CPython VS Flutter

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

Flutter is a popular hybrid mobile app framework developed by Google. It allows developers to build cross-platform applications using a single codebase written in Dart. Unlike many frameworks, Flutter uses its own rendering engine to draw UI components, ensuring consistent design and performance across devices. This approach delivers near-native performance and highly customizable user interfaces. With features like hot reload and a rich widget library, Flutter is widely used for building fast, visually appealing, and scalable mobile applications.

# Inside Ubuntu proot apt update && apt install -y curl git unzip xz-utils zip openjdk-17-jdk # Clone Flutter (ARM64 compatible) cd /root git clone https://github.com/flutter/flutter.git -b stable --depth 1 export PATH=/root/flutter/bin:$PATH # Let Dart figure itself out flutter precache --linux flutter doctor

Not all semantic properties work the same way across platforms. Some platforms support certain properties. Others might behave differently. For example, headingLevel only works on Flutter web. Native iOS supports heading levels. Flutter doesn’t wire this through on iOS (there’s an open issue in the Flutter tracker). Android doesn’t even have the concept of heading levels.

Flutter offers an alternative approach when we need truly native performance or access to device-specific features that web APIs don't expose. The Dart language provides strong typing similar to TypeScript, and the framework renders using native components rather than WebView. For AI applications, Flutter's isolates handle background processing without blocking the UI, essential when you're running lighter ML models on-device for offline functionality.

Flutter : Obviously 😂

With the app market projected to reach over $500 billion by 2025, integrating AI isn't just advantageous—it's essential for staying competitive. Whether you're building a mobile app for education, a web platform for e-commerce, or an enterprise tool for data analysis, AI can accelerate development cycles, reduce costs, and enhance functionality. However, effectiveness depends on context: the app's purpose, your team's expertise, and scalability requirements. As we navigate this topic, remember that the "best" tool often involves combining several for optimal results.

There are more than 10 built-in ways to find the widgets. On this article Only the most reliable and used will be shown, but, if you want to see all of them, check them here.