Assign results of function call in one line in python - python

How can I assign the results of a function call to multiple variables when the results are stored by name (not index-able), in python.
For example (tested in Python 3),
import random
# foo, as defined somewhere else where we can't or don't want to change it
def foo():
t = random.randint(1,100)
# put in a dummy class instead of just "return t,t+1"
# because otherwise we could subscript or just A,B = foo()
class Cat(object):
x = t
y = t + 1
return Cat()
# METHOD 1
# clearly wrong; A should be 1 more than B; they point to fields of different objects
A,B = foo().x, foo().y
print(A,B)
# METHOD 2
# correct, but requires two lines and an implicit variable
t = foo()
A,B = t.x, t.y
del t # don't really want t lying around
print(A,B)
# METHOD 3
# correct and one line, but an obfuscated mess
A,B = [ (t.x,t.y) for t in (foo(),) ][0]
print(A,B)
print(t) # this will raise an exception, but unless you know your python cold it might not be obvious before running
# METHOD 4
# Conforms to the suggestions in the links below without modifying the initial function foo or class Cat.
# But while all subsequent calls are pretty, but we have to use an otherwise meaningless shell function
def get_foo():
t = foo()
return t.x, t.y
A,B = get_foo()
What we don't want to do
If the results were indexable ( Cat extended tuple/list, we had used a namedtuple, etc.), we could simply write A,B = foo() as indicated in the comment above the Cat class. That's what's recommended here , for example.
Let's assume we have a good reason not to allow that. Maybe we like the clarity of assigning from the variable names (if they're more meaningful than x and y) or maybe the object is not primarily a container. Maybe the fields are properties, so access actually involves a method call. We don't have to assume any of those to answer this question though; the Cat class can be taken at face value.
This question already deals with how to design functions/classes the best way possible; if the function's expected return value are already well defined and does not involve tuple-like access, what is the best way to accept multiple values when returning?

I would strongly recommend either using multiple statements, or just keeping the result object without unpacking its attributes. That said, you can use operator.attrgetter for this:
from operator import attrgetter
a, b, c = attrgetter('a', 'b', 'c')(foo())

Related

Why do function attributes (setattr ones) only become available after assigning it as a property to a class and instantiating it?

I apologize if I'm butchering the terminology. I'm trying to understand the code in this example on how to chain a custom function onto a PySpark dataframe. I'd really want to understand exactly what it's doing, and if it is not awful practice before I implement anything.
From the way I'm understanding the code, it:
defines a function g with sub-functions inside of it, that returns a copy of itself
assigns the sub-functions to g as attributes
assigns g as a property of the DataFrame class
I don't think at any step in the process do any of them become a method (when I do getattr, it always says "function")
When I run a (as best as I can do) simplified version of the code (below), it seems like only when I assign the function as a property to a class, and then instantiate at least one copy of the class, do the attributes on the function become available (even outside of the class). I want to understand what and why that is happening.
An answer [here(https://stackoverflow.com/a/17007966/19871699) indicates that this is a behavior, but doesn't really explain what/why it is. I've read this too but I'm having trouble seeing the connection to the code above.
I read here about the setattr part of the code. He doesn't mention exactly the use case above. this post has some use cases where people do it, but I'm not understanding how it directly applies to the above, unless I've missed something.
The confusing part is when the inner attributes become available.
class SampleClass():
def __init__(self):
pass
def my_custom_attribute(self):
def inner_function_one():
pass
setattr(my_custom_attribute,"inner_function",inner_function_one)
return my_custom_attribute
[x for x in dir(my_custom_attribute) if x[0] != "_"]
returns []
then when I do:
SampleClass.custom_attribute = property(my_custom_attribute)
[x for x in dir(my_custom_attribute) if x[0] != "_"]
it returns []
but when I do:
class_instance = SampleClass()
class_instance.custom_attribute
[x for x in dir(my_custom_attribute) if x[0] != "_"]
it returns ['inner_function']
In the code above though, if I do SampleClass.custom_attribute = my_custom_attribute instead of =property(...) the [x for x... code still returns [].
edit: I'm not intending to access the function itself outside of the class. I just don't understand the behavior, and don't like implementing something I don't understand.
So, setattr is not relevant here. This would all work exactly the same without it, say, by just doing my_custom_attribute.inner_function = inner_function_one etc. What is relevant is that the approach in the link you showed (which your example doesn't exactly make clear what the purpose is) relies on using a property, which is a descriptor. But the function won't get called unless you access the attribute corresponding to the property on an instance. This comes down to how property works. For any property, given a class Foo:
Foo.attribute_name = property(some_function)
Then some_function won't get called until you do Foo().attribute_name. That is the whole point of property.
But this whole solution is very confusingly engineered. It relies on the above behavior, and it sets attributes on the function object.
Note, if all you want to do is add some method to your DataFrame class, you don't need any of this. Consider the following example (using pandas for simplicity):
>>> import pandas as pd
>>> def foobar(self):
... print("in foobar with instance", self)
...
>>> pd.DataFrame.baz = foobar
>>> df = pd.DataFrame(dict(x=[1,2,3], y=['a','b','c']))
>>> df
x y
0 1 a
1 2 b
2 3 c
>>> df.baz()
in foobar with instance x y
0 1 a
1 2 b
2 3 c
That's it. You don't need all that rigamarole. Of course, if you wanted to add a nested accessor, df.custom.whatever, you would need something a bit more complicated. You could use the approach in the OP, but I would prefer something more explicit:
import pandas as pd
class AccessorDelegator:
def __init__(self, accessor_type):
self.accessor_type = accessor_type
def __get__(self, instance, cls=None):
return self.accessor_type(instance)
class CustomMethods:
def __init__(self, instance):
self.instance = instance
def foo(self):
# do something with self.instance as if this were your `self` on the dataframe being augmented
print(self.instance.value_counts())
pd.DataFrame.custom = AccessorDelegator(CustomMethods)
df = pd.DataFrame(dict(a=[1,2,3], b=['a','b','c']))
df.foo()
The above will print:
a b
1 a 1
2 b 1
3 c 1
Because when you call a function the attributes within that function aren't returned only the returned value is passed back.
In other words the additional attributes are only available on the returned function and not with 'g' itself.
Try moving setattr() outside of the function.

How to pass one same value as argument to two methods?

I have a simple class as:
connection has db connection
import pandas as pd
from animal import kettle
class cat:
def foo(connection):
a=pd.read_sql('select * from zoo',connection)
return1= kettle.boo1(a)
return2= kettle.boo2(a)
return return1,return2
Now I want to pass a to both boo1 and boo2 of kettle, am I passing it the correct way in above foo()?
I thought above way is correct and I tried this way , but is this correct way to pass?
animal.py:
class kettle:
def boo1(return1):
print(return1)
def boo2(return2):
print(return2)
sorry if this doesn't make any sense,
my intention is passing a to both boo1 and boo2 of kettle class
This looks like the correct approach to me: by assigning the return value of pd.read_sql('select * from zoo', connection) to a first and then passing a to kettle.boo1 and kettle.boo2 you ensure you only do the potentially time-consuming database IO only once.
One thing to keep in mind with this design pattern when you are passing objects such as lists/dicts/dataframes is the question of whether kettle.boo1 changes the value that is in a. If it does, kettle.boo2 will receive the modified version of a as an input, which can lead to unexpected behavior.
A very minimal example is the following:
>>> def foo(x):
... x[0] = 'b'
...
>>> x = ['a'] # define a list of length 1
>>> foo(x) # call a function that modifies the first element in x
>>> print(x) # the value in x has changed
['b']
There are (many) possible solutions for your problem, whatever that might be. I assume you just start out object oriented programming in Python, and get errors along the lines of
unbound method boo1() must be called with kettle instance as first argument
and probably want this solution:
Give your class methods an instance parameter:
def boo1(self, return1):
Instantiate the class kettle in cat.foo:
k = kettle()
Then use it like:
k.boo1(a)
Same for the boo2 method.
Also you probably want to:
return return1 # instead of or after print(return1)
as your methods return None at the moment.

how to assign a new value to a variable inside a function? [duplicate]

Sorry if this is a dumb question, but I've looked for a while and not really found the answer.
If I'm writing a python function, for example:
def function(in1, in2):
in1=in1+1
in2=in2+1
How do I make these changes stick?
I know why they dont, this has been addressed in many answers, but I couldn't find an answer to the question of how to actually make them do so. Without returning values or making some sort of class, is there really no way for a function to operate on its arguments in a global sense?
I also want these variables to not be global themselves, as in I want to be able to do this:
a=1
b=2
c=3
d=4
function(a,b)
function(c,d)
Is this just wishful thinking?
It can be done but I'm warning you - it won't be pretty! What you can do is to capture the caller frame in your function, then pick up the call line, parse it and extract the arguments passed, then compare them with your function signature and create an argument map, then call your function and once your function finishes compare the changes in the local stack and update the caller frame with the mapped changes. If you want to see how silly it can get, here's a demonstration:
# HERE BE DRAGONS
# No, really, here be dragons, this is strictly for demonstration purposes!!!
# Whenever you use this in code a sweet little pixie is brutally killed!
import ast
import inspect
import sys
def here_be_dragons(funct): # create a decorator so we can, hm, enhance 'any' function
def wrapper(*args, **kwargs):
caller = inspect.getouterframes(inspect.currentframe())[1] # pick up the caller
parsed = ast.parse(caller[4][0], mode="single") # parse the calling line
arg_map = {} # a map for our tracked args to establish global <=> local link
for node in ast.walk(parsed): # traverse the parsed code...
# and look for a call to our wrapped function
if isinstance(node, ast.Call) and node.func.id == funct.__name__:
# loop through all positional arguments of the wrapped function
for pos, var in enumerate(funct.func_code.co_varnames):
try: # and try to find them in the captured call
if isinstance(node.args[pos], ast.Name): # named argument!
arg_map[var] = node.args[pos].id # add to our map
except IndexError:
break # no more passed arguments
break # no need for further walking through the ast tree
def trace(frame, evt, arg): # a function to capture the wrapped locals
if evt == "return": # we're only interested in our function return
for arg in arg_map: # time to update our caller frame
caller[0].f_locals[arg_map[arg]] = frame.f_locals.get(arg, None)
profile = sys.getprofile() # in case something else is doing profiling
sys.setprofile(trace) # turn on profiling of the wrapped function
try:
return funct(*args, **kwargs)
finally:
sys.setprofile(profile) # reset our profiling
return wrapper
And now you can easily decorate your function to enable it to perform this ungodly travesty:
# Zap, there goes a pixie... Poor, poor, pixie. It will be missed.
#here_be_dragons
def your_function(in1, in2):
in1 = in1 + 1
in2 = in2 + 1
And now, demonstration:
a = 1
b = 2
c = 3
d = 4
# Now is the time to play and sing along: Queen - A Kind Of Magic...
your_function(a, b) # bam, two pixies down... don't you have mercy?
your_function(c, d) # now you're turning into a serial pixie killer...
print(a, b, c, d) # Woooo! You made it! At the expense of only three pixie lives. Savage!
# prints: (2, 3, 4, 5)
This, obviously, works only for non-nested functions with positional arguments, and only if you pass simple local arguments, feel free to go down the rabbit hole of handling keyword arguments, different stacks, returned/wrapped/chained calls, and other shenanigans if that's what you fancy.
Or, you know, you can use structures invented for this, like globals, classes, or even enclosed mutable objects. And stop murdering pixies.
If you are looking to modify the value of the variables you could have your code be
def func(a,b):
int1 = a + 2
int2 = b + 3
return int1,int2
a = 2
b = 3
a,b = func(a,b)
This allows you to actually change the values of the a and b variables with the function.
you can do:
def function(in1, in2):
return in1 + 1 , in2 + 1
a, b = function(a,b)
c, d = function(c,d)
python functions are closed -> when function(a,b) s called, a and b get reassigned to a local (to the function) references/pointers in1 and in2, which are not accessible outside of the function. provide references to those new values w/o using globals, you will need to pass that back through return.
When you pass an array or non primitive object into a function, you can modify the object's attributes and have those modifications be visible to other references for that object outside, because the object itself contain the pointers to those values, making the visible to anything else holding a pointer to that object.

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.

How to make two functions share the same non global variable (Python)

Is there a way to make function B to be able to access a non global variable that was declared in only in function A, without return statements from function A.
As asked, the question:
Define two functions:
p: prints the value of a variable
q: increments the variable
such that
Initial value of the variable is 0. You can't define the variable in the global
enviroment.
Variable is not located in the global environment and the only way to change it is by invoking q().
The global enviroment should know only p() and q().
Tip: 1) In python, a function can return more than 1 value. 2) A function can be
assigned to a variable.
# Example:
>>> p()
0
>>> q()
>>> q()
>>> p()
2
The question says the global enviroment should know only p and q.
So, taking that literally, it could be done inline using a single function scope:
>>> p, q = (lambda x=[0]: (lambda: print(x[0]), lambda: x.__setitem__(0, x[0] + 1)))()
>>> p()
0
>>> q()
>>> q()
>>> p()
2
Using the tips provided as clues, it could be done something like this:
def make_p_and_q():
context = {'local_var': 0}
def p():
print('{}'.format(context['local_var']))
def q():
context['local_var'] += 1
return p, q
p, q = make_p_and_q()
p() # --> 0
q()
q()
p() # --> 2
The collection of things that functions can access is generally called its scope. One interpretation of your question is whether B can access a "local variable" of A; that is, one that is defined normally as
def A():
x = 1
The answer here is "not easily": Python lets you do a lot, but local variables are one of the things that are not meant to be accessed inside a function.
I suspect what your teacher is getting at is that A can modify things outside of its scope, in order to send information out without sending it through the return value. (Whether this is good coding practise is another matter.) For example, functions are themselves Python objects, and you can assign arbitrary properties to Python objects, so you can actually store values on the function object and read them from outside it.
def a():
a.key = "value"
a()
print a.key
Introspection and hacking with function objects
In fact, you can sort of get at the constant values defined in A by looking at the compiled Python object generated when you define a function. For example, in the example above, "value" is a constant, and constants are stored on the code object:
In [9]: a.func_code.co_consts
Out[9]: (None, 'value')
This is probably not what you meant.
Firstly, it's bad practise to do so. Such variables make debugging difficult and are easy to lose track of, especially in complex code.
Having said that, you can accomplish what you want by declaring a variable as global:
def funcA():
global foo
foo = 3
def funcB():
print foo # output is 3
That's one weird homework assignment; especially the tips make me suspect that you've misunderstood or left out something.
Anyway, here's a simpler solution than the accepted answer: Since calls to q increment the value of the variable, it must be a persistent ("static") variable of some sort. Store it somewhere other than the global namespace, and tell p about it. The obvious place to store it is as an attribute of q:
def q():
q.x += 1
q.x = 0 # Initialize
def p():
print(q.x)

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