Is there a built-in function to print all the current properties and values of an object?

Question

So what I'm looking for here is something like PHP's print_r function.

This is so I can debug my scripts by seeing what's the state of the object in question.

Answer 1

You want vars() mixed with pprint():

from pprint import pprint
pprint(vars(your_object))

Answer 2

You are really mixing together two different things.

Use dir(), vars() or the inspect module to get what you are interested in (I use __builtins__ as an example; you can use any object instead).

>>> l = dir(__builtins__)
>>> d = __builtins__.__dict__

Print that dictionary however fancy you like:

>>> print l
['ArithmeticError', 'AssertionError', 'AttributeError',...

or

>>> from pprint import pprint
>>> pprint(l)
['ArithmeticError',
 'AssertionError',
 'AttributeError',
 'BaseException',
 'DeprecationWarning',
...

>>> pprint(d, indent=2)
{ 'ArithmeticError': <type 'exceptions.ArithmeticError'>,
  'AssertionError': <type 'exceptions.AssertionError'>,
  'AttributeError': <type 'exceptions.AttributeError'>,
...
  '_': [ 'ArithmeticError',
         'AssertionError',
         'AttributeError',
         'BaseException',
         'DeprecationWarning',
...

Pretty printing is also available in the interactive debugger as a command:

(Pdb) pp vars()
{'__builtins__': {'ArithmeticError': <type 'exceptions.ArithmeticError'>,
                  'AssertionError': <type 'exceptions.AssertionError'>,
                  'AttributeError': <type 'exceptions.AttributeError'>,
                  'BaseException': <type 'exceptions.BaseException'>,
                  'BufferError': <type 'exceptions.BufferError'>,
                  ...
                  'zip': <built-in function zip>},
 '__file__': 'pass.py',
 '__name__': '__main__'}

Answer 3

def dump(obj):
  for attr in dir(obj):
    print("obj.%s = %r" % (attr, getattr(obj, attr)))

There are many 3rd-party functions out there that add things like exception handling, national/special character printing, recursing into nested objects etc. according to their authors' preferences. But they all basically boil down to this.

Answer 4

dir has been mentioned, but that'll only give you the attributes' names. If you want their values as well, try __dict__.

class O:
   def __init__ (self):
      self.value = 3

o = O()

Here is the output:

>>> o.__dict__

{'value': 3}

Answer 5

Is there a built-in function to print all the current properties and values of an object?

No. The most upvoted answer excludes some kinds of attributes, and the accepted answer shows how to get all attributes, including methods and parts of the non-public api. But there is no good complete builtin function for this.

So the short corollary is that you can write your own, but it will calculate properties and other calculated data-descriptors that are part of the public API, and you might not want that:

from pprint import pprint
from inspect import getmembers
from types import FunctionType

def attributes(obj):
    disallowed_names = {
      name for name, value in getmembers(type(obj)) 
        if isinstance(value, FunctionType)}
    return {
      name: getattr(obj, name) for name in dir(obj) 
        if name[0] != '_' and name not in disallowed_names and hasattr(obj, name)}

def print_attributes(obj):
    pprint(attributes(obj))

Problems with other answers

Observe the application of the currently top voted answer on a class with a lot of different kinds of data members:

from pprint import pprint

class Obj:
    __slots__ = 'foo', 'bar', '__dict__'
    def __init__(self, baz):
        self.foo = ''
        self.bar = 0
        self.baz = baz
    @property
    def quux(self):
        return self.foo * self.bar

obj = Obj('baz')
pprint(vars(obj))

only prints:

{'baz': 'baz'}

Because vars only returns the __dict__ of an object, and it's not a copy, so if you modify the dict returned by vars, you're also modifying the __dict__ of the object itself.

vars(obj)['quux'] = 'WHAT?!'
vars(obj)

returns:

{'baz': 'baz', 'quux': 'WHAT?!'}

-- which is bad because quux is a property that we shouldn't be setting and shouldn't be in the namespace...

Applying the advice in the currently accepted answer (and others) is not much better:

>>> dir(obj)
['__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__slots__', '__str__', '__subclasshook__', 'bar', 'baz', 'foo', 'quux']

As we can see, dir only returns all (actually just most) of the names associated with an object.

inspect.getmembers, mentioned in the comments, is similarly flawed - it returns all names and values.

From class

When teaching I have my students create a function that provides the semantically public API of an object:

def api(obj):
    return [name for name in dir(obj) if name[0] != '_']

We can extend this to provide a copy of the semantic namespace of an object, but we need to exclude __slots__ that aren't assigned, and if we're taking the request for "current properties" seriously, we need to exclude calculated properties (as they could become expensive, and could be interpreted as not "current"):

from types import FunctionType
from inspect import getmembers

def attrs(obj):
    disallowed_properties = {
        name for name, value in getmembers(type(obj)) 
        if isinstance(value, (property, FunctionType))
    }
    return {
        name: getattr(obj, name) for name in api(obj) 
        if name not in disallowed_properties and hasattr(obj, name)
    }

And now we do not calculate or show the property, quux:

>>> attrs(obj)
{'bar': 0, 'baz': 'baz', 'foo': ''}

Caveats

But perhaps we do know our properties aren't expensive. We may want to alter the logic to include them as well. And perhaps we want to exclude other custom data descriptors instead.

Then we need to further customize this function. And so it makes sense that we cannot have a built-in function that magically knows exactly what we want and provides it. This is functionality we need to create ourselves.

Conclusion

There is no built-in function that does this, and you should do what is most semantically appropriate for your situation.

Answer 6

You can use the "dir()" function to do this.

>>> import sys
>>> dir(sys)
['__displayhook__', '__doc__', '__excepthook__', '__name__', '__stderr__', '__stdin__', '__stdo
t__', '_current_frames', '_getframe', 'api_version', 'argv', 'builtin_module_names', 'byteorder
, 'call_tracing', 'callstats', 'copyright', 'displayhook', 'dllhandle', 'exc_clear', 'exc_info'
 'exc_type', 'excepthook', 'exec_prefix', 'executable', 'exit', 'getcheckinterval', 'getdefault
ncoding', 'getfilesystemencoding', 'getrecursionlimit', 'getrefcount', 'getwindowsversion', 'he
version', 'maxint', 'maxunicode', 'meta_path', 'modules', 'path', 'path_hooks', 'path_importer_
ache', 'platform', 'prefix', 'ps1', 'ps2', 'setcheckinterval', 'setprofile', 'setrecursionlimit
, 'settrace', 'stderr', 'stdin', 'stdout', 'subversion', 'version', 'version_info', 'warnoption
', 'winver']
>>>

Another useful feature is help.

>>> help(sys)
Help on built-in module sys:

NAME
    sys

FILE
    (built-in)

MODULE DOCS
    http://www.python.org/doc/current/lib/module-sys.html

DESCRIPTION
    This module provides access to some objects used or maintained by the
    interpreter and to functions that interact strongly with the interpreter.

    Dynamic objects:

    argv -- command line arguments; argv[0] is the script pathname if known

Answer 7

To print the current state of the object you might:

>>> obj # in an interpreter

or

print repr(obj) # in a script

or

print obj

For your classes define __str__ or __repr__ methods. From the Python documentation:

__repr__(self) Called by the repr() built-in function and by string conversions (reverse quotes) to compute the "official" string representation of an object. If at all possible, this should look like a valid Python expression that could be used to recreate an object with the same value (given an appropriate environment). If this is not possible, a string of the form "<...some useful description...>" should be returned. The return value must be a string object. If a class defines repr() but not __str__(), then __repr__() is also used when an "informal" string representation of instances of that class is required. This is typically used for debugging, so it is important that the representation is information-rich and unambiguous.

__str__(self) Called by the str() built-in function and by the print statement to compute the "informal" string representation of an object. This differs from __repr__() in that it does not have to be a valid Python expression: a more convenient or concise representation may be used instead. The return value must be a string object.

Answer 8

I recommend using help(your_object).

help(dir)

 If called without an argument, return the names in the current scope.
 Else, return an alphabetized list of names comprising (some of) the attributes
 of the given object, and of attributes reachable from it.
 If the object supplies a method named __dir__, it will be used; otherwise
 the default dir() logic is used and returns:
 for a module object: the module's attributes.
 for a class object:  its attributes, and recursively the attributes
 of its bases.
 for any other object: its attributes, its class's attributes, and
 recursively the attributes of its class's base classes.

help(vars)

Without arguments, equivalent to locals().
With an argument, equivalent to object.__dict__.

Answer 9

Might be worth checking out --

Is there a Python equivalent to Perl's Data::Dumper?

My recommendation is this --

https://gist.github.com/1071857

Note that perl has a module called Data::Dumper which translates object data back to perl source code (NB: it does NOT translate code back to source, and almost always you don't want to the object method functions in the output). This can be used for persistence, but the common purpose is for debugging.

There are a number of things standard python pprint fails to achieve, in particular it just stops descending when it sees an instance of an object and gives you the internal hex pointer of the object (errr, that pointer is not a whole lot of use by the way). So in a nutshell, python is all about this great object oriented paradigm, but the tools you get out of the box are designed for working with something other than objects.

The perl Data::Dumper allows you to control how deep you want to go, and also detects circular linked structures (that's really important). This process is fundamentally easier to achieve in perl because objects have no particular magic beyond their blessing (a universally well defined process).

Answer 10

In most cases, using __dict__ or dir() will get you the info you're wanting. If you should happen to need more details, the standard library includes the inspect module, which allows you to get some impressive amount of detail. Some of the real nuggests of info include:

• names of function and method parameters
• class hierarchies
• source code of the implementation of a functions/class objects
• local variables out of a frame object

If you're just looking for "what attribute values does my object have?", then dir() and __dict__ are probably sufficient. If you're really looking to dig into the current state of arbitrary objects (keeping in mind that in python almost everything is an object), then inspect is worthy of consideration.

Answer 11

If you're using this for debugging, and you just want a recursive dump of everything, the accepted answer is unsatisfying because it requires that your classes have good __str__ implementations already. If that's not the case, this works much better:

import json
print(json.dumps(YOUR_OBJECT, 
                 default=lambda obj: vars(obj),
                 indent=1))

Answer 12

Try 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(), show_protected=True, show_static=True, show_properties=True)

Output:

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

Answer 13

A metaprogramming example Dump object with magic:

$ cat dump.py

#!/usr/bin/python
import sys
if len(sys.argv) > 2:
    module, metaklass  = sys.argv[1:3]
    m = __import__(module, globals(), locals(), [metaklass])
    __metaclass__ = getattr(m, metaklass)

class Data:
    def __init__(self):
        self.num = 38
        self.lst = ['a','b','c']
        self.str = 'spam'
    dumps   = lambda self: repr(self)
    __str__ = lambda self: self.dumps()

data = Data()
print data

Without arguments:

$ python dump.py

<__main__.Data instance at 0x00A052D8>

With Gnosis Utils:

$ python dump.py gnosis.magic MetaXMLPickler

<?xml version="1.0"?>
<!DOCTYPE PyObject SYSTEM "PyObjects.dtd">
<PyObject module="__main__" class="Data" id="11038416">
<attr name="lst" type="list" id="11196136" >
  <item type="string" value="a" />
  <item type="string" value="b" />
  <item type="string" value="c" />
</attr>
<attr name="num" type="numeric" value="38" />
<attr name="str" type="string" value="spam" />
</PyObject>

It is a bit outdated but still working.

Answer 14

This prints out all the object contents recursively in json or yaml indented format:

import jsonpickle # pip install jsonpickle
import json
import yaml # pip install pyyaml

serialized = jsonpickle.encode(obj, max_depth=2) # max_depth is optional
print json.dumps(json.loads(serialized), indent=4)
print yaml.dump(yaml.load(serialized), indent=4)

Answer 15

from pprint import pprint

def print_r(the_object):
    print ("CLASS: ", the_object.__class__.__name__, " (BASE CLASS: ", the_object.__class__.__bases__,")")
    pprint(vars(the_object))

Answer 16

Why not something simple:

for key,value in obj.__dict__.iteritems():
    print key,value

Answer 17

If you want to see all the values in a complex data structure, then do something like:

from pprint import pprint
pprint(my_var)

Where my_var is your variable of interest. When I used pprint(vars(my_var)) I got nothing, and other answers here didn't help or the method looked unnecessarily long. By the way, in my particular case, the code I was inspecting had a dictionary of dictionaries.

Worth pointing out that with some custom classes you may just end up with an unhelpful <someobject.ExampleClass object at 0x7f739267f400> kind of output. In that case, you might have to implement a __str__ method, or try some of the other solutions.

I also found that in one instance where I got this object type of output, vars() showed me what I wanted. So a better solution to cover both cases would be to try both individually. But using vars() can sometimes throw an exception, for example, TypeError: vars() argument must have __dict__ attribute.

I'd still like to find something simple that works in all scenarios, without third party libraries.

Answer 18

This works no matter how your varibles are defined within a class, inside __init__ or outside.

your_obj = YourObj()
attrs_with_value = {attr: getattr(your_obj, attr) for attr in dir(your_obj)}

Answer 19

I was needing to print DEBUG info in some logs and was unable to use pprint because it would break it. Instead I did this and got virtually the same thing.

DO = DemoObject()

itemDir = DO.__dict__

for i in itemDir:
    print '{0}  :  {1}'.format(i, itemDir[i])

Answer 20

To dump "myObject":

from bson import json_util
import json

print(json.dumps(myObject, default=json_util.default, sort_keys=True, indent=4, separators=(',', ': ')))

I tried vars() and dir(); both failed for what I was looking for. vars() didn't work because the object didn't have __dict__ (exceptions.TypeError: vars() argument must have __dict__ attribute). dir() wasn't what I was looking for: it's just a listing of field names, doesn't give the values or the object structure.

I think json.dumps() would work for most objects without the default=json_util.default, but I had a datetime field in the object so the standard json serializer failed. See How to overcome "datetime.datetime not JSON serializable" in python?

Answer 21

Just try beeprint.

It will help you not only with printing object variables, but beautiful output as well, like this:

class(NormalClassNewStyle):
  dicts: {
  },
  lists: [],
  static_props: 1,
  tupl: (1, 2)

Answer 22

For everybody struggling with

• vars() not returning all attributes.
• dir() not returning the attributes' values.

The following code prints all attributes of obj with their values:

for attr in dir(obj):
        try:
            print("obj.{} = {}".format(attr, getattr(obj, attr)))
        except AttributeError:
            print("obj.{} = ?".format(attr))

Answer 23

pprint contains a “pretty printer” for producing aesthetically pleasing representations of your data structures. The formatter produces representations of data structures that can be parsed correctly by the interpreter, and are also easy for a human to read. The output is kept on a single line, if possible, and indented when split across multiple lines.

Answer 24

While there are many good answers, here is a 1-liner that can give the attributes AS WELL AS values:

(str(vars(config)).split(",")[1:])

where 'config' is the object in question. I am listing this as a separate answer because I just wanted to simply print the relevant values of the object (excl the __main etc) without using loops or pretty print and didn't find a convenient answer.

Answer 25

This project modifies pprint to show all object field values, it ignores he objects __repr__ member function, it also recurses into nested objects. It works with python3, see https://github.com/MoserMichael/pprintex You can install it via pip: pip install printex

Answer 26

vars() seems to show the attributes of this object, but dir() seems to show attributes of parent class(es) as well. You don't usually need to see inherited attributes such as str, doc. dict etc.

In [1]: class Aaa():
...:     def __init__(self, name, age):
...:         self.name = name
...:         self.age = age
...:
In [2]: class Bbb(Aaa):
...:     def __init__(self, name, age, job):
...:         super().__init__(name, age)
...:         self.job = job
...:
In [3]: a = Aaa('Pullayya',42)

In [4]: b = Bbb('Yellayya',41,'Cop')

In [5]: vars(a)
Out[5]: {'name': 'Pullayya', 'age': 42}

In [6]: vars(b)
Out[6]: {'name': 'Yellayya', 'age': 41, 'job': 'Cop'}

In [7]: dir(a)
Out[7]:
['__class__',
 '__delattr__',
 '__dict__',
 '__dir__',
 '__doc__',
 '__eq__',
 ...
 ...
 '__subclasshook__',
 '__weakref__',
 'age',
 'name']

Answer 27

@dataclass + pprint (recursive, indented, no external libs, Python 3.10)

@dataclass is just amazing, and pprint from Python 3.10 learnt to print dataclasses with indentation, so if you can convert your code to @dataclass this is a very good approach:

from dataclasses import dataclass
from pprint import pprint

@dataclass
class MyClass1:
    s: str
    n0: int
    n1: int
    n2: int
    n3: int
    n4: int
    n5: int
    n6: int
    n7: int
    n8: int
    n9: int

@dataclass
class MyClass2:
    s: str
    n0: int
    n1: int
    n2: int
    n3: int
    n4: int
    n5: int
    n6: int
    n7: int
    n8: int
    n9: int
    my_class_1: MyClass1

obj = MyClass2(s='a', n0=0, n1=1, n2=2, n3=3, n4=4, n5=5, n6=6, n7=7, n8=8, n9=9, my_class_1=MyClass1(s='a', n0=0, n1=1, n2=2, n3=3, n4=4, n5=5, n6=6, n7=7, n8=8, n9=9))
print(obj)
pprint(obj)

Output:

MyClass2(s='a', n0=0, n1=1, n2=2, n3=3, n4=4, n5=5, n6=6, n7=7, n8=8, n9=9, my_class_1=MyClass1(s='a', n0=0, n1=1, n2=2, n3=3, n4=4, n5=5, n6=6, n7=7, n8=8, n9=9))
MyClass2(s='a',
         n0=0,
         n1=1,
         n2=2,
         n3=3,
         n4=4,
         n5=5,
         n6=6,
         n7=7,
         n8=8,
         n9=9,
         my_class_1=MyClass1(s='a',
                             n0=0,
                             n1=1,
                             n2=2,
                             n3=3,
                             n4=4,
                             n5=5,
                             n6=6,
                             n7=7,
                             n8=8,
                             n9=9))

See also: Pretty-print dataclasses prettier with line breaks and indentation

@dataclass also gives you other very good features for free:

• __hash__ and __eq__: Object of custom type as dictionary key
• __slots__: Prevent creating new attributes outside __init__

Vs other answers

Let's create a comparable non @dataclass code

from pprint import pprint

class MyClass1:
    def __init__(self, s, n0, n1, n2, n3, n4, n5, n6, n7, n8, n9):
        self.s = s
        self.n0 = n0
        self.n1 = n1
        self.n2 = n2
        self.n3 = n3
        self.n4 = n4
        self.n5 = n5
        self.n6 = n6
        self.n7 = n7
        self.n8 = n8
        self.n9 = n9

class MyClass2:
    def __init__(self, s, n0, n1, n2, n3, n4, n5, n6, n7, n8, n9, my_class_1):
        self.s = s
        self.n0 = n0
        self.n1 = n1
        self.n2 = n2
        self.n3 = n3
        self.n4 = n4
        self.n5 = n5
        self.n6 = n6
        self.n7 = n7
        self.n8 = n8
        self.n9 = n9
        self.n9 = n9
        self.my_class_1 = my_class_1

obj = MyClass2(s='a', n0=0, n1=1, n2=2, n3=3, n4=4, n5=5, n6=6, n7=7, n8=8, n9=9, my_class_1=MyClass1(s='a', n0=0, n1=1, n2=2, n3=3, n4=4, n5=5, n6=6, n7=7, n8=8, n9=9))
pprint(vars(obj))

pprint(vars(obj)) output is non-recursive:

{'my_class_1': <__main__.MyClass1 object at 0x7fee21a9bf70>,
 'n0': 0,
 'n1': 1,
 'n2': 2,
 'n3': 3,
 'n4': 4,
 'n5': 5,
 'n6': 6,
 'n7': 7,
 'n8': 8,
 'n9': 9,
 's': 'a'}

Tested on Python 3.10.7, Ubuntu 22.10.

Answer 28

You can try the Flask Debug Toolbar.
https://pypi.python.org/pypi/Flask-DebugToolbar

from flask import Flask
from flask_debugtoolbar import DebugToolbarExtension

app = Flask(__name__)

# the toolbar is only enabled in debug mode:
app.debug = True

# set a 'SECRET_KEY' to enable the Flask session cookies
app.config['SECRET_KEY'] = '<replace with a secret key>'

toolbar = DebugToolbarExtension(app)

Answer 29

From the answer, it can be slightly modified to get only 'Attributes' of an object as below:

def getAttributes(obj):
    from pprint import pprint
    from inspect import getmembers
    from types import FunctionType
    
    def attributes(obj):
        disallowed_names = {
          name for name, value in getmembers(type(obj)) 
            if isinstance(value, FunctionType)}
        return {
          name for name in dir(obj) 
            if name[0] != '_' and name not in disallowed_names and hasattr(obj, name)}
    pprint(attributes(obj))

It is helpful when adding this function temporary and can be removed without many changes in existing source code

Answer 30

I have not tested performance, but I believe this is the fastest method to enumerate just the properties / attributes / keys of any object in Python as a list.

# If core==False, ignore __k__ entries
def obj_props(obj, core=False) -> list:
    assert not obj is None, f"obj must not be null (None)"
    _props = []
    _use_dir=False
    def _add(p):
        if not core and p.find('__') == 0: return
        _props.append(p)
    if hasattr(obj, '__dict__'): 
        for p in obj.__dict__.keys(): _add(p)
    elif hasattr(obj, '__slots__'):
        for p in obj.__slots__: _add(p)
    elif hasattr(obj, 'keys'):
        try:
            for p in obj.keys(): _add(p)
        except Exception as ex:
            _props = []
            _use_dir = True
    else:
        _use_dir = True
    if _use_dir:
        # fall back to slow and steady
        for p in dir(obj):
            if not core and p.find('__') == 0: continue
            v = getattr(obj, p)
            v_t = type(v).__name__
            if v_t in ('function', 'method', 'builtin_function_or_method', 'method-wrapper'): continue
            _props.append(p)

    return _props

The above should work with regular python objects (with __dict__), objects using slots (__slots__) and even work with dictionary like objects.

Most other examples utilize dir(obj) which will enumerate all methods and properties of an object which will take a performance hit if you only need its properties.

Answer 31

I like working with python object built-in types keys or values.

For attributes regardless they are methods or variables:

o.keys()

For values of those attributes:

o.values()