format(v, ct, fl_fmt, int_fmt, miss_v, has_invisible) for v in c] | ||
| for c, ct, fl_fmt, int_fmt, miss_v in zip( | ||
| cols, coltypes, float_formats, int_formats, missing_vals | ||
| ) | ||
| ] | ||
|
|
||
| # align columns | ||
| # first set global alignment | ||
| if colglobalalign is not None: # if global alignment provided | ||
| aligns = [colglobalalign] * len(cols) | ||
| else: # default | ||
| aligns = [numalign if ct in [int, float] else stralign for ct in coltypes] | ||
| # then specific alignments | ||
| if colalign is not None: | ||
| assert isinstance(colalign, Iterable) | ||
| if isinstance(colalign, str): | ||
| warnings.warn( | ||
| f"As a string, `colalign` is interpreted as {[c for c in colalign]}. " | ||
| f'Did you mean `colglobalalign = "{colalign}"` or `colalign = ("{colalign}",)`?', | ||
| stacklevel=2, | ||
| ) | ||
| for idx, align in enumerate(colalign): | ||
| if not idx < len(aligns): | ||
| break | ||
| elif align != "global": | ||
| aligns[idx] = align | ||
| minwidths = ( | ||
| [width_fn(h) + min_padding for h in headers] if headers else [0] * len(cols) | ||
| ) | ||
| aligns_copy = aligns.copy() | ||
| # Reset alignments in copy of alignments list to "left" for 'colon_grid' format, | ||
| # which enforces left alignment in the text output of the data. | ||
| if tablefmt == "colon_grid": | ||
| aligns_copy = ["left"] * len(cols) | ||
| cols = [ | ||
| _align_column( | ||
| c, | ||
| a, | ||
| minw, | ||
| has_invisible, | ||
| enable_widechars, | ||
| is_multiline, | ||
| preserve_whitespace, | ||
| ) |
There was a problem hiding this comment.
⚡️Codeflash found 31% (0.31x) speedup for _pipe_line_with_colons
⏱️ Runtime : 4.35 milliseconds → 3.33 milliseconds (best of 215 runs)
📝 Explanation and details
To make the given Python program faster, we can improve the performance of the _pipe_line_with_colons function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version.
Explanation of Changes.
- Reduce Function Calls within Loops: By directly including the logic from
_pipe_segment_with_colonswithin the loop in_pipe_line_with_colons, we avoid the overhead of repeatedly calling the_pipe_segment_with_colonsfunction. - Optimize List Construction: We merged the list comprehension into a standard
forloop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. - Optimize Condition Check: Simplified the alignment checks by directly comparing the
alignvariable instead of storing and passing it around. This reduces the memory overhead.
This will result in decreased execution time particularly when processing larger tables.
✅ Correctness verification report:
| Test | Status |
|---|---|
| ?????? Existing Unit Tests | 🔘 None Found |
| ???? Inspired Regression Tests | 🔘 None Found |
| ???? Generated Regression Tests | ✅ 39 Passed |
| ??? Replay Tests | 🔘 None Found |
| ???? Concolic Coverage Tests | 🔘 None Found |
| 📊 Tests Coverage | undefined |
???? Generated Regression Tests Details
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality Tests
def test_single_column_default_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_multiple_columns_default_alignment():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["", "", ""])
# Specific Alignments Tests
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Mixed Alignments Tests
def test_multiple_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([3, 4, 5], ["left", "center", "right"])
codeflash_output = _pipe_line_with_colons([6, 7, 8], ["right", "decimal", "left"])
# Edge Cases Tests
def test_empty_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([], [])
def test_empty_colaligns_with_non_empty_colwidths():
codeflash_output = _pipe_line_with_colons([3, 4], [])
def test_non_empty_colaligns_with_empty_colwidths():
codeflash_output = _pipe_line_with_colons([], ["left", "right"])
def test_mismatched_lengths_of_colwidths_and_colaligns():
codeflash_output = _pipe_line_with_colons([3, 4], ["left"])
codeflash_output = _pipe_line_with_colons([3], ["left", "right"])
# Large Scale Test Cases
def test_large_number_of_columns():
codeflash_output = _pipe_line_with_colons([5] * 1000, ["left"] * 1000)
codeflash_output = _pipe_line_with_colons([3, 4, 5] * 1000, ["left", "center", "right"] * 1000)
def test_wide_columns():
codeflash_output = _pipe_line_with_colons([100], ["center"])
codeflash_output = _pipe_line_with_colons([200], ["right"])
# Performance and Scalability Tests
def test_performance_with_large_data_samples():
codeflash_output = _pipe_line_with_colons([10] * 10000, ["right"] * 10000)
codeflash_output = _pipe_line_with_colons([1, 2, 3, 4, 5] * 2000, ["left", "center", "right", "decimal", ""] * 2000)
# Special Characters in Alignment Tests
def test_special_characters_in_colaligns():
codeflash_output = _pipe_line_with_colons([5], ["unknown"])
codeflash_output = _pipe_line_with_colons([3, 4], ["left", "unknown"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import re
from collections import namedtuple
# imports
import pytest # used for our unit tests
import wcwidth
from codeflash.code_utils.tabulate import _pipe_line_with_colons
# unit tests
# Basic Functionality
def test_single_column_no_alignment():
codeflash_output = _pipe_line_with_colons([5], [""])
def test_single_column_left_alignment():
codeflash_output = _pipe_line_with_colons([5], ["left"])
def test_single_column_center_alignment():
codeflash_output = _pipe_line_with_colons([5], ["center"])
def test_single_column_right_alignment():
codeflash_output = _pipe_line_with_colons([5], ["right"])
def test_single_column_decimal_alignment():
codeflash_output = _pipe_line_with_colons([5], ["decimal"])
# Multiple Columns with Different Alignments
def test_two_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["left", "right"])
def test_three_columns_mixed_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["center", "decimal", "left"])
# Edge Cases
def test_empty_column_widths_and_alignments():
codeflash_output = _pipe_line_with_colons([], [])
def test_column_widths_without_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [])
def test_column_widths_with_empty_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["", ""])
def test_column_widths_with_partial_alignments():
codeflash_output = _pipe_line_with_colons([5, 7, 3], ["left", ""])
# Large Scale Test Cases
def test_large_number_of_columns_uniform():
colwidths = [5] * 1000
colaligns = ["right"] * 1000
expected_output = "|" + "|".join(["----:"] * 1000) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
def test_large_number_of_columns_mixed():
colwidths = [3, 5, 7] * 333 + [3]
colaligns = ["left", "center", "right"] * 333 + ["decimal"]
expected_output = "|" + "|".join([":--", ":---:", "------:"] * 333 + ["--:"]) + "|"
codeflash_output = _pipe_line_with_colons(colwidths, colaligns)
# Invalid Inputs (Assuming Function Should Handle Gracefully)
def test_negative_column_widths():
codeflash_output = _pipe_line_with_colons([-5, 7], ["left", "right"])
def test_non_string_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [None, "right"])
# Mixed Data Types in Alignments
def test_integers_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [1, "right"])
def test_booleans_and_strings_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], [True, "right"])
# Special Characters in Alignments
def test_special_characters_in_alignments():
codeflash_output = _pipe_line_with_colons([5, 7], ["#", "right"])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.To test or edit this optimization locally git merge codeflash/optimize-pr35-2025-04-01T22.53.38
Suggested change
| # enable smart width functions only if a control code is found | |
| # | |
| # convert the headers and rows into a single, tab-delimited string ensuring | |
| # that any bytestrings are decoded safely (i.e. errors ignored) | |
| plain_text = "\t".join( | |
| chain( | |
| # headers | |
| map(_to_str, headers), | |
| # rows: chain the rows together into a single iterable after mapping | |
| # the bytestring conversino to each cell value | |
| chain.from_iterable(map(_to_str, row) for row in list_of_lists), | |
| ) | |
| ) | |
| has_invisible = _ansi_codes.search(plain_text) is not None | |
| enable_widechars = wcwidth is not None and WIDE_CHARS_MODE | |
| if ( | |
| not isinstance(tablefmt, TableFormat) | |
| and tablefmt in multiline_formats | |
| and _is_multiline(plain_text) | |
| ): | |
| tablefmt = multiline_formats.get(tablefmt, tablefmt) | |
| is_multiline = True | |
| else: | |
| is_multiline = False | |
| width_fn = _choose_width_fn(has_invisible, enable_widechars, is_multiline) | |
| # format rows and columns, convert numeric values to strings | |
| cols = list(izip_longest(*list_of_lists)) | |
| numparses = _expand_numparse(disable_numparse, len(cols)) | |
| coltypes = [_column_type(col, numparse=np) for col, np in zip(cols, numparses)] | |
| if isinstance(floatfmt, str): # old version | |
| float_formats = len(cols) * [ | |
| floatfmt | |
| ] # just duplicate the string to use in each column | |
| else: # if floatfmt is list, tuple etc we have one per column | |
| float_formats = list(floatfmt) | |
| if len(float_formats) < len(cols): | |
| float_formats.extend((len(cols) - len(float_formats)) * [_DEFAULT_FLOATFMT]) | |
| if isinstance(intfmt, str): # old version | |
| int_formats = len(cols) * [ | |
| intfmt | |
| ] # just duplicate the string to use in each column | |
| else: # if intfmt is list, tuple etc we have one per column | |
| int_formats = list(intfmt) | |
| if len(int_formats) < len(cols): | |
| int_formats.extend((len(cols) - len(int_formats)) * [_DEFAULT_INTFMT]) | |
| if isinstance(missingval, str): | |
| missing_vals = len(cols) * [missingval] | |
| else: | |
| missing_vals = list(missingval) | |
| if len(missing_vals) < len(cols): | |
| missing_vals.extend((len(cols) - len(missing_vals)) * [_DEFAULT_MISSINGVAL]) | |
| cols = [ | |
| [_format(v, ct, fl_fmt, int_fmt, miss_v, has_invisible) for v in c] | |
| for c, ct, fl_fmt, int_fmt, miss_v in zip( | |
| cols, coltypes, float_formats, int_formats, missing_vals | |
| ) | |
| ] | |
| # align columns | |
| # first set global alignment | |
| if colglobalalign is not None: # if global alignment provided | |
| aligns = [colglobalalign] * len(cols) | |
| else: # default | |
| aligns = [numalign if ct in [int, float] else stralign for ct in coltypes] | |
| # then specific alignments | |
| if colalign is not None: | |
| assert isinstance(colalign, Iterable) | |
| if isinstance(colalign, str): | |
| warnings.warn( | |
| f"As a string, `colalign` is interpreted as {[c for c in colalign]}. " | |
| f'Did you mean `colglobalalign = "{colalign}"` or `colalign = ("{colalign}",)`?', | |
| stacklevel=2, | |
| ) | |
| for idx, align in enumerate(colalign): | |
| if not idx < len(aligns): | |
| break | |
| elif align != "global": | |
| aligns[idx] = align | |
| minwidths = ( | |
| [width_fn(h) + min_padding for h in headers] if headers else [0] * len(cols) | |
| ) | |
| aligns_copy = aligns.copy() | |
| # Reset alignments in copy of alignments list to "left" for 'colon_grid' format, | |
| # which enforces left alignment in the text output of the data. | |
| if tablefmt == "colon_grid": | |
| aligns_copy = ["left"] * len(cols) | |
| cols = [ | |
| _align_column( | |
| c, | |
| a, | |
| minw, | |
| has_invisible, | |
| enable_widechars, | |
| is_multiline, | |
| preserve_whitespace, | |
| ) | |
| if align != "global": | |
| minwidths = [width_fn(h) + min_padding for h in headers] if headers else [0] * len(cols) | |
| if tab2025-03-31T20:57:26.923907489Z lefmt == "colon_grid": | |
| _align_column(c, a, minw, has_invisible, enable_widechars, is_multiline, preserve_whitespace) | |
| ) | |
| for idx, align in enumerate(colalign): | |
| if not idx < len(aligns): | |
| break | |
| aligns[idx] = align | |
| aligns_copy = aligns.copy() | |
| # Reset alignments in copy of alignments list to "left" for 'colon_grid' format, | |
| # which enforces left alignment in the text output of the data. | |
| aligns_copy = ["left"] * len(cols) | |
| cols = [ |
codeflash-ai bot
added a commit
that referenced
this pull request
Apr 1, 2025
…-profiler`) To make the given Python program faster, we can improve the performance of the `_pipe_line_with_colons` function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version. ### Explanation of Changes. 1. **Reduce Function Calls within Loops**: By directly including the logic from `_pipe_segment_with_colons` within the loop in `_pipe_line_with_colons`, we avoid the overhead of repeatedly calling the `_pipe_segment_with_colons` function. 2. **Optimize List Construction**: We merged the list comprehension into a standard `for` loop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. 3. **Optimize Condition Check**: Simplified the alignment checks by directly comparing the `align` variable instead of storing and passing it around. This reduces the memory overhead. This will result in decreased execution time particularly when processing larger tables.
alvin-r
reviewed
Apr 1, 2025
| return arr.sort() | ||
| """ | ||
| assert code_write_path.read_text("utf-8") == expected_code_main | ||
| finally: |
There was a problem hiding this comment.
it's a temp file
alvin-r
reviewed
Apr 1, 2025
codeflash-ai bot
added a commit
that referenced
this pull request
Apr 1, 2025
…filer`) To optimize the given Python program, we need to analyze the line profiling results and identify the most time-consuming parts of the code. Based on the profiling data, the most significant time spent is on `module.visit(transformer)` and `cst.parse_module(original_code)`. 1. `cst.parse_module(original_code)` - This line is responsible for parsing the original code string into a CST node. It is crucial and necessary, but we can ensure that the input `original_code` is optimized and minimized before parsing. 2. `module.visit(transformer)` - The visit method traverses the CST and applies transformations. The transformation itself needs to be examined and potentially optimized to reduce time complexity. Since the given code itself is tight and straightforward, optimization will focus on ensuring efficiency in the transformations made by `ProfileEnableTransformer`. However, without details about the implementation of `ProfileEnableTransformer`, we can suggest general strategies. - Minimize passes over the CST nodes by combining transformations where possible. - Optimize the transformation logic within `ProfileEnableTransformer`. assuming these transformers and parsers perform minimal redundant operations. In the rewritten code. 1. `has_transformable_content` is introduced to quickly check if the transformation is even needed before proceeding with the heavier operations. This can save time if most of the files do not need transformation. 2. The original code is verified for being non-empty. 3. The `ProfileEnableTransformer` logic is stubbed for simplicity, assuming the key operations are optimized. To further optimize, you'd need to inspect and optimize the `ProfileEnableTransformer` itself based on the specific transformations applied to the CST nodes.
⚡️ Codeflash found optimizations for this PR📄 17% (0.17x) speedup for
|
KRRT7
reviewed
Apr 1, 2025
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my understanding is that 'rich' somehow prints to the console even when we want to get a string out and we might have word wrapping issues with different console sizes
There was a problem hiding this comment.
rich handles all of this yes. it will word wrap, adjust to the console etc etc
codeflash-ai bot
added a commit
that referenced
this pull request
Apr 2, 2025
…-profiler`) To make the given Python program faster, we can improve the performance of the `_pipe_line_with_colons` function by avoiding repeated creation of temporary lists in the list comprehension and minimizing function calls within loops. Here's a rewritten version. ### Explanation of Changes. 1. **Reduce Function Calls within Loops**: By directly including the logic from `_pipe_segment_with_colons` within the loop in `_pipe_line_with_colons`, we avoid the overhead of repeatedly calling the `_pipe_segment_with_colons` function. 2. **Optimize List Construction**: We merged the list comprehension into a standard `for` loop, which makes the logic clearer and avoids temporary list creation overhead in an intermediate step. 3. **Optimize Condition Check**: Simplified the alignment checks by directly comparing the `align` variable instead of storing and passing it around. This reduces the memory overhead. This will result in decreased execution time particularly when processing larger tables.
⚡️ Codeflash found optimizations for this PR📄 31% (0.31x) speedup for
|
codeflash-ai bot
added a commit
that referenced
this pull request
Apr 2, 2025
…ine-profiler`) To optimize the function `_pipe_segment_with_colons` for faster execution, we can simplify the logic by reducing string concatenations and condition checks. Let's rewrite the function. Changes made. 1. Used f-strings for simpler and potentially faster string formatting. 2. Combined the checks for `right` and `decimal` alignments to reduce redundant checks and increase branch prediction efficiency. The core logic and return values remain the same, while the function should perform faster due to simplified string operations and fewer condition checks.
|
@aseembits93 is this ready to merge now? |
|
@misrasaurabh1 ready to merge |
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User description
just the todos here. will edit the description when done.
PR Type
Description
Introduce line profiler API endpoint in aiservice.
Add utilities to inject decorators and enable line profiling.
Update optimizer to use line profiler results.
Enhance tests to validate line profiler integration.
Changes walkthrough 📝
9 files
Add class method sorting function using nested classAdd nested class method sorting function using WrapperClassIntroduce API call for line profiler optimizationCreate utilities for decorator injection and profile enablementAdd comprehensive tabulate functionality for profiling outputExtend models with line profiler results and enumIntegrate and process line profiler results in optimizerImplement parsing and text display for line profiler outputAdd support for running line profiler tests via pytest1 files
Update tests to validate line profiler instrumentation and parsing