Coverage for /pythoncovmergedfiles/medio/medio/src/fuzz_interpolate.py: 69%

1###### Coverage stub 

2import atexit 

3import coverage 

4cov = coverage.coverage(data_file='.coverage', cover_pylib=True) 

5cov.start() 

6# Register an exist handler that will print coverage 

7def exit_handler(): 

8 cov.stop() 

9 cov.save() 

10atexit.register(exit_handler) 

11####### End of coverage stub 

12#!/usr/bin/python3 

13# Copyright 2023 Google LLC 

14# 

15# Licensed under the Apache License, Version 2.0 (the "License"); 

16# you may not use this file except in compliance with the License. 

17# You may obtain a copy of the License at 

18# 

19# http://www.apache.org/licenses/LICENSE-2.0 

20# 

21# Unless required by applicable law or agreed to in writing, software 

22# distributed under the License is distributed on an "AS IS" BASIS, 

23# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 

24# See the License for the specific language governing permissions and 

25# limitations under the License. 

26"""Fuzzes the pandas interpolate function, generating and manipulating DataFrames with various data types to uncover 

27potential edge cases.""" 

28 

29import sys 

30import atheris 

31import pandas as pd 

32 

33 

34def TestOneInput(data): 

35 fdp = atheris.FuzzedDataProvider(data) 

36 

37 try: 

38 rows = fdp.ConsumeIntInRange(1, 15) 

39 num_rows = fdp.ConsumeIntInRange(3, 20) 

40 num_columns = fdp.ConsumeIntInRange(3, 20) 

41 col_names = [fdp.ConsumeString(fdp.ConsumeIntInRange(1, 15)) for _ in range(num_columns)] 

42 

43 df_content = {} 

44 for col_name in col_names: 

45 if fdp.ConsumeBool(): 

46 df_content[col_name] = [fdp.ConsumeInt(10) for _ in range(num_rows)] 

47 elif fdp.ConsumeBool(): 

48 df_content[col_name] = [fdp.ConsumeString(10) for _ in range(num_rows)] 

49 elif fdp.ConsumeBool(): 

50 df_content[col_name] = [fdp.ConsumeIntInRange(0, 2100) for _ in range(num_rows)] 

51 elif fdp.ConsumeBool(): 

52 df_content[col_name] = [fdp.ConsumeFloat() for _ in range(num_rows)] 

53 else: 

54 df_content[col_name] = [fdp.ConsumeBool() for _ in range(num_rows)] 

55 

56 df = pd.DataFrame(df_content) 

57 

58 # Fuzz interpolate options 

59 method = fdp.PickValueInList( 

60 ['linear', 'time', 'index', 'values', 'nearest', 'zero', 'slinear', 'quadratic', 

61 'cubic', 'barycentric', 'krogh', 'polynomial', 'spline', 'bessel', 'holistic', 'akima', 

62 fdp.ConsumeString(15)]) 

63 axis = fdp.PickValueInList([0, 1, 'index', 'columns']) 

64 limit = fdp.ConsumeIntInRange(1, rows) if fdp.ConsumeBool() else None 

65 inplace = fdp.ConsumeBool() 

66 limit_direction = fdp.PickValueInList(['forward', 'backward', 'both', None]) 

67 limit_area = fdp.PickValueInList([None, 'inside', 'outside']) 

68 order = fdp.ConsumeIntInRange(1, 5) if method == 'polynomial' else None 

69 s = fdp.ConsumeFloatInRange(0, 1) if method == 'spline' else None 

70 robust = fdp.ConsumeBool() 

71 

72 df.interpolate( 

73 method=method, 

74 axis=axis, 

75 limit=limit, 

76 inplace=inplace, 

77 limit_direction=limit_direction, 

78 limit_area=limit_area, 

79 order=order, 

80 s=s, 

81 robust=robust 

82 ) 

83 

84 except ( 

85 ValueError # If method argument is invalid 

86 ): 

87 pass 

88 

89 

90def main(): 

91 atheris.Setup(sys.argv, TestOneInput) 

92 atheris.instrument_all() 

93 atheris.Fuzz() 

94 

95 

96if __name__ == "__main__": 

97 main()