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71 KiB
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2400 lines
71 KiB
Markdown
<p align="center"><img src="/images/logo.png" alt=""></p>
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<h1 align="center">What the f*ck Python! 🐍</h1>
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<p align="center">An interesting collection of surprising snippets and lesser-known Python features.</p>
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[![WTFPL 2.0][license-image]][license-url] [![Commit id][commit-image]][commit-url]
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Python, being a beautifully designed high-level and interpreter-based programming language, provides us with many features for the programmer's comfort. But sometimes, the outcomes of a Python snippet may not seem obvious to a regular user at first sight.
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Here is a fun project to collect such tricky & counter-intuitive examples and lesser-known features in Python, attempting to discuss what exactly is happening under the hood!
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While some of the examples you see below may not be WTFs in the truest sense, but they'll reveal some of the interesting parts of Python that you might be unaware of. I find it a nice way to learn the internals of a programming language, and I think you'll find them interesting as well!
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If you're an experienced Python programmer, you can take it as a challenge to get most of them right in first attempt. You may be already familiar with some of these examples, and I might be able to revive sweet old memories of yours being bitten by these gotchas :sweat_smile:
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PS: If you're a returning reader, you can learn about the new modifications [here](https://github.com/satwikkansal/wtfpython/releases/).
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So, here we go...
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# Table of Contents
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<!-- TOC -->
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- [Table of Contents](#table-of-contents)
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- [Structure of the Examples](#structure-of-the-examples)
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- [Usage](#usage)
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- [👀 Examples](#👀-examples)
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- [Section: Strain your brain!](#section-strain-your-brain)
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- [> Strings can be tricky sometimes/微妙的字符串 *](#-strings-can-be-tricky-sometimes微妙的字符串-)
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- [> Time for some hash brownies!/是时候来点蛋糕了!](#-time-for-some-hash-brownies是时候来点蛋糕了)
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- [> Return return everywhere!/到处返回！](#-return-return-everywhere到处返回)
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- [> Deep down, we're all the same./本质上,我们都一样. *](#-deep-down-were-all-the-same本质上我们都一样-)
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- [> For what?/为什么?](#-for-what为什么)
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- [> Evaluation time discrepancy/执行时机差异](#-evaluation-time-discrepancy执行时机差异)
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- [> `is` is not what it is!/出人意料的`is`!](#-is-is-not-what-it-is出人意料的is)
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- [> A tic-tac-toe where X wins in the first attempt!/一蹴即至!](#-a-tic-tac-toe-where-x-wins-in-the-first-attempt一蹴即至)
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- [> The sticky output function/麻烦的输出](#-the-sticky-output-function麻烦的输出)
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- [> `is not ...` is not `is (not ...)`/`is not ...` 不是 `is (not ...)`](#-is-not--is-not-is-not-is-not--不是-is-not-)
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- [> The surprising comma/意外的逗号](#-the-surprising-comma意外的逗号)
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- [> Backslashes at the end of string/字符串末尾的反斜杠](#-backslashes-at-the-end-of-string字符串末尾的反斜杠)
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- [> not knot!/别纠结!](#-not-knot别纠结)
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- [> Half triple-quoted strings](#-half-triple-quoted-strings)
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- [> Midnight time doesn't exist?](#-midnight-time-doesnt-exist)
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- [> What's wrong with booleans?](#-whats-wrong-with-booleans)
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- [> Class attributes and instance attributes](#-class-attributes-and-instance-attributes)
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- [> yielding None](#-yielding-none)
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- [> Mutating the immutable!](#-mutating-the-immutable)
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- [> The disappearing variable from outer scope](#-the-disappearing-variable-from-outer-scope)
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- [> When True is actually False](#-when-true-is-actually-false)
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- [> From filled to None in one instruction...](#-from-filled-to-none-in-one-instruction)
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- [> Subclass relationships *](#-subclass-relationships-)
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- [> The mysterious key type conversion *](#-the-mysterious-key-type-conversion-)
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- [> Let's see if you can guess this?](#-lets-see-if-you-can-guess-this)
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- [Section: Appearances are deceptive!](#section-appearances-are-deceptive)
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- [> Skipping lines?](#-skipping-lines)
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- [> Teleportation *](#-teleportation-)
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- [> Well, something is fishy...](#-well-something-is-fishy)
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- [Section: Watch out for the landmines!](#section-watch-out-for-the-landmines)
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- [> Modifying a dictionary while iterating over it](#-modifying-a-dictionary-while-iterating-over-it)
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- [> Stubborn `del` operator *](#-stubborn-del-operator-)
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- [> Deleting a list item while iterating](#-deleting-a-list-item-while-iterating)
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- [> Loop variables leaking out!](#-loop-variables-leaking-out)
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- [> Beware of default mutable arguments!](#-beware-of-default-mutable-arguments)
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- [> Catching the Exceptions](#-catching-the-exceptions)
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- [> Same operands, different story!](#-same-operands-different-story)
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- [> The out of scope variable](#-the-out-of-scope-variable)
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- [> Be careful with chained operations](#-be-careful-with-chained-operations)
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- [> Name resolution ignoring class scope](#-name-resolution-ignoring-class-scope)
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- [> Needle in a Haystack](#-needle-in-a-haystack)
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- [Section: The Hidden treasures!](#section-the-hidden-treasures)
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- [> Okay Python, Can you make me fly? *](#-okay-python-can-you-make-me-fly-)
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- [> `goto`, but why? *](#-goto-but-why-)
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- [> Brace yourself! *](#-brace-yourself-)
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- [> Let's meet Friendly Language Uncle For Life *](#-lets-meet-friendly-language-uncle-for-life-)
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- [> Even Python understands that love is complicated *](#-even-python-understands-that-love-is-complicated-)
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- [> Yes, it exists!](#-yes-it-exists)
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- [> Inpinity *](#-inpinity-)
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- [> Mangling time! *](#-mangling-time-)
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- [Section: Miscellaneous](#section-miscellaneous)
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- [> `+=` is faster](#--is-faster)
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- [> Let's make a giant string!](#-lets-make-a-giant-string)
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- [> Explicit typecast of strings](#-explicit-typecast-of-strings)
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- [> Minor Ones](#-minor-ones)
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- [Contributing](#contributing)
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- [Acknowledgements](#acknowledgements)
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- [🎓 License](#🎓-license)
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- [Help](#help)
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- [Want to surprise your geeky pythonist friends?](#want-to-surprise-your-geeky-pythonist-friends)
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- [Need a pdf version?](#need-a-pdf-version)
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- [Follow Commit](#follow-commit)
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<!-- /TOC -->
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# Structure of the Examples
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All the examples are structured like below:
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> ### > Some fancy Title *
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> The asterisk at the end of the title indicates the example was not present in the first release and has been recently added.
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>
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> ```py
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> # Setting up the code.
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> # Preparation for the magic...
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> ```
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>
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> **Output (Python version):**
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> ```py
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> >>> triggering_statement
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> Probably unexpected output
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> ```
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> (Optional): One line describing the unexpected output.
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>
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>
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> #### 💡 Explanation:
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>
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> * Brief explanation of what's happening and why is it happening.
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> ```py
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> Setting up examples for clarification (if necessary)
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> ```
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> **Output:**
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> ```py
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> >>> trigger # some example that makes it easy to unveil the magic
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> # some justified output
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> ```
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**Note:** All the examples are tested on Python 3.5.2 interactive interpreter, and they should work for all the Python versions unless explicitly specified in the description.
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# Usage
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A nice way to get the most out of these examples, in my opinion, will be just to read the examples chronologically, and for every example:
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- Carefully read the initial code for setting up the example. If you're an experienced Python programmer, most of the times you will successfully anticipate what's going to happen next.
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- Read the output snippets and,
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+ Check if the outputs are the same as you'd expect.
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+ Make sure if you know the exact reason behind the output being the way it is.
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- If no, take a deep breath, and read the explanation (and if you still don't understand, shout out! and create an issue [here](https://github.com/satwikkansal/wtfPython)).
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- If yes, give a gentle pat on your back, and you may skip to the next example.
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PS: You can also read WTFpython at the command line. There's a pypi package and an npm package (supports colored formatting) for the same.
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To install the npm package [`wtfpython`](https://www.npmjs.com/package/wtfpython)
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```sh
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$ npm install -g wtfpython
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```
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Alternatively, to install the pypi package [`wtfpython`](https://pypi.python.org/pypi/wtfpython)
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```sh
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$ pip install wtfpython -U
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```
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Now, just run `wtfpython` at the command line which will open this collection in your selected `$PAGER`.
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---
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# 👀 Examples
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## Section: Strain your brain!
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### > Strings can be tricky sometimes/微妙的字符串 *
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1\.
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```py
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>>> a = "some_string"
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>>> id(a)
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140420665652016
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>>> id("some" + "_" + "string") # 注意两个的id值是相同的.
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140420665652016
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```
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2\.
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```py
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>>> a = "wtf"
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>>> b = "wtf"
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>>> a is b
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True
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>>> a = "wtf!"
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>>> b = "wtf!"
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>>> a is b
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False
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>>> a, b = "wtf!", "wtf!"
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>>> a is b
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True # 3.7 版本返回结果为 False.
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```
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3\.
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```py
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>>> 'a' * 20 is 'aaaaaaaaaaaaaaaaaaaa'
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True
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>>> 'a' * 21 is 'aaaaaaaaaaaaaaaaaaaaa'
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False # 3.7 版本返回结果为 True
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```
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很好理解, 对吧?
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#### 💡 说明:
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- 这些行为是由于 Cpython 在编译优化时, 某些情况下会尝试使用已经存在的不可变对象而不是每次都创建一个新对象. (这种行为被称作字符串的驻留[string interning])
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- 发生驻留之后, 许多变量可能指向内存中的相同字符串对象. (从而节省内存)
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- 在上面的代码中, 字符串是隐式驻留的. 何时发生隐式驻留则取决于具体的实现. 这里有一些方法可以用来猜测字符串是否会被驻留:
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- 所有长度为 0 和长度为 1 的字符串都被驻留.
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- 字符串在编译时被实现 (`'wtf'` 将被驻留, 但是 `''.join(['w', 't', 'f'])` 将不会被驻留)
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- 字符串中只包含字母，数字或下划线时将会驻留. 所以 `'wtf!'` 由于包含 `!` 而未被驻留. 可以在[这里](https://github.com/python/cpython/blob/3.6/Objects/codeobject.c#L19)找到 CPython 对此规则的实现.
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<img src="/images/string-intern/string_intern.png" alt="">
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- 当在同一行将 `a` 和 `b` 的值设置为 `"wtf!"` 的时候, Python 解释器会创建一个新对象, 然后同时引用第二个变量(译: 仅适用于3.7以下, 详细情况请看[这里](https://github.com/leisurelicht/wtfpython-cn/issues/13)). 如果你在不同的行上进行赋值操作, 它就不会“知道”已经有一个 `wtf！` 对象 (因为 `"wtf!"` 不是按照上面提到的方式被隐式驻留的). 它是一种编译器优化, 特别适用于交互式环境.
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- 常量折叠(constant folding) 是 Python 中的一种 [窥孔优化(peephole optimization)](https://en.wikipedia.org/wiki/Peephole_optimization) 技术. 这意味着在编译时表达式 `'a'*20` 会被替换为 `'aaaaaaaaaaaaaaaaaaaa'` 以减少运行时的时钟周期. 只有长度小于 20 的字符串才会发生常量折叠. (为啥? 想象一下由于表达式 `'a'*10**10` 而生成的 `.pyc` 文件的大小). 相关的源码实现在[这里](https://github.com/python/cpython/blob/3.6/Python/peephole.c#L288).
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- 如果你是使用 3.7 版本中运行上述示例代码, 会发现部分代码的运行结果与注释说明相同. 这是因为在 3.7 版本中, 常量折叠已经从窥孔优化器迁移至新的 AST 优化器, 后者可以以更高的一致性来执行优化. (由 Eugene Toder 和 INADA Naoki 在 [bpo-29469](https://bugs.python.org/issue29469) 和 [bpo-11549](https://bugs.python.org/issue11549) 中贡献.)
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- (译: 但是在最新的 3.8 版本中, 结果又变回去了. 虽然 3.8 版本和 3.7 版本一样, 都是使用 AST 优化器. 目前不确定官方对 3.8 版本的 AST 做了什么调整.)
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---
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### > Time for some hash brownies!/是时候来点蛋糕了!
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* hash brownie指一种含有大麻成分的蛋糕, 所以这里是句双关
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1\.
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```py
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some_dict = {}
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some_dict[5.5] = "Ruby"
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some_dict[5.0] = "JavaScript"
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some_dict[5] = "Python"
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```
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**Output:**
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```py
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>>> some_dict[5.5]
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"Ruby"
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>>> some_dict[5.0]
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"Python"
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>>> some_dict[5]
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"Python"
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```
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"Python" 消除了 "JavaScript" 的存在?
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#### 💡 说明:
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* Python 字典通过检查键值是否相等和比较哈希值来确定两个键是否相同.
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* 具有相同值的不可变对象在Python中始终具有相同的哈希值.
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```py
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>>> 5 == 5.0
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True
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>>> hash(5) == hash(5.0)
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True
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```
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**注意:** 具有不同值的对象也可能具有相同的哈希值（哈希冲突）.
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* 当执行 `some_dict[5] = "Python"` 语句时, 因为Python将 `5` 和 `5.0` 识别为 `some_dict` 的同一个键, 所以已有值 "JavaScript" 就被 "Python" 覆盖了.
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* 这个 StackOverflow的 [回答](https://stackoverflow.com/a/32211042/4354153) 漂亮地解释了这背后的基本原理.
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---
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### > Return return everywhere!/到处返回！
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```py
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def some_func():
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try:
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return 'from_try'
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finally:
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return 'from_finally'
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```
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**Output:**
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```py
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>>> some_func()
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'from_finally'
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```
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#### 💡 说明:
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- 当在 "try...finally" 语句的 `try` 中执行 `return`, `break` 或 `continue` 后, `finally` 子句依然会执行.
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- 函数的返回值由最后执行的 `return` 语句决定. 由于 `finally` 子句一定会执行, 所以 `finally` 子句中的 `return` 将始终是最后执行的语句.
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---
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### > Deep down, we're all the same./本质上,我们都一样. *
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```py
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class WTF:
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pass
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```
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**Output:**
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```py
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>>> WTF() == WTF() # 两个不同的对象应该不相等
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False
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>>> WTF() is WTF() # 也不相同
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False
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>>> hash(WTF()) == hash(WTF()) # 哈希值也应该不同
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True
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>>> id(WTF()) == id(WTF())
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True
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```
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#### 💡 说明:
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* 当调用 `id` 函数时, Python 创建了一个 `WTF` 类的对象并传给 `id` 函数. 然后 `id` 函数获取其id值 (也就是内存地址), 然后丢弃该对象. 该对象就被销毁了.
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* 当我们连续两次进行这个操作时, Python会将相同的内存地址分配给第二个对象. 因为 (在CPython中) `id` 函数使用对象的内存地址作为对象的id值, 所以两个对象的id值是相同的.
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* 综上, 对象的id值仅仅在对象的生命周期内唯一. 在对象被销毁之后, 或被创建之前, 其他对象可以具有相同的id值.
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* 那为什么 `is` 操作的结果为 `False` 呢? 让我们看看这段代码.
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```py
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class WTF(object):
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def __init__(self): print("I")
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def __del__(self): print("D")
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```
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**Output:**
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```py
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>>> WTF() is WTF()
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I
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I
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D
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D
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False
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>>> id(WTF()) == id(WTF())
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I
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D
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I
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D
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True
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```
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正如你所看到的, 对象销毁的顺序是造成所有不同之处的原因.
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---
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### > For what?/为什么?
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```py
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some_string = "wtf"
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some_dict = {}
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for i, some_dict[i] in enumerate(some_string):
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pass
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```
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**Output:**
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```py
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>>> some_dict # 创建了索引字典.
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{0: 'w', 1: 't', 2: 'f'}
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```
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#### 💡 说明:
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* [Python 语法](https://docs.python.org/3/reference/grammar.html) 中对 `for` 的定义是:
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```
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for_stmt: 'for' exprlist 'in' testlist ':' suite ['else' ':' suite]
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```
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其中 `exprlist` 指分配目标. 这意味着对可迭代对象中的**每一项都会执行**类似 `{exprlist} = {next_value}` 的操作.
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一个有趣的例子说明了这一点:
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```py
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for i in range(4):
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print(i)
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i = 10
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```
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**Output:**
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```
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0
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1
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2
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3
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```
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你可曾觉得这个循环只会运行一次?
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|
||
**💡 说明:**
|
||
|
||
- 由于循环在Python中工作方式, 赋值语句 `i = 10` 并不会影响迭代循环, 在每次迭代开始之前, 迭代器(这里指 `range(4)`) 生成的下一个元素就被解包并赋值给目标列表的变量(这里指 `i`)了.
|
||
|
||
* 在每一次的迭代中, `enumerate(some_string)` 函数就生成一个新值 `i` (计数器增加) 并从 `some_string` 中获取一个字符. 然后将字典 `some_dict` 键 `i` (刚刚分配的) 的值设为该字符. 本例中循环的展开可以简化为:
|
||
```py
|
||
>>> i, some_dict[i] = (0, 'w')
|
||
>>> i, some_dict[i] = (1, 't')
|
||
>>> i, some_dict[i] = (2, 'f')
|
||
>>> some_dict
|
||
```
|
||
|
||
---
|
||
|
||
### > Evaluation time discrepancy/执行时机差异
|
||
|
||
1\.
|
||
```py
|
||
array = [1, 8, 15]
|
||
g = (x for x in array if array.count(x) > 0)
|
||
array = [2, 8, 22]
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> print(list(g))
|
||
[8]
|
||
```
|
||
|
||
2\.
|
||
|
||
```py
|
||
array_1 = [1,2,3,4]
|
||
g1 = (x for x in array_1)
|
||
array_1 = [1,2,3,4,5]
|
||
|
||
array_2 = [1,2,3,4]
|
||
g2 = (x for x in array_2)
|
||
array_2[:] = [1,2,3,4,5]
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> print(list(g1))
|
||
[1,2,3,4]
|
||
|
||
>>> print(list(g2))
|
||
[1,2,3,4,5]
|
||
```
|
||
|
||
#### 💡 说明
|
||
|
||
- 在[生成器](https://wiki.python.org/moin/Generators)表达式中, `in` 子句在声明时执行, 而条件子句则是在运行时执行.
|
||
- 所以在运行前, `array` 已经被重新赋值为 `[2, 8, 22]`, 因此对于之前的 `1`, `8` 和 `15`, 只有 `count(8)` 的结果是大于 `0` 的, 所以生成器只会生成 `8`.
|
||
- 第二部分中 `g1` 和 `g2` 的输出差异则是由于变量 `array_1` 和 `array_2` 被重新赋值的方式导致的.
|
||
- 在第一种情况下, `array_1` 被绑定到新对象 `[1,2,3,4,5]`, 因为 `in` 子句是在声明时被执行的， 所以它仍然引用旧对象 `[1,2,3,4]`(并没有被销毁).
|
||
- 在第二种情况下, 对 `array_2` 的切片赋值将相同的旧对象 `[1,2,3,4]` 原地更新为 `[1,2,3,4,5]`. 因此 `g2` 和 `array_2` 仍然引用同一个对象(这个对象现在已经更新为 `[1,2,3,4,5]`).
|
||
|
||
---
|
||
|
||
### > `is` is not what it is!/出人意料的`is`!
|
||
|
||
下面是一个在互联网上非常有名的例子.
|
||
|
||
```py
|
||
>>> a = 256
|
||
>>> b = 256
|
||
>>> a is b
|
||
True
|
||
|
||
>>> a = 257
|
||
>>> b = 257
|
||
>>> a is b
|
||
False
|
||
|
||
>>> a = 257; b = 257
|
||
>>> a is b
|
||
True
|
||
```
|
||
|
||
#### 💡 说明:
|
||
|
||
**`is` 和 `==` 的区别**
|
||
|
||
* `is` 运算符检查两个运算对象是否引用自同一对象 (即, 它检查两个运算对象是否相同).
|
||
* `==` 运算符比较两个运算对象的值是否相等.
|
||
* 因此 `is` 代表引用相同, `==` 代表值相等. 下面的例子可以很好的说明这点,
|
||
```py
|
||
>>> [] == []
|
||
True
|
||
>>> [] is [] # 这两个空列表位于不同的内存地址.
|
||
False
|
||
```
|
||
|
||
**`256` 是一个已经存在的对象, 而 `257` 不是**
|
||
|
||
当你启动Python 的时候, 数值为 `-5` 到 `256` 的对象就已经被分配好了. 这些数字因为经常被使用, 所以会被提前准备好.
|
||
|
||
Python 通过这种创建小整数池的方式来避免小整数频繁的申请和销毁内存空间.
|
||
|
||
引用自 https://docs.python.org/3/c-api/long.html
|
||
> 当前的实现为-5到256之间的所有整数保留一个整数对象数组, 当你创建了一个该范围内的整数时, 你只需要返回现有对象的引用. 所以改变1的值是有可能的. 我怀疑这种行为在Python中是未定义行为. :-)
|
||
|
||
```py
|
||
>>> id(256)
|
||
10922528
|
||
>>> a = 256
|
||
>>> b = 256
|
||
>>> id(a)
|
||
10922528
|
||
>>> id(b)
|
||
10922528
|
||
>>> id(257)
|
||
140084850247312
|
||
>>> x = 257
|
||
>>> y = 257
|
||
>>> id(x)
|
||
140084850247440
|
||
>>> id(y)
|
||
140084850247344
|
||
```
|
||
|
||
这里解释器并没有智能到能在执行 `y = 257` 时意识到我们已经创建了一个整数 `257`, 所以它在内存中又新建了另一个对象.
|
||
|
||
**当 `a` 和 `b` 在同一行中使用相同的值初始化时，会指向同一个对象.**
|
||
|
||
```py
|
||
>>> a, b = 257, 257
|
||
>>> id(a)
|
||
140640774013296
|
||
>>> id(b)
|
||
140640774013296
|
||
>>> a = 257
|
||
>>> b = 257
|
||
>>> id(a)
|
||
140640774013392
|
||
>>> id(b)
|
||
140640774013488
|
||
```
|
||
|
||
* 当 a 和 b 在同一行中被设置为 `257` 时, Python 解释器会创建一个新对象, 然后同时引用第二个变量. 如果你在不同的行上进行, 它就不会 "知道" 已经存在一个 `257` 对象了.
|
||
* 这是一种特别为交互式环境做的编译器优化. 当你在实时解释器中输入两行的时候, 他们会单独编译, 因此也会单独进行优化. 如果你在 `.py` 文件中尝试这个例子, 则不会看到相同的行为, 因为文件是一次性编译的.
|
||
|
||
---
|
||
|
||
### > A tic-tac-toe where X wins in the first attempt!/一蹴即至!
|
||
|
||
```py
|
||
# 我们先初始化一个变量row
|
||
row = [""]*3 #row i['', '', '']
|
||
# 并创建一个变量board
|
||
board = [row]*3
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> board
|
||
[['', '', ''], ['', '', ''], ['', '', '']]
|
||
>>> board[0]
|
||
['', '', '']
|
||
>>> board[0][0]
|
||
''
|
||
>>> board[0][0] = "X"
|
||
>>> board
|
||
[['X', '', ''], ['X', '', ''], ['X', '', '']]
|
||
```
|
||
|
||
我们有没有赋值过3个 "X" 呢？
|
||
|
||
#### 💡 说明:
|
||
|
||
当我们初始化 `row` 变量时, 下面这张图展示了内存中的情况。
|
||
|
||
|
||
|
||
而当通过对 `row` 做乘法来初始化 `board` 时, 内存中的情况则如下图所示 (每个元素 `board[0]`, `board[1]` 和 `board[2]` 都和 `row` 一样引用了同一列表.)
|
||
|
||
|
||
|
||
我们可以通过不使用变量 `row` 生成 `board` 来避免这种情况. ([这个](https://github.com/satwikkansal/wtfpython/issues/68)issue提出了这个需求.)
|
||
|
||
```py
|
||
>>> board = [['']*3 for _ in range(3)]
|
||
>>> board[0][0] = "X"
|
||
>>> board
|
||
[['X', '', ''], ['', '', ''], ['', '', '']]
|
||
```
|
||
|
||
---
|
||
|
||
### > The sticky output function/麻烦的输出
|
||
|
||
```py
|
||
funcs = []
|
||
results = []
|
||
for x in range(7):
|
||
def some_func():
|
||
return x
|
||
funcs.append(some_func)
|
||
results.append(some_func()) # 注意这里函数被执行了
|
||
|
||
funcs_results = [func() for func in funcs]
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> results
|
||
[0, 1, 2, 3, 4, 5, 6]
|
||
>>> funcs_results
|
||
[6, 6, 6, 6, 6, 6, 6]
|
||
```
|
||
|
||
即使每次在迭代中将 `some_func` 加入 `funcs` 前的 `x` 值都不相同, 所有的函数还是都返回6.
|
||
|
||
// 再换个例子
|
||
|
||
```py
|
||
>>> powers_of_x = [lambda x: x**i for i in range(10)]
|
||
>>> [f(2) for f in powers_of_x]
|
||
[512, 512, 512, 512, 512, 512, 512, 512, 512, 512]
|
||
```
|
||
|
||
#### 💡 说明:
|
||
|
||
- 当在循环内部定义一个函数时, 如果该函数在其主体中使用了循环变量, 则闭包函数将与循环变量绑定, 而不是它的值. 因此, 所有的函数都是使用最后分配给变量的值来进行计算的.
|
||
|
||
- 可以通过将循环变量作为命名变量传递给函数来获得预期的结果. **为什么这样可行?** 因为这会在函数内再次定义一个局部变量.
|
||
|
||
```py
|
||
funcs = []
|
||
for x in range(7):
|
||
def some_func(x=x):
|
||
return x
|
||
funcs.append(some_func)
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> funcs_results = [func() for func in funcs]
|
||
>>> funcs_results
|
||
[0, 1, 2, 3, 4, 5, 6]
|
||
```
|
||
|
||
---
|
||
|
||
### > `is not ...` is not `is (not ...)`/`is not ...` 不是 `is (not ...)`
|
||
|
||
```py
|
||
>>> 'something' is not None
|
||
True
|
||
>>> 'something' is (not None)
|
||
False
|
||
```
|
||
|
||
#### 💡 说明:
|
||
|
||
- `is not` 是个单独的二元运算符, 与分别使用 `is` 和 `not` 不同.
|
||
- 如果操作符两侧的变量指向同一个对象, 则 `is not` 的结果为 `False`, 否则结果为 `True`.
|
||
|
||
---
|
||
|
||
### > The surprising comma/意外的逗号
|
||
|
||
**Output:**
|
||
```py
|
||
>>> def f(x, y,):
|
||
... print(x, y)
|
||
...
|
||
>>> def g(x=4, y=5,):
|
||
... print(x, y)
|
||
...
|
||
>>> def h(x, **kwargs,):
|
||
File "<stdin>", line 1
|
||
def h(x, **kwargs,):
|
||
^
|
||
SyntaxError: invalid syntax
|
||
>>> def h(*args,):
|
||
File "<stdin>", line 1
|
||
def h(*args,):
|
||
^
|
||
SyntaxError: invalid syntax
|
||
```
|
||
|
||
#### 💡 说明:
|
||
|
||
- 在Python函数的形式参数列表中, 尾随逗号并不一定是合法的.
|
||
- 在Python中, 参数列表部分用前置逗号定义, 部分用尾随逗号定义. 这种冲突导致逗号被夹在中间, 没有规则定义它.(译:这一句看得我也很懵逼,只能强翻了.详细解释看下面的讨论帖会一目了然.)
|
||
- **注意:** 尾随逗号的问题已经在Python 3.6中被[修复](https://bugs.python.org/issue9232)了. 而这篇[帖子](https://bugs.python.org/issue9232#msg248399)中则简要讨论了Python中尾随逗号的不同用法.
|
||
---
|
||
|
||
### > Backslashes at the end of string/字符串末尾的反斜杠
|
||
|
||
**Output:**
|
||
```
|
||
>>> print("\\ C:\\")
|
||
\ C:\
|
||
>>> print(r"\ C:")
|
||
\ C:
|
||
>>> print(r"\ C:\")
|
||
|
||
File "<stdin>", line 1
|
||
print(r"\ C:\")
|
||
^
|
||
SyntaxError: EOL while scanning string literal
|
||
```
|
||
|
||
#### 💡 说明:
|
||
|
||
- 在以 `r` 开头的原始字符串中, 反斜杠并没有特殊含义.
|
||
```py
|
||
>>> print(repr(r"wt\"f"))
|
||
'wt\\"f'
|
||
```
|
||
- 解释器所做的只是简单的改变了反斜杠的行为, 因此会直接放行反斜杠及后一个的字符. 这就是反斜杠在原始字符串末尾不起作用的原因.
|
||
|
||
---
|
||
|
||
### > not knot!/别纠结!
|
||
|
||
```py
|
||
x = True
|
||
y = False
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> not x == y
|
||
True
|
||
>>> x == not y
|
||
File "<input>", line 1
|
||
x == not y
|
||
^
|
||
SyntaxError: invalid syntax
|
||
```
|
||
|
||
#### 💡 说明:
|
||
|
||
* 运算符的优先级会影响表达式的求值顺序, 而在 Python 中 `==` 运算符的优先级要高于 `not` 运算符.
|
||
* 所以 `not x == y` 相当于 `not (x == y)`, 同时等价于 `not (True == False)`, 最后的运算结果就是 `True`.
|
||
* 之所以 `x == not y` 会抛一个 `SyntaxError` 异常, 是因为它会被认为等价于 `(x == not) y`, 而不是你一开始期望的 `x == (not y)`.
|
||
* 解释器期望 `not` 标记是 `not in` 操作符的一部分 (因为 `==` 和 `not in` 操作符具有相同的优先级), 但是它在 `not` 标记后面找不到 `in` 标记, 所以会抛出 `SyntaxError` 异常.
|
||
|
||
---
|
||
|
||
### > Half triple-quoted strings
|
||
|
||
**Output:**
|
||
```py
|
||
>>> print('wtfpython''')
|
||
wtfpython
|
||
>>> print("wtfpython""")
|
||
wtfpython
|
||
>>> # The following statements raise `SyntaxError`
|
||
>>> # print('''wtfpython')
|
||
>>> # print("""wtfpython")
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
+ Python supports implicit [string literal concatenation](https://docs.python.org/2/reference/lexical_analysis.html#string-literal-concatenation), Example,
|
||
```
|
||
>>> print("wtf" "python")
|
||
wtfpython
|
||
>>> print("wtf" "") # or "wtf"""
|
||
wtf
|
||
```
|
||
+ `'''` and `"""` are also string delimiters in Python which causes a SyntaxError because the Python interpreter was expecting a terminating triple quote as delimiter while scanning the currently encountered triple quoted string literal.
|
||
|
||
---
|
||
|
||
### > Midnight time doesn't exist?
|
||
|
||
```py
|
||
from datetime import datetime
|
||
|
||
midnight = datetime(2018, 1, 1, 0, 0)
|
||
midnight_time = midnight.time()
|
||
|
||
noon = datetime(2018, 1, 1, 12, 0)
|
||
noon_time = noon.time()
|
||
|
||
if midnight_time:
|
||
print("Time at midnight is", midnight_time)
|
||
|
||
if noon_time:
|
||
print("Time at noon is", noon_time)
|
||
```
|
||
|
||
**Output:**
|
||
```sh
|
||
('Time at noon is', datetime.time(12, 0))
|
||
```
|
||
The midnight time is not printed.
|
||
|
||
#### 💡 Explanation:
|
||
|
||
Before Python 3.5, the boolean value for `datetime.time` object was considered to be `False` if it represented midnight in UTC. It is error-prone when using the `if obj:` syntax to check if the `obj` is null or some equivalent of "empty."
|
||
|
||
---
|
||
|
||
### > What's wrong with booleans?
|
||
|
||
1\.
|
||
```py
|
||
# A simple example to count the number of boolean and
|
||
# integers in an iterable of mixed data types.
|
||
mixed_list = [False, 1.0, "some_string", 3, True, [], False]
|
||
integers_found_so_far = 0
|
||
booleans_found_so_far = 0
|
||
|
||
for item in mixed_list:
|
||
if isinstance(item, int):
|
||
integers_found_so_far += 1
|
||
elif isinstance(item, bool):
|
||
booleans_found_so_far += 1
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> integers_found_so_far
|
||
4
|
||
>>> booleans_found_so_far
|
||
0
|
||
```
|
||
|
||
2\.
|
||
```py
|
||
another_dict = {}
|
||
another_dict[True] = "JavaScript"
|
||
another_dict[1] = "Ruby"
|
||
another_dict[1.0] = "Python"
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> another_dict[True]
|
||
"Python"
|
||
```
|
||
|
||
3\.
|
||
```py
|
||
>>> some_bool = True
|
||
>>> "wtf"*some_bool
|
||
'wtf'
|
||
>>> some_bool = False
|
||
>>> "wtf"*some_bool
|
||
''
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Booleans are a subclass of `int`
|
||
```py
|
||
>>> isinstance(True, int)
|
||
True
|
||
>>> isinstance(False, int)
|
||
True
|
||
```
|
||
|
||
* The integer value of `True` is `1` and that of `False` is `0`.
|
||
```py
|
||
>>> True == 1 == 1.0 and False == 0 == 0.0
|
||
True
|
||
```
|
||
|
||
* See this StackOverflow [answer](https://stackoverflow.com/a/8169049/4354153) for the rationale behind it.
|
||
|
||
---
|
||
|
||
### > Class attributes and instance attributes
|
||
|
||
1\.
|
||
```py
|
||
class A:
|
||
x = 1
|
||
|
||
class B(A):
|
||
pass
|
||
|
||
class C(A):
|
||
pass
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> A.x, B.x, C.x
|
||
(1, 1, 1)
|
||
>>> B.x = 2
|
||
>>> A.x, B.x, C.x
|
||
(1, 2, 1)
|
||
>>> A.x = 3
|
||
>>> A.x, B.x, C.x
|
||
(3, 2, 3)
|
||
>>> a = A()
|
||
>>> a.x, A.x
|
||
(3, 3)
|
||
>>> a.x += 1
|
||
>>> a.x, A.x
|
||
(4, 3)
|
||
```
|
||
|
||
2\.
|
||
```py
|
||
class SomeClass:
|
||
some_var = 15
|
||
some_list = [5]
|
||
another_list = [5]
|
||
def __init__(self, x):
|
||
self.some_var = x + 1
|
||
self.some_list = self.some_list + [x]
|
||
self.another_list += [x]
|
||
```
|
||
|
||
**Output:**
|
||
|
||
```py
|
||
>>> some_obj = SomeClass(420)
|
||
>>> some_obj.some_list
|
||
[5, 420]
|
||
>>> some_obj.another_list
|
||
[5, 420]
|
||
>>> another_obj = SomeClass(111)
|
||
>>> another_obj.some_list
|
||
[5, 111]
|
||
>>> another_obj.another_list
|
||
[5, 420, 111]
|
||
>>> another_obj.another_list is SomeClass.another_list
|
||
True
|
||
>>> another_obj.another_list is some_obj.another_list
|
||
True
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Class variables and variables in class instances are internally handled as dictionaries of a class object. If a variable name is not found in the dictionary of the current class, the parent classes are searched for it.
|
||
* The `+=` operator modifies the mutable object in-place without creating a new object. So changing the attribute of one instance affects the other instances and the class attribute as well.
|
||
|
||
---
|
||
|
||
### > yielding None
|
||
|
||
```py
|
||
some_iterable = ('a', 'b')
|
||
|
||
def some_func(val):
|
||
return "something"
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> [x for x in some_iterable]
|
||
['a', 'b']
|
||
>>> [(yield x) for x in some_iterable]
|
||
<generator object <listcomp> at 0x7f70b0a4ad58>
|
||
>>> list([(yield x) for x in some_iterable])
|
||
['a', 'b']
|
||
>>> list((yield x) for x in some_iterable)
|
||
['a', None, 'b', None]
|
||
>>> list(some_func((yield x)) for x in some_iterable)
|
||
['a', 'something', 'b', 'something']
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
- Source and explanation can be found here: https://stackoverflow.com/questions/32139885/yield-in-list-comprehensions-and-generator-expressions
|
||
- Related bug report: http://bugs.python.org/issue10544
|
||
|
||
---
|
||
|
||
### > Mutating the immutable!
|
||
|
||
```py
|
||
some_tuple = ("A", "tuple", "with", "values")
|
||
another_tuple = ([1, 2], [3, 4], [5, 6])
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> some_tuple[2] = "change this"
|
||
TypeError: 'tuple' object does not support item assignment
|
||
>>> another_tuple[2].append(1000) #This throws no error
|
||
>>> another_tuple
|
||
([1, 2], [3, 4], [5, 6, 1000])
|
||
>>> another_tuple[2] += [99, 999]
|
||
TypeError: 'tuple' object does not support item assignment
|
||
>>> another_tuple
|
||
([1, 2], [3, 4], [5, 6, 1000, 99, 999])
|
||
```
|
||
|
||
But I thought tuples were immutable...
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Quoting from https://docs.python.org/2/reference/datamodel.html
|
||
|
||
> Immutable sequences
|
||
An object of an immutable sequence type cannot change once it is created. (If the object contains references to other objects, these other objects may be mutable and may be modified; however, the collection of objects directly referenced by an immutable object cannot change.)
|
||
|
||
* `+=` operator changes the list in-place. The item assignment doesn't work, but when the exception occurs, the item has already been changed in place.
|
||
|
||
---
|
||
|
||
### > The disappearing variable from outer scope
|
||
|
||
```py
|
||
e = 7
|
||
try:
|
||
raise Exception()
|
||
except Exception as e:
|
||
pass
|
||
```
|
||
|
||
**Output (Python 2.x):**
|
||
```py
|
||
>>> print(e)
|
||
# prints nothing
|
||
```
|
||
|
||
**Output (Python 3.x):**
|
||
```py
|
||
>>> print(e)
|
||
NameError: name 'e' is not defined
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Source: https://docs.python.org/3/reference/compound_stmts.html#except
|
||
|
||
When an exception has been assigned using `as` target, it is cleared at the end of the except clause. This is as if
|
||
|
||
```py
|
||
except E as N:
|
||
foo
|
||
```
|
||
|
||
was translated into
|
||
|
||
```py
|
||
except E as N:
|
||
try:
|
||
foo
|
||
finally:
|
||
del N
|
||
```
|
||
|
||
This means the exception must be assigned to a different name to be able to refer to it after the except clause. Exceptions are cleared because, with the traceback attached to them, they form a reference cycle with the stack frame, keeping all locals in that frame alive until the next garbage collection occurs.
|
||
|
||
* The clauses are not scoped in Python. Everything in the example is present in the same scope, and the variable `e` got removed due to the execution of the `except` clause. The same is not the case with functions which have their separate inner-scopes. The example below illustrates this:
|
||
|
||
```py
|
||
def f(x):
|
||
del(x)
|
||
print(x)
|
||
|
||
x = 5
|
||
y = [5, 4, 3]
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>>f(x)
|
||
UnboundLocalError: local variable 'x' referenced before assignment
|
||
>>>f(y)
|
||
UnboundLocalError: local variable 'x' referenced before assignment
|
||
>>> x
|
||
5
|
||
>>> y
|
||
[5, 4, 3]
|
||
```
|
||
|
||
* In Python 2.x the variable name `e` gets assigned to `Exception()` instance, so when you try to print, it prints nothing.
|
||
|
||
**Output (Python 2.x):**
|
||
```py
|
||
>>> e
|
||
Exception()
|
||
>>> print e
|
||
# Nothing is printed!
|
||
```
|
||
|
||
---
|
||
|
||
### > When True is actually False
|
||
|
||
```py
|
||
True = False
|
||
if True == False:
|
||
print("I've lost faith in truth!")
|
||
```
|
||
|
||
**Output:**
|
||
```
|
||
I've lost faith in truth!
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
- Initially, Python used to have no `bool` type (people used 0 for false and non-zero value like 1 for true). Then they added `True`, `False`, and a `bool` type, but, for backward compatibility, they couldn't make `True` and `False` constants- they just were built-in variables.
|
||
- Python 3 was backward-incompatible, so it was now finally possible to fix that, and so this example won't work with Python 3.x!
|
||
|
||
---
|
||
|
||
### > From filled to None in one instruction...
|
||
|
||
```py
|
||
some_list = [1, 2, 3]
|
||
some_dict = {
|
||
"key_1": 1,
|
||
"key_2": 2,
|
||
"key_3": 3
|
||
}
|
||
|
||
some_list = some_list.append(4)
|
||
some_dict = some_dict.update({"key_4": 4})
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> print(some_list)
|
||
None
|
||
>>> print(some_dict)
|
||
None
|
||
```
|
||
|
||
#### 💡 Explanation
|
||
|
||
Most methods that modify the items of sequence/mapping objects like `list.append`, `dict.update`, `list.sort`, etc. modify the objects in-place and return `None`. The rationale behind this is to improve performance by avoiding making a copy of the object if the operation can be done in-place (Referred from [here](http://docs.python.org/2/faq/design.html#why-doesn-t-list-sort-return-the-sorted-list))
|
||
|
||
---
|
||
|
||
### > Subclass relationships *
|
||
|
||
**Output:**
|
||
```py
|
||
>>> from collections import Hashable
|
||
>>> issubclass(list, object)
|
||
True
|
||
>>> issubclass(object, Hashable)
|
||
True
|
||
>>> issubclass(list, Hashable)
|
||
False
|
||
```
|
||
|
||
The Subclass relationships were expected to be transitive, right? (i.e., if `A` is a subclass of `B`, and `B` is a subclass of `C`, the `A` _should_ a subclass of `C`)
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Subclass relationships are not necessarily transitive in Python. Anyone is allowed to define their own, arbitrary `__subclasscheck__` in a metaclass.
|
||
* When `issubclass(cls, Hashable)` is called, it simply looks for non-Falsey "`__hash__`" method in `cls` or anything it inherits from.
|
||
* Since `object` is hashable, but `list` is non-hashable, it breaks the transitivity relation.
|
||
* More detailed explanation can be found [here](https://www.naftaliharris.com/blog/python-subclass-intransitivity/).
|
||
|
||
---
|
||
|
||
### > The mysterious key type conversion *
|
||
|
||
```py
|
||
class SomeClass(str):
|
||
pass
|
||
|
||
some_dict = {'s':42}
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> type(list(some_dict.keys())[0])
|
||
str
|
||
>>> s = SomeClass('s')
|
||
>>> some_dict[s] = 40
|
||
>>> some_dict # expected: Two different keys-value pairs
|
||
{'s': 40}
|
||
>>> type(list(some_dict.keys())[0])
|
||
str
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Both the object `s` and the string `"s"` hash to the same value because `SomeClass` inherits the `__hash__` method of `str` class.
|
||
* `SomeClass("s") == "s"` evaluates to `True` because `SomeClass` also inherits `__eq__` method from `str` class.
|
||
* Since both the objects hash to the same value and are equal, they are represented by the same key in the dictionary.
|
||
* For the desired behavior, we can redefine the `__eq__` method in `SomeClass`
|
||
```py
|
||
class SomeClass(str):
|
||
def __eq__(self, other):
|
||
return (
|
||
type(self) is SomeClass
|
||
and type(other) is SomeClass
|
||
and super().__eq__(other)
|
||
)
|
||
|
||
# When we define a custom __eq__, Python stops automatically inheriting the
|
||
# __hash__ method, so we need to define it as well
|
||
__hash__ = str.__hash__
|
||
|
||
some_dict = {'s':42}
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> s = SomeClass('s')
|
||
>>> some_dict[s] = 40
|
||
>>> some_dict
|
||
{'s': 40, 's': 42}
|
||
>>> keys = list(some_dict.keys())
|
||
>>> type(keys[0]), type(keys[1])
|
||
(__main__.SomeClass, str)
|
||
```
|
||
|
||
---
|
||
|
||
### > Let's see if you can guess this?
|
||
|
||
```py
|
||
a, b = a[b] = {}, 5
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> a
|
||
{5: ({...}, 5)}
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* According to [Python language reference](https://docs.python.org/2/reference/simple_stmts.html#assignment-statements), assignment statements have the form
|
||
```
|
||
(target_list "=")+ (expression_list | yield_expression)
|
||
```
|
||
and
|
||
> An assignment statement evaluates the expression list (remember that this can be a single expression or a comma-separated list, the latter yielding a tuple) and assigns the single resulting object to each of the target lists, from left to right.
|
||
|
||
* The `+` in `(target_list "=")+` means there can be **one or more** target lists. In this case, target lists are `a, b` and `a[b]` (note the expression list is exactly one, which in our case is `{}, 5`).
|
||
|
||
* After the expression list is evaluated, it's value is unpacked to the target lists from **left to right**. So, in our case, first the `{}, 5` tuple is unpacked to `a, b` and we now have `a = {}` and `b = 5`.
|
||
|
||
* `a` is now assigned to `{}` which is a mutable object.
|
||
|
||
* The second target list is `a[b]` (you may expect this to throw an error because both `a` and `b` have not been defined in the statements before. But remember, we just assigned `a` to `{}` and `b` to `5`).
|
||
|
||
* Now, we are setting the key `5` in the dictionary to the tuple `({}, 5)` creating a circular reference (the `{...}` in the output refers to the same object that `a` is already referencing). Another simpler example of circular reference could be
|
||
```py
|
||
>>> some_list = some_list[0] = [0]
|
||
>>> some_list
|
||
[[...]]
|
||
>>> some_list[0]
|
||
[[...]]
|
||
>>> some_list is some_list[0]
|
||
True
|
||
>>> some_list[0][0][0][0][0][0] == some_list
|
||
True
|
||
```
|
||
Similar is the case in our example (`a[b][0]` is the same object as `a`)
|
||
|
||
* So to sum it up, you can break the example down to
|
||
```py
|
||
a, b = {}, 5
|
||
a[b] = a, b
|
||
```
|
||
And the circular reference can be justified by the fact that `a[b][0]` is the same object as `a`
|
||
```py
|
||
>>> a[b][0] is a
|
||
True
|
||
```
|
||
|
||
---
|
||
|
||
---
|
||
|
||
## Section: Appearances are deceptive!
|
||
|
||
### > Skipping lines?
|
||
|
||
**Output:**
|
||
```py
|
||
>>> value = 11
|
||
>>> valuе = 32
|
||
>>> value
|
||
11
|
||
```
|
||
|
||
Wut?
|
||
|
||
**Note:** The easiest way to reproduce this is to simply copy the statements from the above snippet and paste them into your file/shell.
|
||
|
||
#### 💡 Explanation
|
||
|
||
Some non-Western characters look identical to letters in the English alphabet but are considered distinct by the interpreter.
|
||
|
||
```py
|
||
>>> ord('е') # cyrillic 'e' (Ye)
|
||
1077
|
||
>>> ord('e') # latin 'e', as used in English and typed using standard keyboard
|
||
101
|
||
>>> 'е' == 'e'
|
||
False
|
||
|
||
>>> value = 42 # latin e
|
||
>>> valuе = 23 # cyrillic 'e', Python 2.x interpreter would raise a `SyntaxError` here
|
||
>>> value
|
||
42
|
||
```
|
||
|
||
The built-in `ord()` function returns a character's Unicode [code point](https://en.wikipedia.org/wiki/Code_point), and different code positions of Cyrillic 'e' and Latin 'e' justify the behavior of the above example.
|
||
|
||
---
|
||
|
||
### > Teleportation *
|
||
|
||
```py
|
||
import numpy as np
|
||
|
||
def energy_send(x):
|
||
# Initializing a numpy array
|
||
np.array([float(x)])
|
||
|
||
def energy_receive():
|
||
# Return an empty numpy array
|
||
return np.empty((), dtype=np.float).tolist()
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> energy_send(123.456)
|
||
>>> energy_receive()
|
||
123.456
|
||
```
|
||
|
||
Where's the Nobel Prize?
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Notice that the numpy array created in the `energy_send` function is not returned, so that memory space is free to reallocate.
|
||
* `numpy.empty()` returns the next free memory slot without reinitializing it. This memory spot just happens to be the same one that was just freed (usually, but not always).
|
||
|
||
---
|
||
|
||
### > Well, something is fishy...
|
||
|
||
```py
|
||
def square(x):
|
||
"""
|
||
A simple function to calculate the square of a number by addition.
|
||
"""
|
||
sum_so_far = 0
|
||
for counter in range(x):
|
||
sum_so_far = sum_so_far + x
|
||
return sum_so_far
|
||
```
|
||
|
||
**Output (Python 2.x):**
|
||
|
||
```py
|
||
>>> square(10)
|
||
10
|
||
```
|
||
|
||
Shouldn't that be 100?
|
||
|
||
**Note:** If you're not able to reproduce this, try running the file [mixed_tabs_and_spaces.py](/mixed_tabs_and_spaces.py) via the shell.
|
||
|
||
#### 💡 Explanation
|
||
|
||
* **Don't mix tabs and spaces!** The character just preceding return is a "tab", and the code is indented by multiple of "4 spaces" elsewhere in the example.
|
||
* This is how Python handles tabs:
|
||
> First, tabs are replaced (from left to right) by one to eight spaces such that the total number of characters up to and including the replacement is a multiple of eight <...>
|
||
* So the "tab" at the last line of `square` function is replaced with eight spaces, and it gets into the loop.
|
||
* Python 3 is kind enough to throw an error for such cases automatically.
|
||
|
||
**Output (Python 3.x):**
|
||
```py
|
||
TabError: inconsistent use of tabs and spaces in indentation
|
||
```
|
||
|
||
---
|
||
|
||
---
|
||
|
||
## Section: Watch out for the landmines!
|
||
|
||
|
||
### > Modifying a dictionary while iterating over it
|
||
|
||
```py
|
||
x = {0: None}
|
||
|
||
for i in x:
|
||
del x[i]
|
||
x[i+1] = None
|
||
print(i)
|
||
```
|
||
|
||
**Output (Python 2.7- Python 3.5):**
|
||
|
||
```
|
||
0
|
||
1
|
||
2
|
||
3
|
||
4
|
||
5
|
||
6
|
||
7
|
||
```
|
||
|
||
Yes, it runs for exactly **eight** times and stops.
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* Iteration over a dictionary that you edit at the same time is not supported.
|
||
* It runs eight times because that's the point at which the dictionary resizes to hold more keys (we have eight deletion entries, so a resize is needed). This is actually an implementation detail.
|
||
* How deleted keys are handled and when the resize occurs might be different for different Python implementations.
|
||
* For more information, you may refer to this StackOverflow [thread](https://stackoverflow.com/questions/44763802/bug-in-python-dict) explaining a similar example in detail.
|
||
|
||
---
|
||
|
||
### > Stubborn `del` operator *
|
||
|
||
```py
|
||
class SomeClass:
|
||
def __del__(self):
|
||
print("Deleted!")
|
||
```
|
||
|
||
**Output:**
|
||
1\.
|
||
```py
|
||
>>> x = SomeClass()
|
||
>>> y = x
|
||
>>> del x # this should print "Deleted!"
|
||
>>> del y
|
||
Deleted!
|
||
```
|
||
|
||
Phew, deleted at last. You might have guessed what saved from `__del__` being called in our first attempt to delete `x`. Let's add more twist to the example.
|
||
|
||
2\.
|
||
```py
|
||
>>> x = SomeClass()
|
||
>>> y = x
|
||
>>> del x
|
||
>>> y # check if y exists
|
||
<__main__.SomeClass instance at 0x7f98a1a67fc8>
|
||
>>> del y # Like previously, this should print "Deleted!"
|
||
>>> globals() # oh, it didn't. Let's check all our global variables and confirm
|
||
Deleted!
|
||
{'__builtins__': <module '__builtin__' (built-in)>, 'SomeClass': <class __main__.SomeClass at 0x7f98a1a5f668>, '__package__': None, '__name__': '__main__', '__doc__': None}
|
||
```
|
||
|
||
Okay, now it's deleted :confused:
|
||
|
||
#### 💡 Explanation:
|
||
+ `del x` doesn’t directly call `x.__del__()`.
|
||
+ Whenever `del x` is encountered, Python decrements the reference count for `x` by one, and `x.__del__()` when x’s reference count reaches zero.
|
||
+ In the second output snippet, `y.__del__()` was not called because the previous statement (`>>> y`) in the interactive interpreter created another reference to the same object, thus preventing the reference count to reach zero when `del y` was encountered.
|
||
+ Calling `globals` caused the existing reference to be destroyed and hence we can see "Deleted!" being printed (finally!).
|
||
|
||
---
|
||
|
||
### > Deleting a list item while iterating
|
||
|
||
```py
|
||
list_1 = [1, 2, 3, 4]
|
||
list_2 = [1, 2, 3, 4]
|
||
list_3 = [1, 2, 3, 4]
|
||
list_4 = [1, 2, 3, 4]
|
||
|
||
for idx, item in enumerate(list_1):
|
||
del item
|
||
|
||
for idx, item in enumerate(list_2):
|
||
list_2.remove(item)
|
||
|
||
for idx, item in enumerate(list_3[:]):
|
||
list_3.remove(item)
|
||
|
||
for idx, item in enumerate(list_4):
|
||
list_4.pop(idx)
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> list_1
|
||
[1, 2, 3, 4]
|
||
>>> list_2
|
||
[2, 4]
|
||
>>> list_3
|
||
[]
|
||
>>> list_4
|
||
[2, 4]
|
||
```
|
||
|
||
Can you guess why the output is `[2, 4]`?
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* It's never a good idea to change the object you're iterating over. The correct way to do so is to iterate over a copy of the object instead, and `list_3[:]` does just that.
|
||
|
||
```py
|
||
>>> some_list = [1, 2, 3, 4]
|
||
>>> id(some_list)
|
||
139798789457608
|
||
>>> id(some_list[:]) # Notice that python creates new object for sliced list.
|
||
139798779601192
|
||
```
|
||
|
||
**Difference between `del`, `remove`, and `pop`:**
|
||
* `del var_name` just removes the binding of the `var_name` from the local or global namespace (That's why the `list_1` is unaffected).
|
||
* `remove` removes the first matching value, not a specific index, raises `ValueError` if the value is not found.
|
||
* `pop` removes the element at a specific index and returns it, raises `IndexError` if an invalid index is specified.
|
||
|
||
**Why the output is `[2, 4]`?**
|
||
- The list iteration is done index by index, and when we remove `1` from `list_2` or `list_4`, the contents of the lists are now `[2, 3, 4]`. The remaining elements are shifted down, i.e., `2` is at index 0, and `3` is at index 1. Since the next iteration is going to look at index 1 (which is the `3`), the `2` gets skipped entirely. A similar thing will happen with every alternate element in the list sequence.
|
||
|
||
* Refer to this StackOverflow [thread](https://stackoverflow.com/questions/45946228/what-happens-when-you-try-to-delete-a-list-element-while-iterating-over-it) explaining the example
|
||
* See also this nice StackOverflow [thread](https://stackoverflow.com/questions/45877614/how-to-change-all-the-dictionary-keys-in-a-for-loop-with-d-items) for a similar example related to dictionaries in Python.
|
||
|
||
---
|
||
|
||
### > Loop variables leaking out!
|
||
|
||
1\.
|
||
```py
|
||
for x in range(7):
|
||
if x == 6:
|
||
print(x, ': for x inside loop')
|
||
print(x, ': x in global')
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
6 : for x inside loop
|
||
6 : x in global
|
||
```
|
||
|
||
But `x` was never defined outside the scope of for loop...
|
||
|
||
2\.
|
||
```py
|
||
# This time let's initialize x first
|
||
x = -1
|
||
for x in range(7):
|
||
if x == 6:
|
||
print(x, ': for x inside loop')
|
||
print(x, ': x in global')
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
6 : for x inside loop
|
||
6 : x in global
|
||
```
|
||
|
||
3\.
|
||
```
|
||
x = 1
|
||
print([x for x in range(5)])
|
||
print(x, ': x in global')
|
||
```
|
||
|
||
**Output (on Python 2.x):**
|
||
```
|
||
[0, 1, 2, 3, 4]
|
||
(4, ': x in global')
|
||
```
|
||
|
||
**Output (on Python 3.x):**
|
||
```
|
||
[0, 1, 2, 3, 4]
|
||
1 : x in global
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
- In Python, for-loops use the scope they exist in and leave their defined loop-variable behind. This also applies if we explicitly defined the for-loop variable in the global namespace before. In this case, it will rebind the existing variable.
|
||
|
||
- The differences in the output of Python 2.x and Python 3.x interpreters for list comprehension example can be explained by following change documented in [What’s New In Python 3.0](https://docs.python.org/3/whatsnew/3.0.html) documentation:
|
||
|
||
> "List comprehensions no longer support the syntactic form `[... for var in item1, item2, ...]`. Use `[... for var in (item1, item2, ...)]` instead. Also, note that list comprehensions have different semantics: they are closer to syntactic sugar for a generator expression inside a `list()` constructor, and in particular the loop control variables are no longer leaked into the surrounding scope."
|
||
|
||
---
|
||
|
||
### > Beware of default mutable arguments!
|
||
|
||
```py
|
||
def some_func(default_arg=[]):
|
||
default_arg.append("some_string")
|
||
return default_arg
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> some_func()
|
||
['some_string']
|
||
>>> some_func()
|
||
['some_string', 'some_string']
|
||
>>> some_func([])
|
||
['some_string']
|
||
>>> some_func()
|
||
['some_string', 'some_string', 'some_string']
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
- The default mutable arguments of functions in Python aren't really initialized every time you call the function. Instead, the recently assigned value to them is used as the default value. When we explicitly passed `[]` to `some_func` as the argument, the default value of the `default_arg` variable was not used, so the function returned as expected.
|
||
|
||
```py
|
||
def some_func(default_arg=[]):
|
||
default_arg.append("some_string")
|
||
return default_arg
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> some_func.__defaults__ #This will show the default argument values for the function
|
||
([],)
|
||
>>> some_func()
|
||
>>> some_func.__defaults__
|
||
(['some_string'],)
|
||
>>> some_func()
|
||
>>> some_func.__defaults__
|
||
(['some_string', 'some_string'],)
|
||
>>> some_func([])
|
||
>>> some_func.__defaults__
|
||
(['some_string', 'some_string'],)
|
||
```
|
||
|
||
- A common practice to avoid bugs due to mutable arguments is to assign `None` as the default value and later check if any value is passed to the function corresponding to that argument. Example:
|
||
|
||
```py
|
||
def some_func(default_arg=None):
|
||
if not default_arg:
|
||
default_arg = []
|
||
default_arg.append("some_string")
|
||
return default_arg
|
||
```
|
||
|
||
---
|
||
|
||
### > Catching the Exceptions
|
||
|
||
```py
|
||
some_list = [1, 2, 3]
|
||
try:
|
||
# This should raise an ``IndexError``
|
||
print(some_list[4])
|
||
except IndexError, ValueError:
|
||
print("Caught!")
|
||
|
||
try:
|
||
# This should raise a ``ValueError``
|
||
some_list.remove(4)
|
||
except IndexError, ValueError:
|
||
print("Caught again!")
|
||
```
|
||
|
||
**Output (Python 2.x):**
|
||
```py
|
||
Caught!
|
||
|
||
ValueError: list.remove(x): x not in list
|
||
```
|
||
|
||
**Output (Python 3.x):**
|
||
```py
|
||
File "<input>", line 3
|
||
except IndexError, ValueError:
|
||
^
|
||
SyntaxError: invalid syntax
|
||
```
|
||
|
||
#### 💡 Explanation
|
||
|
||
* To add multiple Exceptions to the except clause, you need to pass them as parenthesized tuple as the first argument. The second argument is an optional name, which when supplied will bind the Exception instance that has been raised. Example,
|
||
```py
|
||
some_list = [1, 2, 3]
|
||
try:
|
||
# This should raise a ``ValueError``
|
||
some_list.remove(4)
|
||
except (IndexError, ValueError), e:
|
||
print("Caught again!")
|
||
print(e)
|
||
```
|
||
**Output (Python 2.x):**
|
||
```
|
||
Caught again!
|
||
list.remove(x): x not in list
|
||
```
|
||
**Output (Python 3.x):**
|
||
```py
|
||
File "<input>", line 4
|
||
except (IndexError, ValueError), e:
|
||
^
|
||
IndentationError: unindent does not match any outer indentation level
|
||
```
|
||
|
||
* Separating the exception from the variable with a comma is deprecated and does not work in Python 3; the correct way is to use `as`. Example,
|
||
```py
|
||
some_list = [1, 2, 3]
|
||
try:
|
||
some_list.remove(4)
|
||
|
||
except (IndexError, ValueError) as e:
|
||
print("Caught again!")
|
||
print(e)
|
||
```
|
||
**Output:**
|
||
```
|
||
Caught again!
|
||
list.remove(x): x not in list
|
||
```
|
||
|
||
---
|
||
|
||
### > Same operands, different story!
|
||
|
||
1\.
|
||
```py
|
||
a = [1, 2, 3, 4]
|
||
b = a
|
||
a = a + [5, 6, 7, 8]
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> a
|
||
[1, 2, 3, 4, 5, 6, 7, 8]
|
||
>>> b
|
||
[1, 2, 3, 4]
|
||
```
|
||
|
||
2\.
|
||
```py
|
||
a = [1, 2, 3, 4]
|
||
b = a
|
||
a += [5, 6, 7, 8]
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> a
|
||
[1, 2, 3, 4, 5, 6, 7, 8]
|
||
>>> b
|
||
[1, 2, 3, 4, 5, 6, 7, 8]
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* `a += b` doesn't always behave the same way as `a = a + b`. Classes *may* implement the *`op=`* operators differently, and lists do this.
|
||
|
||
* The expression `a = a + [5,6,7,8]` generates a new list and sets `a`'s reference to that new list, leaving `b` unchanged.
|
||
|
||
* The expression `a += [5,6,7,8]` is actually mapped to an "extend" function that operates on the list such that `a` and `b` still point to the same list that has been modified in-place.
|
||
|
||
---
|
||
|
||
### > The out of scope variable
|
||
|
||
```py
|
||
a = 1
|
||
def some_func():
|
||
return a
|
||
|
||
def another_func():
|
||
a += 1
|
||
return a
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> some_func()
|
||
1
|
||
>>> another_func()
|
||
UnboundLocalError: local variable 'a' referenced before assignment
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
* When you make an assignment to a variable in scope, it becomes local to that scope. So `a` becomes local to the scope of `another_func`, but it has not been initialized previously in the same scope which throws an error.
|
||
* Read [this](http://sebastianraschka.com/Articles/2014_python_scope_and_namespaces.html) short but an awesome guide to learn more about how namespaces and scope resolution works in Python.
|
||
* To modify the outer scope variable `a` in `another_func`, use `global` keyword.
|
||
```py
|
||
def another_func()
|
||
global a
|
||
a += 1
|
||
return a
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> another_func()
|
||
2
|
||
```
|
||
|
||
---
|
||
|
||
### > Be careful with chained operations
|
||
|
||
```py
|
||
>>> (False == False) in [False] # makes sense
|
||
False
|
||
>>> False == (False in [False]) # makes sense
|
||
False
|
||
>>> False == False in [False] # now what?
|
||
True
|
||
|
||
>>> True is False == False
|
||
False
|
||
>>> False is False is False
|
||
True
|
||
|
||
>>> 1 > 0 < 1
|
||
True
|
||
>>> (1 > 0) < 1
|
||
False
|
||
>>> 1 > (0 < 1)
|
||
False
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
As per https://docs.python.org/2/reference/expressions.html#not-in
|
||
|
||
> Formally, if a, b, c, ..., y, z are expressions and op1, op2, ..., opN are comparison operators, then a op1 b op2 c ... y opN z is equivalent to a op1 b and b op2 c and ... y opN z, except that each expression is evaluated at most once.
|
||
|
||
While such behavior might seem silly to you in the above examples, it's fantastic with stuff like `a == b == c` and `0 <= x <= 100`.
|
||
|
||
* `False is False is False` is equivalent to `(False is False) and (False is False)`
|
||
* `True is False == False` is equivalent to `True is False and False == False` and since the first part of the statement (`True is False`) evaluates to `False`, the overall expression evaluates to `False`.
|
||
* `1 > 0 < 1` is equivalent to `1 > 0 and 0 < 1` which evaluates to `True`.
|
||
* The expression `(1 > 0) < 1` is equivalent to `True < 1` and
|
||
```py
|
||
>>> int(True)
|
||
1
|
||
>>> True + 1 #not relevant for this example, but just for fun
|
||
2
|
||
```
|
||
So, `1 < 1` evaluates to `False`
|
||
|
||
---
|
||
|
||
### > Name resolution ignoring class scope
|
||
|
||
1\.
|
||
```py
|
||
x = 5
|
||
class SomeClass:
|
||
x = 17
|
||
y = (x for i in range(10))
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> list(SomeClass.y)[0]
|
||
5
|
||
```
|
||
|
||
2\.
|
||
```py
|
||
x = 5
|
||
class SomeClass:
|
||
x = 17
|
||
y = [x for i in range(10)]
|
||
```
|
||
|
||
**Output (Python 2.x):**
|
||
```py
|
||
>>> SomeClass.y[0]
|
||
17
|
||
```
|
||
|
||
**Output (Python 3.x):**
|
||
```py
|
||
>>> SomeClass.y[0]
|
||
5
|
||
```
|
||
|
||
#### 💡 Explanation
|
||
- Scopes nested inside class definition ignore names bound at the class level.
|
||
- A generator expression has its own scope.
|
||
- Starting from Python 3.X, list comprehensions also have their own scope.
|
||
|
||
---
|
||
|
||
### > Needle in a Haystack
|
||
|
||
1\.
|
||
```py
|
||
x, y = (0, 1) if True else None, None
|
||
```
|
||
|
||
**Output:**
|
||
```
|
||
>>> x, y # expected (0, 1)
|
||
((0, 1), None)
|
||
```
|
||
|
||
Almost every Python programmer has faced a similar situation.
|
||
|
||
2\.
|
||
```py
|
||
t = ('one', 'two')
|
||
for i in t:
|
||
print(i)
|
||
|
||
t = ('one')
|
||
for i in t:
|
||
print(i)
|
||
|
||
t = ()
|
||
print(t)
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
one
|
||
two
|
||
o
|
||
n
|
||
e
|
||
tuple()
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
* For 1, the correct statement for expected behavior is `x, y = (0, 1) if True else (None, None)`.
|
||
* For 2, the correct statement for expected behavior is `t = ('one',)` or `t = 'one',` (missing comma) otherwise the interpreter considers `t` to be a `str` and iterates over it character by character.
|
||
* `()` is a special token and denotes empty `tuple`.
|
||
|
||
---
|
||
|
||
---
|
||
|
||
|
||
## Section: The Hidden treasures!
|
||
|
||
This section contains few of the lesser-known interesting things about Python that most beginners like me are unaware of (well, not anymore).
|
||
|
||
### > Okay Python, Can you make me fly? *
|
||
|
||
Well, here you go
|
||
|
||
```py
|
||
import antigravity
|
||
```
|
||
|
||
**Output:**
|
||
Sshh.. It's a super secret.
|
||
|
||
#### 💡 Explanation:
|
||
+ `antigravity` module is one of the few easter eggs released by Python developers.
|
||
+ `import antigravity` opens up a web browser pointing to the [classic XKCD comic](http://xkcd.com/353/) about Python.
|
||
+ Well, there's more to it. There's **another easter egg inside the easter egg**. If you look at the [code](https://github.com/python/cpython/blob/master/Lib/antigravity.py#L7-L17), there's a function defined that purports to implement the [XKCD's geohashing algorithm](https://xkcd.com/426/).
|
||
|
||
---
|
||
|
||
### > `goto`, but why? *
|
||
|
||
```py
|
||
from goto import goto, label
|
||
for i in range(9):
|
||
for j in range(9):
|
||
for k in range(9):
|
||
print("I'm trapped, please rescue!")
|
||
if k == 2:
|
||
goto .breakout # breaking out from a deeply nested loop
|
||
label .breakout
|
||
print("Freedom!")
|
||
```
|
||
|
||
**Output (Python 2.3):**
|
||
```py
|
||
I'm trapped, please rescue!
|
||
I'm trapped, please rescue!
|
||
Freedom!
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
- A working version of `goto` in Python was [announced](https://mail.python.org/pipermail/python-announce-list/2004-April/002982.html) as an April Fool's joke on 1st April 2004.
|
||
- Current versions of Python do not have this module.
|
||
- Although it works, but please don't use it. Here's the [reason](https://docs.python.org/3/faq/design.html#why-is-there-no-goto) to why `goto` is not present in Python.
|
||
|
||
---
|
||
|
||
### > Brace yourself! *
|
||
|
||
If you are one of the people who doesn't like using whitespace in Python to denote scopes, you can use the C-style {} by importing,
|
||
|
||
```py
|
||
from __future__ import braces
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
File "some_file.py", line 1
|
||
from __future__ import braces
|
||
SyntaxError: not a chance
|
||
```
|
||
|
||
Braces? No way! If you think that's disappointing, use Java.
|
||
|
||
#### 💡 Explanation:
|
||
+ The `__future__` module is normally used to provide features from future versions of Python. The "future" here is however ironic.
|
||
+ This is an easter egg concerned with the community's feelings on this issue.
|
||
|
||
---
|
||
|
||
### > Let's meet Friendly Language Uncle For Life *
|
||
|
||
**Output (Python 3.x)**
|
||
```py
|
||
>>> from __future__ import barry_as_FLUFL
|
||
>>> "Ruby" != "Python" # there's no doubt about it
|
||
File "some_file.py", line 1
|
||
"Ruby" != "Python"
|
||
^
|
||
SyntaxError: invalid syntax
|
||
|
||
>>> "Ruby" <> "Python"
|
||
True
|
||
```
|
||
|
||
There we go.
|
||
|
||
#### 💡 Explanation:
|
||
- This is relevant to [PEP-401](https://www.python.org/dev/peps/pep-0401/) released on April 1, 2009 (now you know, what it means).
|
||
- Quoting from the PEP-401
|
||
> Recognized that the != inequality operator in Python 3.0 was a horrible, finger pain inducing mistake, the FLUFL reinstates the <> diamond operator as the sole spelling.
|
||
- There were more things that Uncle Barry had to share in the PEP; you can read them [here](https://www.python.org/dev/peps/pep-0401/).
|
||
|
||
---
|
||
|
||
### > Even Python understands that love is complicated *
|
||
|
||
```py
|
||
import this
|
||
```
|
||
|
||
Wait, what's **this**? `this` is love :heart:
|
||
|
||
**Output:**
|
||
```
|
||
The Zen of Python, by Tim Peters
|
||
|
||
Beautiful is better than ugly.
|
||
Explicit is better than implicit.
|
||
Simple is better than complex.
|
||
Complex is better than complicated.
|
||
Flat is better than nested.
|
||
Sparse is better than dense.
|
||
Readability counts.
|
||
Special cases aren't special enough to break the rules.
|
||
Although practicality beats purity.
|
||
Errors should never pass silently.
|
||
Unless explicitly silenced.
|
||
In the face of ambiguity, refuse the temptation to guess.
|
||
There should be one-- and preferably only one --obvious way to do it.
|
||
Although that way may not be obvious at first unless you're Dutch.
|
||
Now is better than never.
|
||
Although never is often better than *right* now.
|
||
If the implementation is hard to explain, it's a bad idea.
|
||
If the implementation is easy to explain, it may be a good idea.
|
||
Namespaces are one honking great idea -- let's do more of those!
|
||
```
|
||
|
||
It's the Zen of Python!
|
||
|
||
```py
|
||
>>> love = this
|
||
>>> this is love
|
||
True
|
||
>>> love is True
|
||
False
|
||
>>> love is False
|
||
False
|
||
>>> love is not True or False
|
||
True
|
||
>>> love is not True or False; love is love # Love is complicated
|
||
True
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* `this` module in Python is an easter egg for The Zen Of Python ([PEP 20](https://www.python.org/dev/peps/pep-0020)).
|
||
* And if you think that's already interesting enough, check out the implementation of [this.py](https://hg.python.org/cpython/file/c3896275c0f6/Lib/this.py). Interestingly, the code for the Zen violates itself (and that's probably the only place where this happens).
|
||
* Regarding the statement `love is not True or False; love is love`, ironic but it's self-explanatory.
|
||
|
||
---
|
||
|
||
### > Yes, it exists!
|
||
|
||
**The `else` clause for loops.** One typical example might be:
|
||
|
||
```py
|
||
def does_exists_num(l, to_find):
|
||
for num in l:
|
||
if num == to_find:
|
||
print("Exists!")
|
||
break
|
||
else:
|
||
print("Does not exist")
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> some_list = [1, 2, 3, 4, 5]
|
||
>>> does_exists_num(some_list, 4)
|
||
Exists!
|
||
>>> does_exists_num(some_list, -1)
|
||
Does not exist
|
||
```
|
||
|
||
**The `else` clause in exception handling.** An example,
|
||
|
||
```py
|
||
try:
|
||
pass
|
||
except:
|
||
print("Exception occurred!!!")
|
||
else:
|
||
print("Try block executed successfully...")
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
Try block executed successfully...
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
- The `else` clause after a loop is executed only when there's no explicit `break` after all the iterations.
|
||
- `else` clause after try block is also called "completion clause" as reaching the `else` clause in a `try` statement means that the try block actually completed successfully.
|
||
|
||
---
|
||
|
||
### > Inpinity *
|
||
|
||
The spelling is intended. Please, don't submit a patch for this.
|
||
|
||
**Output (Python 3.x):**
|
||
```py
|
||
>>> infinity = float('infinity')
|
||
>>> hash(infinity)
|
||
314159
|
||
>>> hash(float('-inf'))
|
||
-314159
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
- Hash of infinity is 10⁵ x π.
|
||
- Interestingly, the hash of `float('-inf')` is "-10⁵ x π" in Python 3, whereas "-10⁵ x e" in Python 2.
|
||
|
||
---
|
||
|
||
### > Mangling time! *
|
||
|
||
```py
|
||
class Yo(object):
|
||
def __init__(self):
|
||
self.__honey = True
|
||
self.bitch = True
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> Yo().bitch
|
||
True
|
||
>>> Yo().__honey
|
||
AttributeError: 'Yo' object has no attribute '__honey'
|
||
>>> Yo()._Yo__honey
|
||
True
|
||
```
|
||
|
||
Why did `Yo()._Yo__honey` work? Only Indian readers would understand.
|
||
|
||
#### 💡 Explanation:
|
||
|
||
* [Name Mangling](https://en.wikipedia.org/wiki/Name_mangling) is used to avoid naming collisions between different namespaces.
|
||
* In Python, the interpreter modifies (mangles) the class member names starting with `__` (double underscore) and not ending with more than one trailing underscore by adding `_NameOfTheClass` in front.
|
||
* So, to access `__honey` attribute, we are required to append `_Yo` to the front which would prevent conflicts with the same name attribute defined in any other class.
|
||
|
||
---
|
||
|
||
---
|
||
|
||
## Section: Miscellaneous
|
||
|
||
|
||
### > `+=` is faster
|
||
|
||
```py
|
||
# using "+", three strings:
|
||
>>> timeit.timeit("s1 = s1 + s2 + s3", setup="s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000", number=100)
|
||
0.25748300552368164
|
||
# using "+=", three strings:
|
||
>>> timeit.timeit("s1 += s2 + s3", setup="s1 = ' ' * 100000; s2 = ' ' * 100000; s3 = ' ' * 100000", number=100)
|
||
0.012188911437988281
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
+ `+=` is faster than `+` for concatenating more than two strings because the first string (example, `s1` for `s1 += s2 + s3`) is not destroyed while calculating the complete string.
|
||
|
||
---
|
||
|
||
### > Let's make a giant string!
|
||
|
||
```py
|
||
def add_string_with_plus(iters):
|
||
s = ""
|
||
for i in range(iters):
|
||
s += "xyz"
|
||
assert len(s) == 3*iters
|
||
|
||
def add_bytes_with_plus(iters):
|
||
s = b""
|
||
for i in range(iters):
|
||
s += b"xyz"
|
||
assert len(s) == 3*iters
|
||
|
||
def add_string_with_format(iters):
|
||
fs = "{}"*iters
|
||
s = fs.format(*(["xyz"]*iters))
|
||
assert len(s) == 3*iters
|
||
|
||
def add_string_with_join(iters):
|
||
l = []
|
||
for i in range(iters):
|
||
l.append("xyz")
|
||
s = "".join(l)
|
||
assert len(s) == 3*iters
|
||
|
||
def convert_list_to_string(l, iters):
|
||
s = "".join(l)
|
||
assert len(s) == 3*iters
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> timeit(add_string_with_plus(10000))
|
||
1000 loops, best of 3: 972 µs per loop
|
||
>>> timeit(add_bytes_with_plus(10000))
|
||
1000 loops, best of 3: 815 µs per loop
|
||
>>> timeit(add_string_with_format(10000))
|
||
1000 loops, best of 3: 508 µs per loop
|
||
>>> timeit(add_string_with_join(10000))
|
||
1000 loops, best of 3: 878 µs per loop
|
||
>>> l = ["xyz"]*10000
|
||
>>> timeit(convert_list_to_string(l, 10000))
|
||
10000 loops, best of 3: 80 µs per loop
|
||
```
|
||
|
||
Let's increase the number of iterations by a factor of 10.
|
||
|
||
```py
|
||
>>> timeit(add_string_with_plus(100000)) # Linear increase in execution time
|
||
100 loops, best of 3: 9.75 ms per loop
|
||
>>> timeit(add_bytes_with_plus(100000)) # Quadratic increase
|
||
1000 loops, best of 3: 974 ms per loop
|
||
>>> timeit(add_string_with_format(100000)) # Linear increase
|
||
100 loops, best of 3: 5.25 ms per loop
|
||
>>> timeit(add_string_with_join(100000)) # Linear increase
|
||
100 loops, best of 3: 9.85 ms per loop
|
||
>>> l = ["xyz"]*100000
|
||
>>> timeit(convert_list_to_string(l, 100000)) # Linear increase
|
||
1000 loops, best of 3: 723 µs per loop
|
||
```
|
||
|
||
#### 💡 Explanation
|
||
- You can read more about [timeit](https://docs.python.org/3/library/timeit.html) from here. It is generally used to measure the execution time of snippets.
|
||
- Don't use `+` for generating long strings — In Python, `str` is immutable, so the left and right strings have to be copied into the new string for every pair of concatenations. If you concatenate four strings of length 10, you'll be copying (10+10) + ((10+10)+10) + (((10+10)+10)+10) = 90 characters instead of just 40 characters. Things get quadratically worse as the number and size of the string increases (justified with the execution times of `add_bytes_with_plus` function)
|
||
- Therefore, it's advised to use `.format.` or `%` syntax (however, they are slightly slower than `+` for short strings).
|
||
- Or better, if already you've contents available in the form of an iterable object, then use `''.join(iterable_object)` which is much faster.
|
||
- `add_string_with_plus` didn't show a quadratic increase in execution time unlike `add_bytes_with_plus` because of the `+=` optimizations discussed in the previous example. Had the statement been `s = s + "x" + "y" + "z"` instead of `s += "xyz"`, the increase would have been quadratic.
|
||
```py
|
||
def add_string_with_plus(iters):
|
||
s = ""
|
||
for i in range(iters):
|
||
s = s + "x" + "y" + "z"
|
||
assert len(s) == 3*iters
|
||
|
||
>>> timeit(add_string_with_plus(10000))
|
||
100 loops, best of 3: 9.87 ms per loop
|
||
>>> timeit(add_string_with_plus(100000)) # Quadratic increase in execution time
|
||
1 loops, best of 3: 1.09 s per loop
|
||
```
|
||
|
||
---
|
||
|
||
### > Explicit typecast of strings
|
||
|
||
```py
|
||
a = float('inf')
|
||
b = float('nan')
|
||
c = float('-iNf') #These strings are case-insensitive
|
||
d = float('nan')
|
||
```
|
||
|
||
**Output:**
|
||
```py
|
||
>>> a
|
||
inf
|
||
>>> b
|
||
nan
|
||
>>> c
|
||
-inf
|
||
>>> float('some_other_string')
|
||
ValueError: could not convert string to float: some_other_string
|
||
>>> a == -c #inf==inf
|
||
True
|
||
>>> None == None # None==None
|
||
True
|
||
>>> b == d #but nan!=nan
|
||
False
|
||
>>> 50/a
|
||
0.0
|
||
>>> a/a
|
||
nan
|
||
>>> 23 + b
|
||
nan
|
||
```
|
||
|
||
#### 💡 Explanation:
|
||
|
||
`'inf'` and `'nan'` are special strings (case-insensitive), which when explicitly typecasted to `float` type, are used to represent mathematical "infinity" and "not a number" respectively.
|
||
|
||
---
|
||
|
||
### > Minor Ones
|
||
|
||
* `join()` is a string operation instead of list operation. (sort of counter-intuitive at first usage)
|
||
|
||
**💡 Explanation:**
|
||
If `join()` is a method on a string then it can operate on any iterable (list, tuple, iterators). If it were a method on a list, it'd have to be implemented separately by every type. Also, it doesn't make much sense to put a string-specific method on a generic `list` object API.
|
||
|
||
* Few weird looking but semantically correct statements:
|
||
+ `[] = ()` is a semantically correct statement (unpacking an empty `tuple` into an empty `list`)
|
||
+ `'a'[0][0][0][0][0]` is also a semantically correct statement as strings are [sequences](https://docs.python.org/3/glossary.html#term-sequence)(iterables supporting element access using integer indices) in Python.
|
||
+ `3 --0-- 5 == 8` and `--5 == 5` are both semantically correct statements and evaluate to `True`.
|
||
|
||
* Given that `a` is a number, `++a` and `--a` are both valid Python statements but don't behave the same way as compared with similar statements in languages like C, C++ or Java.
|
||
```py
|
||
>>> a = 5
|
||
>>> a
|
||
5
|
||
>>> ++a
|
||
5
|
||
>>> --a
|
||
5
|
||
```
|
||
|
||
**💡 Explanation:**
|
||
+ There is no `++` operator in Python grammar. It is actually two `+` operators.
|
||
+ `++a` parses as `+(+a)` which translates to `a`. Similarly, the output of the statement `--a` can be justified.
|
||
+ This StackOverflow [thread](https://stackoverflow.com/questions/3654830/why-are-there-no-and-operators-in-python) discusses the rationale behind the absence of increment and decrement operators in Python.
|
||
|
||
* Python uses 2 bytes for local variable storage in functions. In theory, this means that only 65536 variables can be defined in a function. However, python has a handy solution built in that can be used to store more than 2^16 variable names. The following code demonstrates what happens in the stack when more than 65536 local variables are defined (Warning: This code prints around 2^18 lines of text, so be prepared!):
|
||
```py
|
||
import dis
|
||
exec("""
|
||
def f():
|
||
""" + """
|
||
""".join(["X"+str(x)+"=" + str(x) for x in range(65539)]))
|
||
|
||
f()
|
||
|
||
print(dis.dis(f))
|
||
```
|
||
|
||
* Multiple Python threads won't run your *Python code* concurrently (yes you heard it right!). It may seem intuitive to spawn several threads and let them execute your Python code concurrently, but, because of the [Global Interpreter Lock](https://wiki.python.org/moin/GlobalInterpreterLock) in Python, all you're doing is making your threads execute on the same core turn by turn. Python threads are good for IO-bound tasks, but to achieve actual parallelization in Python for CPU-bound tasks, you might want to use the Python [multiprocessing](https://docs.python.org/2/library/multiprocessing.html) module.
|
||
|
||
* List slicing with out of the bounds indices throws no errors
|
||
```py
|
||
>>> some_list = [1, 2, 3, 4, 5]
|
||
>>> some_list[111:]
|
||
[]
|
||
```
|
||
|
||
* `int('١٢٣٤٥٦٧٨٩')` returns `123456789` in Python 3. In Python, Decimal characters include digit characters, and all characters that can be used to form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO. Here's an [interesting story](http://chris.improbable.org/2014/8/25/adventures-in-unicode-digits/) related to this behavior of Python.
|
||
|
||
* `'abc'.count('') == 4`. Here's an approximate implementation of `count` method, which would make the things more clear
|
||
```py
|
||
def count(s, sub):
|
||
result = 0
|
||
for i in range(len(s) + 1 - len(sub)):
|
||
result += (s[i:i + len(sub)] == sub)
|
||
return result
|
||
```
|
||
The behavior is due to the matching of empty substring(`''`) with slices of length 0 in the original string.
|
||
|
||
---
|
||
|
||
# Contributing
|
||
|
||
All patches are Welcome! Please see [CONTRIBUTING.md](/CONTRIBUTING.md) for further details.
|
||
|
||
For discussions, you can either create a new [issue](https://github.com/satwikkansal/wtfpython/issues/new) or ping on the Gitter [channel](https://gitter.im/wtfpython/Lobby)
|
||
|
||
# Acknowledgements
|
||
|
||
The idea and design for this collection were initially inspired by Denys Dovhan's awesome project [wtfjs](https://github.com/denysdovhan/wtfjs). The overwhelming support by the community gave it the shape it is in right now.
|
||
|
||
#### Some nice Links!
|
||
* https://www.youtube.com/watch?v=sH4XF6pKKmk
|
||
* https://www.reddit.com/r/Python/comments/3cu6ej/what_are_some_wtf_things_about_python
|
||
* https://sopython.com/wiki/Common_Gotchas_In_Python
|
||
* https://stackoverflow.com/questions/530530/python-2-x-gotchas-and-landmines
|
||
* https://stackoverflow.com/questions/1011431/common-pitfalls-in-python
|
||
* https://www.python.org/doc/humor/
|
||
* https://www.codementor.io/satwikkansal/python-practices-for-efficient-code-performance-memory-and-usability-aze6oiq65
|
||
|
||
# 🎓 License
|
||
|
||
[![CC 4.0][license-image]][license-url]
|
||
|
||
© [Satwik Kansal](https://satwikkansal.xyz)
|
||
|
||
[license-url]: http://www.wtfpl.net
|
||
[license-image]: https://img.shields.io/badge/License-WTFPL%202.0-lightgrey.svg?style=flat-square
|
||
|
||
## Help
|
||
|
||
If you have any wtfs, ideas or suggestions, please share.
|
||
|
||
## Surprise your geeky pythonist friends?
|
||
|
||
You can use these quick links to recommend wtfpython to your friends,
|
||
|
||
[Twitter](https://twitter.com/intent/tweet?url=https://github.com/satwikkansal/wtfpython&hastags=python,wtfpython)
|
||
| [Linkedin](https://www.linkedin.com/shareArticle?url=https://github.com/satwikkansal&title=What%20the%20f*ck%20Python!&summary=An%20interesting%20collection%20of%20subtle%20and%20tricky%20Python%20snippets.)
|
||
|
||
## Need a pdf version?
|
||
|
||
I've received a few requests for the pdf version of wtfpython. You can add your details [here](https://satwikkansal.xyz/wtfpython-pdf/) to get the pdf as soon as it is finished.
|
||
|
||
## Follow Commit
|
||
|
||
[![Commit id][commit-image]][commit-url]
|
||
|
||
[commit-url]: https://github.com/satwikkansal/wtfpython/commit/30e05a5973930c38cdb59f1c02b85b19b22ac531
|
||
[commit-image]: https://img.shields.io/badge/Commit-30e05a-yellow.svg
|