#swift#analysis#analytics#cocoapods#crashlytics#debug#debugger#debugging#hacktoberfest#layout_debugger#leak_detection#log#logs_analysis#networking#performance_analysis#sandbox#swift#swift6#ui#uikit#view
DebugSwift is a comprehensive toolkit that simplifies debugging for Swift iOS apps by providing real-time monitoring of network requests, performance metrics (CPU, memory, FPS), crash reports, and app resources like keychain and user defaults. It includes interface tools for visualizing layouts with grid overlays and touch indicators, plus memory leak detection and console logging. The main benefit is that you can quickly identify and fix issues during development without leaving your app—just shake your device to toggle the debug panel, making troubleshooting faster and more efficient.
https://github.com/DebugSwift/DebugSwift
https://www.cybrary.it/course/python/
Python for #Security Professionals.
This course will take you from basic concepts to advanced scripts in just over 10 hours of material, with a focus on #networking and security.
https://pypi.python.org/pypi/django-debug-toolbar
A configurable set of panels that display various #debug information about the current #request/#response.
The #Django_Debug_Toolbar is a configurable set of panels that display various debug information about the current request/response and when clicked, display more details about the panel’s content.
Here’s a screenshot of the toolbar in action:
https://dzone.com/articles/pyflakes-passive-checker
There are several code #analysis tools for Python. The most well known is pylint. Then there’s pychecker and now we’re moving on to #pyflakes. The pyflakes project is a part of something known as the Divmod Project. Pyflakes doesn’t actually execute the code it checks, unlike #pychecker. Of course, #pylint also doesn’t execute the code. Regardless, we’ll take a quick look at it and see how pyflakes works and if it’s better than the competition.
gc — #Garbage#Collector interface
This module provides an interface to the #optional garbage collector. It provides the ability to disable the collector, tune the collection frequency, and set #debugging options. It also provides access to unreachable #objects that the collector found but cannot free. Since the collector supplements the reference counting already used in Python, you can disable the collector if you are sure your program does not create reference cycles.
https://docs.python.org/3/library/gc.html
https://pypi.python.org/pypi/uvloop
#uvloop is a fast, drop-in replacement of the built-in #asyncio event loop. uvloop is released under the MIT license.
uvloop and asyncio, combined with the power of async/await in Python 3.5, makes it easier than ever to write high-performance #networking code in Python.
uvloop makes asyncio fast. In fact, it is at least 2x faster than #nodejs, #gevent, as well as any other Python #asynchronous framework. The performance of uvloop-based asyncio is close to that of Go programs.