1. # 012.Test_py_memory_001.py
    2. import sys
    3. n = int(sys.argv[1])
    6. @profile
    7. def r():
    8.     import pandas as pd
    9.     import numpy as np
    10.     import time
    11.     N = n
    12.     data = pd.DataFrame(np.random.uniform(1, 9, (N, 38)))
    13.     data[data[12] > 5]
    14.     time.sleep(2)
    17. r()

    通过调用memory_profiler模块，

    1. pip install memory_profiler
    2. pip install psutil
    4. cat 012.Test_py_memory_001.py
    5. """
    6. import sys
    7. n = int(sys.argv[1])
    9. @profile
    10. def r():
    11.   import pandas as pd
    12.   import numpy as np
    13.   import time
    14.   N = n
    15.   data = pd.DataFrame(np.random.uniform(1,9,(N, 38)))
    16.   data[data[12] > 5]
    17.   time.sleep(2)
    19. r()
    20. """
    22. py3 -m memory_profiler 012.Test_py_memory_001.py 10
    23. """
    24. Filename: 012.Test_py_memory_001.py
    26. Line #    Mem usage    Increment   Line Contents
    27. ================================================
    28.      4   28.727 MiB   28.727 MiB   @profile
    29.      5                             def r():
    30.      6   69.566 MiB   40.840 MiB     import pandas as pd
    31.      7   69.566 MiB    0.000 MiB     import numpy as np
    32.      8   69.566 MiB    0.000 MiB     import time
    33.      9   69.566 MiB    0.000 MiB     N = n
    34.     10   69.566 MiB    0.000 MiB     data = pd.DataFrame(np.random.uniform(1,9,(N, 38)))
    35.     11   69.805 MiB    0.238 MiB     data[data[12] > 5]
    36.     12   69.805 MiB    0.000 MiB     time.sleep(2)
    37. """
    39. py3 -m memory_profiler 012.Test_py_memory_001.py 100
    40. """
    41. Filename: 012.Test_py_memory_001.py
    43. Line #    Mem usage    Increment   Line Contents
    44. ================================================
    45.      4   28.730 MiB   28.730 MiB   @profile
    46.      5                             def r():
    47.      6   69.570 MiB   40.840 MiB     import pandas as pd
    48.      7   69.570 MiB    0.000 MiB     import numpy as np
    49.      8   69.570 MiB    0.000 MiB     import time
    50.      9   69.570 MiB    0.000 MiB     N = n
    51.     10   69.570 MiB    0.000 MiB     data = pd.DataFrame(np.random.uniform(1,9,(N, 38)))
    52.     11   69.809 MiB    0.238 MiB     data[data[12] > 5]
    53.     12   69.809 MiB    0.000 MiB     time.sleep(2)
    54. """
    56. py3 -m memory_profiler 012.Test_py_memory_001.py 1000
    57. """
    58. Filename: 012.Test_py_memory_001.py
    60. Line #    Mem usage    Increment   Line Contents
    61. ================================================
    62.      4   28.730 MiB   28.730 MiB   @profile
    63.      5                             def r():
    64.      6   69.574 MiB   40.844 MiB     import pandas as pd
    65.      7   69.574 MiB    0.000 MiB     import numpy as np
    66.      8   69.574 MiB    0.000 MiB     import time
    67.      9   69.574 MiB    0.000 MiB     N = n
    68.     10   69.816 MiB    0.242 MiB     data = pd.DataFrame(np.random.uniform(1,9,(N, 38)))
    69.     11   70.324 MiB    0.508 MiB     data[data[12] > 5]
    70.     12   70.324 MiB    0.000 MiB     time.sleep(2)
    71. """
    73. py3 -m memory_profiler 012.Test_py_memory_001.py 10000
    74. """
    75. Filename: 012.Test_py_memory_001.py
    77. Line #    Mem usage    Increment   Line Contents
    78. ================================================
    79.      4   28.723 MiB   28.723 MiB   @profile
    80.      5                             def r():
    81.      6   69.566 MiB   40.844 MiB     import pandas as pd
    82.      7   69.566 MiB    0.000 MiB     import numpy as np
    83.      8   69.566 MiB    0.000 MiB     import time
    84.      9   69.566 MiB    0.000 MiB     N = n
    85.     10   72.641 MiB    3.074 MiB     data = pd.DataFrame(np.random.uniform(1,9,(N, 38)))
    86.     11   72.922 MiB    0.281 MiB     data[data[12] > 5]
    87.     12   72.922 MiB    0.000 MiB     time.sleep(2)
    88. """
    90. py3 -m memory_profiler 012.Test_py_memory_001.py 100000
    91. """
    92. Filename: 012.Test_py_memory_001.py
    94. Line #    Mem usage    Increment   Line Contents
    95. ================================================
    96.      4   28.727 MiB   28.727 MiB   @profile
    97.      5                             def r():
    98.      6   69.574 MiB   40.848 MiB     import pandas as pd
    99.      7   69.574 MiB    0.000 MiB     import numpy as np
    100.      8   69.574 MiB    0.000 MiB     import time
    101.      9   69.574 MiB    0.000 MiB     N = n
    102.     10   98.691 MiB   29.117 MiB     data = pd.DataFrame(np.random.uniform(1,9,(N, 38)))
    103.     11  100.473 MiB    1.781 MiB     data[data[12] > 5]
    104.     12  100.473 MiB    0.000 MiB     time.sleep(2)
    105. """
    107. py3 -m memory_profiler 012.Test_py_memory_001.py 1000000
    108. """
    109. Filename: 012.Test_py_memory_001.py
    111. Line #    Mem usage    Increment   Line Contents
    112. ================================================
    113.      4   28.723 MiB   28.723 MiB   @profile
    114.      5                             def r():
    115.      6   69.574 MiB   40.852 MiB     import pandas as pd
    116.      7   69.574 MiB    0.000 MiB     import numpy as np
    117.      8   69.574 MiB    0.000 MiB     import time
    118.      9   69.574 MiB    0.000 MiB     N = n
    119.     10  359.598 MiB  290.023 MiB     data = pd.DataFrame(np.random.uniform(1,9,(N, 38)))
    120.     11  369.070 MiB    9.473 MiB     data[data[12] > 5]
    121.     12  369.070 MiB    0.000 MiB     time.sleep(2)
    122. """