TypeError: _slow_trap_ramp() takes 1 positional argument but 2 were given
def demag_chip(self):
coil_probe_constant = float(514.5)
field_sweep = [50 * i * (-1)**(i + 1) for i in range(20, 0, -1)] #print as list
for j in field_sweep:
ramp = self._slow_trap_ramp(j)
def _set_trap_ramp(self):
set_trap_ramp = InstrumentsClass.KeysightB2962A.set_trap_ramp
return set_trap_ramp
def _slow_trap_ramp(self):
slow_trap_ramp = ExperimentsSubClasses.FraunhoferAveraging.slow_trap_ramp
return slow_trap_ramp
The error is straightforward.
ramp = self._slow_trap_ramp(j)
You are calling this method with an argument j, but the method doesn't take an argument (other than self, which is used to pass the object).
Re-define your method to accept an argument if you want to pass it one:
def _slow_trap_ramp(self, j):
It looks like your code extract contains methods of some class, whose full definition is not shown, and you are calling one method from another method (self._slow_trap_ramp(j)). When you call a method, Python automatically passes self before any other arguments. So you need to change def _slow_trap_ramp(self) to def _slow_trap_ramp(self, j).
Update in response to comment
To really help, we would need to see more of the class you are writing, and also some info on the other objects you are calling. But I am going to go out on a limb and guess that your code looks something like this:
InstrumentsClass.py
class KeysightB2962A
def __init__(self):
...
def set_trap_ramp(self):
...
ExperimentsSubClasses.py
class FraunhoferAveraging
def __init__(self):
...
def slow_trap_ramp(self, j):
...
Current version of main.py
import InstrumentsClass, ExperimentsSubClasses
class MyClass
def __init__(self)
...
def demag_chip(self):
coil_probe_constant = float(514.5)
field_sweep = [50 * i * (-1)**(i + 1) for i in range(20, 0, -1)] #print as list
for j in field_sweep:
ramp = self._slow_trap_ramp(j)
def _set_trap_ramp(self):
set_trap_ramp = InstrumentsClass.KeysightB2962A.set_trap_ramp
return set_trap_ramp
def _slow_trap_ramp(self):
slow_trap_ramp = ExperimentsSubClasses.FraunhoferAveraging.slow_trap_ramp
return slow_trap_ramp
if __name__ == "__main__":
my_obj = MyClass()
my_obj.demag_chip()
If this is the case, then these are the main problems:
Python passes self and j to MyClass._slow_trap_ramp, but you've only defined it to accept self (noted above),
you are using class methods from KeysightB2962A and FraunhoferAveraging directly instead of instantiating the class and using the instance's methods, and
you are returning references to the methods instead of calling the methods.
You can fix all of these by changing the code to look like this (see embedded comments):
New version of main.py
import InstrumentsClass, ExperimentsSubClasses
class MyClass
def __init__(self)
# create instances of the relevant classes (note parentheses at end)
self.keysight = InstrumentsClass.KeysightB2962A()
self.fraun_averaging = ExperimentsSubClasses.FraunhoferAveraging()
def demag_chip(self):
coil_probe_constant = float(514.5)
field_sweep = [50 * i * (-1)**(i + 1) for i in range(20, 0, -1)] #print as list
for j in field_sweep:
ramp = self._slow_trap_ramp(j)
def _set_trap_ramp(self):
# call instance method (note parentheses at end)
return self.keysight.set_trap_ramp()
def _slow_trap_ramp(self, j): # accept both self and j
# call instance method (note parentheses at end)
return self.fraun_averaging.slow_trap_ramp(j)
if __name__ == "__main__":
my_obj = MyClass()
my_obj.demag_chip()
Related
def MainCount(f):
def progFirst(*args,**kwargs):
progFirst.calls+=1
return f(*args,**kwargs)
progFirst.calls=0
return progFirst
#MainCount
def progSecond(i):
return i+1
#MainCount
def Count(i=0,j=1):
return i*j+1
print(progSecond.calls)
for n in range(5):
progSecond(n)
Count(j=0,i=1)
print(Count.calls)
Output :0
1
As per my understanding MainCount(probSecond) but I am not understant then how probSecond.calls equal to zero same in Count.calls also
As You Can See in MainCount function probFirst.Calls is attribute of function .When MainCount(probSecond) Now probSecond.calls is also attribute of MainCount function.
# A Python example to demonstrate that
# decorators can be useful attach data
# A decorator function to attach
# data to func
def attach_data(func):
func.data = 3
return func
#attach_data
def add (x, y):
return x + y
# Driver code
# This call is equivalent to attach_data()
# with add() as parameter
print(add(2, 3))
print(add.data)
I am trying to implement a function (make_q) that returns a list of functions(Q) that are generated using the argument that make_q gets (P). Q is a variable dependent to n(=len(P)) and making the Q functions are similar, so it can be done in a for loop but here is the catch if I name the function in the loop, they will all have the same address so I only get the last Q, Is there to bypass this?
Here is my code,
def make_q(self):
Temp_P=[p for p in self.P]
Q=()
for i in range(self.n-1):
p=min(Temp_P)
q=max(Temp_P)
index_p=Temp_P.index(p)
index_q=Temp_P.index(q)
def tempQ():
condition=random.random()
if condition<=(p*self.n):
return index_p
else:
return index_q
Temp_Q=list(Q)
Temp_Q.append(tempQ)
Q=tuple(Temp_Q)
q-=(1-p*self.n)/self.n
Temp_P[index_q]=q
Temp_P.pop(index_p)
return Q
test.Q
(<function __main__.Test.make_q.<locals>.tempQ()>,
<function __main__.Test.make_q.<locals>.tempQ()>,
<function __main__.Test.make_q.<locals>.tempQ()>,
<function __main__.Test.make_q.<locals>.tempQ()>,
<function __main__.Test.make_q.<locals>.tempQ()>)
I also tried to make them a tuple so they have different addresses but it didn't work.
Is there a way to name functions(tempQ) dynamic like tempQi
jasonharper's observation and solution in comments is correct(and should be the accepted answer). But since you asked about metaclasses, I am posting this anyway.
In python, each class is a type , with "name", "bases" (base classes) and "attrs"(all members of a class). Essentially, a metaclass defines a behaviour of a class, you can read more about it at https://www.python-course.eu/python3_metaclasses.php and various other online tutorials.
The __new__ method runs when a class is set up. Note the usage of attrs where your class member self.n is accessed by attrs['n'] (as attrs is a dict of all class members). I am defining functions tempQ_0, tempQ_1... dynamically. As you can see, we can also add docstrings to this dynamically defined class members.
import random
class MyMetaClass(type):
def __new__(cls, name, bases, attrs):
Temp_P = [p for p in attrs['P']]
for i in range(attrs['n'] - 1):
p = min(Temp_P)
q = max(Temp_P)
index_p = Temp_P.index(p)
index_q = Temp_P.index(q)
def fget(self, index_p=index_p, index_q=index_q): # this is an unbound method
condition = random.random()
return index_p if condition <= (p * self.n) else index_q
attrs['tempQ_{}'.format(i)] = property(fget, doc="""
This function returns {} or {} randomly""".format(index_p, index_q))
q -= (1 - p * attrs['n']) / attrs['n']
Temp_P[index_q] = q
Temp_P.pop(index_p)
return super(MyMetaClass, cls).__new__(cls, name, bases, attrs)
# PY2
# class MyClass(object):
# __metaclass__ = MyMetaClass
# n = 3
# P = [3, 6, 8]
# PY3
class MyClass(metaclass=MyMetaClass):
n = 3
P = [3, 6, 8]
# or use with_metaclass from future.utils for both Py2 and Py3
# print(dir(MyClass))
print(MyClass.tempQ_0, MyClass.tempQ_1)
output
<property object at 0x10e5fbd18> <property object at 0x10eaad0e8>
So your list of functions is [MyClass.tempQ_0, MyClass.tempQ_1]
Please try via formatted strings, for eg: "function_{}.format(name)" also, how do you want your output to look like?
I'm trying to use ray module to on an existing code based on if an env variable is true or not.
This is what I've done so far. this code structure is similar to mine but not exactly due to it's size.
import os
if os.getenv("PARALLEL"):
import ray
ray.init()
class A(object):
def __init__(self, attr):
self.attr = attr
def may_be_remote(func):
return ray.remote(func) if os.getenv("PARALLEL") else func
#may_be_remote
def do_work(self):
#work code
def execute(self, n):
for _ in range(n):
do_work.remote()
Then, I call the execute function of class A :
a = A()
a.execute(7)
I get AttributeError : 'function' has no attribute 'remote' on that line.
Where did I go wrong with this code please?
You are accessing remote() on the function do_work, which is not defined.
Did you mean to just call do_work()?
Unfortunately ray makes it hard to get transparent code to switch easily as you intend.
Following https://docs.ray.io/en/latest/ray-overview/index.html#parallelizing-python-classes-with-ray-actors the quite strange insert-.remote syntax is like...
import os
use_ray = os.getenv("PARALLEL") is not None
if use_ray:
import ray
ray.init()
def maybe_remote(cls):
return ray.remote(cls) if use_ray else cls
#maybe_remote
class A:
def __init__(self, attr):
self.attr = attr
def do_work(self, foo): # do something
self.attr += foo
def get_attr(self): # return value maybe from remote worker
return self.attr
if __name__ == '__main__':
n = 7
if use_ray:
a = A.remote(0)
for i in range(1, n + 1):
a.do_work.remote(i)
result = ray.get(a.get_attr.remote())
else:
a = A(0)
for i in range(1, n + 1):
a.do_work(i)
result = a.get_attr()
expect = int((n / 2) * (n + 1))
assert expect == result
Not sure there is also an easy (decorator) solution for the differences in the method calls.
A cleaned up version of the code including the solution to the problem (thanks #JohanL!) can be found as a Gist on GitHub.
The following code snipped (CPython 3.[4,5,6]) illustrates my intention (as well as my problem):
from functools import partial
import multiprocessing
from pprint import pprint as pp
NUM_CORES = multiprocessing.cpu_count()
class some_class:
some_dict = {'some_key': None, 'some_other_key': None}
def some_routine(self):
self.some_dict.update({'some_key': 'some_value'})
def some_other_routine(self):
self.some_dict.update({'some_other_key': 77})
def run_routines_on_objects_in_parallel_and_return(in_object_list, routine_list):
func_handle = partial(__run_routines_on_object_and_return__, routine_list)
with multiprocessing.Pool(processes = NUM_CORES) as p:
out_object_list = list(p.imap_unordered(
func_handle,
(in_object for in_object in in_object_list)
))
return out_object_list
def __run_routines_on_object_and_return__(routine_list, in_object):
for routine_name in routine_list:
getattr(in_object, routine_name)()
return in_object
object_list = [some_class() for item in range(20)]
pp([item.some_dict for item in object_list])
new_object_list = run_routines_on_objects_in_parallel_and_return(
object_list,
['some_routine', 'some_other_routine']
)
pp([item.some_dict for item in new_object_list])
verification_object_list = [
__run_routines_on_object_and_return__(
['some_routine', 'some_other_routine'],
item
) for item in object_list
]
pp([item.some_dict for item in verification_object_list])
I am working with a list of objects of type some_class. some_class has a property, a dictionary, named some_dict and a few methods, which can modify the dict (some_routine and some_other_routine). Sometimes, I want to call a sequence of methods on all the objects in the list. Because this is computationally intensive, I intend to distribute the objects over multiple CPU cores (using multiprocessing.Pool and imap_unordered - the list order does not matter).
The routine __run_routines_on_object_and_return__ takes care of calling the list of methods on one individual object. From what I can tell, this is working just fine. I am using functools.partial for simplifying the structure of the code a bit - the multiprocessing pool therefore has to handle the list of objects as an input parameter only.
The problem is ... it does not work. The objects contained in the list returned by imap_unordered are identical to the objects I fed into it. The dictionaries within the objects look just like before. I have used similar mechanisms for working on lists of dictionaries directly without a glitch, so I somehow suspect that there is something wrong with modifying an object property which happens to be a dictionary.
In my example, verification_object_list contains the correct result (though it is generated in a single process/thread). new_object_list is identical to object_list, which should not be the case.
What am I doing wrong?
EDIT
I found the following question, which has an actually working and applicable answer. I modified it a bit following my idea of calling a list of methods on every object and it works:
import random
from multiprocessing import Pool, Manager
class Tester(object):
def __init__(self, num=0.0, name='none'):
self.num = num
self.name = name
def modify_me(self):
self.num += random.normalvariate(mu=0, sigma=1)
self.name = 'pla' + str(int(self.num * 100))
def __repr__(self):
return '%s(%r, %r)' % (self.__class__.__name__, self.num, self.name)
def init(L):
global tests
tests = L
def modify(i_t_nn):
i, t, nn = i_t_nn
for method_name in nn:
getattr(t, method_name)()
tests[i] = t # copy back
return i
def main():
num_processes = num = 10 #note: num_processes and num may differ
manager = Manager()
tests = manager.list([Tester(num=i) for i in range(num)])
print(tests[:2])
args = ((i, t, ['modify_me']) for i, t in enumerate(tests))
pool = Pool(processes=num_processes, initializer=init, initargs=(tests,))
for i in pool.imap_unordered(modify, args):
print("done %d" % i)
pool.close()
pool.join()
print(tests[:2])
if __name__ == '__main__':
main()
Now, I went a bit further and introduced my original some_class into the game, which contains a the described dictionary property some_dict. It does NOT work:
import random
from multiprocessing import Pool, Manager
from pprint import pformat as pf
class some_class:
some_dict = {'some_key': None, 'some_other_key': None}
def some_routine(self):
self.some_dict.update({'some_key': 'some_value'})
def some_other_routine(self):
self.some_dict.update({'some_other_key': 77})
def __repr__(self):
return pf(self.some_dict)
def init(L):
global tests
tests = L
def modify(i_t_nn):
i, t, nn = i_t_nn
for method_name in nn:
getattr(t, method_name)()
tests[i] = t # copy back
return i
def main():
num_processes = num = 10 #note: num_processes and num may differ
manager = Manager()
tests = manager.list([some_class() for i in range(num)])
print(tests[:2])
args = ((i, t, ['some_routine', 'some_other_routine']) for i, t in enumerate(tests))
pool = Pool(processes=num_processes, initializer=init, initargs=(tests,))
for i in pool.imap_unordered(modify, args):
print("done %d" % i)
pool.close()
pool.join()
print(tests[:2])
if __name__ == '__main__':
main()
The diff between working and not working is really small, but I still do not get it:
diff --git a/test.py b/test.py
index b12eb56..0aa6def 100644
--- a/test.py
+++ b/test.py
## -1,15 +1,15 ##
import random
from multiprocessing import Pool, Manager
+from pprint import pformat as pf
-class Tester(object):
- def __init__(self, num=0.0, name='none'):
- self.num = num
- self.name = name
- def modify_me(self):
- self.num += random.normalvariate(mu=0, sigma=1)
- self.name = 'pla' + str(int(self.num * 100))
+class some_class:
+ some_dict = {'some_key': None, 'some_other_key': None}
+ def some_routine(self):
+ self.some_dict.update({'some_key': 'some_value'})
+ def some_other_routine(self):
+ self.some_dict.update({'some_other_key': 77})
def __repr__(self):
- return '%s(%r, %r)' % (self.__class__.__name__, self.num, self.name)
+ return pf(self.some_dict)
def init(L):
global tests
## -25,10 +25,10 ## def modify(i_t_nn):
def main():
num_processes = num = 10 #note: num_processes and num may differ
manager = Manager()
- tests = manager.list([Tester(num=i) for i in range(num)])
+ tests = manager.list([some_class() for i in range(num)])
print(tests[:2])
- args = ((i, t, ['modify_me']) for i, t in enumerate(tests))
+ args = ((i, t, ['some_routine', 'some_other_routine']) for i, t in enumerate(tests))
What is happening here?
Your problem is due to two things; namely that you are using a class variable and that you are running your code in different processes.
Since different processes do not share memory, all objects and parameters must be pickled and sent from the original process to the process that executes it. When the parameter is an object, its class is not sent with it. Instead the receiving process uses its own blueprint (i.e. class).
In your current code, you pass the object as a parameter, update it and return it. However, the updates are not made to the object, but rather to the class itself, since you are updating a class variable. However, this update is not sent back to your main process, and therefore you are left with your not updated class.
What you want to do, is to make some_dict a part of your object, rather than of your class. This is easily done by an __init__() method. Thus modify some_class as:
class some_class:
def __init__(self):
self.some_dict = {'some_key': None, 'some_other_key': None}
def some_routine(self):
self.some_dict.update({'some_key': 'some_value'})
def some_other_routine(self):
self.some_dict.update({'some_other_key': 77})
This will make your program work as you intend it to. You almost always want to setup your object in an __init__() call, rather than as class variables, since in the latter case the data will be shared between all instances (and can be updated by all). That is not normally what you want, when you encapsulate data and state in an object of a class.
EDIT: It seems I was mistaken in whether the class is sent with the pickled object. After further inspection of what happens, I think also the class itself, with its class variables are pickled. Since, if the class variable is updated before sending the object to the new process, the updated value is available. However it is still the case that the updates done in the new process are not relayed back to the original class.
I wrote the following program:
def split_and_add(invoer):
rij = invoer.split('=')
rows = []
for line in rij:
rows.append(process_row(line))
return rows
def process_row(line):
temp_coordinate_row = CoordinatRow()
rij = line.split()
for coordinate in rij:
coor = process_coordinate(coordinate)
temp_coordinate_row.add_coordinaterow(coor)
return temp_coordinate_row
def process_coordinate(coordinate):
cords = coordinate.split(',')
return Coordinate(int(cords[0]),int(cords[1]))
bestand = file_input()
rows = split_and_add(bestand)
for row in range(0,len(rows)-1):
rij = rows[row].weave(rows[row+1])
print rij
With this class:
class CoordinatRow(object):
def __init__(self):
self.coordinaterow = []
def add_coordinaterow(self, coordinate):
self.coordinaterow.append(coordinate)
def weave(self,other):
lijst = []
for i in range(len(self.coordinaterow)):
lijst.append(self.coordinaterow[i])
try:
lijst.append(other.coordinaterow[i])
except IndexError:
pass
self.coordinaterow = lijst
return self.coordinaterow
However there is an error in
for row in range(0,len(rows)-1):
rij = rows[row].weave(rows[row+1])
print rij
The outcome of the print statement is as follows:
[<Coordinates.Coordinate object at 0x021F5630>, <Coordinates.Coordinate object at 0x021F56D0>]
It seems as if the program doesn't acces the actual object and printing it. What am i doing wrong here ?
This isn't an error. This is exactly what it means for Python to "access the actual object and print it". This is what the default string representation for a class looks like.
If you want to customize the string representation of your class, you do that by defining a __repr__ method. The typical way to do it is to write a method that returns something that looks like a constructor call for your class.
Since you haven't shown us the definition of Coordinate, I'll make some assumptions here:
class Coordinate(object):
def __init__(self, x, y):
self.x, self.y = x, y
# your other existing methods
def __repr__(self):
return '{}({}, {})'.format(type(self).__name__, self.x, self.y)
If you don't define this yourself, you end up inheriting __repr__ from object, which looks something like:
return '<{} object at {:#010x}>'.format(type(self).__qualname__, id(self))
Sometimes you also want a more human-readable version of your objects. In that case, you also want to define a __str__ method:
def __str__(self):
return '<{}, {}>'.format(self.x, self.y)
Now:
>>> c = Coordinate(1, 2)
>>> c
Coordinate(1, 2)
>>> print(c)
<1, 2>
But notice that the __str__ of a list calls __repr__ on all of its members:
>>> cs = [c]
>>> print(cs)
[Coordinate(1, 2)]