Python代码调试

简介:

 原来不怎么喜欢调试,写的程序大了,感觉调试也是很有必要的,简单总结一下几种常用的调试方式

1.print输出

  不要小看print输出,有时候,或许这是最快的方式。通过print将某个变量的值输出,再和预期的值进行比较,有问题的话再去分析源码看看哪里有错误。

2.logging模块

  这个模块比较强大,也很有用,完全可以替代print。logging模块可以定义日志级别,包括NOTSET < DEBUG < INFO < WARNING < ERROR < CRITICAL这几个级别,通过设置可以输出某个级别以上的日志,可以选择将日志保存到文件或者在屏幕输出。具体用法可以参考python手册

3.用bpython编写代码

  这个编辑器的优点是写完一行代码之后立即执行,然后我们能立即看到结果,出现问题可以及时撤销代码,编写完成可以将代码保存。代码提示功能也挺强大的。

4.用python -i来执行代码

  这样执行之后,程序并没有立即退出。而是打开一个python交互式命令行界面,在这里我们可以执行一些命令,比如 dir() 来查看变量和函数,直接输入变量名我们就能查看变量的值。如果程序异常退出的话,也会保留“现场”,我们可以从现场来分析,找到错误。

5.pdb调试

  最后讲这个神器。

  看了一下官方文档,pdb模块是用bdp模块和cmd模块来实现的。实现类似pdb的功能。

  使用这个模块的话简单的方法就是设置断点,先倒入pdb模块,然后在需要停下的地方执行pdb.set_trace()命令,这样程序执行到这个命令的时候就会停下来,然后我们就能输入一些pdb命令来进行调试了。可以单步执行,继续执行,可以查看变量的值,可以执行一些语句,可以显示将要执行的代码块,可以让程序跳转,执行另外的语句。

  详细的命令可以参考官方文档:

复制代码
h(elp) [command]
Without argument, print the list of available commands. With a command as argument, print help about that command. help pdb displays the full documentation file; if the environment variable PAGER is defined, the file is piped through that command instead. Since thecommand argument must be an identifier, help exec must be entered to get help on the ! command.
w(here)
Print a stack trace, with the most recent frame at the bottom. An arrow indicates the current frame, which determines the context of most commands.
d(own)
Move the current frame one level down in the stack trace (to a newer frame).
u(p)
Move the current frame one level up in the stack trace (to an older frame).
b(reak) [[filename:]lineno | function[, condition]]
With a lineno argument, set a break there in the current file. With a function argument, set a break at the first executable statement within that function. The line number may be prefixed with a filename and a colon, to specify a breakpoint in another file (probably one that hasn’t been loaded yet). The file is searched on sys.path. Note that each breakpoint is assigned a number to which all the other breakpoint commands refer.
If a second argument is present, it is an expression which must evaluate to true before the breakpoint is honored.
Without argument, list all breaks, including for each breakpoint, the number of times that breakpoint has been hit, the current ignore count, and the associated condition if any.
tbreak [[filename:]lineno | function[, condition]]
Temporary breakpoint, which is removed automatically when it is first hit. The arguments are the same as break.
cl(ear) [filename:lineno | bpnumber [bpnumber ...]]
With a filename:lineno argument, clear all the breakpoints at this line. With a space separated list of breakpoint numbers, clear those breakpoints. Without argument, clear all breaks (but first ask confirmation).
disable [bpnumber [bpnumber ...]]
Disables the breakpoints given as a space separated list of breakpoint numbers. Disabling a breakpoint means it cannot cause the program to stop execution, but unlike clearing a breakpoint, it remains in the list of breakpoints and can be (re-)enabled.
enable [bpnumber [bpnumber ...]]
Enables the breakpoints specified.
ignore bpnumber [count]
Sets the ignore count for the given breakpoint number. If count is omitted, the ignore count is set to 0. A breakpoint becomes active when the ignore count is zero. When non-zero, the count is decremented each time the breakpoint is reached and the breakpoint is not disabled and any associated condition evaluates to true.
condition bpnumber [condition]
Condition is an expression which must evaluate to true before the breakpoint is honored. If condition is absent, any existing condition is removed; i.e., the breakpoint is made unconditional.
commands [bpnumber]
Specify a list of commands for breakpoint number bpnumber. The commands themselves appear on the following lines. Type a line containing just ‘end’ to terminate the commands. An example:
(Pdb) commands 1
(com) print some_variable
(com) end
(Pdb)
To remove all commands from a breakpoint, type commands and follow it immediately with end; that is, give no commands.
With no bpnumber argument, commands refers to the last breakpoint set.
You can use breakpoint commands to start your program up again. Simply use the continue command, or step, or any other command that resumes execution.
Specifying any command resuming execution (currently continue, step, next, return, jump, quit and their abbreviations) terminates the command list (as if that command was immediately followed by end). This is because any time you resume execution (even with a simple next or step), you may encounter another breakpoint–which could have its own command list, leading to ambiguities about which list to execute.
If you use the ‘silent’ command in the command list, the usual message about stopping at a breakpoint is not printed. This may be desirable for breakpoints that are to print a specific message and then continue. If none of the other commands print anything, you see no sign that the breakpoint was reached.
New in version 2.5.
s(tep)
Execute the current line, stop at the first possible occasion (either in a function that is called or on the next line in the current function).
n(ext)
Continue execution until the next line in the current function is reached or it returns. (The difference between next and step is that stepstops inside a called function, while next executes called functions at (nearly) full speed, only stopping at the next line in the current function.)
unt(il)
Continue execution until the line with the line number greater than the current one is reached or when returning from current frame.
New in version 2.6.
r(eturn)
Continue execution until the current function returns.
c(ont(inue))
Continue execution, only stop when a breakpoint is encountered.
j(ump) lineno
Set the next line that will be executed. Only available in the bottom-most frame. This lets you jump back and execute code again, or jump forward to skip code that you don’t want to run.
It should be noted that not all jumps are allowed — for instance it is not possible to jump into the middle of a for loop or out of afinally clause.
l(ist) [first[, last]]
List source code for the current file. Without arguments, list 11 lines around the current line or continue the previous listing. With one argument, list 11 lines around at that line. With two arguments, list the given range; if the second argument is less than the first, it is interpreted as a count.
a(rgs)
Print the argument list of the current function.
p expression
Evaluate the expression in the current context and print its value.
Note print can also be used, but is not a debugger command — this executes the Python print statement.
pp expression
Like the p command, except the value of the expression is pretty-printed using the pprint module.
alias [name [command]]
Creates an alias called name that executes command. The command must not be enclosed in quotes. Replaceable parameters can be indicated by %1, %2, and so on, while %* is replaced by all the parameters. If no command is given, the current alias for name is shown. If no arguments are given, all aliases are listed.
Aliases may be nested and can contain anything that can be legally typed at the pdb prompt. Note that internal pdb commands can be overridden by aliases. Such a command is then hidden until the alias is removed. Aliasing is recursively applied to the first word of the command line; all other words in the line are left alone.
As an example, here are two useful aliases (especially when placed in the .pdbrc file):
#Print instance variables (usage "pi classInst")
alias pi for k in %1.__dict__.keys(): print "%1.",k,"=",%1.__dict__[k]
#Print instance variables in self
alias ps pi self
unalias name
Deletes the specified alias.
[!]statement
Execute the (one-line) statement in the context of the current stack frame. The exclamation point can be omitted unless the first word of the statement resembles a debugger command. To set a global variable, you can prefix the assignment command with a global command on the same line, e.g.:
(Pdb) global list_options; list_options = ['-l']
(Pdb)
run [args ...]
Restart the debugged Python program. If an argument is supplied, it is split with “shlex” and the result is used as the new sys.argv. History, breakpoints, actions and debugger options are preserved. “restart” is an alias for “run”.
New in version 2.6.
q(uit)
Quit from the debugger. The program being executed is aborted.
复制代码

 


本文转自ma6174博客园博客,原文链接:http://www.cnblogs.com/ma6174/archive/2013/01/18/2865091.html,如需转载请自行联系原作者

相关文章
|
1天前
|
数据采集 JSON API
【2024-简洁版】python爬虫 批量查询自己所有CSDN文章的质量分:方便快速上手修改代码
【2024-简洁版】python爬虫 批量查询自己所有CSDN文章的质量分:方便快速上手修改代码
8 0
|
2天前
|
Python
Python中的装饰器:提升代码可读性与复用性
Python中的装饰器是一种强大的工具,能够提升代码的可读性和复用性。本文将深入探讨装饰器的原理、用法以及在实际项目中的应用,帮助读者更好地理解和利用这一特性,提升代码质量和开发效率。
|
3天前
|
监控 Python
Python中的装饰器:提升代码可读性与可维护性
Python中的装饰器是一种强大的工具,可以在不修改函数源代码的情况下,增加新的功能。本文将介绍装饰器的基本概念,以及如何使用装饰器来提升代码的可读性和可维护性。通过实例演示,读者将了解装饰器在各种场景下的灵活运用,从而更好地理解并应用于实际开发中。
|
3天前
|
缓存 Python
Python中的装饰器:提升代码可读性与灵活性
在Python编程中,装饰器是一种强大的工具,可以通过在函数或方法周围包装额外的功能来提升代码的可读性和灵活性。本文将深入探讨装饰器的概念、用法和实际应用,帮助读者更好地理解并运用这一Python编程的利器。
|
4天前
|
缓存 并行计算 Serverless
优化Python代码性能的5个技巧
在日常Python编程中,代码性能的优化是一个重要的议题。本文介绍了5个实用的技巧,帮助你提高Python代码的执行效率,包括使用适当的数据结构、优化循环结构、利用内置函数、使用生成器表达式以及并行化处理。通过这些技巧,你可以更高效地编写Python代码,提升程序的性能和响应速度。
|
5天前
|
Python
探索Python中的装饰器:提升代码灵活性与可维护性
Python中的装饰器是一种强大的工具,可以在不改变原有代码结构的情况下,动态地添加功能或修改函数的行为。本文将深入探讨装饰器的原理、常见用法以及如何利用装饰器提升代码的灵活性和可维护性。
|
5天前
|
机器学习/深度学习 自然语言处理 算法
Python遗传算法GA对长短期记忆LSTM深度学习模型超参数调优分析司机数据|附数据代码
Python遗传算法GA对长短期记忆LSTM深度学习模型超参数调优分析司机数据|附数据代码
|
5天前
|
数据可视化 Python
python中Copula在多元联合分布建模可视化2实例合集|附数据代码
python中Copula在多元联合分布建模可视化2实例合集|附数据代码
|
5天前
|
人工智能 Python
Python中的反对称矩阵:理论、应用与代码实践
Python中的反对称矩阵:理论、应用与代码实践
23 1
|
5天前
|
机器学习/深度学习 存储 算法
Python套索回归lasso、SCAD、LARS分析棒球运动员薪水3个实例合集|附数据代码
Python套索回归lasso、SCAD、LARS分析棒球运动员薪水3个实例合集|附数据代码