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All About Decorators in Python (www.pythonmorsels.com)
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submitted 1 month ago* (last edited 1 month ago) by Rick_C137@programming.dev to c/python@programming.dev

Hi,

I've discover haml and pug [^1] ( both web template engine )

It's totally Pytonic ! ( and make even more sense to use it with python rather than JS 🤮 )

I've look, if it exist for Python, but so far, I've found only

The first, only convert pug into another template :/
The second, didn't pass the alpha version.
The third, require dependence, not maintained etc.. \

So I didn't found a Python package that could do haml/pug to html directly, without too much dependence...

For example:

From

html
  head title Example for Python discuss
  body
    h1 Hello world
    p This is a paragraph.

To

<html>
  <head>
    <title>Example for Python discuss</title>
  </head>
  <body>
    <h1>Hello world</h1>
    <p>This is a paragraph.</p>
  </body>
</html>

Do you know if such thing exist ?
If not, I will build my own (FLOSS). ( I'm open to any advice to do so :) )

Thanks

[^1]:Pug is a template engine heavily influenced by Haml and implemented with JavaScript 🤮 for Node.js

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submitted 1 month ago* (last edited 1 month ago) by Rick_C137@programming.dev to c/python@programming.dev

Hi,

I'm following my previous post
How encrypt email with a GnuPG public key ? [ solved ]

So I managed to encrypt the email body with GnuPG public key.. But I don't figure how I can do the same for the title ?!
ThunderBird manage it.. any idea how ?
asked on Official Thunderbird forum

Thanks.

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From Enaml's docs:

Enaml brings the declarative UI paradigm to Python in a seamlessly integrated fashion. The grammar of the Enaml language is a strict superset of Python. This means that any valid Python file is also a valid Enaml file, though the converse is not necessary true. The tight integration with Python means that the developer feels at home and uses standard Python syntax when expressing how their data models bind to the visual attributes of the UI.

. . .

Enaml’s declarative widgets provide a layer of abstraction on top of the widgets of a toolkit rendering library. Enaml ships with a backend based on Qt5/6 and third-party projects such as enaml-web and enaml-native provides alternative backends.


A maintainer of Enaml has just opened a brainstorm discussion on the next major development goals.

It's a project I've long admired, though rarely used, and I'd love to see it get some attention and a revamp. I think the bar these days has been raised by projects like QML and Slint, which provide a great context in which to set new goals.

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submitted 1 month ago by neme@lemm.ee to c/python@programming.dev
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submitted 1 month ago* (last edited 1 month ago) by EveryMuffinIsNowEncrypted@lemmy.blahaj.zone to c/python@programming.dev

Note: The attached image is a screenshot of page 31 of Dr. Charles Severance's book, Python for Everybody: Exploring Data Using Python 3 (2024-01-01 Revision).


I thought = was a mathematical operator, not a logical operator; why does Python use

>= instead of >==, or <= instead of <==, or != instead of !==?

Thanks in advance for any clarification. I would have posted this in the help forums of FreeCodeCamp, but I wasn't sure if this question was too.......unspecified(?) for that domain.

Cheers!

 


Edit: I think I get it now! Thanks so much to everyone for helping, and @FizzyOrange@programming.dev and @itslilith@lemmy.blahaj.zone in particular! ^_^

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🧵 Free-Threaded Wheels (hugovk.github.io)

via https://mastodon.social/@hugovk/113385974873569374

hugovk.github.io/free-threaded-wheels/ tracks how many of the top 360 PyPI packages have free-threaded wheels.

Green packages (currently 3%) offer has free-threaded wheels

Uncoloured packages (82%) offer pure-Python wheels

Orange packages (16%) have no wheels ready for free-threading (yet!)

See also Quansight Labs' https://py-free-threading.github.io/tracking/ for a smaller yet fine-grained tracker that also includes build tools.

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I store my programs in a cryptomator vault which uses a fuse virtual drive (The default on Linux), but when trying to update pip inside a venv I get an error, then any subsequent use of pip also throws an error and {path_to_venv}/lib/python3.12/site-packages/pip/ becomes empty.

I imagine this is an issue that would happen in any FUSE drive although I don't know how to test that.

Here are the logs

  • OS : Fedora 40
  • pip version: 23.3.2 updating to 24.2
  • python version: 3.12.7

I already made a bug report on the github

Does anyone know a temporary workaround for this ?

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Started a Simulation with Python Blog (quantasticjourney.blogspot.com)

The first post of a new python blog I started if anyone is interested.

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I am including the full text of the post


Despite not being a pure functional language, a lot of praise that python receives are for features that stem from functional paradigms. Many are second nature to python programmers, but over the years I have seen people miss out on some important features. I gathered a few, along with examples, to give a brief demonstration of the convenience they can bring.

Replace if/else with or

With values that might be None, you can use or instead of if/else to provide a default. I had used this for years with Javascript, without knowing it was also possible in Python.

def get_greeting_prefix(user_title: str | None):
	if user_title:
		return user_title
	return ""

Above snippet can shortened to this:

def get_greeting_prefix(user_title: str | None):
	return user_title or ""

Pattern Matching and Unpacking

The overdue arrival of match to python means that so many switch style statements are expressed instead with convoluted if/else blocks. Using match is not even from the functional paradigm, but combining it with unpacking opens up new possibilities for writing more concise code.

Let's start by looking at a primitive example of unpacking. Some libraries have popularised use of [a, b] = some_fun(), but unpacking in python is much powerful than that.

[first, *mid, last] = [1, 2, 3, 4, 5]
# first -> 1, mid -> [2, 3, 4], last -> 5

Matching Lists

Just look at the boost in readability when we are able to name and extract relevant values effortlessly:

def sum(numbers: [int]):
	if len(numbers) == 0:
		return 0
	else:
		return numbers[0] + sum(numbers[1:])
def sum(numbers: [int]):
	match numbers:
		case []:
			return 0
		case [first, *rest]:
			return first + sum(rest)

Matching Dictionaries

Smooth, right? We can go even further with dictionaries. This example is not necessarily better than its if/else counterpart, but I will use it for the purpose of demonstrating the functionality.

sample_country = {"economic_zone": "EEA", "country_code": "AT"}

def determine_tourist_visa_requirement(country: dict[str, str]):
	match country:
		case {"economic_zone": "EEA"}:
			return "no_visa"
		case {"country_code": code} if code in tourist_visa_free_countries:
			return "non_tourist_visa_only"
		case default:
			return "visa_required"		

Matching Dataclasses

Let’s write a function that does a primitive calculation of an estimated number of days for shipment

@dataclass
class Address:
	street: str
	zip_code: str
	country_code: str
def calculate_shipping_estimate(address: Address) -> int:
	match address:
		case Address(zip_code=zc) if close_to_warehouse(zc):
			return 1
		case Address(country_code=cc) if cc in express_shipping_countries:
			return 2
		case default:
			return provider_estimate(city.coordinates)

Comprehensions

List comprehensions get their deserved spotlight, but I’ve seen cases where dictionary comprehension would’ve cut multiple lines. You can look at examples on this page on python.org

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I am working on a rudimentary Breakout clone, and I was doing the wall collision. I have a function that I initially treated as a Boolean, but I changed it to return a different value depending on which wall the ball hit. I used the walrus operator to capture this value while still treating the function like a bool. I probably could have just defined a variable as the function's return value, then used it in an if statement. But it felt good to use this new thing I'd only heard about, and didn't really understand what it did. I was honestly kind of surprised when it actually worked like I was expecting it to! Pretty cool.

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Python 3.14.0 alpha 1 (discuss.python.org)
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submitted 2 months ago* (last edited 2 months ago) by jnovinger@programming.dev to c/python@programming.dev
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(For context, I'm basically referring to Python 3.12 "multiprocessing.Pool Vs. concurrent.futures.ThreadPoolExecutor"...)

Today I read that multiple cores (parallelism) help in CPU bound operations. Meanwhile, multiple threads (concurrency) is due when the tasks are I/O bound.

Is this correct? Anyone cares to elaborate for me?

At least from a theorethical standpoint. Of course, many real work has a mix of both, and I'd better start with profiling where the bottlenecks really are.

If serves of anything having a concrete "algorithm". Let's say, I have a function that applies a map-reduce strategy reading data chunks from a file on disk, and I'm computing some averages from these data, and saving to a new file.

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I know Python basics, what next? (learnbyexample.github.io)
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submitted 2 months ago* (last edited 2 months ago) by Rick_C137@programming.dev to c/python@programming.dev

Hi,

I'm already using

from smtplib import SMTP_SSL
from email.message import EmailMessage

To send emails.

Now I would like to be able to encrypt them with the public key of the recipient. ( PublicKey.asc )

an A.I provide me this

import smtplib
from email.message import EmailMessage
from cryptography.hazmat.primitives.asymmetric import ec
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.ciphers.aead import AESGCM

# Load the ECC public key from the .asc file
with open('recipient_public_key.asc', 'rb') as key_file:
    public_key_bytes = key_file.read()
public_key = ec.EllipticCurvePublicKey.from_public_bytes(
    ec.SECP384R1(),
    public_key_bytes
)

# Create the email message
msg = EmailMessage()
msg.set_content('This is the encrypted email.')
msg['Subject'] = 'Encrypted Email'
msg['From'] = 'you@example.com'
msg['To'] = 'recipient@example.com'

# Encrypt the email message using the ECC public key
nonce = bytes.fromhex('000102030405060708090a0b0c0d0e0f')
cipher = AESGCM(public_key.public_key().secret_key_bytes)
ciphertext = cipher.encrypt(nonce, msg.as_bytes(), None)

# Send the encrypted email
server = smtplib.SMTP('smtp.example.com')
server.send_message(msg, from_addr='you@example.com', to_addr='recipient@example.com')
server.quit()

# Save the encrypted email to a file
with open('encrypted_email.bin', 'wb') as f:
    f.write(ciphertext)

I like the approach, only one "low level" import cryptography

but the code seem wrong. if the body has been encrypted as ciphertext I don't see this one included while sending the email.

How are you doing it ? or do you have good tutorial, documentations ? because I found nothing "pure and simple" meaning not with of unnecessary stuff.

Thanks.

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