Python setattr() to function takes initial function name - python

I do understand how setattr() works in python, but my question is when i try to dynamically set an attribute and give it an unbound function as a value, so the attribute is a callable, the attribute ends up taking the name of the unbound function when i call attr.__name__ instead of the name of the attribute.
Here's an example:
I have a Filter class:
class Filter:
def __init__(self, column=['poi_id', 'tp.event'], access=['con', 'don']):
self.column = column
self.access = access
self.accessor_column = dict(zip(self.access, self.column))
self.set_conditions()
def condition(self, name):
# i want to be able to get the name of the dynamically set
# function and check `self.accessor_column` for a value, but when
# i do `setattr(self, 'accessor', self.condition)`, the function
# name is always set to `condition` rather than `accessor`
return name
def set_conditions(self):
mapping = list(zip(self.column, self.access))
for i in mapping:
poi_column = i[0]
accessor = i[1]
setattr(self, accessor, self.condition)
In the class above, the set_conditions function dynamically set attributes (con and don) of the Filter class and assigns them a callable, but they retain the initial name of the function.
When i run this:
>>> f = Filter()
>>> print(f.con('linux'))
>>> print(f.con.__name__)
Expected:
linux
con (which should be the name of the dynamically set attribute)
I get:
linux
condition (name of the value (unbound self.condition) of the attribute)
But i expect f.con.__name__ to return the name of the attribute (con) and not the name of the unbound function (condition) assigned to it.
Can someone please explain to me why this behaviour is such and how can i go around it?
Thanks.

function.__name__ is the name under which the function has been initially defined, it has nothing to do with the name under which it is accessed. Actually, the whole point of function.__name__ is to correctly identify the function whatever name is used to access it. You definitly want to read this for more on what Python's "names" are.
One of the possible solutions here is replace the static definition of condition with a closure:
class Filter(object):
def __init__(self, column=['poi_id', 'tp.event'], access=['con', 'don']):
self.column = column
self.access = access
self.accessor_column = dict(zip(self.access, self.column))
self.set_conditions()
def set_conditions(self):
mapping = list(zip(self.column, self.access))
for column_name, accessor_name in mapping:
def accessor(name):
print("in {}.accessor '{}' for column '{}'".format(self, accessor_name, column_name))
return name
# this is now technically useless but helps with inspection
accessor.__name__ = accessor_name
setattr(self, accessor_name, accessor)
As a side note (totally unrelated but I thought you may want to know this), using mutable objects as function arguments defaults is one of the most infamous Python gotchas and may yield totally unexpected results, ie:
>>> f1 = Filter()
>>> f2 = Filter()
>>> f1.column
['poi_id', 'tp.event']
>>> f2.column
['poi_id', 'tp.event']
>>> f2.column.append("WTF")
>>> f1.column
['poi_id', 'tp.event', 'WTF']
EDIT:
thank you for your answer, but it doesn't touch my issue here. My problem is not how functions are named or defined, my problem it that when i use setattr() and i set an attribute and i give it a function as it's value, i can access the value and perform what the value does, but since it's a function, why doesn't it return it's name as the function name
Because as I already explained above, the function's __name__ attribute and the name of the Filter instance attribute(s) refering to this function are totally unrelated, and the function knows absolutely nothing about the names of variables or attributes that reference it, as explained in the reference article I linked to.
Actually the fact that the object you're passing to setattr is a function is totally irrelevant, from the object's POV it's just a name and an object, period. And actually the fact you're binding this object (function or just whatever object) to an instance attribute (whether directly or using setattr(), it works just the same) instead of a plain variable is also totally irrelevant - none of those operation will have any impact on the object that is bound (except for increasing it's ref counter but that's a CPython implementation detail - other implementations may implement garbage collection diffently).

May I suggest you this :
from types import SimpleNamespace
class Filter:
def __init__(self, column=['poi_id', 'tp.event'], access=['con', 'don']):
self.column = column
self.access = access
self.accessor_column = dict(zip(self.access, self.column))
self.set_conditions()
def set_conditions(self):
for i in self.access:
setattr(self, i, SimpleNamespace(name=i, func=lambda name: name))
f = Filter()
print(f.con.func('linux'))
>>> linux
print(f.con.name)
>>> con
[edited after bruno desthuilliers's comment.]

Related

TypeError: __init__() missing 1 required positional argument: 'lists'

I created a class, something like below -
class child:
def __init__(self,lists):
self.myList = lists
def find_mean(self):
mean=np.mean(self.myList)
return mean
and when I create an onject something like below -
obj=child()
it gives the error -
TypeError: __init__() missing 1 required positional argument: 'lists'
if I create object like below then it works well -
obj=child([44,22,55)
or If I create the class like below -
class child:
def find_mean(self,myList):
mean=np.mean(myList)
return mean
and then I create the object like below -
obj=child()
then also it works well, however I need to make it in the way I explained in the very begining. Can you please help me understand this context?
In the first example, the __init__ method expects two parameters:
self is automatically filled in by Python.
lists is a parameter which you must give it. It will try to assign this value to a new variable called self.myList, and it won't know what value it is supposed to use if you don't give it one.
In the second example, you have not written an __init__ method. This means that Python creates its own default __init__ function which will not require any parameters. However, the find_mean method now requires you to give it a parameter instead.
When you say you want to create it in the way you explained at the beginning, this is actually impossible: the class requires a value, and you are not giving it one.
Therefore, it is hard for me to tell what you really want to do. However, one option might be that you want to create the class earlier, and then add a list to it later on. In this case, the code would look like this:
import numpy as np
class Child:
def __init__(self, lists=None):
self.myList = lists
def find_mean(self):
if self.myList is None:
return np.nan
mean = np.mean(self.myList)
return mean
This code allows you to create the object earlier, and add a list to it later. If you try to call find_mean without giving it a list, it will simply return nan:
child = Child()
print(child.find_mean()) # Returns `nan`
child.myList = [1, 2, 3]
print(child.find_mean()) # Returns `2`
the code you have at the top of your question defines a class called child, which has one attribute, lists, which is assigned at the time of instance creation in the __init__ method. This means that you must supply a list when creating an instance of child.
class child:
def __init__(self, lists):
self.myList = lists
def find_mean(self):
mean=np.mean(self.myList)
return mean
# works because a list is provided
obj = child([44,22,55])
# does not work because no list is given
obj = child() # TypeError
If you create the class like in your second example, __init__ is no longer being explicitly specified, and as such, the object has no attributes that must be assigned at instance creation:
class child:
def find_mean(self, myList):
mean=np.mean(myList)
return mean
# does not work because `child()` does not take any arguments
obj = child([44,22,55]) # TypeError
# works because no list is needed
obj = child()
The only way to both have the myList attribute, and not need to specify it at creation would be to assign a default value to it:
class child:
def find_mean(self,myList=None):
mean=np.mean(myList)
return mean
# now this will work
obj = child()
# as will this
obj = child([24, 35, 27])

Class instance attributes derived from other instance attributes

I apologise if the title is cryptic, I could not think of a way to describe my problem in a sentence. I am building some code in python2.7 that I describe below.
Minimal working example
My code has a Parameter class that implements attributes such as name and value, which looks something like this.
class Parameter(object):
def __init__(self, name, value=None, error=None, dist=None, prior=None):
self.name = name
self._value = value # given value for parameter, this is going to be changed very often in an MCMC sampler
self.error = error # initial estimate of error for the parameter, will only be set once
self._dist = dist # a distribution for the parameter, will only be set once
self.prior = prior
#property
def value(self):
return self._value
#property
def dist(self):
return self._dist
The class also has several properties that returns the mean, median, etc. of Parameter.dist if a distribution is given.
I have another class, e.g. ParameterSample, that creates a population of different Parameter objects. Some of these Parameter objects have their attributes (e.g. value, error) set using the Parameter.set_parameter() function, but some other Parameter objects are not explicitly set, but their value and dist attributes depend on some of the other Parameter objects that are set:
class ParameterSample(object):
def __init__(self):
varied_parameters = ('a', 'b') # parameter names whose `value` attribute is varied
derived_parameters = ('c',) # parameter names whose `value` attribute is varied, but depends on `a.value` and `b.value`
parameter_names = varied_parameters + derived_parameters
# create `Parameter` objects for each parameter name
for name in parameter_names:
setattr(self, name, Parameter(name))
def set_parameter(self, name, **kwargs):
for key, val in kwargs.items():
if key == 'value':
key = '_'.join(['', key]) # add underscore to set `Parameter._value`
setattr(getattr(self, name), key, val) # basically does e.g. `self.a.value = 1`
I can now create a ParameterSample and use them like this:
parobj = ParameterSample()
parobj.set_parameter('a', value=1, error=0.1)
parobj.set_parameter('b', value=2, error=0.5)
parobj.a.value
>>> 1
parobj.b.error
>>> 0.5
parobj.set_parameter('b', value=3)
parobj.b.value
>>> 3
parobj.b.error
>>> 0.5
What I want
What I ultimately want, is to use Parameter.c the same way. For example:
parobj.c.value
>>> 4 # returns parobj.a.value + parobj.b.value
parobj.c.dist
>>> None # returns a.dist + b.dist, but since they are not currently set it is None
c therefore needs to be a Parameter object with all the same attributes as a and b, but where its value and dist are updated according to the current attributes of a and b.
However, I should also mention that I want to be able to set the allowed prior ranges for parameter c, e.g. parobj.set_parameter('c', prior=(0,10)) before making any calls to its value -- so c needs to be an already defined Parameter object upon the creation of the ParameterSample object.
How would I implement this into my ParameterSample class?
What I've tried
I have tried looking into making my own decorators, but I am not sure if that is the way to go since I don't fully understand how I would use those.
I've also considered adding a #property to c that creates a new Parameter object every time it is called, but I feel like that is not the way to go since it may slow down the code.
I should also note that the ParameterSample class above is going to be inherited in a different class, so whatever the solution is it should be able to be used in this setting:
class Companion(ParameterSample)
def __init__(self, name):
self.name = name
super(Companion, self).__init__()
comp = Companion(name='Earth')
comp.set_parameter('a', value=1)
comp.set_parameter('b', value=3)
comp.c.value
>>> 4
I could not get this to work in Python 2 - the setattr calls never seemed to propagate the attributes to the child classes (Companion would have no c attribute).
I was more successful with Python 3 though. Since you have two parameter types (varied vs. derived), it makes sense IMO to have two classes to implement the behavior, instead of treating them all as one.
I added a DerivedParameter class, inheriting from Parameter that takes a dependents argument (along with its parent class' args/kwargs), but redefining value and dist to give dependent behavior:
class DerivedParameter(Parameter):
def __init__(self, name, dependents, **kwargs):
self._dependents = dependents
super().__init__(name, **kwargs)
#property
def value(self):
try:
return sum(x._value for x in self._dependents if x is not None)
except TypeError:
return None
#property
def dist(self):
try:
return sum(x._dist for x in self._dependents if x is not None)
except TypeError:
return None
Then I adjusted how your parameter objects are added:
class ParameterSample:
def __init__(self):
# Store as instance attributes to reference later
self.varied_params = ('a', 'b') # parameter names whose `value` attribute is varied
self.derived_params = ('c',) # parameter names whose `value` attribute is varied, but depends on `a.value` and `b.value`
# No more combined names
# create `Parameter` objects for each varied parameter name
for name in self.varied_params:
setattr(self, name, Parameter(name))
# Create `DerivedParameter` objects for each derived parameter
# Derived parameters depend on all `Parameter` objects. It wasn't
# clear if this was the desired behavior though.
params = [v for _, v in self.__dict__.items() if isinstance(v, Parameter)]
for name in self.derived_params:
setattr(self, name, DerivedParameter(name, params))
def set_parameter(self, name, **kwargs):
for key, val in kwargs.items():
if key == 'value':
key = '_'.join(['', key]) # add underscore to set `Parameter._value`
setattr(getattr(self, name), key, val) # basically does e.g. `self.a.value = 1`
From this, I could then replicate your given example desired behavior:
>>> comp = Companion(name='Earth')
>>> comp.set_parameter('a', value=1)
>>> comp.set_parameter('b', value=3)
>>> print(comp.c.value)
>>> print(comp.c.dist)
4
None
>>> comp.set_parameter('c', prior=(0,10))
>>> print(comp.c.prior)
(0, 10)
As I pointed out in the comments, the design above ends up causing all derived parameters to use all varied parameters as their dependents - effectively making c and a potential d identical. You should be able to fix this fairly easily with some parameters/conditions.
Overall, I would have to agree with #Error - Syntactical Remorse though. This is a pretty complicated way to go about designing classes and would make maintenance confusing at best. I would strongly encourage you to reconsider your design and try to find an adaptable general solution that doesn't involve dynamic creation of attributes like this.

Get array name in function it is passed to [duplicate]

I already read How to get a function name as a string?.
How can I do the same for a variable? As opposed to functions, Python variables do not have the __name__ attribute.
In other words, if I have a variable such as:
foo = dict()
foo['bar'] = 2
I am looking for a function/attribute, e.g. retrieve_name() in order to create a DataFrame in Pandas from this list, where the column names are given by the names of the actual dictionaries:
# List of dictionaries for my DataFrame
list_of_dicts = [n_jobs, users, queues, priorities]
columns = [retrieve_name(d) for d in list_of_dicts]
With Python 3.8 one can simply use f-string debugging feature:
>>> foo = dict()
>>> f'{foo=}'.split('=')[0]
'foo'
One drawback of this method is that in order to get 'foo' printed you have to add f'{foo=}' yourself. In other words, you already have to know the name of the variable. In other words, the above code snippet is exactly the same as just
>>> 'foo'
Even if variable values don't point back to the name, you have access to the list of every assigned variable and its value, so I'm astounded that only one person suggested looping through there to look for your var name.
Someone mentioned on that answer that you might have to walk the stack and check everyone's locals and globals to find foo, but if foo is assigned in the scope where you're calling this retrieve_name function, you can use inspect's current frame to get you all of those local variables.
My explanation might be a little bit too wordy (maybe I should've used a "foo" less words), but here's how it would look in code (Note that if there is more than one variable assigned to the same value, you will get both of those variable names):
import inspect
x, y, z = 1, 2, 3
def retrieve_name(var):
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
return [var_name for var_name, var_val in callers_local_vars if var_val is var]
print(retrieve_name(y))
If you're calling this function from another function, something like:
def foo(bar):
return retrieve_name(bar)
foo(baz)
And you want the baz instead of bar, you'll just need to go back a scope further. This can be done by adding an extra .f_back in the caller_local_vars initialization.
See an example here: ideone
The only objects in Python that have canonical names are modules, functions, and classes, and of course there is no guarantee that this canonical name has any meaning in any namespace after the function or class has been defined or the module imported. These names can also be modified after the objects are created so they may not always be particularly trustworthy.
What you want to do is not possible without recursively walking the tree of named objects; a name is a one-way reference to an object. A common or garden-variety Python object contains no references to its names. Imagine if every integer, every dict, every list, every Boolean needed to maintain a list of strings that represented names that referred to it! It would be an implementation nightmare, with little benefit to the programmer.
TL;DR
Use the Wrapper helper from python-varname:
from varname.helpers import Wrapper
foo = Wrapper(dict())
# foo.name == 'foo'
# foo.value == {}
foo.value['bar'] = 2
For list comprehension part, you can do:
n_jobs = Wrapper(<original_value>)
users = Wrapper(<original_value>)
queues = Wrapper(<original_value>)
priorities = Wrapper(<original_value>)
list_of_dicts = [n_jobs, users, queues, priorities]
columns = [d.name for d in list_of_dicts]
# ['n_jobs', 'users', 'queues', 'priorities']
# REMEMBER that you have to access the <original_value> by d.value
I am the author of the python-varname package. Please let me know if you have any questions or you can submit issues on Github.
The long answer
Is it even possible?
Yes and No.
We are retrieving the variable names at runtime, so we need a function to be called to enable us to access the previous frames to retrieve the variable names. That's why we need a Wrapper there. In that function, at runtime, we are parsing the source code/AST nodes in the previous frames to get the exact variable name.
However, the source code/AST nodes in the previous frames are not always available, or they could be modified by other environments (e.g: pytest's assert statement). One simple example is that the codes run via exec(). Even though we are still able to retrieve some information from the bytecode, it needs too much effort and it is also error-prone.
How to do it?
First of all, we need to identify which frame the variable is given. It's not always simply the direct previous frame. For example, we may have another wrapper for the function:
from varname import varname
def func():
return varname()
def wrapped():
return func()
x = wrapped()
In the above example, we have to skip the frame inside wrapped to get to the right frame x = wrapped() so that we are able to locate x. The arguments frame and ignore of varname allow us to skip some of these intermediate frames. See more details in the README file and the API docs of the package.
Then we need to parse the AST node to locate where the variable is assigned value (function call) to. It's not always just a simple assignment. Sometimes there could be complex AST nodes, for example, x = [wrapped()]. We need to identify the correct assignment by traversing the AST tree.
How reliable is it?
Once we identify the assignment node, it is reliable.
varname is all depending on executing package to look for the node. The node executing detects is ensured to be the correct one (see also this).
It partially works with environments where other AST magics apply, including pytest, ipython, macropy, birdseye, reticulate with R, etc. Neither executing nor varname is 100% working with those environments.
Do we need a package to do it?
Well, yes and no, again.
If your scenario is simple, the code provided by #juan Isaza or #scohe001 probably is enough for you to work with the case where a variable is defined at the direct previous frame and the AST node is a simple assignment. You just need to go one frame back and retrieve the information there.
However, if the scenario becomes complicated, or we need to adopt different application scenarios, you probably need a package like python-varname, to handle them. These scenarios may include to:
present more friendly messages when the source code is not available or AST nodes are not accessible
skip intermediate frames (allows the function to be wrapped or called in other intermediate frames)
automatically ignores calls from built-in functions or libraries. For example: x = str(func())
retrieve multiple variable names on the left-hand side of the assignment
etc.
How about the f-string?
Like the answer provided by #Aivar Paalberg. It's definitely fast and reliable. However, it's not at runtime, meaning that you have to know it's foo before you print the name out. But with varname, you don't have to know that variable is coming:
from varname import varname
def func():
return varname()
# In external uses
x = func() # 'x'
y = func() # 'y'
Finally
python-varname is not only able to detect the variable name from an assignment, but also:
Retrieve variable names directly, using nameof
Detect next immediate attribute name, using will
Fetch argument names/sources passed to a function using argname
Read more from its documentation.
However, the final word I want to say is that, try to avoid using it whenever you can.
Because you can't make sure that the client code will run in an environment where the source node is available or AST node is accessible. And of course, it costs resources to parse the source code, identify the environment, retrieve the AST nodes and evaluate them when needed.
On python3, this function will get the outer most name in the stack:
import inspect
def retrieve_name(var):
"""
Gets the name of var. Does it from the out most frame inner-wards.
:param var: variable to get name from.
:return: string
"""
for fi in reversed(inspect.stack()):
names = [var_name for var_name, var_val in fi.frame.f_locals.items() if var_val is var]
if len(names) > 0:
return names[0]
It is useful anywhere on the code. Traverses the reversed stack looking for the first match.
I don't believe this is possible. Consider the following example:
>>> a = []
>>> b = a
>>> id(a)
140031712435664
>>> id(b)
140031712435664
The a and b point to the same object, but the object can't know what variables point to it.
def name(**variables):
return [x for x in variables]
It's used like this:
name(variable=variable)
>> my_var = 5
>> my_var_name = [ k for k,v in locals().items() if v == my_var][0]
>> my_var_name
'my_var'
In case you get an error if myvar points to another variable, try this (suggested by #mherzog)-
>> my_var = 5
>> my_var_name = [ k for k,v in locals().items() if v is my_var][0]
>> my_var_name
'my_var'
locals() - Return a dictionary containing the current scope's local variables.
by iterating through this dictionary we can check the key which has a value equal to the defined variable, just extracting the key will give us the text of variable in string format.
from (after a bit changes)
https://www.tutorialspoint.com/How-to-get-a-variable-name-as-a-string-in-Python
I wrote the package sorcery to do this kind of magic robustly. You can write:
from sorcery import dict_of
columns = dict_of(n_jobs, users, queues, priorities)
and pass that to the dataframe constructor. It's equivalent to:
columns = dict(n_jobs=n_jobs, users=users, queues=queues, priorities=priorities)
Here's one approach. I wouldn't recommend this for anything important, because it'll be quite brittle. But it can be done.
Create a function that uses the inspect module to find the source code that called it. Then you can parse the source code to identify the variable names that you want to retrieve. For example, here's a function called autodict that takes a list of variables and returns a dictionary mapping variable names to their values. E.g.:
x = 'foo'
y = 'bar'
d = autodict(x, y)
print d
Would give:
{'x': 'foo', 'y': 'bar'}
Inspecting the source code itself is better than searching through the locals() or globals() because the latter approach doesn't tell you which of the variables are the ones you want.
At any rate, here's the code:
def autodict(*args):
get_rid_of = ['autodict(', ',', ')', '\n']
calling_code = inspect.getouterframes(inspect.currentframe())[1][4][0]
calling_code = calling_code[calling_code.index('autodict'):]
for garbage in get_rid_of:
calling_code = calling_code.replace(garbage, '')
var_names, var_values = calling_code.split(), args
dyn_dict = {var_name: var_value for var_name, var_value in
zip(var_names, var_values)}
return dyn_dict
The action happens in the line with inspect.getouterframes, which returns the string within the code that called autodict.
The obvious downside to this sort of magic is that it makes assumptions about how the source code is structured. And of course, it won't work at all if it's run inside the interpreter.
This function will print variable name with its value:
import inspect
def print_this(var):
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
print(str([k for k, v in callers_local_vars if v is var][0])+': '+str(var))
***Input & Function call:***
my_var = 10
print_this(my_var)
***Output**:*
my_var: 10
>>> locals()['foo']
{}
>>> globals()['foo']
{}
If you wanted to write your own function, it could be done such that you could check for a variable defined in locals then check globals. If nothing is found you could compare on id() to see if the variable points to the same location in memory.
If your variable is in a class, you could use className.dict.keys() or vars(self) to see if your variable has been defined.
I have a method, and while not the most efficient...it works! (and it doesn't involve any fancy modules).
Basically it compares your Variable's ID to globals() Variables' IDs, then returns the match's name.
def getVariableName(variable, globalVariables=globals().copy()):
""" Get Variable Name as String by comparing its ID to globals() Variables' IDs
args:
variable(var): Variable to find name for (Obviously this variable has to exist)
kwargs:
globalVariables(dict): Copy of the globals() dict (Adding to Kwargs allows this function to work properly when imported from another .py)
"""
for globalVariable in globalVariables:
if id(variable) == id(globalVariables[globalVariable]): # If our Variable's ID matches this Global Variable's ID...
return globalVariable # Return its name from the Globals() dict
In Python, the def and class keywords will bind a specific name to the object they define (function or class). Similarly, modules are given a name by virtue of being called something specific in the filesystem. In all three cases, there's an obvious way to assign a "canonical" name to the object in question.
However, for other kinds of objects, such a canonical name may simply not exist. For example, consider the elements of a list. The elements in the list are not individually named, and it is entirely possible that the only way to refer to them in a program is by using list indices on the containing list. If such a list of objects was passed into your function, you could not possibly assign meaningful identifiers to the values.
Python doesn't save the name on the left hand side of an assignment into the assigned object because:
It would require figuring out which name was "canonical" among multiple conflicting objects,
It would make no sense for objects which are never assigned to an explicit variable name,
It would be extremely inefficient,
Literally no other language in existence does that.
So, for example, functions defined using lambda will always have the "name" <lambda>, rather than a specific function name.
The best approach would be simply to ask the caller to pass in an (optional) list of names. If typing the '...','...' is too cumbersome, you could accept e.g. a single string containing a comma-separated list of names (like namedtuple does).
I think it's so difficult to do this in Python because of the simple fact that you never will not know the name of the variable you're using. So, in his example, you could do:
Instead of:
list_of_dicts = [n_jobs, users, queues, priorities]
dict_of_dicts = {"n_jobs" : n_jobs, "users" : users, "queues" : queues, "priorities" : priorities}
Many of the answers return just one variable name. But that won't work well if more than one variable have the same value. Here's a variation of Amr Sharaki's answer which returns multiple results if more variables have the same value.
def getVariableNames(variable):
results = []
globalVariables=globals().copy()
for globalVariable in globalVariables:
if id(variable) == id(globalVariables[globalVariable]):
results.append(globalVariable)
return results
a = 1
b = 1
getVariableNames(a)
# ['a', 'b']
just another way to do this based on the content of input variable:
(it returns the name of the first variable that matches to the input variable, otherwise None. One can modify it to get all variable names which are having the same content as input variable)
def retrieve_name(x, Vars=vars()):
for k in Vars:
if isinstance(x, type(Vars[k])):
if x is Vars[k]:
return k
return None
If the goal is to help you keep track of your variables, you can write a simple function that labels the variable and returns its value and type. For example, suppose i_f=3.01 and you round it to an integer called i_n to use in a code, and then need a string i_s that will go into a report.
def whatis(string, x):
print(string+' value=',repr(x),type(x))
return string+' value='+repr(x)+repr(type(x))
i_f=3.01
i_n=int(i_f)
i_s=str(i_n)
i_l=[i_f, i_n, i_s]
i_u=(i_f, i_n, i_s)
## make report that identifies all types
report='\n'+20*'#'+'\nThis is the report:\n'
report+= whatis('i_f ',i_f)+'\n'
report+=whatis('i_n ',i_n)+'\n'
report+=whatis('i_s ',i_s)+'\n'
report+=whatis('i_l ',i_l)+'\n'
report+=whatis('i_u ',i_u)+'\n'
print(report)
This prints to the window at each call for debugging purposes and also yields a string for the written report. The only downside is that you have to type the variable twice each time you call the function.
I am a Python newbie and found this very useful way to log my efforts as I program and try to cope with all the objects in Python. One flaw is that whatis() fails if it calls a function described outside the procedure where it is used. For example, int(i_f) was a valid function call only because the int function is known to Python. You could call whatis() using int(i_f**2), but if for some strange reason you choose to define a function called int_squared it must be declared inside the procedure where whatis() is used.
Maybe this could be useful:
def Retriever(bar):
return (list(globals().keys()))[list(map(lambda x: id(x), list(globals().values()))).index(id(bar))]
The function goes through the list of IDs of values from the global scope (the namespace could be edited), finds the index of the wanted/required var or function based on its ID, and then returns the name from the list of global names based on the acquired index.
Whenever I have to do it, mostly while communicating json schema and constants with the frontend I define a class as follows
class Param:
def __init__(self, name, value):
self.name = name
self.value = value
Then define the variable with name and value.
frame_folder_count = Param({'name':'frame_folder_count', 'value':10})
Now you can access the name and value using the object.
>>> frame_folder_count.name
'frame_folder_count'
>>> def varname(v, scope=None):
d = globals() if not scope else vars(scope); return [k for k in d if d[k] == v]
...
>>> d1 = {'a': 'ape'}; d2 = {'b': 'bear'}; d3 = {'c': 'cat'}
>>> ld = [d1, d2, d3]
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3']]
>>> d5 = d3
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3', 'd5']]
>>> def varname(v, scope=None):
d = globals() if not scope else vars(scope); return [k for k in d if d[k] is v]
...
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3', 'd5']]
As you see and is noted here, there can be multiple variables with the same value or even address, so using a wrapper to keep the names with the data is best.
Following method will not return the name of variable but using this method you can create data frame easily if variable is available in global scope.
class CustomDict(dict):
def __add__(self, other):
return CustomDict({**self, **other})
class GlobalBase(type):
def __getattr__(cls, key):
return CustomDict({key: globals()[key]})
def __getitem__(cls, keys):
return CustomDict({key: globals()[key] for key in keys})
class G(metaclass=GlobalBase):
pass
x, y, z = 0, 1, 2
print('method 1:', G['x', 'y', 'z']) # Outcome: method 1: {'x': 0, 'y': 1, 'z': 2}
print('method 2:', G.x + G.y + G.z) # Outcome: method 2: {'x': 0, 'y': 1, 'z': 2}
A = [0, 1]
B = [1, 2]
pd.DataFrame(G.A + G.B) # It will return a data frame with A and B columns
Some of the previous cases would fail if there are two variables with the same value. So it is convenient to alert it:
Defining function:
# Variable to string of variable name
def var_name(variable,i=0):
results = []
for name in globals():
if eval(name) == variable:
results.append(name)
if len(results) > 1:
print('Warning:' )
print(' var_name() has found',len(results), 'possible outcomes.')
print(' Please choose the suitable parameter "i". Where "i" is the index')
print(' that matches your choice from the list below.')
print(' ',results) ; print('')
return results[i]
Use:
var_1 = 10
var_name(var_1) # Output will be "var_1"
If you have 2 variables with the same value like var_1 = 8 and var_2 = 8, then a warning will appear.
var_1 = 8
var_2 = 8
var_name(var_2) # Output will be "var_1" too but Warning will appear
You can get your variable as kwargs and return it as string:
var=2
def getVarName(**kwargs):
return list(kwargs.keys())[0]
print (getVarName(var = var))
Note: variable name must be equal to itself.
I try to get name from inspect locals, but it cann't process var likes a[1], b.val.
After it, I got a new idea --- get var name from the code, and I try it succ!
code like below:
#direct get from called function code
def retrieve_name_ex(var):
stacks = inspect.stack()
try:
func = stacks[0].function
code = stacks[1].code_context[0]
s = code.index(func)
s = code.index("(", s + len(func)) + 1
e = code.index(")", s)
return code[s:e].strip()
except:
return ""
You can try the following to retrieve the name of a function you defined (does not work for built-in functions though):
import re
def retrieve_name(func):
return re.match("<function\s+(\w+)\s+at.*", str(func)).group(1)
def foo(x):
return x**2
print(retrieve_name(foo))
# foo
When finding the name of a variable from its value,
you may have several variables equal to the same value,
for example var1 = 'hello' and var2 = 'hello'.
My solution:
def find_var_name(val):
dict_list = []
global_dict = dict(globals())
for k, v in global_dict.items():
dict_list.append([k, v])
return [item[0] for item in dict_list if item[1] == val]
var1 = 'hello'
var2 = 'hello'
find_var_name('hello')
Outputs
['var1', 'var2']
Compressed version of iDilip's answer:
import inspect
def varname(x):
return [k for k,v in inspect.currentframe().f_back.f_locals.items() if v is x][0]
hi = 123
print(varname(hi))
It's totally possible to get the name of an instance variable, so long as it is the property of a class.
I got this from Effective Python by Brett Slatkin. Hope it helps someone:
The class must implement the get, set, and set_name dunder methods, which are part of the "Descriptor Protocol"
This worked when I ran it:
class FieldThatKnowsItsName():
def __init__(self):
self.name = None
self._value= None
self.owner = None
def __set_name__(self, owner, name):
self.name = name
self.owner = owner
self.owner.fields[self.name] = self
def __get__(self, instance, instance_type):
return self
def __set__(self, instance, value):
self = value
class SuperTable:
fields = {}
field_1=FieldThatKnowsItsName()
field_2=FieldThatKnowsItsName()
table = SuperTable()
print(table.field_1.name)
print(table.field_2.name)
You can then add methods and or extend your datatype as you like.
As a bonus, the set_name(self, owner, name) dunder also passes the parent instance, so the Field class instance can register itself with the parent.
I got this from Effective Python by Brett Slatkin. It took a while to figure out how to implement.
How can I do the same for a variable? As opposed to functions, Python variables do not have the __name__ attribute.
The problem comes up because you are confused about terminology, semantics or both.
"variables" don't belong in the same category as "functions". A "variable" is not a thing that takes up space in memory while the code is running. It is just a name that exists in your source code - so that when you're writing the code, you can explain which thing you're talking about. Python uses names in the source code to refer to (i.e., give a name to) values. (In many languages, a variable is more like a name for a specific location in memory where the value will be stored. But Python's names actually name the thing in question.)
In Python, a function is a value. (In some languages, this is not the case; although there are bytes of memory used to represent the actual executable code, it isn't a discrete chunk of memory that your program logic gets to interact with directly.) In Python, every value is an object, meaning that you can assign names to it freely, pass it as an argument, return it from a function, etc. (In many languages, this is not the case.) Objects in Python have attributes, which are the things you access using the . syntax. Functions in Python have a __name__ attribute, which is assigned when the function is created. Specifically, when a def statement is executed (in most languages, creation of a function works quite differently), the name that appears after def is used as a value for the __name__ attribute, and also, independently, as a variable name that will get the function object assigned to it.
But most objects don't have an attribute like that.
In other words, if I have a variable such as:
That's the thing: you don't "have" the variable in the sense that you're thinking of. You have the object that is named by that variable. Anything else depends on the information incidentally being stored in some other object - such as the locals() of the enclosing function. But it would be better to store the information yourself. Instead of relying on a variable name to carry information for you, explicitly build the mapping between the string name you want to use for the object, and the object itself.

Why does assigning to self not work, and how to work around the issue?

I have a class (list of dicts) and I want it to sort itself:
class Table(list):
…
def sort (self, in_col_name):
self = Table(sorted(self, key=lambda x: x[in_col_name]))
but it doesn't work at all. Why? How to avoid it? Except for sorting it externally, like:
new_table = Table(sorted(old_table, key=lambda x: x['col_name'])
Isn't it possible to manipulate the object itself? It's more meaningful to have:
class Table(list):
pass
than:
class Table(object):
l = []
…
def sort (self, in_col_name):
self.l = sorted(self.l, key=lambda x: x[in_col_name])
which, I think, works.
And in general, isn't there any way in Python which an object is able to change itself (not only an instance variable)?
You can't re-assign to self from within a method and expect it to change external references to the object.
self is just an argument that is passed to your function. It's a name that points to the instance the method was called on. "Assigning to self" is equivalent to:
def fn(a):
a = 2
a = 1
fn(a)
# a is still equal to 1
Assigning to self changes what the self name points to (from one Table instance to a new Table instance here). But that's it. It just changes the name (in the scope of your method), and does affect not the underlying object, nor other names (references) that point to it.
Just sort in place using list.sort:
def sort(self, in_col_name):
super(Table, self).sort(key=lambda x: x[in_col_name])
Python is pass by value, always. This means that assigning to a parameter will never have an effect on the outside of the function. self is just the name you chose for one of the parameters.
I was intrigued by this question because I had never thought about this. I looked for the list.sort code, to see how it's done there, but apparently it's in C. I think I see where you're getting at; what if there is no super method to invoke? Then you can do something like this:
class Table(list):
def pop_n(self, n):
for _ in range(n):
self.pop()
>>> a = Table(range(10))
>>> a.pop_n(3)
>>> print a
[0, 1, 2, 3, 4, 5, 6]
You can call self's methods, do index assignments to self and whatever else is implemented in its class (or that you implement yourself).

Python - Call an object from a list of objects

I have a class, and I would like to be able to create multiple objects of that class and place them in an array. I did it like so:
rooms = []
rooms.append(Object1())
...
rooms.append(Object4())
I then have a dict of functions, and I would like to pass the object to the function. However, I'm encountering some problems..For example, I have a dict:
dict = {'look': CallLook(rooms[i])}
I'm able to pass it into the function, however; in the function if I try to call an objects method it gives me problems
def CallLook(current_room)
current_room.examine()
I'm sure that there has to be a better way to do what I'm trying to do, but I'm new to Python and I haven't seen a clean example on how to do this. Anyone have a good way to implement a list of objects to be passed into functions? All of the objects contain the examine method, but they are objects of different classes. (I'm sorry I didn't say so earlier)
The specific error states: TypeError: 'NoneType' object is not callable
Anyone have a good way to implement a list of objects to be passed into functions? All of the objects contain the examine method, but they are objects of different classes. (I'm sorry I didn't say so earlier)
This is Python's plain duck-typing.
class Room:
def __init__(self, name):
self.name = name
def examine(self):
return "This %s looks clean!" % self.name
class Furniture:
def __init__(self, name):
self.name = name
def examine(self):
return "This %s looks comfortable..." % self.name
def examination(l):
for item in l:
print item.examine()
list_of_objects = [ Room("Living Room"), Furniture("Couch"),
Room("Restrooms"), Furniture("Bed") ]
examination(list_of_objects)
Prints:
This Living Room looks clean!
This Couch looks comfortable...
This Restrooms looks clean!
This Bed looks comfortable...
As for your specific problem: probably you have forgotten to return a value from examine()? (Please post the full error message (including full backtrace).)
I then have a dict of functions, and I would like to pass the object to the function. However, I'm encountering some problems..For example, I have a dict:
my_dict = {'look': CallLook(rooms[i])} # this is no dict of functions
The dict you have created may evaluate to {'look': None} (assuming your examine() doesn't return a value.) Which could explain the error you've observed.
If you wanted a dict of functions you needed to put in a callable, not an actual function call, e.g. like this:
my_dict = {'look': CallLook} # this is a dict of functions
if you want to bind the 'look' to a specific room you could redefine CallLook:
def CallLook(current_room)
return current_room.examine # return the bound examine
my_dict = {'look': CallLook(room[i])} # this is also a dict of functions
Another issue with your code is that you are shadowing the built-in dict() method by naming your local dictionary dict. You shouldn't do this. This yields nasty errors.
Assuming you don't have basic problems (like syntax errors because the code you have pasted is not valid Python), this example shows you how to do what you want:
>>> class Foo():
... def hello(self):
... return 'hello'
...
>>> r = [Foo(),Foo(),Foo()]
>>> def call_method(obj):
... return obj.hello()
...
>>> call_method(r[1])
'hello'
Assuming you have a class Room the usual way to create a list of instances would be using a list comprehension like this
rooms = [Room() for i in range(num_rooms)]
I think there are some things you may not be getting about this:
dict = {'look': CallLook(rooms[i])}
This creates a dict with just one entry: a key 'look', and a value which is the result of evaluating CallLook(rooms[i]) right at the point of that statement. It also then uses the name dict to store this object, so you can no longer use dict as a constructor in that context.
Now, the error you are getting tells us that rooms[i] is None at that point in the programme.
You don't need CallLook (which is also named non-standardly) - you can just use the expression rooms[i].examine(), or if you want to evaluate the call later rooms[i].examine.
You probably don't need the dict at all.
That is not a must, but in some cases, using hasattr() is good... getattr() is another way to get an attribute off an object...
So:
rooms = [Obj1(),Obj2(),Obj3()]
if hasattr(rooms[i], 'examine'):#First check if our object has selected function or attribute...
getattr(rooms[i], 'examine') #that will just evaluate the function do not call it, and equals to Obj1().examine
getattr(rooms[i], 'examine')() # By adding () to the end of getattr function, we evalute and then call the function...
You may also pass parameters to examine function like:
getattr(rooms[i], 'examine')(param1, param2)
I'm not sure of your requirement, but you can use dict to store multiple object of a class.
May be this will help,
>>> class c1():
... print "hi"
...
hi
>>> c = c1()
>>> c
<__main__.c1 instance at 0x032165F8>
>>> d ={}
>>> for i in range (10):
... d[i] = c1()
...
>>> d[0]
<__main__.c1 instance at 0x032166E8>
>>> d[1]
<__main__.c1 instance at 0x032164B8>
>>>
It will create a object of c1 class and store it in dict. Obviously, in this case you can use list instead of dict.

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