Merge pull request #21466 from lujun9972/add-MjAyMTAzMzEgVXNlIHRoaXMgb3BlbiBzb3VyY2UgdG9vbCB0byBtb25pdG9yIHZhcmlhYmxlcyBpbiBQeXRob24ubWQK

自动选题[tech]: 20210331 Use this open source tool to monitor variables in Python

sources/tech/20210331 Use this open source tool to monitor variables in Python.md

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+[#]: subject: (Use this open source tool to monitor variables in Python)
+[#]: via: (https://opensource.com/article/21/4/monitor-debug-python)
+[#]: author: (Tian Gao https://opensource.com/users/gaogaotiantian)
+[#]: collector: (lujun9972)
+[#]: translator: ( )
+[#]: reviewer: ( )
+[#]: publisher: ( )
+[#]: url: ( )
+
+Use this open source tool to monitor variables in Python
+======
+Watchpoints is a simple but powerful tool to help you with monitoring
+variables while debugging Python.
+![Looking back with binoculars][1]
+
+When debugging code, you're often faced with figuring out when a variable changes. Without any advanced tools, you have the option of using print statements to announce the variables when you expect them to change. However, this is a very ineffective way because the variables could change in many places, and constantly printing them to a terminal is noisy, while printing them to a log file becomes unwieldy.
+
+This is a common issue, but now there is a simple but powerful tool to help you with monitoring variables: [watchpoints][2].
+
+The [watchpoint concept is common in C and C++ debuggers][3] to monitor memories, but there's a lack of equivalent tools in Python. `watchpoints` fills in the gap.
+
+### Installing
+
+To use it, you must first install it by using `pip`:
+
+
+```
+`$ python3 -m pip install watchpoints`
+```
+
+### Using watchpoints in Python
+
+For any variable you'd like to monitor, use the **watch** function on it.
+
+
+```
+from watchpoints import watch
+
+a = 0
+watch(a)
+a = 1
+```
+
+As the variable changes, information about its value is printed to **stdout**:
+
+
+```
+====== Watchpoints Triggered ======
+
+Call Stack (most recent call last):
+  <module> (my_script.py:5):
+> a = 1
+a:
+0
+->
+1
+```
+
+The information includes:
+
+  * The line where the variable was changed.
+  * The call stack.
+  * The previous/current value of the variable.
+
+
+
+It not only works with the variable itself, but it also works with object changes:
+
+
+```
+from watchpoints import watch
+
+a = []
+watch(a)
+a = {} # Trigger
+a["a"] = 2 # Trigger
+```
+
+The callback is triggered when the variable **a** is reassigned, but also when the object assigned to a is changed.
+
+What makes it even more interesting is that the monitor is not limited by the scope. You can watch the variable/object anywhere you want, and the callback is triggered no matter what function the program is executing.
+
+
+```
+from watchpoints import watch
+
+def func(var):
+    var["a"] = 1
+
+a = {}
+watch(a)
+func(a)
+```
+
+For example, this code prints:
+
+
+```
+====== Watchpoints Triggered ======
+
+Call Stack (most recent call last):
+
+  <module> (my_script.py:8):
+> func(a)
+  func (my_script.py:4):
+> var["a"] = 1
+a:
+{}
+->
+{'a': 1}
+```
+
+The **watch** function can monitor more than a variable. It can also monitor the attributes and an element of a dictionary or list.
+
+
+```
+from watchpoints import watch
+
+class MyObj:
+    def __init__(self):
+        self.a = 0
+
+obj = MyObj()
+d = {"a": 0}
+watch(obj.a, d["a"]) # Yes you can do this
+obj.a = 1 # Trigger
+d["a"] = 1 # Trigger
+```
+
+This could help you narrow down to some specific objects that you are interested in.
+
+If you are not happy about the format of the output, you can customize it. Just define your own callback function:
+
+
+```
+watch(a, callback=my_callback)
+
+# Or set it globally
+
+watch.config(callback=my_callback)
+```
+
+You can even bring up **pdb** when the trigger is hit:
+
+
+```
+`watch.config(pdb=True)`
+```
+
+This behaves similarly to **breakpoint()**, giving you a debugger-like experience.
+
+If you don’t want to import the function in every single file, you can make it global by using **install** function:
+
+
+```
+`watch.install() # or watch.install("func_name") and use it as func_name()`
+```
+
+Personally, I think the coolest thing about watchpoints is its intuitive usage. Are you interested in some data? Just "watch" it, and you'll know when your variable changes.
+
+### Try watchpoints
+
+I developed and maintain `watchpoints` on [GitHub][2], and have released it under the licensed under Apache 2.0. Install it and use it, and of course contribution is always welcome.
+
+--------------------------------------------------------------------------------
+
+via: https://opensource.com/article/21/4/monitor-debug-python
+
+作者：[Tian Gao][a]
+选题：[lujun9972][b]
+译者：[译者ID](https://github.com/译者ID)
+校对：[校对者ID](https://github.com/校对者ID)
+
+本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
+
+[a]: https://opensource.com/users/gaogaotiantian
+[b]: https://github.com/lujun9972
+[1]: https://opensource.com/sites/default/files/styles/image-full-size/public/lead-images/look-binoculars-sight-see-review.png?itok=NOw2cm39 (Looking back with binoculars)
+[2]: https://github.com/gaogaotiantian/watchpoints
+[3]: https://opensource.com/article/21/3/debug-code-gdb