wtfpython VS CPython

Hi, author of the repo (https://github.com/satwikkansal/wtfpython) here, pleasantly surprised to wake up to this thread about it. The intention of the project is not to put Python in a bad light relative to other languages, the intention was to explore it more deeply through (sometimes contrived) snippets that give non-obvious outputs. I believe for a regular Python programmer, the "Slippery Slopes" section is a must-know. The first section (Strain your brain), does contain some patterns that you may not ever see in real world, the goal there is to just learn about internals. Agreed some of them are very obvious for a well-learned programmer, and some of them aren't even Python specific, it does help a lot of beginner to intermediate programmers. I remember it being given as a supplementary material in one of the CS-based course.

It is curated with something-for-everyone approach, I expect people to learn a thing or two about Python / CS after going through the snippets. I haven't updated it in a while in a major way, but looking at the feedback I'll try to organise them better, and add new snippets (I have a long personal list that I maintain) in a future release!

After reading this page:

https://github.com/satwikkansal/wtfpython?tab=readme-ov-file#-needles-in-a-haystack-

I wonder if there's any language that thought about all edge cases and avoided exceptions and such gotchas at the design level.

JS is notorious for such WTFs but even Python—which I've used for over a decade now—has surprised me countless times.

Is Haskell also like that? How about Lisps (CL, Racket, Clojure, Scheme, etc.)?

In my mind,I just automatically translate a EXPRESSION1 b EXPRESSION2 c as (a EXPRESSION1 b) and (b EXPRESSION2 c), so there's no ambiguity. But I agree, it can be VERY confusing,so I tend to write code that is easy to read without being a master. for example, think what you would have thought this evaluates to:

False is False is False. If you thought, True, you were right :)

I would recommend to take a look at one of my favourite repos for more[1].

[1]https://github.com/satwikkansal/wtfpython

See this for an explanation - https://github.com/satwikkansal/wtfpython?tab=readme-ov-file...

> `all([])` returns True since the iterable is empty.

Haven’t seen it mentioned in the replies, so here it is. Have a look at “What the f*ck Python? 😱” on GitHub: https://github.com/satwikkansal/wtfpython

https://github.com/satwikkansal/wtfpython

"Mutating the immutable" is my personal favourite - the second line of code fails with an exception despite having already succeeded:

 >>> t = ([1, 2], 5, 6)

Here's the relevant diff: https://github.com/python/cpython/pull/137968/files#diff-966...

Search is limited to 20 attributes and non-descriptors only to avoid arbitrary code execution.

I assume constructing AttributeErrors isn't highly performance sensitive.

If there is an audience for release notes I haven't seen anything better than just committing entries to pre-release folder as you change things and have release automation compile the folder into the actual release notes. Python and many other large projects handle it like this: https://github.com/python/cpython/tree/main/Misc/NEWS.d/next (The release notes for major releases are crafted manually)

Python Software Foundation. Python Programming Language. https://www.python.org/

import smtplib from email.mime.text import MIMEText from email.mime.multipart import MIMEMultipart from email.mime.base import MIMEBase from email import encoders # SMTP Server details port = 587 smtp_server = "smtp.sendlayer.net" username = "paulie" # Your username generated by SendLayer password = "sendlayer_smtp_password" # Your password generated by SendLayer sender_email = "paulie@example.com" receiver_email = "johndoe@example.com" # Email content subject = "Email Example with Attachment" html_message = """\ Hi, This is a test email sent from "https://www.python.org">Python using "https://sendlayer.com">SendLayer's SMTP server The email also includes an attachment """ # Create a multipart message and set headers message = MIMEMultipart() message["From"] = sender_email message["Subject"] = subject message["To"] = receiver_email # Attach the HTML part message.attach(MIMEText(html_message, "html")) # Specify the file path for the attachment filename = "./path/to/attachment/file.pdf" # Change this to the correct path # Open the file in binary mode with open(filename, "rb") as attachment: part = MIMEBase("application", "octet-stream") part.set_payload(attachment.read()) # Encode file in ASCII characters to send by email encoders.encode_base64(part) # Add header as key/value pair to attachment part part.add_header("Content-Disposition", f"attachment; filename= {filename}") # Add attachment to message message.attach(part) # Send the email with smtplib.SMTP(smtp_server, port) as server: server.starttls() server.login(username, password) server.sendmail(sender_email, receiver_email, message.as_string()) print('Email sent successfully')

import requests from concurrent.futures import ThreadPoolExecutor URLS = [ "https://www.python.org/", "https://www.djangoproject.com/", "https://flask.palletsprojects.com/", ] def fetch_url(url: str): print(f"Fetching {url}...") response = requests.get(url) print(f"Fetched {url} with status {response.status_code}") return len(response.content) with ThreadPoolExecutor(max_workers=5) as executor: # The map function runs `fetch_url` for each item in URLS results = executor.map(fetch_url, URLS) for url, length in zip(URLS, results): print(f"URL: {url}, Length: {length}")

Use KeysView and ValuesView instead of dict_keys and dict_values respectively because type checkers don't support dict_keys and dict_values in _collections_abc.

According to the benchmark in the PR that introduced this optimization, sorting a list that consists only of floats rather than a list of floats with even a single integer at the end is almost twice as fast.

If you want to a UUIDv7 key for partitioning your table by date (e.g., one partition per day or month), you need to be able to compute the partition range via the minimal UUIDv7 for a given date.

There is some discussion whether or not to add helpers for this to Python‘s uuid7 module: https://github.com/python/cpython/issues/130843#issuecomment...

With respect to tagged pointers, there seems to be some recent movements on that front in CPython: https://github.com/python/cpython/issues/132509