There are two ways that some Python programmers overuse lambda. Doing this almost always mkes your code less readable, and for no corresponding benefit.

Don't use lambda for named functions

Some programmers don't understand that in Python, def and lambda define exactly the same kind of function object. (Especially since the equivalent is not true in C++, Ruby, and many other languages.)

The differences between def and lambda are:

  • def gives you a named function, lambda an anonymous function.
  • def lets you include statements in the body, lambda only an expression.
  • lambda can be used within an expression, def cannot.

So, when you want to, e.g., define a short callback in the middle of an async request or a GUI widget constructor, especially when it doesn't have an obvious good name, use lamdba.

But when you want to define a named function, use def.

In other words, don't write this:

  • iszero = lambda x: hash(x) == hash(0)
(There are other problems with that function, but let's ignore them…)

What's wrong with lambda for named functions?

  • Following idioms matters.
  • That "iszero" function up there may be bound the the module global name "iszero"—but if it shows up in a traceback, or you print it out at the interactive prompt, or use the inspect module on it, its name is actually <lambda>. That's not nearly as useful.
  • The def statement's syntax parallels function call syntax: "def iszero(x):" means it's called with "iszero(x)". That isn't true for "iszero = lambda x:".
  • If you later need to change the body to, say, add a try/except around it, you can't do that in a lambda.

But isn't lambda a lot more concise?

In exchange for dropping the 6-letter "return" keyword, and possibly a pair of parens, you've replaced a 3-letter "def" keyword with a 6-letter "lambda" keyword, and added a space and an equals sign. How much more concise do you think that's going to be? Test it yourself; you save 1-3 characters this way; that's it.

If you're thinking that lambda can go on one line and def can't, of course it can:
  • def iszero(x): return hash(x) == hash(0)
Sure, PEP 8 says that one-line compound statements are "generally discouraged", but it includes plenty of "Yes" examples that do exactly that; when the recommendations section of a document that itself is only a guideline specifically points out that something is just a "usually don't" rather than a hard "don't", that means something.

And, more importantly, avoiding making your code arguably unpythonic by transforming it into something definitely even more unpythonic is not helping.

And if you're just doing it to trick your linter, I shouldn't have to explain why using a linter but then tricking it is kind of pointless.

Don't use lambda when you don't need a function

In Python, there should be one, and only one, obvious way to do it. And yet we have both comprehensions and higher-order functions like map and filter. Why?

When you have an expression to map or filter with, a comprehension is the obvious way to do it.

When you have a function to map or filter with, the higher-order function is the obvious way to do it.

It's a little silly (and maybe inefficient) to wrap a function call in an expression just to avoid calling map; it's a lot sillier (and more inefficient) to wrap an expression in a function just so you _can_ call map. Compare:
  • vals = (x+2*y for x, y in zip(xs, ys)) # good
  • vals = map(lambda (x, y): x+2*y, zip(xs, ys)) # bad, and illegal in Python 3
  • vals = map(lambda xy: xy[0]+2*xy[1], zip(xs, ys)) # even worse, but legal
The point of your code is not calling a function that adds some numbers, it's just adding some numbers. There's no clearer way to write that than "x+2*y".

Of course the silliest of all is doing both of these things—you have a function, which you wrap in an expression which you then wrap in a function again:
  • vals = map(spam, vals) # good
  • vals = map(lambda x: spam(x), vals) # really?

Borderline cases

Sometimes, you have a function, but it may not be very obvious to all readers:
  • vals = (x+y for x, y in zip(xs, ys)) # good
  • vals = map(operator.add, zip(xs, ys)) # also good
Or the only expression that can replace a function is a higher-order expression that some readers may not grasp:
  • vals.sort(key=functools.partial(spam, maxval)) # decent
  • vals.sort(key=lambda x: spam(maxval, x)) # also decent
Here, it's really a judgment call. It depends who you expect to be reading your code, and what feels most natural to you, and maybe even what the surrounding code looks like.

Of course when you need to do something that you can't quite do with the higher-order tools that Python has provided, it's even more obviously a judgment call. You don't want to write (or install off PyPI) a right-partial, argument-flip, or compose function just to avoid one use of lambda—but to avoid 200 uses of lambda throughout a project, maybe you do.

Comprehensions only handle map and filter

As great as comprehensions are, they don't let you replace functools.reduce or itertools.dropwhile, only map and filter. If you are going to use functions like that, you don't have any choice but to wrap up your transforming expression or predicate test in a function. Of course sometimes that's a reason not to use those functions (Guido likes to say inside every reduce is a for loop screaming to get out), but sometimes it isn't. Again, each case is a judgment call.

So why do we even have lambda?

Because every time Guido suggests getting rid of it, the rest of the community shouts him down. :)

More seriously, lambda is great for exactly the kinds of examples I gave above—a short and simple button callback, or sorting key, or dropwhile predicate; doing something that's just outside the grasp of partial; etc.

Sometimes you need a function that's anonymous, trivial, and can be written in-line within an expression. And that's why we have lambda.
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It's been more than a decade since Typical Programmer Greg Jorgensen taught the word about Abject-Oriented Programming.

Much of what he said still applies, but other things have changed. Languages in the Abject-Oriented space have been borrowing ideas from another paradigm entirely—and then everyone realized that languages like Python, Ruby, and JavaScript had been doing it for years and just hadn't noticed (because these languages do not require you to declare what you're doing, or even to know what you're doing). Meanwhile, new hybrid languages borrow freely from both paradigms.

This other paradigm—which is actually older, but was largely constrained to university basements until recent years—is called Functional Addiction.
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I haven't posted anything new in a couple years (partly because I attempted to move to a different blogging platform where I could write everything in markdown instead of HTML but got frustrated—which I may attempt again), but I've had a few private comments and emails on some of the old posts, so I decided to do some followups.

A couple years ago, I wrote a blog post on greenlets, threads, and processes.
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Looking before you leap

Python is a duck-typed language, and one where you usually trust EAFP ("Easier to Ask Forgiveness than Permission") over LBYL ("Look Before You Leap"). In Java or C#, you need "interfaces" all over the place; you can't pass something to a function unless it's an instance of a type that implements that interface; in Python, as long as your object has the methods and other attributes that the function needs, no matter what type it is, everything is good.
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Background

Currently, CPython’s internal bytecode format stores instructions with no args as 1 byte, instructions with small args as 3 bytes, and instructions with large args as 6 bytes (actually, a 3-byte EXTENDED_ARG followed by a 3-byte real instruction). While bytecode is implementation-specific, many other implementations (PyPy, MicroPython, …) use CPython’s bytecode format, or variations on it.

Python exposes as much of this as possible to user code.
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If you want to skip all the tl;dr and cut to the chase, jump to Concrete Proposal.

Why can’t we write list.len()? Dunder methods C++ Python Locals What raises on failure? Method objects What about set and delete? Data members Namespaces Bytecode details Lookup overrides Introspection C API Concrete proposal CPython Analysis

Why can’t we write list.len()?

Python is an OO language. To reverse a list, you call lst.reverse(); to search a list for an element, you call lst.index().
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Many people, when they first discover the heapq module, have two questions:

Why does it define a bunch of functions instead of a container type? Why don't those functions take a key or reverse parameter, like all the other sorting-related stuff in Python? Why not a type?

At the abstract level, it's often easier to think of heaps as an algorithm rather than a data structure.
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Currently, in CPython, if you want to process bytecode, either in C or in Python, it’s pretty complicated.

The built-in peephole optimizer has to do extra work fixing up jump targets and the line-number table, and just punts on many cases because they’re too hard to deal with. PEP 511 proposes a mechanism for registering third-party (or possibly stdlib) optimizers, and they’ll all have to do the same kind of work.
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One common "advanced question" on places like StackOverflow and python-list is "how do I dynamically create a function/method/class/whatever"? The standard answer is: first, some caveats about why you probably don't want to do that, and then an explanation of the various ways to do it when you really do need to.

But really, creating functions, methods, classes, etc. in Python is always already dynamic.

Some cases of "I need a dynamic function" are just "Yeah? And you've already got one".
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A few years ago, Cesare di Mauro created a project called WPython, a fork of CPython 2.6.4 that “brings many optimizations and refactorings”. The starting point of the project was replacing the bytecode with “wordcode”. However, there were a number of other changes on top of it.

I believe it’s possible that replacing the bytecode with wordcode would be useful on its own.
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Many languages have a for-each loop. In some, like Python, it’s the only kind of for loop:

for i in range(10): print(i) In most languages, the loop variable is only in scope within the code controlled by the for loop,[1] except in languages that don’t have granular scopes at all, like Python.[2]

So, is that i a variable that gets updated each time through the loop or is it a new constant that gets defined each time through the loop?

Almost every language treats it as a reused variable.
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