.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/advanced/interfacing_with_cpp.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_advanced_interfacing_with_cpp.py>`
        to download the full example code or to run this example in your browser via Binder

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_advanced_interfacing_with_cpp.py:


============================
7.5 interfacing with C++
============================

This lesson describes how to call functions/modules written in C++ into python and

.. GENERATED FROM PYTHON SOURCE LINES 8-17

.. code-block:: default


    import time   
    import ctypes
    import subprocess
    from ctypes import c_char_p, c_uint, c_size_t, POINTER, Structure

    import numpy as np
    import pandas as pd








.. GENERATED FROM PYTHON SOURCE LINES 18-25

.. code-block:: default


    start = time.time()
    for i in range(100):
        pd.read_csv('daily_q.csv', index_col=0)

    print(f"with pandas: {time.time() - start:.2f} seconds")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    with pandas: 3.36 seconds




.. GENERATED FROM PYTHON SOURCE LINES 26-85

.. code-block:: default


    # Specify the C++ source file and the output executable name
    cpp_source_file = 'read_csv_gpt.cpp'
    output_library = 'read_csv_gpt.so'

    # Compile the C++ code as a library
    compile_command = f'g++ -shared -o {output_library}  -fPIC {cpp_source_file}'
    process = subprocess.run(compile_command, shell=True, text=True, capture_output=True)

    if process.returncode != 0:
        print(process.stderr)
    else:
        print('Compilation successful')

    # Define the CSVRow structure
    class CSVRow(Structure):
    
        _fields_ = [("date", ctypes.c_char * 20),
                    ("floatValue", ctypes.c_float)]

    # Load the shared library
    csv_reader = ctypes.CDLL(f'./{output_library}')  # Use the correct path for your .so/.dll file

    # Define the argument and return types of the functions
    csv_reader.processCSVFile.argtypes = [c_char_p, POINTER(c_uint), POINTER(c_size_t)]
    csv_reader.processCSVFile.restype = POINTER(CSVRow)

    csv_reader.freeCSVRows.argtypes = [POINTER(CSVRow)]
    csv_reader.freeCSVRows.restype = None

    def read_csv(file_path):
        # Call the processCSVFile function
        station = c_uint(0)
        size = c_size_t(0)
        rows = csv_reader.processCSVFile(file_path, ctypes.byref(station), ctypes.byref(size))

        # Access the returned data
        data = [None] * size.value
        index = [None] * size.value
        for i in range(size.value):
            index[i] = rows[i].date.decode('utf-8')
            data[i] = rows[i].floatValue

        df = pd.DataFrame(data, columns=[str(station.value)], index=index)
        df.replace(-9999.0, np.nan, inplace=True)

        # Free the allocated memory
        csv_reader.freeCSVRows(rows)

        return df

    df = read_csv(b'daily_q.csv')

    start = time.time()
    for i in range(100):
        read_csv(b'daily_q.csv')

    print(f"With C++: {time.time() - start:.2f} seconds")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Compilation successful
    With C++: 7.45 seconds




.. GENERATED FROM PYTHON SOURCE LINES 86-97

.. code-block:: default


    # Load the shared library
    csv_reader = ctypes.CDLL(f'./{output_library}')   # Use the correct path for your .so/.dll file

    # # Define the argument and return types of the functions
    csv_reader.processCSVFileFast.argtypes = [ctypes.c_char_p, ctypes.POINTER(ctypes.c_uint), ctypes.POINTER(ctypes.c_size_t), ctypes.POINTER(ctypes.c_size_t)]
    csv_reader.processCSVFileFast.restype = ctypes.c_void_p

    csv_reader.freeCSVRowsFast.argtypes = [ctypes.c_void_p]
    csv_reader.freeCSVRowsFast.restype = None








.. GENERATED FROM PYTHON SOURCE LINES 98-124

.. code-block:: default


    def read_csvFast(file_path):
        # Call the processCSVFileFast function
        total = ctypes.c_uint(0)
        size = ctypes.c_size_t(0)
        row_size = ctypes.c_size_t(0)
        ptr = csv_reader.processCSVFileFast(file_path, ctypes.byref(total), ctypes.byref(size), ctypes.byref(row_size))

        # # Check if the pointer is NULL
        # if not ptr:
        #     raise MemoryError("Failed to allocate memory for CSV data")

        # Convert the pointer to a numpy array
        buffer = (ctypes.c_char * (size.value * row_size.value)).from_address(ptr)
        data = np.frombuffer(buffer, dtype=[('date', 'S20'), (str(total.value), 'f4')])

        # Create a pandas DataFrame from the numpy array
        df = pd.DataFrame(data)

        # Convert the 'date' column to string
        df.index = df['date'].str.decode('utf-8')

        # Free the allocated memory
        csv_reader.freeCSVRowsFast(ptr)
        return df








.. GENERATED FROM PYTHON SOURCE LINES 125-132

.. code-block:: default


    start = time.time()
    for i in range(100):
        df = read_csvFast(b'daily_q.csv')

    print(f"With C++: {time.time() - start:.2f} seconds")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    With C++: 5.48 seconds




.. GENERATED FROM PYTHON SOURCE LINES 133-153

.. code-block:: default



    def read_csvFast1(file_path):
        # Call the processCSVFileFast function
        total = ctypes.c_uint(0)
        size = ctypes.c_size_t(0)
        row_size = ctypes.c_size_t(0)
        ptr = csv_reader.processCSVFileFast(file_path, ctypes.byref(total), ctypes.byref(size), ctypes.byref(row_size))

        # Convert the pointer to a numpy array
        buffer = (ctypes.c_char * (size.value * row_size.value)).from_address(ptr)
        data = np.frombuffer(buffer, dtype=[('date', 'S20'), (str(total.value), 'f4')])

        # Convert the 'date' column to string
        #index = df['date'].str.decode('utf-8')

        # Free the allocated memory
        csv_reader.freeCSVRowsFast(ptr)
        return data








.. GENERATED FROM PYTHON SOURCE LINES 154-159

.. code-block:: default


    start = time.time()
    for i in range(100):
        df = read_csvFast1(b'daily_q.csv')

    print(f"With C++ in numpy: {time.time() - start:.2f} seconds")



.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    With C++ in numpy: 2.38 seconds





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  19.278 seconds)


.. _sphx_glr_download_auto_examples_advanced_interfacing_with_cpp.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example


    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/AtrCheema/python-seekho/master?urlpath=lab/tree/notebooks/auto_examples/advanced/interfacing_with_cpp.ipynb
        :alt: Launch binder
        :width: 150 px

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: interfacing_with_cpp.py <interfacing_with_cpp.py>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: interfacing_with_cpp.ipynb <interfacing_with_cpp.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

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