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Icecream：Python 调试别再只用 print()
Icecream: Never use print() to debug again in Python
2019 — 2021，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
Icecream 是一个 Python 调试库，让你用 ic() 代替 print()：它会自动打印变量名、表达式和值，还支持检查函数执行、带颜色输出等，省去手写调试语句的麻烦。项目在 GitHub 上开源，2019 和 2021 两次登上 Hacker News 首页。
为什么经久不衰：print 调试是每个程序员的日常，这个库把最常用的调试动作做到极致顺手，多年后仍是 Python 生态里被反复推荐的经典小工具。
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Python 3.8 的 f-string = 语法已内置类似功能，无需第三方库
用 Python 3.8+ 的 f-string 也能做到同样的事，只需在变量名后加一个等号：print(f"{d['key'][1]=}") 会输出 d['key'][1]='one'。
kissgyorgy查看英文原文
You can do the same thing with Python 3.8+ by using f-strings and just appending "=" to the variable name: >>> print(f"{d['key'][1]=}") d['key'][1]='one'
推荐同类工具 PySnooper，用装饰器追踪函数执行全过程
当代码行为和我的心智模型不符时，我会用 PySnooper。它和 Icecream 一样宣称“再也不用 print 调试”，只需给函数加个装饰器，运行时就会自动打印每行代码执行情况和变量的变化过程。
jshprentz查看英文原文
I use PySnooper[1] when code behavior deviates inscrutably from my mental model. Like Icecream, PySnooper exhorts, "Never use print for debugging again." A simple example: import pysnooper @pysnooper.snoop() def add_up(numbers): total = 0 for number in numbers: total += number return total add_up([123, 456]) When run, PySnooper prints the activity of the decorated function or method: $ python example.py Source path:... /home/joel/example.py Starting var:.. numbers = [123, 456] 08:46:58.742543 call 4 def add_up(numbers): 08:46:58.742692 line 5 total = 0 New var:....... total = 0 08:46:58.742722 line 6 for number in numbers: New var:....... number = 123 08:46:58.742755 line 7 total += number Modified var:.. total = 123 08:46:58.742787 line 6 for number in numbers: Modified var:.. number = 456 08:46:58.742818 line 7 total += number Modified var:.. total = 579 08:46:58.742847 line 6 for number in numbers: 08:46:58.742876 line 8 return total 08:46:58.742898 return 8 return total Return value:.. 579 Elapsed time: 00:00:00.000405 [1] https://github.com/cool-RR/PySnooper
推荐另一个极简调试工具 q，用法几乎无限制
还有一个更好记的替代品 q：只需 import q，它既能当函数用（q(x)），也能当变量用（q|x、q/x，利用不同运算符优先级），还能当装饰器用（@q），几乎任何场景都能快速插入调试输出。
nneonneo查看英文原文
For an even easier-to-remember alternative, there’s q: https://github.com/zestyping/q All you need is `import q`. q works like a function (q(x)), like a variable (q|x and q/x, so you get different operator precedences) and like a decorator (@q), so it can be used in practically any circumstance for a quick debug print. Plus, the name sounds like you’re interrogating something.
内置 breakpoint() 加调试器已足够好，print 调试的优势场景越来越少
我以前也大量用 print 调试，后来试了 Python 3.7 起内置的 breakpoint()，现在离不开 PDB 这类真正的调试器了。print() 只比 breakpoint() 少打几个字符而已，pytest 还有 --pdb 选项可在测试失败时直接进入调试会话。我想不出还有什么场景 print 调试比真正的调试器更好。
bow_查看英文原文
I used to do print debugging a lot. And then I tried using the `breakpoint()` call available since Python 3.7[1], and now I can't imagine doing any serious debugging without PDB (or any other debugger). (I mentioned Python, since this is linking to the Python-flavor of Icecream). Sure, there are still times when just calling print() is sufficient. But they are becoming less frequent. `print()` is only shorter than `breakpoint()` by just 5 - len(variable_name_to_print) characters after all. I know `import pdb; pdb.set_trace()` was available before, though `breakpoint()` is just a lot simpler, among others for the reasons they mentioned in the PEP. There is also the `--pdb` flag in pytest[2], that lets me jump into a PDB session upon test failure. All of this makes me think, what are the cases where print-level debugging is the better option in Python, compared to using an actual debugger? [1] https://www.python.org/dev/peps/pep-0553/ [2] https://docs.pytest.org/en/latest/usage.html#using-the-builtin-breakpoint-function
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