For simplicity's sake, let's consider writing instead of reading for now.

So when you use open() like say:

with open("test.dat", "wb") as f:
    f.write(b"Hello World")
    f.write(b"Hello World")
    f.write(b"Hello World")

After executing that a file called test.dat will be created, containing 3x Hello World. The data wont be kept in memory after it's written to the file (unless being kept by a name).

Now when you consider io.BytesIO() instead:

with io.BytesIO() as f:
    f.write(b"Hello World")
    f.write(b"Hello World")
    f.write(b"Hello World")

Which instead of writing the contents to a file, it's written to an in memory buffer. In other words a chunk of RAM. Essentially writing the following would be the equivalent:

buffer = b""
buffer += b"Hello World"
buffer += b"Hello World"
buffer += b"Hello World"

In relation to the example with the with statement, then at the end there would also be a del buffer.

The key difference here is optimization and performance. io.BytesIO is able to do some optimizations that makes it faster than simply concatenating all the b"Hello World" one by one.

Just to prove it here's a small benchmark:

  • Concat: 1.3529 seconds
  • BytesIO: 0.0090 seconds

import io
import time

begin = time.time()
buffer = b""
for i in range(0, 50000):
    buffer += b"Hello World"
end = time.time()
seconds = end - begin
print("Concat:", seconds)

begin = time.time()
buffer = io.BytesIO()
for i in range(0, 50000):
    buffer.write(b"Hello World")
end = time.time()
seconds = end - begin
print("BytesIO:", seconds)

Besides the performance gain, using BytesIO instead of concatenating has the advantage that BytesIO can be used in place of a file object. So say you have a function that expects a file object to write to. Then you can give it that in-memory buffer instead of a file.

The difference is that open("myfile.jpg", "rb") simply loads and returns the contents of myfile.jpg; whereas, BytesIO again is just a buffer containing some data.

Since BytesIO is just a buffer - if you wanted to write the contents to a file later - you'd have to do:

buffer = io.BytesIO()
# ...
with open("test.dat", "wb") as f:
    f.write(buffer.getvalue())

Also, you didn't mention a version; I'm using Python 3. Related to the examples: I'm using the with statement instead of calling f.close()

Answer from vallentin on Stack Overflow
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Python
docs.python.org › 3 › library › io.html
io — Core tools for working with streams — Python 3.14.6 documentation
Its subclasses, BufferedWriter, ... interface to seekable streams. Another BufferedIOBase subclass, BytesIO, is a stream of in-memory bytes....
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DigitalOcean
digitalocean.com › community › tutorials › python-io-bytesio-stringio
Python io.BytesIO and io.StringIO: Memory File Guide | DigitalOcean
August 3, 2022 - There are many ways in which we can use the io module to perform stream and buffer operations in Python. We will demonstrate a lot of examples here to prove the point. Let’s get started. Just like what we do with variables, data can be kept as bytes in an in-memory buffer when we use the io module’s Byte IO operations. Here is a sample program to demonstrate this: import io stream_str = io.BytesIO(b"JournalDev Python: \x00\x01") print(stream_str.getvalue())
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Python
wiki.python.org › moin › BytesIO
BytesIO - Python Wiki
April 28, 2011 - 1 class BytesIO(object): 2 """ A file-like API for reading and writing bytes objects. 3 4 Mostly like StringIO, but write() calls modify the underlying 5 bytes object.
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AskPython
askpython.com › home › python io module: the complete practical reference
Python IO Module: The Complete Practical Reference - AskPython
February 16, 2023 - In this article, we learned about using the Python IO module, and it’s two main classes – io.BytesIO and io.StringIO for reading and writing byte and string data onto a buffer.
Top answer
1 of 2
208

For simplicity's sake, let's consider writing instead of reading for now.

So when you use open() like say:

with open("test.dat", "wb") as f:
    f.write(b"Hello World")
    f.write(b"Hello World")
    f.write(b"Hello World")

After executing that a file called test.dat will be created, containing 3x Hello World. The data wont be kept in memory after it's written to the file (unless being kept by a name).

Now when you consider io.BytesIO() instead:

with io.BytesIO() as f:
    f.write(b"Hello World")
    f.write(b"Hello World")
    f.write(b"Hello World")

Which instead of writing the contents to a file, it's written to an in memory buffer. In other words a chunk of RAM. Essentially writing the following would be the equivalent:

buffer = b""
buffer += b"Hello World"
buffer += b"Hello World"
buffer += b"Hello World"

In relation to the example with the with statement, then at the end there would also be a del buffer.

The key difference here is optimization and performance. io.BytesIO is able to do some optimizations that makes it faster than simply concatenating all the b"Hello World" one by one.

Just to prove it here's a small benchmark:

  • Concat: 1.3529 seconds
  • BytesIO: 0.0090 seconds

import io
import time

begin = time.time()
buffer = b""
for i in range(0, 50000):
    buffer += b"Hello World"
end = time.time()
seconds = end - begin
print("Concat:", seconds)

begin = time.time()
buffer = io.BytesIO()
for i in range(0, 50000):
    buffer.write(b"Hello World")
end = time.time()
seconds = end - begin
print("BytesIO:", seconds)

Besides the performance gain, using BytesIO instead of concatenating has the advantage that BytesIO can be used in place of a file object. So say you have a function that expects a file object to write to. Then you can give it that in-memory buffer instead of a file.

The difference is that open("myfile.jpg", "rb") simply loads and returns the contents of myfile.jpg; whereas, BytesIO again is just a buffer containing some data.

Since BytesIO is just a buffer - if you wanted to write the contents to a file later - you'd have to do:

buffer = io.BytesIO()
# ...
with open("test.dat", "wb") as f:
    f.write(buffer.getvalue())

Also, you didn't mention a version; I'm using Python 3. Related to the examples: I'm using the with statement instead of calling f.close()

2 of 2
42

Using open opens a file on your hard drive. Depending on what mode you use, you can read or write (or both) from the disk.

A BytesIO object isn't associated with any real file on the disk. It's just a chunk of memory that behaves like a file does. It has the same API as a file object returned from open (with mode r+b, allowing reading and writing of binary data).

BytesIO (and it's close sibling StringIO which is always in text mode) can be useful when you need to pass data to or from an API that expect to be given a file object, but where you'd prefer to pass the data directly. You can load your input data you have into the BytesIO before giving it to the library. After it returns, you can get any data the library wrote to the file from the BytesIO using the getvalue() method. (Usually you'd only need to do one of those, of course.)

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Python
docs.python.org › 3.9 › library › io.html
io — Core tools for working with streams — Python 3.9.24 documentation
Its subclasses, BufferedWriter, ... provides a buffered interface to seekable streams. Another BufferedIOBase subclass, BytesIO, is a stream of in-memory bytes....
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7-Zip Documentation
documentation.help › python-3-7-3 › io.html
io — Core tools for working with streams - Python 3.7.3 Documentation
March 25, 2019 - Its subclasses, BufferedWriter, BufferedReader, and BufferedRWPair buffer streams that are readable, writable, and both readable and writable. BufferedRandom provides a buffered interface to random access streams. Another BufferedIOBase subclass, BytesIO, is a stream of in-memory bytes.
Find elsewhere
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ProgramCreek
programcreek.com › python › example › 1734 › io.BytesIO
Python Examples of io.BytesIO
def _deserialize(self, data, type_): if self.compress: # decompress the data if needed data = lz4.frame.decompress(data) if type_ == _NUMPY: # deserialize numpy arrays buf = io.BytesIO(data) data = np.load(buf) elif type_ == _PICKLE: # deserialize other python objects data = pickle.loads(data) else: # Otherwise we just return data as it is (bytes) pass return data
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MicroPython
docs.micropython.org › en › latest › library › io.html
io – input/output streams — MicroPython latest documentation
1 week ago - StringIO is used for text-mode I/O (similar to a normal file opened with “t” modifier). BytesIO is used for binary-mode I/O (similar to a normal file opened with “b” modifier). Initial contents of file-like objects can be specified with string parameter (should be normal string for ...
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GeeksforGeeks
geeksforgeeks.org › python › stringio-and-bytesio-for-managing-data-as-file-object
Stringio And Bytesio For Managing Data As File Object - GeeksforGeeks
July 24, 2025 - BytesIO is like a virtual file that exists in the computer's memory, just like `StringIO`. However, it's tailored to handle binary data (bytes) instead of text. It lets you perform operations on these bytes, such as reading and writing, as if ...
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Webkul
webkul.com › home › python: using stringio and bytesio for managing data as file object
Python: Using StringIO and BytesIO for managing data as file object - Webkul Blog
October 1, 2019 - Using buffer modules(StringIO, BytesIO, cStringIO) we can impersonate string or bytes data like a file.These buffer modules help us to mimic our data like a normal file which we can further use for processing.
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Runebook.dev
runebook.dev › en › docs › python › library › io › io.BytesIO
python - BytesIO Gotchas and Workarounds: Fixing Empty Reads and TypeErrors
The io.BytesIO class is a memory-based binary stream. Think of it as a file you can read from and write to, but instead of being saved on your hard drive, it exists only in your computer's RAM (Random Access Memory).
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CodeRivers
coderivers.org › blog › io-bytesio-python
Python's `io.BytesIO`: A Comprehensive Guide - CodeRivers
February 22, 2026 - By understanding the fundamental ... data, mocking file-like objects, or performing other I/O operations, io.BytesIO is a valuable addition to your Python toolkit. Python Official Documentation: io — Core tools for working with streams...
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Learning Machine
gallon.me › using-the-bytesio-class-in-python
Using the BytesIO Class in Python - Learning Machine
February 14, 2025 - The io.BytesIO class in Python is an in-memory stream for binary data. It provides a file-like interface that lets you read and write bytes just like you would with a file, but all the data is...
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Python
docs.python.org › 3.6 › library › io.html
16.2. io — Core tools for working with streams — Python 3.6.15 documentation
Its subclasses, BufferedWriter, BufferedReader, and BufferedRWPair buffer streams that are readable, writable, and both readable and writable. BufferedRandom provides a buffered interface to random access streams. Another BufferedIOBase subclass, BytesIO, is a stream of in-memory bytes.
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CodeRivers
coderivers.org › blog › python-iobytesio
Python io.BytesIO: An In - Depth Exploration - CodeRivers
February 22, 2026 - io.BytesIO is a class in the Python io module that represents an in-memory binary stream. It inherits from the io.BufferedIOBase class, which provides a buffer for reading and writing operations.