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dflookdflook
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Format Python code
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Lines changed: 721 additions & 356 deletions

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‎corpus_test/generate_report.py‎

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@@ -183,6 +183,7 @@ def format_difference(compare: Iterable[Result], base: Iterable[Result]) -> str:
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else:
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return s
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def report_larger_than_original(results_dir: str, python_versions: str, minifier_sha: str) -> str:
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yield '''
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## Larger than original
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for entry in larger_than_original:
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yield f'| {entry.corpus_entry} | {entry.original_size} | {entry.minified_size} ({entry.minified_size - entry.original_size:+}) |'
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def report_unstable(results_dir: str, python_versions: str, minifier_sha: str) -> str:
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yield '''
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## Unstable
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for entry in unstable:
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yield f'| {entry.corpus_entry} | {python_version} | {entry.original_size} |'
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def report_exceptions(results_dir: str, python_versions: str, minifier_sha: str) -> str:
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yield '''
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## Exceptions
@@ -243,6 +246,7 @@ def report_exceptions(results_dir: str, python_versions: str, minifier_sha: str)
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if not exceptions_found:
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yield ' None | | |'
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def report_larger_than_base(results_dir: str, python_versions: str, minifier_sha: str, base_sha: str) -> str:
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yield '''
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## Top 10 Larger than base
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if not there_are_some_larger_than_base:
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yield '| N/A | N/A | N/A |'
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def report_slowest(results_dir: str, python_versions: str, minifier_sha: str) -> str:
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yield '''
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## Top 10 Slowest
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for entry in sorted(summary.entries.values(), key=lambda entry: entry.time, reverse=True)[:10]:
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yield f'| {entry.corpus_entry} | {entry.original_size} | {entry.minified_size} | {entry.time:.3f} |'
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def report(results_dir: str, minifier_ref: str, minifier_sha: str, base_ref: str, base_sha: str) -> Iterable[str]:
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"""
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Generate a report comparing the results of two versions of python-minifier

‎corpus_test/generate_results.py‎

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@@ -34,7 +34,6 @@ def minify_corpus_entry(corpus_path, corpus_entry):
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with open(os.path.join(corpus_path, corpus_entry), 'rb') as f:
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source = f.read()
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result = Result(corpus_entry, len(source), 0, 0, '')
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start_time = time.time()
@@ -133,6 +132,7 @@ def corpus_test(corpus_path, results_path, sha, regenerate_results):
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print('Finished')
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def bool_parse(value):
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return value == 'true'
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‎hypo_test/README.md‎

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# Hypothesis tests
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The hypothesis strategies in this directory generate an AST that python can parse.
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It does not take care to generate semantically valid programs.
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It does not take care to generate semantically valid programs.
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Failure cases should shrink into valid programs, though.
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TODO:
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Assignment targets: (in comprehensions too)
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- Tuples, sets??
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Starred
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Call arguments
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Delete targets
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ImportFrom levels
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functiondef args
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Await
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f-strings
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Starred
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Call arguments
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Delete targets
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ImportFrom levels
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functiondef args
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Await
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f-strings

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