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Upload 3 files
Browse files- app.py +32 -0
- requirements.txt +3 -0
- utils.py +133 -0
app.py
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import gradio as gr
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import utils
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DESCRIPTION = """
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This Space helps you find out the top-n slow tests from a particular GitHub Action run step. It also buckets the tests w.r.t their durations.
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"""
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ARTICLE = """
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To obtain the article name you're looking for, you need to scroll down the run page (for [example](https://github.com/huggingface/diffusers/actions/runs/8430950874/)) and select one from the 'Artifacts' section.
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"""
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with gr.Interface(
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fn=utils.analyze_tests,
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inputs=[
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gr.Textbox(info="GitHub repository ID", placeholder="huggingface/diffusers"),
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gr.Textbox(placeholder="GitHub token", type="password"),
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gr.Textbox(placeholder="GitHub Action run ID"),
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gr.Textbox(info="Artifact name", placeholder="pr_flax_cpu_test_reports"),
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gr.Slider(2, 20, value=1, label="top-n", info="Top-n slow tests."),
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],
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outputs=gr.Markdown(label="output"),
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examples=[
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['huggingface/diffusers', 'ghp_XXX', '8430950874', 'pr_torch_cpu_pipelines_test_reports', 5],
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],
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title="Short analysis of PR tests!",
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description=DESCRIPTION,
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article=ARTICLE,
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allow_flagging="never",
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cache_examples=False,
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) as demo:
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demo.queue()
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demo.launch(show_error=True)
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requirements.txt
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zipfile
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tempfile
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requests
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utils.py
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import requests
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import zipfile
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import tempfile
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def group_tests_by_duration(file_path: str) -> dict:
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# Define the buckets and their labels
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buckets = [(0, 5), (5, 10), (10, 15), (15, 20), (20, float('inf'))]
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bucket_names = ["0-5s", "5-10s", "10-15s", "15-20s", ">20s"]
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test_groups = {name: [] for name in bucket_names}
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# Process the file with error handling
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with open(file_path, 'r') as file:
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for line in file:
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try:
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parts = line.split()
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# Extracting duration and test name, ignoring lines that don't match expected format
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if len(parts) >= 3 and 's' in parts[0]:
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duration = float(parts[0].rstrip('s')) # Remove 's' and convert to float
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test_name = ' '.join(parts[2:]) # Join back the test name parts
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# Assign test to the correct bucket based on duration
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for (start, end), bucket_name in zip(buckets, bucket_names):
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if start <= duration < end:
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test_groups[bucket_name].append((duration, test_name))
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break
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except ValueError:
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# Skip lines that cannot be parsed properly
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continue
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return test_groups
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def extract_top_n_tests(file_path, n=10):
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test_durations = []
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# Reading and processing the file
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with open(file_path, 'r') as file:
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for line in file:
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parts = line.split()
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if len(parts) >= 3 and parts[1] == 'call':
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duration_s = parts[0].rstrip('s') # Remove the 's' from the duration
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try:
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duration = float(duration_s)
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test_name = ' '.join(parts[2:])
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test_durations.append((duration, test_name))
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except ValueError:
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# Skip lines that cannot be converted to float
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continue
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# Sort the list in descending order of duration
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test_durations.sort(reverse=True, key=lambda x: x[0])
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# Extract the top N tests
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top_n_tests = {test[1]: f"{test[0]}s"
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for i, test in enumerate(test_durations[:n])}
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return top_n_tests
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def fetch_test_duration_artifact(repo_id, token, run_id, artifact_name):
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# Construct the API URL
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owner_repo = repo_id.split("/")
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artifacts_url = f'https://api.github.com/repos/{owner_repo[0]}/{owner_repo[1]}/actions/runs/{run_id}/artifacts'
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# Set up the headers with your authentication token
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headers = {'Authorization': f'token {token}'}
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# Send the request to get a list of artifacts from the specified run
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response = requests.get(artifacts_url, headers=headers)
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response.raise_for_status() # Raise an exception for HTTP error responses
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# Search for the artifact with the specified name
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download_url = None
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for artifact in response.json().get('artifacts', []):
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if artifact['name'] == artifact_name:
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download_url = artifact['archive_download_url']
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break
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if download_url:
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# Download the artifact
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download_response = requests.get(download_url, headers=headers, stream=True)
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download_response.raise_for_status()
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# Save the downloaded artifact to a file
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zip_file_path = f'{artifact_name}.zip'
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with open(zip_file_path, 'wb') as file:
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for chunk in download_response.iter_content(chunk_size=128):
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file.write(chunk)
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# Extract the duration text file
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with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:
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# Check if the specified file exists in the zip
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zip_files = zip_ref.namelist()
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for file in zip_files:
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if "duration" in file:
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zip_ref.extract(file, ".")
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break
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return file
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else:
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raise ValueError("Error 🥲")
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def format_to_markdown_str(test_bucket_map, top_n_slow_tests, repo_id, run_id, artifact_name):
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run_url = f"https://github.com/{repo_id}/actions/runs/{run_id}/"
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markdown_str = f"""
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## Top {len(top_n_slow_tests)} slow test for {artifact_name}\n
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"""
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for test, duration in top_n_slow_tests.items():
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markdown_str += f"* {test.split('/')[-1]}: {duration}\n"
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markdown_str += """
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## Bucketed durations of the tests\n
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"""
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for bucket, num_tests in test_bucket_map.items():
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if ">" in bucket:
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bucket = f"\{bucket}"
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markdown_str += f"* {bucket}: {num_tests} tests\n"
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markdown_str += f"\nRun URL: [{run_url}]({run_url})."
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return markdown_str
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def analyze_tests(repo_id, token, run_id, artifact_name, top_n):
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test_duration_file = fetch_test_duration_artifact(repo_id=repo_id, token=token, run_id=run_id, artifact_name=artifact_name)
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grouped_tests_map = group_tests_by_duration(test_duration_file)
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test_bucket_map = {bucket: len(tests) for bucket, tests in grouped_tests_map.items()}
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print(test_bucket_map)
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top_n_slow_tests = extract_top_n_tests(test_duration_file, n=top_n)
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print(top_n_slow_tests)
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return format_to_markdown_str(test_bucket_map, top_n_slow_tests, repo_id, run_id, artifact_name)
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