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Python Find permutable list in a dict list

Given
listOfDict = [{'ref': 1, 'a': 1, 'b': 2, 'c': 3},
{'ref': 2, 'a': 4, 'b': 5, 'c': 6},
{'ref': 3, 'a': 7, 'b': 8, 'c': 9}]
Lets' consider a list of permutable integer
[7,8,9]=[7,9,8]=[8,7,9]=[8,9,7]=[9,7,8]=[9,8,7] # (3!)
Each of this list has a unique mapping ref, so how given for (8,7,9) can I get ref=3 ?
Also in real case I might until 10 (a,b,c,d,e,f,g,h,i,j)...

You can generate a dictionary that maps the values as frozenset to the value of ref:
listOfDict = [{'ref': 1, 'a': 1, 'b': 2, 'c': 3},
{'ref': 2, 'a': 4, 'b': 5, 'c': 6},
{'ref': 3, 'a': 7, 'b': 8, 'c': 9}]
keys = ['a', 'b', 'c']
out = {frozenset(d[k] for k in keys): d['ref'] for d in listOfDict}
# {frozenset({1, 2, 3}): 1,
# frozenset({4, 5, 6}): 2,
# frozenset({7, 8, 9}): 3}
example:
check = frozenset((8,7,9))
out[check]
# 3
but I don't know in advance the name of the other keys!
Then use this approach:
out = {}
for d in listOfDict:
d2 = d.copy() # this is to avoid modifying the original object
out[frozenset(d2.values())] = d2.pop('ref')
out
or as a comprehension:
out = dict(((d2:=d.copy()).pop('ref'), frozenset(d2.values()))[::-1]
for d in listOfDict)

Here is a commented solution to your problem. The idea is to compare the sorted list of the values in a, b, c etc with the sorted values in list_of_ints. The sorted values will be the same for all permutations of a given set of numbers.
def get_ref(list_of_ints):
# Loop through dictionaries in listOfDict.
for dictionary in listOfDict:
# Get list of values in each dictionary.
vals = [dictionary[key] for key in dictionary if key != "ref"]
if sorted(vals) == sorted(list_of_ints):
# If sorted values are equal to sorted list of ints, return ref.
return dictionary["ref"])
By the way, I believe it would be cleaner to structure this data as a dict of dicts in the following way:
dicts = {
1: {'a': 1, 'b': 2, 'c': 3},
2: {'a': 4, 'b': 5, 'c': 6},
3: {'a': 7, 'b': 8, 'c': 9}
}
The code would then be:
def get_ref(list_of_ints):
for ref, dictionary in dicts.items():
if sorted(dictionary.values()) == sorted(list_of_ints):
return ref
Assuming that all integers in the permutations are unique, the code can be simplified further using sets instead of sorted lists.

Since its a list of dict I can call each dict as it self by using for loop
and record the first number on ref
for i in listOfDict:
ref_num=i["ref"]
and to turn dictunary to list we simply use:
z=list(i.values())
then the last step is to find if its the same input list if so we print/return the ref number
if z[1:]==InputList:
return ref_num
and the code should be like this:
listOfDict = [
{"ref": 1,
"a": 1,
"b": 2,
"c": 3},
{"ref": 2,
"a": 4,
"b": 5,
"c": 6},
{"ref": 3,
"a": 7,
"b": 8,
"c": 9},]
def find_ref_Num(InputList):
for i in listOfDict:
ref_num=i["ref"]
z=list(i.values())
if z[1:]==InputList:
return ref_num
print ("your ref number is: "+str(find_ref_Num([7,8,9])))

How to update a dictionary at specific positions? [duplicate]

This question already has answers here:
How to insert key-value pair into dictionary at a specified position?
(8 answers)
Closed 1 year ago.
I have dictionary like below:
data = {'a': 1, 'c': 2, 'd': 3}
Is there any way to update my above dictionary after particular key? For example you want to add 'b':4 after 'a':1, and at the end add 'E':6 — so final output map should look like below:
data = {'a': 1, 'b':4, 'c': 2, 'd': 3, 'E':6}
I have gone through some documentation but I did not find any reference where we can update dictionary at particular position.

May this solve your problem and the return value is also dict not list
import operator
data = {'a': 1, 'c': 2, 'd': 3}
data['b'] = 4
data['e'] = 6
sorted_d = dict(sorted(data.items(), key=operator.itemgetter(0)))
Output
{'a': 1, 'b': 4, 'c': 2, 'd': 3, 'e': 6}

For example, you updated your data dict with like this below:
data = {'a': 1, 'd': 3, 'c': 2, 'e':6, 'b':4}
Then you can do something like this:
# x[0] is referring to the key here. if you want to sort based on the value
# then it will be x[1]
sort_orders = dict(sorted(data.items(), key=lambda x: x[0]))
which will give:
{'a': 1, 'b': 4, 'c': 2, 'd': 3, 'e': 6}
Note: this might be case sensitive while sorting the order.

Dictionary values and list values within a function

I have a dictionary with product names and prices:
products = {'a': 2, 'b': 3, 'c': 4, 'd': 5, 'e': 6, 'f': 7, 'g': 8}
And a list with amounts of each product:
amounts = [3, 0, 5, 1, 3, 2, 0]
I want to get an output shown there total price of that order.
Not using functions I seem to get it right:
products = {'a': 2, 'b': 3, 'c': 4, 'd': 5, 'e': 6, 'f': 7, 'g': 8}
amounts = [3, 0, 5, 1, 3, 2, 0]
res_list = []
order = []
for value in products.values():
res_list.append(value)
for i in range(0, len(res_list)):
order.append(amounts[i] * res_list[i])
total = sum(order)
print(res_list)
print(order) #this line and the one above are not really necessary
print(total)
Output : 63
But when I try using this code within a function I am having some problems. this is what I have tried:
products = {'a': 2, 'b': 3, 'c': 4, 'd': 5, 'e': 6, 'f': 7, 'g': 8}
amounts = [3, 0, 5, 1, 3, 2, 0]
#order = []
def order(prod):
res_list = []
for value in prod.values():
res_list.append(value)
return res_list
prices = order(products)
print(prices)
def order1(prices):
order =[]
for i in range(0, len(prices)):
order.append(amounts[i] * prices[i])
total = sum(order)
return total
print(order1(prices))
Not working the way it is intended.
Thanks for all the help I am learning.

The immediate problem is that your lines:
total = sum(order)
return total
are indented too much, so that they are inside the for loop. Outside of a function, the bug does not matter too much, because all that happens is that the total is recalculated on every iteration but the final value is the one that is used. But inside the function, what will happen is that it will return on the first iteration.
Reducing the indentation so that it is outside the for loop will fix this.
def order1(prices):
order =[]
for i in range(0, len(prices)):
order.append(amounts[i] * prices[i])
total = sum(order)
return total
However, separate from that, you are relying on the order within the dictionary, which is only guaranteed for Python 3.7 and more recent. If you want to allow the code to be run reliably on earlier versions of Python, you can use an OrderedDict.
from collections import OrderedDict
products = OrderedDict([('a', 2), ('b', 3), ('c', 4), ('d', 5),
('e', 6), ('f', 7), ('g', 8)])
Incidentally, your order function is unnecessary. If you want to convert products.values() (a dictionary values iterator) to a list, just use:
prices = list(products.values())
Also, in order1 it is unnecessary to build up an order list and sum it - you could use:
total = 0
for i in range(0, len(prices)):
total += amounts[i] * prices[i]
That is probably enough to be getting on with for now, but if you wish to make a further refinement, then look up about how zip is used, and think how it could be used with your loop over amounts and prices.

Just zip products.values() and amounts, find the product of each pair, and then finally sum the result
>>> products = {'a': 2, 'b': 3, 'c': 4, 'd': 5, 'e': 6, 'f': 7, 'g': 8}
>>> amounts = [3, 0, 5, 1, 3, 2, 0]
>>>
>>> sum(i*j for i,j in zip(products.values(), amounts))
63

You can do this.
products = {'a': 2, 'b': 3, 'c': 4, 'd': 5, 'e': 6, 'f': 7, 'g': 8}
amounts = [3, 0, 5, 1, 3, 2, 0]
def order(products, amounts):
res_list = []
order = []
for value in products.values():
res_list.append(value)
for i in range(0, len(res_list)):
order.append(amounts[i] * res_list[i])
total = sum(order)
print(res_list)
print(order) #this line and the one above are not really necessary
print(total)
return(total)
order(products, amounts)

You don't really need to iterate twice assuming that the amount of items in products and in amounts is the same.
products = {'a': 2, 'b': 3, 'c': 4, 'd': 5, 'e': 6, 'f': 7, 'g': 8}
amounts = [3, 0, 5, 1, 3, 2, 0]
def order(products: dict, amounts: list):
total = 0
for idx, (_key, val) in enumerate(products.items()):
total = total + amounts[idx] * val
return total
print(order(products, amounts))
Note: The order of the items in the dictionary is not guaranteed, you might want to look into different data structures that link together products and amounts in a better way, i.e.:
products = {'a': 2, 'b': 3, 'c': 4, 'd': 5, 'e': 6, 'f': 7, 'g': 8}
amounts = {'a': 3, 'b': 0, 'c': 5, 'd': 1, 'e': 3, 'f': 2, 'g': 0}
In this way you could do this:
def order(products: dict, amounts: dict):
total = 0
for key, val in products.items():
total = total + val * amounts[key]
return total
print(order(products, amounts))

Once we're at it, let's get fancy with numpy, since in the end, you just want the dot product prices x amounts:
import numpy as np
total = np.dot(list(products.values()), amounts)
63
But seriously, I'd strictly use either lists or dicts for both datasets, not mix them up, since that can seriously cause problems with order syncronisation between them, even if you are on Python 3.7 with the changes made there as mentioned.

Nesting dictionary algorithm

Suppose I have the following dictionary:
{'a': 0, 'b': 1, 'c': 2, 'c.1': 3, 'd': 4, 'd.1': 5, 'd.1.2': 6}
I wish to write an algorithm which outputs the following:
{
"a": 0,
"b": 1,
"c": {
"c": 2,
"c.1": 3
},
"d":{
"d": 4,
"d.1": {
"d.1": 5,
"d.1.2": 6
}
}
}
Note how the names are repeated inside the dictionary. And some have variable level of nesting (eg. "d").
I was wondering how you would go about doing this, or if there is a python library for this? I know you'd have to use recursion for something like this, but my recursion skills are quite poor. Any thoughts would be highly appreciated.

You can use a recursive function for this or just a loop. The tricky part is wrapping existing values into dictionaries if further child nodes have to be added below them.
def nested(d):
res = {}
for key, val in d.items():
t = res
# descend deeper into the nested dict
for x in [key[:i] for i, c in enumerate(key) if c == "."]:
if x in t and not isinstance(t[x], dict):
# wrap leaf value into another dict
t[x] = {x: t[x]}
t = t.setdefault(x, {})
# add actual key to nested dict
if key in t:
# already exists, go one level deeper
t[key][key] = val
else:
t[key] = val
return res
Your example:
d = {'a': 0, 'b': 1, 'c': 2, 'c.1': 3, 'd': 4, 'd.1': 5, 'd.1.2': 6}
print(nested(d))
# {'a': 0,
# 'b': 1,
# 'c': {'c': 2, 'c.1': 3},
# 'd': {'d': 4, 'd.1': {'d.1': 5, 'd.1.2': 6}}}

Nesting dictionary algorithm ...
how you would go about doing this,
sort the dictionary items
group the result by index 0 of the keys (first item in the tuples)
iterate over the groups
if there are is than one item in a group make a key for the group and add the group items as the values.

Slightly shorter recursion approach with collections.defaultdict:
from collections import defaultdict
data = {'a': 0, 'b': 1, 'c': 2, 'c.1': 3, 'd': 4, 'd.1': 5, 'd.1.2': 6}
def group(d, p = []):
_d, r = defaultdict(list), {}
for n, [a, *b], c in d:
_d[a].append((n, b, c))
for a, b in _d.items():
if (k:=[i for i in b if i[1]]):
r['.'.join(p+[a])] = {**{i[0]:i[-1] for i in b if not i[1]}, **group(k, p+[a])}
else:
r[b[0][0]] = b[0][-1]
return r
print(group([(a, a.split('.'), b) for a, b in data.items()]))
Output:
{'a': 0, 'b': 1, 'c': {'c': 2, 'c.1': 3}, 'd': {'d': 4, 'd.1': {'d.1': 5, 'd.1.2': 6}}}

Remap data according to ranking

I have the following:
d = {"a":3,"b":2,"c":3,"d":2,"e":2,"f":3,"g":4, "h":6}
m = {v: i+1 for i,v in enumerate(sorted(set(d.values()),reverse=True))}
r = {k:m[d[k]] for k in d}
where r is:
{'a': 3, 'd': 4, 'b': 4, 'c': 3, 'e': 4, 'f': 3, 'g': 2, 'h': 1}
So "h" has the highest value, 6, in d so it is remapped to 1 in r. Then 'g' is ranked 2 since it has the next highest value, 4 in d.
My solution works fine but I was wondering if there is a more elegant solution.

Python dicts don't keep order. If you want that you need an OrderedDict.
Use Counter to get the ranks. Then turn that into a list of tuples or into an OrderedDict.
from collections import Counter, OrderedDict
d = {"a":3,"b":2,"c":3,"d":2,"e":2,"f":3,"g":4, "h":6}
c = Counter(d)
# if you want a list of tuples
ranked_list = [(pair[0],rank+1) for rank,pair in enumerate(c.most_common())]
# [('h', 1),('g', 2),('f', 3),('a', 4),('c', 5),('b', 6),('d', 7), ('e', 8)]
# if you want a dict:
ranked_dict = OrderedDict(ranked_list)
# OrderedDict([('h', 1),('g', 2),('f', 3),('a', 4),('c', 5),('b', 6),('d', 7), ('e', 8)])

You can use this:
d = {"a":3,"b":2,"c":3,"d":2,"e":2,"f":3,"g":4, "h":6}
# sort the dictionary items by -value, throw away old value and use the
# enumerate position starting at 1 instead - no backreferencing in the old
# dict needed here
k = {k:idx for idx,(k,_) in enumerate(sorted(d.items(), key = lambda x:-x[1]),1)}
print(k)
Output:
{'h': 1, 'g': 2, 'a': 3, 'c': 4, 'f': 5, 'b': 6, 'd': 7, 'e': 8}

def ranker(d):
ranks = sorted(set(d.values()),reverse=True)
ranks = {r:i+1 for i,r in enumerate(ranks)}
return {k: ranks[v] for k,v in d.items()}