![]() ![]() In addition to the features of pdb/pydb, the debugger supports syntax coloring (via pygments), has extensive on-line help (in rendered reStructuredText), readthedocs documentation, command completion, a smarter eval, debugger macros written in Python, and more.Īn extension of the pdb module of the standard library. Decompilation is also used to provide sensible debugging inside exec strings, and more accurate position information when stopped or in showing a stack trace. This is the only debugger that I (rocky) am aware of that uses decompilation technology (also written by me), so that you can debug CPython bytcode files where no source code is available. Pyclewn currently supports gdb and pdb.Ī rewrite of pdb/pydb with closer compliance to gdb. Pyclewn allows you to use Vim as a front end to a debugger. A deprecated version of pydb comes with this package. ![]() DDD displays data structures as graphs and plots. Graphical front-end for command-line debuggers such as GDB, DBX, WDB, Ladebug, JDB, XDB, the Perl debugger, the bash debugger, GNU Make debugger, or the Python debugger. (Predecessor of rpdb2 and winpdb) rpdb.py improves pdb's usability and adds support for remote debugging, multiple threads debugging, post mortem of unhandled exceptions, and for debugging of embedded scripts. pdbrc for Python's standard debugger, pdb, which allows you to run arbitrary Python commands on pdb startup. This is a key step in being able to write and deploy powerful automation tools.The standard library debugger, part of all Python installations.Ī visual, console-based, full-screen debugger, designed as a more comfortable drop-in replacement for pdb. We’ll also explain how to set up your own developer environment in your machine. To finish, we’ll put all this together by using the tools that we’ve acquired to process data and generate automatic reports. We'll even touch on automatic testing, which allow us to automate how we check if our code is correct. ![]() We'll also dive into Bash scripting and regular expressions - both very powerful tools for anyone working with systems. We'll then learn how to read and write different types of files, and use subprocesses and input streams. We’ll kick off by exploring how to execute Python locally, and organize and use code across different Python files. ![]() That’s a super useful skill for IT Specialists to know. And, this might feel like a stretch right now, but you’ll also write a program that processes a bunch of errors in an actual log file and then generates a summary file. You’ll also have learned about regular expressions - a very powerful tool for processing text files - and you’ll get practice using the Linux command line on a virtual machine. By the end of this course, you’ll be able to manipulate files and processes on your computer’s operating system. ![]()
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December 2022
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