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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,147 @@ | ||
| # Copyright 2023 Google LLC | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| import argparse | ||
| import importlib | ||
| import inspect | ||
| import sys | ||
| from typing import Dict, List | ||
|
|
||
| import bigframes | ||
| import bigframes.pandas as bpd | ||
|
|
||
| PRESENT = "present" | ||
| NOT_PRESENT = "not_present" | ||
|
|
||
| CLASSES = [ | ||
| bpd.DataFrame, | ||
| bpd.Series, | ||
| bpd.Index, | ||
| bigframes.session.Session, | ||
| bigframes.operations.strings.StringMethods, | ||
| bigframes.operations.datetimes.DatetimeMethods, | ||
| bigframes.operations.structs.StructAccessor, | ||
| ] | ||
|
|
||
| ML_MODULE_NAMES = [ | ||
| "cluster", | ||
| "compose", | ||
| "decomposition", | ||
| "ensemble", | ||
| "linear_model", | ||
| "metrics", | ||
| "model_selection", | ||
| "pipeline", | ||
| "preprocessing", | ||
| "llm", | ||
| "forecasting", | ||
| "imported", | ||
| "remote", | ||
| ] | ||
|
|
||
| for module_name in ML_MODULE_NAMES: | ||
| module = importlib.import_module(f"bigframes.ml.{module_name}") | ||
| classes_ = [ | ||
| class_ for _, class_ in inspect.getmembers(module, predicate=inspect.isclass) | ||
| ] | ||
| CLASSES.extend(classes_) | ||
|
|
||
|
|
||
| def get_code_samples_summary() -> Dict[str, Dict[str, List[str]]]: | ||
| """Get Summary of the code samples coverage in BigFrames APIs. | ||
| Returns: | ||
| Summary: A dictionary of the format | ||
| { | ||
| class_1: { | ||
| "present": [method1, method2, ...], | ||
| "not_present": [method3, method4, ...] | ||
| }, | ||
| class_2: { | ||
| ... | ||
| } | ||
| } | ||
| """ | ||
| summary: Dict[str, Dict[str, List[str]]] = dict() | ||
|
|
||
| for class_ in CLASSES: | ||
| class_key = f"{class_.__module__}.{class_.__name__}" | ||
| summary[class_key] = {PRESENT: [], NOT_PRESENT: []} | ||
|
|
||
| members = inspect.getmembers(class_) | ||
|
|
||
| for name, obj in members: | ||
| # ignore private methods | ||
| if name.startswith("_") and not name.startswith("__"): | ||
| continue | ||
|
|
||
| def predicate(impl): | ||
| return ( | ||
| # This includes class methods like `from_dict`, `from_records` | ||
| inspect.ismethod(impl) | ||
| # This includes instance methods like `dropna`, join` | ||
| or inspect.isfunction(impl) | ||
| # This includes properties like `shape`, `values` but not | ||
| # generic properties like `__weakref__` | ||
| or (inspect.isdatadescriptor(impl) and not name.startswith("__")) | ||
| ) | ||
|
|
||
| if not predicate(obj): | ||
| continue | ||
|
|
||
| # At this point we have a property or a public method | ||
| impl = getattr(class_, name) | ||
|
|
||
| docstr = inspect.getdoc(impl) | ||
| code_samples_present = docstr and "**Examples:**" in docstr | ||
| key = PRESENT if code_samples_present else NOT_PRESENT | ||
| summary[class_key][key].append(name) | ||
|
|
||
| return summary | ||
|
|
||
|
|
||
| if __name__ == "__main__": | ||
| parser = argparse.ArgumentParser( | ||
| description="Get a summary of code samples coverage in BigFrames APIs." | ||
| ) | ||
| parser.add_argument( | ||
| "-d", | ||
| "--details", | ||
| type=bool, | ||
| action=argparse.BooleanOptionalAction, | ||
| default=False, | ||
| help="Whether to print APIs with and without code samples.", | ||
| ) | ||
|
|
||
| args = parser.parse_args(sys.argv[1:]) | ||
|
|
||
| summary = get_code_samples_summary() | ||
|
|
||
| total_with_code_samples = 0 | ||
| total = 0 | ||
| for class_, class_summary in summary.items(): | ||
| apis_with_code_samples = len(class_summary[PRESENT]) | ||
| total_with_code_samples += apis_with_code_samples | ||
|
|
||
| apis_total = len(class_summary[PRESENT]) + len(class_summary[NOT_PRESENT]) | ||
| total += apis_total | ||
|
|
||
| coverage = 100 * apis_with_code_samples / apis_total | ||
| print(f"{class_}: {coverage:.1f}% ({apis_with_code_samples}/{apis_total})") | ||
| if args.details: | ||
| print(f"===> APIs WITH code samples: {class_summary[PRESENT]}") | ||
| print(f"===> APIs WITHOUT code samples: {class_summary[NOT_PRESENT]}") | ||
|
|
||
| coverage = 100 * total_with_code_samples / total | ||
| print(f"Total: {coverage:.1f}% ({total_with_code_samples}/{total})") |