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.
You want vars()
mixed with pprint()
:
from pprint import pprint
pprint(vars(your_object))
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__'}
__dict__
member (an re.MatchObject
for instance), but builtin dir()
works for all objects.
print re.compile(r'slots').search('No slots here either.').__slots__
inspect
module in your answer? I think it is the closest thing to print_r or var_dump.
dir()
, then? dir()
only returns a list of names, and not all of those exist in vars()
or in the __dict__
attribute.
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.
getmembers()
function in the standard inspect
module, but I thought this would be more useful in that it illustrates how to do introspection in general.
__dict__
(such as __doc__
and __module__
). Furthermore, __dict__
doesn't work at all for objects declared with __slots__
. In general, __dict__
shows user-level properties that are actually stored in a dictionary internally. dir() shows more.
__dict__
attribute/member. I know it's crazy, but true. Built-ins like int
and str
or re.MatchObject
s are common examples. Try 'hello'.__dict__
, then try dir('hello')
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}
set
doesn't have __dict__
, so for them it will fail with AttributeError: 'set' object has no attribute '__dict__'
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.
from collections import * ; obj=Counter([3,4])
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
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.
print "DEBUG: object value: " + repr(obj)
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).
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__.
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.
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))
TypeError: vars() argument must have __dict__ attribute
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)
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.
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))
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)
Why not something simple:
for key,value in obj.__dict__.iteritems():
print key,value
for key,value in obj.__dict__.iteritems(): print key,value
?
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)}
{attr: getattr(your_obj, attr) for attr in dir(your_obj) and "__" not in attr}
I've upvoted the answer that mentions only pprint. To be clear, 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.
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])
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?
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))
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)
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.
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.
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)
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']
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
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
Success story sharing
vars()
simply returns the__dict__
of its argument and that is also the fallback ofdir()
in case there is no__dir__
method. so usedir()
in the first place, as i said.dir()
gives you all the built in things you probably don't care about like__str__
and__new__
.var()
doesn't.__dict__
attribute.vars()
gives the values of the fields, whiledir()
leaves them a mystery.