mirror of https://github.com/google/oss-fuzz.git
87 lines
3.1 KiB
Python
87 lines
3.1 KiB
Python
#!/usr/bin/python3
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# Copyright 2023 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""This fuzzer script targets the pandas melt and map functions, creating a variety of DataFrames with mixed data
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types and then transforming them using melting and mapping operations."""
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import sys
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import atheris
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import pandas as pd
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def TestOneInput(data):
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fdp = atheris.FuzzedDataProvider(data)
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try:
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groups = {
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fdp.ConsumeString(10): fdp.ConsumeUnicodeNoSurrogates(10),
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fdp.ConsumeString(10): fdp.ConsumeUnicodeNoSurrogates(10)
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}
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num_rows = fdp.ConsumeIntInRange(3, 30)
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num_columns = fdp.ConsumeIntInRange(3, 30)
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col_names = [fdp.ConsumeString(fdp.ConsumeIntInRange(1, 15)) for _ in range(num_columns)]
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df_content = {}
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for col_name in col_names:
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if fdp.ConsumeBool():
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df_content[col_name] = [fdp.ConsumeInt(10) for _ in range(num_rows)]
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elif fdp.ConsumeBool():
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df_content[col_name] = [fdp.ConsumeString(10) for _ in range(num_rows)]
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elif fdp.ConsumeBool():
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df_content[col_name] = [fdp.ConsumeIntInRange(0, 2100) for _ in range(num_rows)]
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elif fdp.ConsumeBool():
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df_content[col_name] = [fdp.ConsumeFloat() for _ in range(num_rows)]
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else:
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df_content[col_name] = [fdp.ConsumeBool() for _ in range(num_rows)]
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id_vars_data = [
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col_names[fdp.ConsumeIntInRange(0, len(col_names) - 1)],
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col_names[fdp.ConsumeIntInRange(0, len(col_names) - 1)],
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col_names[fdp.ConsumeIntInRange(0, len(col_names) - 1)]
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]
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if fdp.ConsumeBool():
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id_vars_data.append(fdp.ConsumeString(fdp.ConsumeIntInRange(1, 15)))
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df = pd.DataFrame(df_content)
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name = fdp.ConsumeString(20)
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df = pd.melt(
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df,
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id_vars=id_vars_data,
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value_vars=[
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col_names[fdp.ConsumeIntInRange(0, len(col_names) - 1)],
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col_names[fdp.ConsumeIntInRange(0, len(col_names) - 1)]
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],
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var_name='gf', value_name=fdp.ConsumeString(10)
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)
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local_var_name = 'gf' if fdp.ConsumeBool() else fdp.ConsumeString(10)
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df[name] = df[local_var_name].map(groups)
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except (
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KeyError, # if `id_vars` are not in the frame.
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ValueError # if initial data from seed is empty and fdp produces empty data.
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):
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pass
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def main():
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atheris.Setup(sys.argv, TestOneInput)
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atheris.instrument_all()
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atheris.Fuzz()
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if __name__ == "__main__":
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main()
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