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Fix e2e test and bubble sort test discovery

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afik.cohen 2024-01-04 18:59:03 -08:00
parent 6a9dd684e4
commit 15c9c17670
7 changed files with 21 additions and 10 deletions
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3
code_to_optimize/bubble_sort_deps.py
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@ -1,7 +1,6 @@
from code_to_optimize.bubble_sort_dep1_helper import dep1_comparer
from code_to_optimize.bubble_sort_dep2_swap import dep2_swap
from cli.code_to_optimize.bubble_sort_dep1_helper import dep1_comparer
def sorter_deps(arr):
for i in range(len(arr)):

2
code_to_optimize/tests/pytest/test_bubble_sort.py
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@ -1,4 +1,4 @@
from cli.code_to_optimize.bubble_sort import sorter
from code_to_optimize.bubble_sort import sorter
def test_sort():

2
code_to_optimize/tests/pytest/test_bubble_sort_in_class.py
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@ -1,4 +1,4 @@
from cli.code_to_optimize.bubble_sort import sorter
from code_to_optimize.bubble_sort import sorter
class TestSorter:

2
code_to_optimize/tests/pytest/test_pig_latin.py
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@ -1,6 +1,6 @@
import pickle
from cli.code_to_optimize.pig_latin import pig_latin
from code_to_optimize.pig_latin import pig_latin
def log_test_values(values, test_name):

2
code_to_optimize/tests/unittest/test_bubble_sort.py
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@ -1,6 +1,6 @@
import unittest
from cli.code_to_optimize.bubble_sort import sorter
from code_to_optimize.bubble_sort import sorter
class TestPigLatin(unittest.TestCase):

2
code_to_optimize/use_cosine_similarity_from_other_file.py
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@ -1,6 +1,6 @@
from typing import Optional, List, Tuple
from cli.code_to_optimize.math_utils import cosine_similarity_top_k, Matrix
from code_to_optimize.math_utils import cosine_similarity_top_k, Matrix
def use_cosine_similarity(

18
codeflash/main.py
View file

@ -191,6 +191,7 @@ class Optimizer:
logging.info("No functions found to optimize. Exiting...")
return
function_to_tests: dict[str, list[TestsInFile]] = discover_unit_tests(self.test_cfg)
logging.info(f"Found {len(function_to_tests.values())} existing unit tests.")
for path in file_to_funcs_to_optimize:
logging.info(f"Examining file {path} ...")
# TODO: Sequence the functions one goes through intelligently. If we are optimizing f(g(x)), then we might want to first
@ -547,13 +548,24 @@ class Optimizer:
f.write(explanation_final)
f.write("\n---------\n")
subprocess.run(["black", path], stdout=subprocess.PIPE)
logging.info("Formatting code with black... ")
result = subprocess.run(
["black", path], stdout=subprocess.PIPE, stderr=subprocess.PIPE
)
if result.returncode == 0:
logging.info("OK")
else:
logging.error("Failed to format")
test_files_to_preserve.add(generated_tests_path)
logging.info(
f"⚡️ Optimization successful! 📄 {function_name} in {path} 📈 {speedup * 100:.2f}% ({speedup:.2f}x) faster"
)
pr: Optional[int] = env_utils.get_pr_number()
if pr is not None:
logging.info(f"Suggesting changes to PR #{pr}")
logging.info(f"Suggesting changes to PR #{pr} ...")
owner, repo = get_repo_owner_and_name()
cfapi.suggest_changes(
@ -581,7 +593,7 @@ class Optimizer:
if os.path.exists(generated_tests_path):
os.remove(generated_tests_path)
if not self.found_atleast_one_optimization:
logging.info(f"No optimizations found.")
logging.info(f"❌ No optimizations found.")
finally:
# TODO: Also revert the file/function being optimized if the process did not succeed