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chore: add script to compute code samples coverage #428
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# 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. | ||
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import argparse | ||
import importlib | ||
import inspect | ||
import sys | ||
from typing import Dict, List | ||
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import bigframes | ||
import bigframes.pandas as bpd | ||
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PRESENT = "present" | ||
NOT_PRESENT = "not_present" | ||
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CLASSES = [ | ||
bpd.DataFrame, | ||
bpd.Series, | ||
bpd.Index, | ||
bigframes.session.Session, | ||
bigframes.operations.strings.StringMethods, | ||
bigframes.operations.datetimes.DatetimeMethods, | ||
bigframes.operations.structs.StructAccessor, | ||
] | ||
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ML_MODULE_NAMES = [ | ||
"cluster", | ||
"compose", | ||
"decomposition", | ||
"ensemble", | ||
"linear_model", | ||
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"metrics", | ||
"model_selection", | ||
"pipeline", | ||
"preprocessing", | ||
"llm", | ||
"forecasting", | ||
"imported", | ||
"remote", | ||
] | ||
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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_) | ||
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def get_code_samples_summary() -> Dict[str, Dict[str, List[str]]]: | ||
"""Get Summary of the code samples coverage in BigFrames APIs. | ||
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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() | ||
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for class_ in CLASSES: | ||
class_key = f"{class_.__module__}.{class_.__name__}" | ||
summary[class_key] = {PRESENT: [], NOT_PRESENT: []} | ||
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members = inspect.getmembers(class_) | ||
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for name, obj in members: | ||
# ignore private methods | ||
if name.startswith("_") and not name.startswith("__"): | ||
continue | ||
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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("__")) | ||
) | ||
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if not predicate(obj): | ||
continue | ||
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# At this point we have a property or a public method | ||
impl = getattr(class_, name) | ||
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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) | ||
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return summary | ||
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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.", | ||
) | ||
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args = parser.parse_args(sys.argv[1:]) | ||
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summary = get_code_samples_summary() | ||
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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 | ||
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apis_total = len(class_summary[PRESENT]) + len(class_summary[NOT_PRESENT]) | ||
total += apis_total | ||
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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]}") | ||
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coverage = 100 * total_with_code_samples / total | ||
print(f"Total: {coverage:.1f}% ({total_with_code_samples}/{total})") |
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