有一个python代码库构建就是为了这个目的:inspect在python 2.7中介绍过

object.__dict__

尝试ppretty

from ppretty import ppretty


class A(object):
    s = 5

    def __init__(self):
        self._p = 8

    @property
    def foo(self):
        return range(10)


print ppretty(A(), indent='    ', depth=2, width=30, seq_length=6,
              show_protected=True, show_private=False, show_static=True,
              show_properties=True, show_address=True)

输出:

__main__.A at 0x1debd68L (
    _p = 8, 
    foo = [0, 1, 2, ..., 7, 8, 9], 
    s = 5
)

Vars (obj)返回对象的属性。

If you want to look inside a live object, then python's inspect module is a good answer. In general, it works for getting the source code of functions that are defined in a source file somewhere on disk. If you want to get the source of live functions and lambdas that were defined in the interpreter, you can use dill.source.getsource from dill. It also can get the code for from bound or unbound class methods and functions defined in curries... however, you might not be able to compile that code without the enclosing object's code.

>>> from dill.source import getsource
>>> 
>>> def add(x,y):
...   return x+y
... 
>>> squared = lambda x:x**2
>>> 
>>> print getsource(add)
def add(x,y):
  return x+y

>>> print getsource(squared)
squared = lambda x:x**2

>>> 
>>> class Foo(object):
...   def bar(self, x):
...     return x*x+x
... 
>>> f = Foo()
>>> 
>>> print getsource(f.bar)
def bar(self, x):
    return x*x+x

>>> 

有一个很酷的工具叫objexplore。下面是一个简单的例子，关于如何在pandas数据框架上使用它的探索功能。

import pandas as pd
df=pd.read_csv('https://storage.googleapis.com/download.tensorflow.org/data/heart.csv')

from objexplore import explore
explore(df)

将在你的shell中弹出以下内容: