watchpoints 0.2.5
watchpoints monitors read and write on variables
Requires Python: >=3.6

# watchpoints

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watchpoints is an easy-to-use, intuitive variable/object monitor tool for python that behaves similar to watchpoints in gdb.

## Install

```
pip install watchpoints
```

## Usage

### watch

Simply ```watch``` the variables you need to monitor!

```python
from watchpoints import watch

a = 0
watch(a)
a = 1
```

will generate

```
====== Watchpoints Triggered ======
Call Stack (most recent call last):
  <module> (my_script.py:5):
>   a = 1
a:
0
->
1
```

It works on both variable change and object change

```python
from watchpoints import watch

a = []
watch(a)
a.append(1)  # Trigger
a = {}  # Trigger
```

Even better, it can track the changes of the object after the changes of the variable

```python
from watchpoints import watch

a = []
watch(a)
a = {}  # Trigger
a["a"] = 2  # Trigger
```

Without doubts, it works whenever the object is changed, even if it's not in the same scope

```python
from watchpoints import watch

def func(var):
    var["a"] = 1

a = {}
watch(a)
func(a)
```

```
====== 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}
```

As you can imagine, you can monitor attributes of an object, or a specific element of a list or a dict

```python
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
```

Also, watchpoints supports native ```threading``` library for multi-threading. It will tell you which thread is changing the
value as well.

```
====== Watchpoints Triggered ======
---- Thread-1 ----
Call Stack (most recent call last):
  _bootstrap (/usr/lib/python3.8/threading.py:890):
>   self._bootstrap_inner()
  _bootstrap_inner (/usr/lib/python3.8/threading.py:932):
>   self.run()
  run (my_script.py:15):
>   a[0] = i
a:
[0]
->
[1]
```

**watchpoints will try to guess what you want to monitor, and monitor it as you expect**(well most of the time)

### unwatch

When you are done with the variable, you can unwatch it.

```python
from watchpoints import watch, unwatch

a = 0
watch(a)
a = 1
unwatch(a)
a = 2  # nothing will happen
```

Or you can unwatch everything by passing no argument to it

```python
unwatch()  # unwatch everything
```

### print to different stream

Like the ``print`` function, you can choose the output stream for watch print using ``file`` argument. The default
value is ``sys.stderr``.

```python
f = open("watch.log", "w")
a = 0
watch(a, file=f)
a = 1
f.close()
```

Be aware that **the stream needs to be available when the variable is changed**! So the following code **WON'T WORK**:

```python
a = 0
with open("watch.log", "w") as f:
    watch(a, file=f)
a = 1
```

Or you could just give a filename to ``watch``. It will append to the file.

```python
watch(a, file="watch.log")
```

Use config if you want to make it global

```python
watch.config(file="watch.log")
```

### customize printer

You can use your own printer function to print the object, instead of the default ``objprint`` with ``custom_printer``

```python
# This will use built-in print function for the objects
watch(a, custom_printer=print)
```

Use config if you want to make it global

```python
watch.config(custom_printer=print)
```

### alias

You can give an alias to a monitored variable, so you can unwatch it anywhere. And the alias will be printed instead of the variable name
```python
from watchpoints import watch, unwatch

watch(a, alias="james")
# Many other stuff, scope changes
unwatch("james")
```

### conditional callback

You can give an extra condition filter to do "conditional watchpoints". Pass a function ```func(obj)``` which returns ```True```
if you want to trigger the callback to ```when``` of ```watch```

```python
a = 0
watch(a, when=lambda x: x > 0)
a = -1  # Won't trigger
a = 1  # Trigger
```

### variable vs object

When you do ```watch()``` on an object, you are actually tracking both the object and the variable holding it. In most cases, that's what
you want anyways. However, you can configure precisely which you want to track.

```python
a = []
watch(a, track="object")
a.append(1)  # Trigger
a = {}  # Won't trigger because the list object does not change

a = []
watch(a, track="variable")
a.append(1)  #  Won't trigger, because "a" still holds the same object
a = {}  # Trigger
```

### object compare and deepcopy

Nested object comparison is tricky. It's hard to find a solid standard to compare complicated customized objects.
By default, watchpoints will do a shallow copy of the object. You can override this behavior by passing ```deepcopy=True``` to ```watch()```

```python
watch(a, deepcopy=True)
```

watchpoints will honor ```__eq__``` method for user-defined classes first. If ```__eq__``` is not implemented, watchpoints will compare
```__dict__```(basically attibures) of the object if using shallow copy, and raise an ```NotImplementedError``` if using deepcopy.

The reason behind this is, if you deepcopied a complicated structure, there's no way for watchpoints to figure out if it's the same object
without user defined ```__eq__``` function.

#### customize copy and compare

For your own data structures, you can provide a customized copy and/or customized compare function for watchpoints to better suit your need.

watchpoints will use the copy function you provide to copy the object for reference, and use your compare function to check if that
object is changed. If copy function or compare function is not provided, it falls to default as mentioned above.

```cmp``` argument takes a function that will take two objects as arguments and return a ```boolean``` representing whether the objects
are **different**

```python
def my_cmp(obj1, obj2):
    return obj1.id != obj2.id

watch(a, cmp=my_cmp)
```

```copy``` argument takes a function that will take a object and return a copy of it

```python
def my_copy(obj):
    return MyObj(id=obj.id)

watch(a, copy=my_copy)
```

### stack limit

You can specify the call stack limit printed using ```watch.config()```. The default value is ```5```, any positive integer is accepted.
You can use ```None``` for unlimited call stack, which means it will prints out all the frames.

```python
watch.config(stack_limit=10)
```

You can also set different stack limits for each monitored variable by passing ``stack_limit`` argument to ``watch``

```python
# This will only change stack_limit for a
watch(a, stack_limit=10)
```

### customize callback

Of course sometimes you want to print in your own format, or even do something more than print. You can use your own callback for monitored variables

```python
watch(a, callback=my_callback)
```

The callback function takes three arguments

```python
def my_callback(frame, elem, exec_info)
```

* ```frame``` is the current frame when a change is detected.
* ```elem``` is a ```WatchElement``` object that I'm too lazy to describe for now.
* ```exec_info``` is a tuple of ```(funcname, filename, lineno)``` of the line that changed the variable

You can also set change the callback function globally by

```python
watch.config(callback=my_callback)
```

Use ```restore()``` to restore the default callback
```python
watch.restore()
```

### Integrating with pdb

watchpoints can be used with pdb with ease. You can trigger pdb just like using ```breakpoint()``` when
your monitored variable is changed. Simply do

```python
watch.config(pdb=True)
```

When you are in pdb, use ```q(uit)``` command to exit pdb, and the next change on the variable will trigger the pdb again.

### Avoid import

Sometimes it's a hassle having to import the function in every single file. You can install the watch function to builtins
and be able to call it in any files:

```python
watch.install()  # or watch.install("func_name") and use it as func_name()
# Remove it from the builtins
watch.uninstall()  # if installed with a name, pass it to uninstall() as well
```

## Limitations

* watchpoints uses ```sys.settrace()``` so it is not compatible with other libraries that use the same function.
* watchpoints will slow down your program significantly, like other debuggers, so use it for debugging purpose only
* ```watch()``` needs to be used by itself, not nested in other functions, to be correctly parsed
* at this point, there might be other issues because it's still in development phase

## Bugs/Requests

Please send bug reports and feature requests through [github issue tracker](https://github.com/gaogaotiantian/watchpoints/issues).

## License

Copyright Tian Gao, 2020.

Distributed under the terms of the  [Apache 2.0 license](https://github.com/gaogaotiantian/watchpoints/blob/master/LICENSE).