The current API is that:
flattenalways returns a copy.ravelreturns a contiguous view of the original array whenever possible. This isn't visible in the printed output, but if you modify the array returned by ravel, it may modify the entries in the original array. If you modify the entries in an array returned from flatten this will never happen. ravel will often be faster since no memory is copied, but you have to be more careful about modifying the array it returns.reshape((-1,))gets a view whenever the strides of the array allow it even if that means you don't always get a contiguous array.
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The current API is that:
flattenalways returns a copy.ravelreturns a contiguous view of the original array whenever possible. This isn't visible in the printed output, but if you modify the array returned by ravel, it may modify the entries in the original array. If you modify the entries in an array returned from flatten this will never happen. ravel will often be faster since no memory is copied, but you have to be more careful about modifying the array it returns.reshape((-1,))gets a view whenever the strides of the array allow it even if that means you don't always get a contiguous array.
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As explained here a key difference is that:
flattenis a method of an ndarray object and hence can only be called for true numpy arrays.ravelis a library-level function and hence can be called on any object that can successfully be parsed.
For example ravel will work on a list of ndarrays, while flatten is not available for that type of object.
@IanH also points out important differences with memory handling in his answer.
GeeksforGeeks
geeksforgeeks.org › python › differences-flatten-ravel-numpy
Differences between Flatten() and Ravel() Numpy Functions - GeeksforGeeks
November 8, 2022 - This demonstrates that flatten() does return a copy of the Numpy input array. ... Here, we will create a Numpy array, and then by using the ravel() function we have changed the element in the flattened 1D NumPy array.
Videos
03:16
NumPy ravel() vs flatten() - Array Flattening Explained | Python ...
03:59
9: How to flatten and ravel arrays in NumPy - YouTube
07:54
NumPy Reshape Explained | Flatten vs Ravel, Transpose & Array ...
09:22
Numpy Array Shape Manipulation using Reshape, Ravel, and Flatten ...
12:26
Python NumPy Tutorial 12 - Reshape vs Flatten vs Ravel vs Transpose ...
DataCamp
datacamp.com › doc › numpy › flatten-vs-ravel
NumPy Flatten vs Ravel
In this syntax, `flatten` creates a new array, while `ravel` tries to return a view of the original array, minimizing memory usage. A "view" in NumPy is an array that shares the same data buffer as the original array, allowing for efficient memory use.
Medium
medium.com › @prathik.codes › numpy-ravel-vs-flatten-understanding-the-difference-f65324a78289
NumPy: ravel() vs flatten() — Understanding the Difference | by Prathik C | Medium
January 19, 2026 - ravel() offers better performance by returning a view when possible, while flatten() provides safety by always returning a copy. Understanding this distinction helps you write more efficient and bug-free NumPy code.
Naukri
naukri.com › code360 › library › difference-between-flatten-and-ravel-functions-in-numpy
Difference Between Flatten and Ravel Functions in Numpy
March 27, 2024 - Almost there... just a few more seconds
Reddit
reddit.com › r/learnpython › ravel vs. flatten
r/learnpython on Reddit: ravel vs. flatten
March 11, 2020 -
Hi, I heard that if the values in the result were contiguous in the original array, ravel does not produce a copy of the underlying values. What does that mean? How do I know if the values in the result were contagious in the original array not? In practice, is it recommended to use flattern or ravel all the time?
Scaler
scaler.com › home › topics › difference between flatten and ravel functions in numpy?
Difference between flatten and ravel functions in Numpy? | Scaler Topics
May 4, 2023 - The main functional distinction is that flatten is a function of an ndarray object and hence only works with genuine numpy arrays. ravel(), on the other hand, is a library-level function that may be invoked on any object that can be correctly parsed.
Codemia
codemia.io › knowledge-hub › path › what_is_the_difference_between_flatten_and_ravel_functions_in_numpy
What is the difference between flatten and ravel functions ...
Enhance your system design skills with over 120 practice problems, detailed solutions, and hands-on exercises
CodingNomads
codingnomads.com › np-reshape-np-flatten-np-ravel
NumPy Array Manipulation: np.reshape, np.flatten, np.ravel ...
While NumPy flatten() returns a copy of the array, NumPy ravel() and Numpy reshape(-1) generally return a view unless they need to make a copy for memory layout reasons.
Lovestoblog
machinelearningminds.lovestoblog.com › numpy-ravel-vs-flatten-vs-squeeze
Numpy Ravel v/s Numpy Flatten v/s Numpy Squeeze
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Vultr Docs
docs.vultr.com › python › third-party › numpy › ravel
Python Numpy ravel() - Flatten Array | Vultr Docs
November 14, 2024 - This code converts two_d_array, a 2x3 matrix, into a flattened one-dimensional array. The ravel() function processes the elements in row-major (C-style) order by default, yielding the output [1 2 3 4 5 6].
NumPy
numpy.org › doc › 2.2 › reference › generated › numpy.ndarray.flatten.html
numpy.ndarray.flatten — NumPy v2.2 Manual
A copy of the input array, flattened to one dimension. See also · ravel · Return a flattened array. flat · A 1-D flat iterator over the array.
Kaggle
kaggle.com › discussions › questions-and-answers › 466028
np.ravel() vs np.flatten()
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NumPy
numpy.org › doc › 2.2 › reference › generated › numpy.ravel.html
numpy.ravel — NumPy v2.2 Manual
numpy.ravel(a, order='C')[source]# Return a contiguous flattened array. A 1-D array, containing the elements of the input, is returned. A copy is made only if needed. As of NumPy 1.10, the returned array will have the same type as the input array. (for example, a masked array will be returned for a masked array input) Parameters: aarray_like ·
KajoData
kajodata.com › main page › knowledge base – excel, sql, python, powerbi, tableau, statistics › knowledge base – python › how numpy ravel works in python? best example
How numpy ravel works in Python? Best example - KajoData
April 15, 2025 - Unlike some other flattening methods in NumPy, ravel() tries to return a view of the original array whenever possible instead of creating a completely separate copy.
Better Programming
betterprogramming.pub › 5-ways-to-flatten-an-array-in-numpy-dd6d79042139
5 Ways To Flatten an Array in NumPy | by Lev Maximov | Better Programming
May 29, 2023 - Usually, you don’t need to worry too much about the difference: the recipe “flatten is always a copy, and reshape(-1) is a view whenever possible” from “NumPy Illustrated” is enough for most use cases.
H2K Infosys
h2kinfosys.com › blog › using the numpy reshape and numpy flatten in python
Using the NumPy Reshape and NumPy Flatten in Python
December 17, 2025 - Both flatten() and ravel() are used to convert multi-dimensional arrays into one-dimensional arrays, but they have distinct behaviors: · flatten(): Returns a copy of the original array.
Sharp Sight
sharpsight.ai › blog › numpy-ravel
Numpy Ravel, Explained - Sharp Sight
February 6, 2024 - This is called the ‘F‘ order, because this is how the Fortran programming language stores and retrieves data. The Numpy Ravel function returns a 1-dimensional, flattened array that has the same elements as the input (ordered according to ...
YouTube
youtube.com › watch
Flatten() and Ravel() Numpy Functions and their Differences | Module NumPy Tutorial - Part 23 - YouTube
Flatten() and Ravel() Numpy Functions and Differences between Flatten() and Ravel() Numpy module Functions==================================NumPy Module Tuto...
Published October 3, 2022
YouTube
youtube.com › data thinkers
19. Ravel Vs. Flatten Vs. Reshape(-1) in Numpy - YouTube
In this NumPy tutorial video, I have compared Ravel Vs. Flatten Vs. Reshape(-1).arr.ravel():(i) Return only reference/view of the original array(ii) If you m...
Published August 23, 2020 Views 945