I have answered my own question - see answer below
I'm writing a class, and I want this behavior:
a = f(10,20)
some_funct(a.row) # some_function is given 10
some_funct(a.col) # some_function is given 20
some_funct(a) # some_function is given a tuple of 10, 20 <-- THIS ONE :)
The last behavior is stumping me. I have not seen any examples that cover this.
Thus far:
class f(object):
"""Simple 2d object"""
row: int
col: int
def __init__(self, row, col):
self.row = row
self.col = col
Explictly I do not want another method, say, self.both = row, col.
I just want to 'call' the instance
I'm new to classes, so any improvements are welcome. Properties, setters, getters etc.
EDIT 1:
Replaced "print" with "some_function" in the question, and modified title
You can do like this
class f(object):
"""Simple 2d object"""
row: int
col: int
def __init__(self, row, col):
self.row = row
self.col = col
def __str__(self):
return f"row = {row}, col = {col}"
and print like this
a = f(10,20)
print(a) # row = 10, col = 20
This might help
class f(object):
"""Simple 2d object"""
row: int
col: int
def __init__(self, row, col):
self.row = row
self.col = col
def some_funct(self):
return (self.row, self.col)
You can access like
a = f(10,20)
a.some_funct() # (10, 20)
# or
row, col = a.some_funct()
From python 3.7 dataclasses have been introduced and their goal is to create classes that mainly contains data. Dataclasses comes with some helper function that extract the class attributes dict/tuples. e.g.
from dataclasses import dataclass,asdict,astuple
#dataclass
class f:
x: int
y: int
f_instance = f(10,20)
asdict(f_instance) # --> {'x': 10, 'y': 20}
astuple(f_instance) # -> (10,20)
EDIT I : Another technique would be to use namedtuple e.g.:
from collections import namedtuple
f = namedtuple('p',['row','col'])
a =f(10,20)
a.row #-> 10
a.col #-> 20
class f(tuple):
"""Simple 2d object"""
def __new__(cls, x, y):
return tuple.__new__(f, (x, y))
def __init__(self, x, y):
self.col = x
self.row = y
foo = f(1,2)
print(foo.col)
>>>1
print(foo.row)
>>>2
print(foo)
>>>(1, 2)
Importantly:
If you want it to behave like a tuple then make it a subclass of tuple.
Much stuffing around but stumbled upon an external site which gave me clues about the keywords to search on here. The SO question is here but I have modified that answer slightly.
I'm still a little confused because the other site says to use new in the init as well but does not give a clear example.
I have a situation where I am generating a number of template nested lists with n organised elements where each number in the template corresponds to the index from a flat list of n values:
S =[[[2,4],[0,3]], [[1,5],[6,7]],[[10,9],[8,11],[13,12]]]
For each of these templates, the values inside them correspond to the index value from a flat list like so:
A = ["a","b","c","d","e","f","g","h","i","j","k","l","m","n"]
to get;
B = [[["c","e"],["a","d"]], [["b","f"],["g","h"]],[["k","j"],["i","l"],["n","m"]]]
How can I populate the structure S with the values from list A to get B, considering that:
- the values of list A can change in value but not in a number
- the template can have any depth of nested structure of but will only use an index from A once as the example shown above.
I did this with the very ugly append unflatten function below that works if the depth of the template is not more then 3 levels. Is there a better way of accomplishing it using generators, yield so it works for any arbitrary depth of template.
Another solution I thought but couldn't implement is to set the template as a string with generated variables and then assigning the variables with new values using eval()
def unflatten(item, template):
# works up to 3 levels of nested lists
tree = []
for el in template:
if isinstance(el, collections.Iterable) and not isinstance(el, str):
tree.append([])
for j, el2 in enumerate(el):
if isinstance(el2, collections.Iterable) and not isinstance(el2, str):
tree[-1].append([])
for k, el3 in enumerate(el2):
if isinstance(el3, collections.Iterable) and not isinstance(el3, str):
tree[-1][-1].append([])
else:
tree[-1][-1].append(item[el3])
else:
tree[-1].append(item[el2])
else:
tree.append(item[el])
return tree
I need a better solution that can be employed to accomplish this when doing the above recursively and for n = 100's of organised elements.
UPDATE 1
The timing function I am using is this one:
def timethis(func):
'''
Decorator that reports the execution time.
'''
#wraps(func)
def wrapper(*args, **kwargs):
start = time.time()
result = func(*args, **kwargs)
end = time.time()
print(func.__name__, end-start)
return result
return wrapper
and I am wrapping the function suggested by #DocDrivin inside another to call it with a one-liner. Below it is my ugly append function.
#timethis
def unflatten(A, S):
for i in range(100000):
# making sure that you don't modify S
rebuilt_list = copy.deepcopy(S)
# create the mapping dict
adict = {key: val for key, val in enumerate(A)}
# the recursive worker function
def worker(alist):
for idx, entry in enumerate(alist):
if isinstance(entry, list):
worker(entry)
else:
# might be a good idea to catch key errors here
alist[idx] = adict[entry]
#build list
worker(rebuilt_list)
return rebuilt_list
#timethis
def unflatten2(A, S):
for i in range (100000):
#up to level 3
temp_tree = []
for i, el in enumerate(S):
if isinstance(el, collections.Iterable) and not isinstance(el, str):
temp_tree.append([])
for j, el2 in enumerate(el):
if isinstance(el2, collections.Iterable) and not isinstance(el2, str):
temp_tree[-1].append([])
for k, el3 in enumerate(el2):
if isinstance(el3, collections.Iterable) and not isinstance(el3, str):
temp_tree[-1][-1].append([])
else:
temp_tree[-1][-1].append(A[el3])
else:
temp_tree[-1].append(A[el2])
else:
temp_tree.append(A[el])
return temp_tree
The recursive method is much better syntax, however, it is considerably slower then using the append method.
You can do this by using recursion:
import copy
S =[[[2,4],[0,3]], [[1,5],[6,7]],[[10,9],[8,11],[13,12]]]
A = ["a","b","c","d","e","f","g","h","i","j","k","l","m","n"]
# making sure that you don't modify S
B = copy.deepcopy(S)
# create the mapping dict
adict = {key: val for key, val in enumerate(A)}
# the recursive worker function
def worker(alist):
for idx, entry in enumerate(alist):
if isinstance(entry, list):
worker(entry)
else:
# might be a good idea to catch key errors here
alist[idx] = adict[entry]
worker(B)
print(B)
This yields the following output for B:
[[['c', 'e'], ['a', 'd']], [['b', 'f'], ['g', 'h']], [['k', 'j'], ['i', 'l'], ['n', 'm']]]
I did not check if the list entry can actually be mapped with the dict, so you might want to add a check (marked the spot in the code).
Small edit: just saw that your desired output (probably) has a typo. Index 3 maps to "d", not to "c". You might want to edit that.
Big edit: To prove that my proposal is not as catastrophic as it seems at a first glance, I decided to include some code to test its runtime. Check this out:
import timeit
setup1 = '''
import copy
S =[[[2,4],[0,3]], [[1,5],[6,7]],[[10,9],[8,11],[13,12]]]
A = ["a","b","c","d","e","f","g","h","i","j","k","l","m","n"]
adict = {key: val for key, val in enumerate(A)}
# the recursive worker function
def worker(olist):
alist = copy.deepcopy(olist)
for idx, entry in enumerate(alist):
if isinstance(entry, list):
worker(entry)
else:
alist[idx] = adict[entry]
return alist
'''
code1 = '''
worker(S)
'''
setup2 = '''
import collections
S =[[[2,4],[0,3]], [[1,5],[6,7]],[[10,9],[8,11],[13,12]]]
A = ["a","b","c","d","e","f","g","h","i","j","k","l","m","n"]
def unflatten2(A, S):
#up to level 3
temp_tree = []
for i, el in enumerate(S):
if isinstance(el, collections.Iterable) and not isinstance(el, str):
temp_tree.append([])
for j, el2 in enumerate(el):
if isinstance(el2, collections.Iterable) and not isinstance(el2, str):
temp_tree[-1].append([])
for k, el3 in enumerate(el2):
if isinstance(el3, collections.Iterable) and not isinstance(el3, str):
temp_tree[-1][-1].append([])
else:
temp_tree[-1][-1].append(A[el3])
else:
temp_tree[-1].append(A[el2])
else:
temp_tree.append(A[el])
return temp_tree
'''
code2 = '''
unflatten2(A, S)
'''
print(f'Recursive func: { [i/10000 for i in timeit.repeat(setup = setup1, stmt = code1, repeat = 3, number = 10000)] }')
print(f'Original func: { [i/10000 for i in timeit.repeat(setup = setup2, stmt = code2, repeat = 3, number = 10000)] }')
I am using the timeit module to do my tests. When running this snippet, you will get an output similar to this:
Recursive func: [8.74395573977381e-05, 7.868373290111777e-05, 7.9051584698027e-05]
Original func: [3.548609419958666e-05, 3.537480780214537e-05, 3.501355930056888e-05]
These are the average times of 10000 iterations, and I decided to run it 3 times to show the fluctuation. As you can see, my function in this particular case is 2.22 to 2.50 times slower than the original, but still acceptable. The slowdown is probably due to using deepcopy.
Your test has some flaws, e.g. you redefine the mapping dict at every iteration. You wouldn't do that normally, instead you would give it as a param to the function after defining it once.
You can use generators with recursion
A = ["a","b","c","d","e","f","g","h","i","j","k","l","m","n"]
S = [[[2,4],[0,3]], [[1,5],[6,7]],[[10,9],[8,11],[13,12]]]
A = {k: v for k, v in enumerate(A)}
def worker(alist):
for e in alist:
if isinstance(e, list):
yield list(worker(e))
else:
yield A[e]
def do(alist):
return list(worker(alist))
This is also a recursive approach, just avoiding individual item assignment and letting list do the work by reading the values "hot off the CPU" from your generator. If you want, you can Try it online!-- setup1 and setup2 copied from #DocDriven 's answer (but I recommend you don't exaggerate with the numbers, do it locally if you want to play around).
Here are example time numbers:
My result: [0.11194685893133283, 0.11086182110011578, 0.11299032904207706]
result1: [1.0810202199500054, 1.046933784848079, 0.9381260159425437]
result2: [0.23467918601818383, 0.236218704842031, 0.22498539905063808]
I am trying to create a calorie counter the standard input goes like this:
python3 calories.txt < test.txt
Inside calories the food is the following format: apples 500
The problem I am having is that whenever I calculate the values for the person it seems to never return to an empty list..
import sys
food = {}
eaten = {}
finished = {}
total = 0
#mappings
def calories(x):
with open(x,"r") as file:
for line in file:
lines = line.strip().split()
key = " ".join(lines[0:-1])
value = lines[-1]
food[key] = value
def calculate(x):
a = []
for keys,values in x.items():
for c in values:
try:
a.append(int(food[c]))
except:
a.append(100)
print("before",a)
a = []
total = sum(a) # Problem here
print("after",a)
print(total)
def main():
calories(sys.argv[1])
for line in sys.stdin:
lines = line.strip().split(',')
for c in lines:
values = lines[0]
keys = lines[1:]
eaten[values] = keys
calculate(eaten)
if __name__ == '__main__':
main()
Edit - forgot to include what test.txt would look like:
joe,almonds,almonds,blue cheese,cabbage,mayonnaise,cherry pie,cola
mary,apple pie,avocado,broccoli,butter,danish pastry,lettuce,apple
sandy,zuchini,yogurt,veal,tuna,taco,pumpkin pie,macadamia nuts,brazil nuts
trudy,waffles,waffles,waffles,chicken noodle soup,chocolate chip cookie
How to make it easier on yourself:
When reading the calories-data, convert the calories to int() asap, no need to do it every time you want to sum up somthing that way.
Dictionary has a .get(key, defaultvalue) accessor, so if food not found, use 100 as default is a 1-liner w/o try: ... except:
This works for me, not using sys.stdin but supplying the second file as file as well instead of piping it into the program using <.
I modified some parsings to remove whitespaces and return a [(name,cal),...] tuplelist from calc.
May it help you to fix it to your liking:
def calories(x):
with open(x,"r") as file:
for line in file:
lines = line.strip().split()
key = " ".join(lines[0:-1])
value = lines[-1].strip() # ensure no whitespaces in
food[key] = int(value)
def getCal(foodlist, defValueUnknown = 100):
"""Get sum / total calories of a list of ingredients, unknown cost 100."""
return sum( food.get(x,defValueUnknown ) for x in foodlist) # calculate it, if unknown assume 100
def calculate(x):
a = []
for name,foods in x.items():
a.append((name, getCal(foods))) # append as tuple to list for all names/foods eaten
return a
def main():
calories(sys.argv[1])
with open(sys.argv[2]) as f: # parse as file, not piped in via sys.stdin
for line in f:
lines = line.strip().split(',')
for c in lines:
values = lines[0].strip()
keys = [x.strip() for x in lines[1:]] # ensure no whitespaces in
eaten[values] = keys
calced = calculate(eaten) # calculate after all are read into the dict
print (calced)
Output:
[('joe', 1400), ('mary', 1400), ('sandy', 1600), ('trudy', 1000)]
Using sys.stdin and piping just lead to my console blinking and waiting for manual input - maybe VS related...