Python memoryview() Method

The Python memoryview() built-in function creates a memory view object that exposes the internal buffer of an object supporting the buffer protocol, such as bytes and bytearray. It accepts a single parameter, the object whose internal data you want to access, and returns a memoryview object that lets you read and, in the case of mutable types like bytearray, modify the underlying data without copying it. This is particularly valuable when working with large binary datasets, image processing buffers, or network packet payloads where creating copies of data would waste memory and slow down execution. By slicing a memoryview, you obtain a new view into the same memory rather than allocating a new buffer, which makes operations on large byte sequences significantly more efficient. The function is commonly used in performance-critical code that processes binary file formats, communicates over sockets, or manipulates byte-level data structures in scientific computing pipelines.

What does memoryview() return?

The memoryview() function returns a memoryview object that provides a buffer-oriented view of the underlying binary data, allowing element access by index and zero-copy slicing of the original buffer.

When should you use memoryview()?

Use memoryview() when you need to manipulate slices of large binary data without copying the bytes into new objects, such as when processing binary file formats, streaming network data, or working with shared memory buffers in high-performance applications.

All the objects in python require storage space at the runtime and memoryview() method will return how much storage passed object will take.

The syntax of memoryview() is:

memoryview(object)

Python memoryview() Parameters

The memoryview() method takes only one parameter as argument:

• object - An object that is exposed using bytes or bytearray.

Example 1: How to use memoryview() in python?

x = memoryview(b"Hello")

print(x)

#return the Unicode of the first character
print(x[0])

#return the Unicode of the second character
print(x[1])

Output:

<memory at 0x7f9efbddadc0>
72
101

Common Use Cases

Working with binary file I/O is one of the most frequent applications of memoryview(). When reading a large binary file into a bytearray, you can create a memory view to parse specific sections of the file, such as headers and data blocks, without copying any bytes. This approach is especially useful when processing image files, audio streams, or serialized data formats.

Network programming also benefits from memoryview(). When sending or receiving data over sockets, you can use a memory view to slice a buffer and send only a portion of it, or to write incoming data directly into a specific offset of a pre-allocated buffer. This reduces garbage collection pressure and improves throughput for high-volume data transfer.

Another practical use case is modifying parts of a bytearray in place. Since memoryview on a bytearray supports item assignment, you can update specific bytes or slices of a buffer without rebuilding the entire array, which is essential in protocols that require patching fields in binary messages.

If you are working with byte-level data, you may also find the Python bytes() and Python bytearray() functions useful for creating the buffer objects that memoryview() operates on.

Rules of memoryview()

• Passed object must be whose internal data is to be exposed