"I thought that memory leaks were impossible in Python?", I said to myself, staring incredulously at my screen. It was 8:00 PM. The memory use of my crawler was slowly, but steadily increasing. As I hadn't changed any significant portion of my code, this made no sense at all. Had I introduced a new bug? If so, where was it? Here follows the full story of how I tracked down a memory leak in my Pyth
RevPDB A "reverse debugger" is a debugger where you can go forward and backward in time. It is an uncommon feature, at least in the open source world, but I have no idea why. I have used undodb-gdb and rr, which are reverse debuggers for C code, and I can only say that they saved me many, many days of poking around blindly in gdb. The PyPy team is pleased to give you "RevPDB", a reverse-debugger s
Voltron is an extensible debugger UI toolkit written in Python. It aims to improve the user experience of various debuggers (LLDB, GDB, VDB and WinDbg) by enabling the attachment of utility views that can retrieve and display data from the debugger host. By running these views in other TTYs, you can build a customised debugger user interface to suit your needs. Voltron does not aim to be everythin
pdb has been, is and probably always will be the bread and butter of Python programmers when they need to find the root cause of a problem in their applications — it’s a built-in and easy to use debugger. But there are cases when pdb can’t help you, e.g. if your app is stuck somewhere, and you want to attach to a running process to find out why, without restarting it. This is where gdb shines. Why
We’ve asked many of our residents at Hacker School what qualities all great programmers share. There’s very little agreement – clearly, there are a multitude of ways to be a great programmer, and you can think of a counter-example for almost every quality you can name. One of the rare non-controversial statements came first from Jessica McKellar, who identified systematic debugging as a key skill.
Python debugging tools 05 June 2013 (updated 17 February 2016) This is an overview of the tools and practices I've used for debugging or profiling purposes. This is not necessarily complete, there are so many tools so I'm listing only what I think is best or relevant. If you know better tools or have other preferences, please comment below. Logging * Yes, really. Can't stress enough how important
Inspiration Jarvis was inspired by works of Bret Victor, especially his talk Inventing on Principle. The central idea is that the feedback loop when you are coding should be the shortest possible, so you can see the effect of your code changes instantly, or almost. Jarvis implements a (small ?) subset of these ideas. Those ideas are also used in the Light Table KickStarter project. What can I do w
This article covers several techniques for debugging Python programs. The applicability of these techniques ranges from simple scripts to complex applications. The topics that are covered include launching an interactive console from within your program, using the Python debugger, and implementing robust logging. Various tips are included along the way to help you debug and fix problems quickly an
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