Python Memory Mapping

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Now, before you start rolling your eyes and muttering under your breath about how boring this sounds, let me just say: I get it. Memory mapping isn’t exactly the most thrilling topic in the world of programming. But trust me when I say that its a game-changer for anyone who works with large datasets or files on a regular basis.

So what is memory mapping, you ask? Well, lets start by breaking down the term itself: memory and mapping. In this context, we’re talking about computer memory (RAM) and how it can be used to access data that is stored in files on your hard drive.

When you open a file using Python, the contents of that file are loaded into RAM so that they can be accessed more quickly than if they were still sitting on your hard drive. This process is called loading or reading the file into memory. But what happens when you have a really large file (like, say, a 10GB video file) and you want to access specific parts of it? Do you have to load the entire thing into RAM at once?

The answer is no! Thats where memory mapping comes in. With memory mapping, we can create a view or mapping of a portion of that large file in our computer’s memory. This allows us to access specific parts of the file without having to load the entire thing into RAM at once.

So how does this work? Lets take a look at some code:

# Import the mmap module to use memory mapping
import mmap

# Define the file name of the large file we want to access
filename = 'my_big_file.bin'

# Open the file in read-only mode and assign it to the variable 'f'
with open(filename, 'rb') as f:
    # Get the size of the file in bytes and assign it to the variable 'size'
    size = os.path.getsize(filename)
    # Set the access mode to read-only and assign it to the variable 'access'
    access = mmap.ACCESS_READ
    # Set the protection mode to read-only and assign it to the variable 'prot'
    prot = mmap.PROT_READ
    # Set the flags to shared and assign it to the variable 'flags'
    flags = mmap.MAP_SHARED
    # Create a memory map of the file using the file descriptor, size, access mode, protection mode, and flags
    # Assign it to the variable 'mm'
    mm = mmap.mmap(f.fileno(), 0, size, access, prot, flags)

In this example, we’re using the `mmap` module to create a memory mapping of our big file (which is assumed to be named “my_big_file.bin”). We first open the file in binary mode and get its size using Pythons built-in `os` library.

Next, we set up some flags for how we want to access the data: we’re going to read it (ACCESS_READ), and we don’t need any special permissions (PROT_READ). We also specify that we want to share this memory mapping with other processes (MAP_SHARED) so that multiple programs can use it at once.

Finally, we create the actual memory mapping using Pythons `mmap` module. This creates a new object called “mm” which represents our view of the file in memory.

Now that we have this memory mapping set up, we can access specific parts of the file just like any other variable:

# Creating a memory mapping using Python's `mmap` module
# This creates a new object called "mm" which represents our view of the file in memory
mm = mmap.mmap(fileno, 0, access=mmap.ACCESS_READ) # fileno is the file descriptor, 0 is the length of the mapping, and access specifies the permissions for the mapping

# Accessing data from the memory mapping
data = mm[1024*1024*5] # Get byte at index 5MB (assuming a 64-bit system)
print(data) # Prints the byte at index 5MB

# Explanation: This script creates a memory mapping using the `mmap` module and accesses a specific byte from the mapping. The `mmap` module allows us to access files as if they were in memory, making it more efficient to work with large files. The `fileno` parameter is the file descriptor, which is used to identify the file being mapped. The `access` parameter specifies the permissions for the mapping, in this case, we are only reading from the file. The `data` variable stores the byte at index 5MB, which is then printed to the console.

In this example, we’re accessing the byte that is located at an offset of 6MB from the beginning of our file. This allows us to work with specific parts of the data without having to load the entire thing into memory at once.

Memory mapping in Python: a game-changer for anyone who works with large datasets or files on a regular basis. It’s not exactly the most thrilling topic, but trust me when I say that it can save you hours of time and frustration.

Later!

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