mirror of
https://github.com/GoogleCloudPlatform/vertex-ai-samples.git
synced 2026-09-26 14:42:04 +00:00
Ci cd 2 (#1802)
* update: record tallied results to GCS bucket * fix: test percent * update: accumulator support * fix: use args for where to store results * fix: args for results file * fix: gs bucket ptrfix * fix: tuning args * fix: ci/cd test on openin artifacts bucket * fix: 2nd try at bucket issue * fix: 2nd try at bucket issue * debug: bucket issue * debug: bucket issue * debug: bucket issue * debug: bucket issue * debug: bucket issue * debug: bucket issue * debug: no entries written * debug: no entries written * debug: not accumulating * debug: not accumulating * debug: not accumulating * debug: not accumulating * Update requirements.txt * debug: not accumulating * debug: not accumulating * debug: matching notebook name * debug: pandas problem * debug: import issues * debug: load * Update requirements.txt * Update requirements.txt * debug: read csv * debug: read csv * debug: read csv * debug: indxer * debug: indexer * debug: accum * debug: accum * debug: accum * debug: accum * debug: accum * debug: accum * debug: accum * debug: casting * debug: casting * debug: casting * debug: casting * debug: duration nit * debug: duration nit * fix: flaky * fix: BUILD_ID * fix: BUILD_ID * fix: BUILD_ID * fix: BUILD_ID * fix: BUILD_ID * fix: BUILD_ID * fix: BUILD_ID * fix: review * fix: review * fix: review * fix: biz logic * fix: biz logic * fix: review * fix: build_id required * fix: use json format * review: JSON simplifing * review: JSON simplifing * update: NotbookExecutionResult updates * fix: revert to JSON * update: use util to read from bucket * fix: remove pandas inmport
This commit is contained in:
@@ -17,7 +17,7 @@
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import argparse
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import pathlib
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import random
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import os
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import execute_changed_notebooks_helper
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@@ -47,6 +47,12 @@ parser.add_argument(
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required=False,
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default=100,
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)
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parser.add_argument(
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"--build_id",
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type=str,
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help="The build id (which may be a Cloud Build job specific or user explicit.",
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required=True
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)
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parser.add_argument(
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"--base_branch",
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help="The base git branch to diff against to find changed files.",
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@@ -129,26 +135,35 @@ changed_notebooks = execute_changed_notebooks_helper.get_changed_notebooks(
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base_branch=args.base_branch,
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)
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results_bucket = f"{args.artifacts_bucket}"
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results_file = f"{args.build_id}.json"
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if args.test_percent == 100:
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notebooks = changed_notebooks
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accumulative_results = {}
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else:
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notebooks = [changed_notebook for changed_notebook in changed_notebooks if random.randint(1, 100) < args.test_percent]
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accumulative_results = execute_changed_notebooks_helper.load_results(results_bucket, results_file)
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notebooks = [changed_notebook for changed_notebook in changed_notebooks if execute_changed_notebooks_helper.select_notebook(changed_notebook, accumulative_results, args.test_percent)]
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if args.dry_run:
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print("Dry run ...\n")
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for notebook in notebooks:
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print(f"Would execute: {notebook.path}")
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print(f"Would execute: {notebook}")
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else:
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execute_changed_notebooks_helper.process_and_execute_notebooks(
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notebooks=notebooks,
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container_uri=args.container_uri,
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staging_bucket=args.staging_bucket,
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artifacts_bucket=args.artifacts_bucket,
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results_file=results_file,
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accumulative_results=accumulative_results,
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should_parallelize=args.should_parallelize,
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timeout=args.timeout,
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variable_project_id=args.variable_project_id,
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variable_region=args.variable_region,
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variable_service_account=args.variable_service_account,
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variable_vpc_network=args.variable_vpc_network,
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private_pool_id=args.private_pool_id,
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private_pool_id=args.private_pool_id
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)
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@@ -21,11 +21,15 @@ import json
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import git
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import operator
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import os
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import io
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import json
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import pathlib
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import re
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import subprocess
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import random
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from google.cloud import storage
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import utils
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from typing import List, Optional
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from typing import List, Optional, Dict, Any
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from utils import util
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import execute_notebook_helper
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@@ -65,7 +69,9 @@ def format_timedelta(delta: datetime.timedelta) -> str:
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@dataclasses.dataclass
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class NotebookExecutionResult:
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name: str
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path: str
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duration: datetime.timedelta
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start_time: datetime.datetime
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is_pass: bool
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log_url: str
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output_uri: str
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@@ -80,6 +86,40 @@ class NotebookExecutionResult:
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else:
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return None
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def load_results(results_bucket: str,
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results_file: str) -> Dict[str,Any]:
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'''
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Load accumulated notebook test results
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'''
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print("Loading existing accumulative results ...")
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accumulative_results = {}
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try:
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content = util.download_blob_into_memory(results_bucket, results_file, download_as_text=True)
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accumulative_results = json.loads(content)
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print(accumulative_results)
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except Exception as e:
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print(e)
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# If there are no accumulative results, an empty dict is returned
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return accumulative_results
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def select_notebook(changed_notebook: str,
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accumulative_results: Dict[str, Any],
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test_percent: int) -> bool:
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'''
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Algorithm to randomly select a notebook, but weight the propbability of selected based on past failures
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'''
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if changed_notebook in accumulative_results:
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pass_count = accumulative_results[changed_notebook]['passed']
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fail_count = accumulative_results[changed_notebook]['failed']
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else:
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pass_count = 1
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fail_count = 0
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return (random.randint(1, 100) * (1 + (fail_count / (pass_count + fail_count))) < test_percent)
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def _process_notebook(
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notebook_path: str,
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@@ -191,7 +231,9 @@ def process_and_execute_notebook(
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result = NotebookExecutionResult(
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name=tag,
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path=notebook,
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duration=datetime.timedelta(seconds=0),
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start_time=datetime.datetime.now(),
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is_pass=False,
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output_uri=notebook_output_uri,
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log_url="",
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@@ -201,7 +243,6 @@ def process_and_execute_notebook(
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)
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# TODO: Handle cases where multiple notebooks have the same name
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time_start = datetime.datetime.now()
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operation = None
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try:
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# Get the python version for running the notebook if specified
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@@ -247,9 +288,10 @@ def process_and_execute_notebook(
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# Block and wait for the result
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operation_result = operation.result(timeout=timeout_in_seconds)
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result.duration = datetime.datetime.now() - time_start
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result.duration = datetime.datetime.now() - result.start_time
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result.is_pass = True
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print(f"{notebook} PASSED in {format_timedelta(result.duration)}.")
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except Exception as error:
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result.error_message = str(error)
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@@ -268,7 +310,7 @@ def process_and_execute_notebook(
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except Exception as error:
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result.error_message = str(error)
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result.duration = datetime.datetime.now() - time_start
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result.duration = datetime.datetime.now() - result.start_time
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result.is_pass = False
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print(
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@@ -336,12 +378,54 @@ def get_changed_notebooks(
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return notebooks
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def _save_results(results: List[NotebookExecutionResult],
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accumulative_results: Dict[str,Any],
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artifacts_bucket: str,
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results_file: str):
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artifacts_bucket = artifacts_bucket.replace("gs://", "").split('/')[0]
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print("Updating accumulative results ...")
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for result in results:
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if result.path in accumulative_results:
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accumulative_results[result.path]['duration'] = result.duration.total_seconds()
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accumulative_results[result.path]['start_time'] = str(result.start_time)
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if result.is_pass:
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accumulative_results[result.path]['passed'] += 1
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else:
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accumulative_results[result.path]['failed'] += 1
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print(f"updating {result.path}")
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else:
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if result.is_pass:
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pass_count = 1
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fail_count = 0
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else:
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pass_count = 0
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fail_count = 1
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accumulative_results[result.path] = {
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'duration': result.duration.total_seconds(),
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'start_time': str(result.start_time),
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'passed': pass_count,
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'failed': fail_count
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}
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print(f"adding {result.path}")
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print("Saving accumulative results ...")
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content = json.dumps(accumulative_results)
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client = storage.Client()
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bucket = client.get_bucket(artifacts_bucket)
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bucket.blob(str(results_file)).upload_from_string(content, 'text/json')
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def process_and_execute_notebooks(
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notebooks: List[str],
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container_uri: str,
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staging_bucket: str,
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artifacts_bucket: str,
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results_file: str,
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accumulative_results: List[NotebookExecutionResult],
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should_parallelize: bool,
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timeout: int,
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variable_project_id: str,
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@@ -369,6 +453,10 @@ def process_and_execute_notebooks(
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Required. The GCS staging bucket to write source code to.
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artifacts_bucket (str):
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Required. The GCS staging bucket to write executed notebooks to.
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results_file (str):
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Required: The path to the artifacts bucket to save results
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accumulative_results (List):
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Required: The in-memory previous accumulative notebook CI/CD test results.
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variable_project_id (str):
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Required. The value for PROJECT_ID to inject into notebooks.
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variable_region (str):
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@@ -471,7 +559,7 @@ def process_and_execute_notebooks(
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print("=" * 100)
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build_id = results_sorted[0].build_id
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logs_bucket_name = (results_sorted[0].logs_bucket).removeprefix("gs://")
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logs_bucket_name = (results_sorted[0].logs_bucket).replace("gs://", "")
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log_file_name = f"log-{build_id}.txt"
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log_contents = util.download_blob_into_memory(
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@@ -489,6 +577,11 @@ def process_and_execute_notebooks(
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else:
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print(log_contents)
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_save_results(results_sorted,
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accumulative_results,
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artifacts_bucket,
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results_file)
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print("\n=== END RESULTS===\n")
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total_notebook_duration = functools.reduce(
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@@ -36,7 +36,7 @@ steps:
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- -c
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- |
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. workspace/env/bin/activate &&
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python3 .cloud-build/execute_changed_notebooks_cli.py --test_paths_file "${_TEST_PATHS_FILE}" --base_branch "${_FORCED_BASE_BRANCH}" --container_uri ${_PYTHON_IMAGE} --staging_bucket ${_GCS_STAGING_BUCKET} --artifacts_bucket ${_GCS_STAGING_BUCKET}/executed_notebooks/PR_${_PR_NUMBER}/BUILD_${BUILD_ID} --variable_project_id ${PROJECT_ID} --variable_region ${_GCP_REGION} --variable_service_account ${_GCP_SERVICE_ACCOUNT} --variable_vpc_network "${_GPC_VPC_NETWORK_NAME}" `if [ ! -z "${_PRIVATE_POOL_NAME}" ]; then echo "--private_pool_id ${_PRIVATE_POOL_NAME}"; fi`
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python3 .cloud-build/execute_changed_notebooks_cli.py --test_paths_file "${_TEST_PATHS_FILE}" --base_branch "${_FORCED_BASE_BRANCH}" --container_uri ${_PYTHON_IMAGE} --staging_bucket ${_GCS_STAGING_BUCKET} --artifacts_bucket ${_GCS_STAGING_BUCKET}/executed_notebooks/PR_${_PR_NUMBER}/BUILD_${BUILD_ID} --variable_project_id ${PROJECT_ID} --variable_region ${_GCP_REGION} --variable_service_account ${_GCP_SERVICE_ACCOUNT} --variable_vpc_network "${_GPC_VPC_NETWORK_NAME}" `if [ ! -z "${_PRIVATE_POOL_NAME}" ]; then echo "--private_pool_id ${_PRIVATE_POOL_NAME}"; fi` --build_id ${BUILD_ID}
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env:
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- 'IS_TESTING=1'
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timeout: 86400s
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@@ -3,12 +3,15 @@ numpy
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jupyter
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nbconvert
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papermill
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pandas
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matplotlib
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tabulate
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google-cloud-aiplatform
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google-cloud-storage
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google-cloud-build
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google-cloud-storage
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ratemate
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GitPython
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tqdm
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fsspec
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pandas
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