How to Flatten nested Python lists without recursion limits?

Unfollow Follow

Miley

Updated on January 19, 2026 in

Python

Hi all,
I’m working on cleaning up some dataset imports, and I need to flatten nested lists of unknown depth. I tried using a recursive function and also attempted itertools.chain.from_iterable, but I’m stuck when depth varies.

Here’s what I’ve tried:

This works but is slow for really deep nesting. Are there faster or more Pythonic ways to handle this? Any library recommendations?

Thanks!

<p data-start="3124" data-end="3359">Hi all,<br data-start="3131" data-end="3134" />I’m working on cleaning up some dataset imports, and I need to flatten nested lists of unknown depth. I tried using a recursive function and also attempted <code data-start="3292" data-end="3323">itertools.chain.from_iterable</code>, but I’m stuck when depth varies.</p>
<p data-start="3366" data-end="3389">Here’s what I’ve tried:</p>
<div class="contain-inline-size rounded-2xl corner-superellipse/1.1 relative bg-token-sidebar-surface-primary">
<div class="sticky top-[calc(--spacing(9)+var(--header-height))] @w-xl/main:top-9">
<div class="absolute end-0 bottom-0 flex h-9 items-center pe-2">
<div class="bg-token-bg-elevated-secondary text-token-text-secondary flex items-center gap-4 rounded-sm px-2 font-sans text-xs"> </div>
</div>
</div>
<div class="overflow-y-auto p-4" dir="ltr"><code class="whitespace-pre! language-python"><span class="hljs-keyword">def</span> <span class="hljs-title function_">flatten</span>(<span class="hljs-params">lst</span>):<br />
    result = []<br />
    <span class="hljs-keyword">for</span> x <span class="hljs-keyword">in</span> lst:<br />
        <span class="hljs-keyword">if</span> <span class="hljs-built_in">isinstance</span>(x, <span class="hljs-built_in">list</span>):<br />
            result.extend(flatten(x))<br />
        <span class="hljs-keyword">else</span>:<br />
            result.append(x)<br />
    <span class="hljs-keyword">return</span> result<br />
</code></div>
</div>
<p data-start="3613" data-end="3744">This works but is slow for really deep nesting. Are there faster or more Pythonic ways to handle this? Any library recommendations?</p>
<p data-start="3751" data-end="3758">Thanks!</p>

Cancel

2
106
3 weeks ago
0

Reply

Write your reply here to join the conversation

YOUR PREVIEW

Avatar

Kapil 6 days ago

A common reason people hit recursion limits when flattening nested lists is because the recursive approach doesn’t scale well with deeply nested structures. In practice, an iterative solution is usually safer and easier to reason about.

One simple pattern is to use an explicit stack instead of recursion. You start with the original list on the stack, then keep popping elements. If the element is a list, you push its contents back onto the stack; if it’s not, you add it to the result. This mimics recursion but avoids call-stack limits entirely.

The key detail is preserving order. To do that, you typically push items onto the stack in reverse order so they come out correctly when popped.

This approach is:

Safe for deeply nested lists
Easy to debug
More memory-predictable than recursion

If you only need shallow flattening, tools like itertools.chain can help, but for unknown or arbitrary nesting depth, an explicit stack is usually the most robust solution.

In production code, I’ve found this pattern clearer than recursive helpers once the nesting gets non-trivial.

Liked by

Reply

<p>A common reason people hit recursion limits when flattening nested lists is because the recursive approach doesn’t scale well with deeply nested structures. In practice, an iterative solution is usually safer and easier to reason about.</p><br />
<p>One simple pattern is to use an explicit stack instead of recursion. You start with the original list on the stack, then keep popping elements. If the element is a list, you push its contents back onto the stack; if it’s not, you add it to the result. This mimics recursion but avoids call-stack limits entirely.</p><br />
<p>The key detail is preserving order. To do that, you typically push items onto the stack in reverse order so they come out correctly when popped.</p><br />
<p>This approach is:</p><br />
<ul><br />
<li><br />
<p>Safe for deeply nested lists</p><br />
</li><br />
<li><br />
<p>Easy to debug</p><br />
</li><br />
<li><br />
<p>More memory-predictable than recursion</p><br />
</li><br />
</ul><br />
<p>If you only need shallow flattening, tools like itertools.chain can help, but for unknown or arbitrary nesting depth, an explicit stack is usually the most robust solution.</p><br />
<p>In production code, I’ve found this pattern clearer than recursive helpers once the nesting gets non-trivial.</p>

Cancel

Shahir on January 21, 2026

I’ve run into this exact issue before. Your recursive approach is correct logically, but as you’ve noticed, it starts to struggle once nesting gets deep because of recursion overhead and call stack limits.

One practical way around this is to avoid recursion entirely and flatten iteratively using a stack. It tends to be faster and more predictable for unknown or deeply nested structures. Libraries like itertools are great, but they work best when the nesting depth is known or shallow.

If performance really matters and the data is large, I’ve also found it useful to question whether the structure needs to be fully flattened upfront, or if processing items lazily as they’re encountered is enough. That alone can save a lot of time and memory.

Curious what kind of data volumes you’re dealing with. That usually changes which approach makes the most sense.

Liked by

Reply

<p data-start="121" data-end="326">I’ve run into this exact issue before. Your recursive approach is correct logically, but as you’ve noticed, it starts to struggle once nesting gets deep because of recursion overhead and call stack limits.</p><br />
<p data-start="328" data-end="610">One practical way around this is to avoid recursion entirely and flatten iteratively using a stack. It tends to be faster and more predictable for unknown or deeply nested structures. Libraries like itertools are great, but they work best when the nesting depth is known or shallow.</p><br />
<p data-start="612" data-end="871">If performance really matters and the data is large, I’ve also found it useful to question whether the structure needs to be fully flattened upfront, or if processing items lazily as they’re encountered is enough. That alone can save a lot of time and memory.</p><br />
<p data-start="612" data-end="871">Curious what kind of data volumes you’re dealing with. That usually changes which approach makes the most sense.</p>

Cancel