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REFERENCEpython

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Memoryview

AI & DATA SCIENCE // memoryview

memoryview lets you access the internal buffer of an object like bytes or bytearray without copying its data.

Syntax

mv = memoryview(some_bytes)
mv[0]
mv[1:4]

Deep Dive Course

Normally, slicing a bytes or bytearray object copies the sliced portion into a brand-new object. memoryview instead wraps the original buffer and exposes the same slicing/indexing interface without copying any data — slicing a memoryview returns another memoryview pointing into the same underlying memory. This matters for performance when working with large binary data, like parsing a big network buffer or file, where copying would be wasteful.

1Understanding Memoryview

Normally, slicing a bytes or bytearray object copies the sliced portion into a brand-new object. memoryview instead wraps the original buffer and exposes the same slicing/indexing interface without copying any data — slicing a memoryview returns another memoryview pointing into the same underlying memory. This matters for performance when working with large binary data, like parsing a big network buffer or file, where copying would be wasteful.

💡

Reach for memoryview specifically when profiling shows that slicing large bytes/bytearray objects is copying more data than necessary — for small, everyday byte strings, it's not worth the added complexity.

editor.html
data = bytearray(b"Hello, World!")
view = memoryview(data)
print(view[7:12].tobytes())
localhost:3000

2Practical Example

Here is a real-world application of Memoryview showing how it is used in production Python code.

editor.html
buf = bytearray(b"abcdef")
view = memoryview(buf)
view[0:2] = b"XY"
print(buf)
localhost:3000

3Best Practices

Follow these guidelines when working with Memoryview:

1. Use memoryview when repeatedly slicing large binary buffers to avoid the cost of copying data on every slice

2. Combine memoryview with bytearray, not bytes, when you also need to modify the underlying buffer in place

3. Call bytes(mv) or bytearray(mv) to materialize a real copy once you're done working with the zero-copy view

⚠️

Tip: Reach for memoryview specifically when profiling shows that slicing large bytes/bytearray objects is copying more data than necessary — for small, everyday byte strings, it's not worth the added complexity.

editor.html
data = bytearray(b"Hello, World!")
view = memoryview(data)
print(view[7:12].tobytes())
localhost:3000

Examples

Example 01Basic Usage
data = bytearray(b"Hello, World!")
view = memoryview(data)
print(view[7:12].tobytes())
Example 02Advanced Example
buf = bytearray(b"abcdef")
view = memoryview(buf)
view[0:2] = b"XY"
print(buf)

Best Practices

  • Use memoryview when repeatedly slicing large binary buffers to avoid the cost of copying data on every slice
  • Combine memoryview with bytearray, not bytes, when you also need to modify the underlying buffer in place
  • Call bytes(mv) or bytearray(mv) to materialize a real copy once you're done working with the zero-copy view

Interview Question

What performance problem does memoryview solve when working with large binary data?

Hint: Think about what a normal slice of a bytes object does to memory.

Slicing a bytes or bytearray object normally allocates a brand-new object and copies the sliced bytes into it. For large buffers sliced repeatedly, like when parsing a big file or network stream, those copies add up in both time and memory. memoryview exposes the same buffer without copying, so slicing it just creates a lightweight view pointing at the existing memory, which is copied only if and when you explicitly convert it back to bytes.

Exercises

MediumPractice using Memoryview in a real scenario.
View Solution
data = bytearray(b"Hello, World!")
view = memoryview(data)
print(view[7:12].tobytes())

Frequently Asked Questions

What performance problem does memoryview solve when working with large binary data?

Slicing a bytes or bytearray object normally allocates a brand-new object and copies the sliced bytes into it. For large buffers sliced repeatedly, like when parsing a big file or network stream, those copies add up in both time and memory. memoryview exposes the same buffer without copying, so slicing it just creates a lightweight view pointing at the existing memory, which is copied only if and when you explicitly convert it back to bytes.

Related Functions

bytesbytearraybuffer protocol