Related
I was making a program where first parameter is a list and second parameter is a list of dictionaries. I want to return a list of lists like this:
As an example, if this were a function call:
make_lists(['Example'],
[{'Example': 'Made-up', 'Extra Keys' : 'Possible'}]
)
the expected return value would be:
[ ['Made-up'] ]
As an second example, if this were a function call:
make_lists(['Hint', 'Num'],
[{'Hint': 'Length 2 Not Required', 'Num' : 8675309},
{'Num': 1, 'Hint' : 'Use 1st param order'}]
)
the expected return value would be:
[ ['Length 2 Not Required', 8675309],
['Use 1st param order', 1]
]
I have written a code for this but my code does not return a list of lists, it just returns a single list. Please can someone explain?
def make_lists(s,lod):
a = []
lol =[]
i = 0
for x in lod:
for y in x:
for k in s:
if(y==k):
lol.append(x.get(y))
i = i+1
return lol
Expected Output:
[ ['Length 2 Not Required', 8675309],['Use 1st param order', 1] ]
Output:
['Length 2 Not Required', 8675309, 1, 'Use 1st param order']
The whole point of dictionaries, is that you can access them by key:
def make_lists(keys, dicts):
result = []
for d in dicts:
vals = [d[k] for k in keys if k in d]
if len(vals) > 0:
result.append(vals)
return result
Let's have a look what happens here:
We still have the result array, which accumulates the answers, but now it's called result instead of lol
Next we iterate through every dictionary:
for d in dicts:
For each dictionary d, we create a list, which is a lookup in that dictionary for the keys in keys, if the key k is in the dictionary d:
vals = [d[k] for k in keys if k in d]
The specs don't detail this, but I assume if none of the keys are in the dictionary, you don't want it added to the array. For that, we have a check if vals have any results, and only then we add it to the results:
if len(vals) > 0:
result.append(vals)
Try this code - I've managed to modify your existing code slighty, and added explanation in the comments. Essentially, you just need to use a sub-list and add that to the master list lol, and then in each loop iteration over elements in lod, append to the sub-list instead of the outermost list.
def make_lists(s,lod):
a = []
lol =[]
i = 0
for x in lod:
## Added
# Here we want to create a new list, and add it as a sub-list
# within 'lol'
lols = []
lol.append(lols)
## Done
for y in x:
for k in s:
if(y==k):
# Changed 'lol' to 'lols' here
lols.append(x.get(y))
i = i+1
return lol
print(make_lists(['Example'], [{'Example': 'Made-up', 'Extra Keys' : 'Possible'}]))
print(make_lists(['Hint', 'Num'], [{'Hint': 'Length 2 Not Required', 'Num' : 8675309}, {'Num': 1, 'Hint' : 'Use 1st param order'}]))
Prints:
[['Made-up']]
[['Length 2 Not Required', 8675309], [1, 'Use 1st param order']]
A simpler solution
For a cleaner (and potentially more efficient approach), I'd suggest using builtins like map and using a list comprehension to tackle this problem:
def make_lists(s, lod):
return [[*map(dict_obj.get, s)] for dict_obj in lod]
But note, that this approach includes elements as None in cases where the desired keys in s are not present in the dictionary objects within the list lod.
To work around that, you can pass the result of map to the filter builtin function so that None values (which represent missing keys in dictionaries) are then stripped out in the result:
def make_lists(s, lod):
return [[*filter(None, map(dict_obj.get, s))] for dict_obj in lod]
print(make_lists(['Example'], [{'Extra Keys' : 'Possible'}]))
print(make_lists(['Hint', 'Num'], [{'Num' : 8675309}, {'Num': 1, 'Hint' : 'Use 1st param order'}]))
Output:
[[]]
[[8675309], ['Use 1st param order', 1]]
I want to write a code to sort arr based on customAl order, and not use sorted function.
customAl = [dshbanfmg]
arr = [bba,abb,baa,mggfba,mffgh......]
psudo code:
def sortCA(arr, customAl):
dt = {}
generate dt order based on customAl
look up and sort arr
return result
newArr = [bba,baa,abb,mffgh,mggfba......]
I know there's a similiar question but the answer is wrapped in sorted function which I don't wish to use. anyone has a better solution than unsorted, or dictionary which takes space?
Sorting string values according to a custom alphabet in Python
In my opinion, programming is a trade-off, it depends on which part you care most.
Specifically, in this scenario, you can choose to trade time for space by str.index, or you can trade space for time with an extra index dict:
customAl = 'dshbanfmg'
arr = ['bba', 'abb', 'baa', 'mggfba', 'mffgh']
# trade time for space
# no extra space but, but O(n) to index
def sortCA1(arr, customAl):
return sorted(arr, key=lambda x: [customAl.index(c) for c in x])
# trade space for time
# extra space O(n), but O(1) to index
def sortCA2(arr, customAl):
dt = {c: i for i, c in enumerate(customAl)}
return sorted(arr, key=lambda x: [dt[c] for c in x])
# output: ['bba', 'baa', 'abb', 'mffgh', 'mggfba']
Here is a version which not use sorted function, we can use a bucket based on custom alphabet order. split the arr by 1st char, if one bucket has multiple elements then split by 2nd char recursively...kind of radix sort:
one thing to mention, the length is different, so we should add a bucket to record none index str.
def sortCA3(arr, customAl):
dt = {c: i + 1 for i, c in enumerate(customAl)} # keep 0 for none bucket
def bucket_sort(arr, start):
new_arr = []
buckets = [[] for _ in range(len(customAl) + 1)]
for s in arr:
if start < len(s):
buckets[dt[s[start]]].append(s)
else:
buckets[0].append(s)
for bucket in buckets:
if len(bucket) == 1:
new_arr += bucket
elif len(bucket) > 1:
new_arr += bucket_sort(bucket, start+1)
return new_arr
return bucket_sort(arr, 0)
test and output
customAl = 'dshbanfmg'
arr = ['bba', 'bb', 'abb', 'baa', 'mggfba', 'mffgh'] # add `bb` for test
print(sortCA4(arr, customAl))
Okay, so this is a little hard to explain, but here goes:
I have a dictionary, which I'm adding content to. The content is a hashed username (key) with an IP address (value).
I was putting the hashes into an order by running them against base 16, and then using Collection.orderedDict.
So, the dictionary looked a little like this:
d = {'1234': '8.8.8.8', '2345':'0.0.0.0', '3213':'4.4.4.4', '4523':'1.1.1.1', '7654':'1.3.3.7', '9999':'127.0.0.1'}
What I needed was a mechanism that would allow me to pick one of those keys, and get the key/value item one higher and one lower. So, for example, If I were to pick 2345, the code would return the key:value combinations '1234:8.8.8.8' and '3213:4.4.4.4'
So, something like:
for i in d:
while i < len(d)
if i == '2345':
print i.nextItem
print i.previousItem
break()
Edit: OP now states that they are using OrderedDicts but the use case still requires this sort of approach.
Since dicts are not ordered you cannot directly do this. From your example, you are trying to reference the item like you would use a linked list.
A quick solution would be instead to extract the keys and sort them then iterate over that list:
keyList=sorted(d.keys())
for i,v in enumerate(keyList):
if v=='eeee':
print d[keyList[i+1]]
print d[keyList[i-1]]
The keyList holds the order of your items and you have to go back to it to find out what the next/previous key is to get the next/previous value. You also have to check for i+1 being greater than the list length and i-1 being less than 0.
You can use an OrderedDict similarly but I believe that you still have to do the above with a separate list as OrderedDict doesn't have next/prev methods.
As seen in the OrderedDict source code,
if you have a key and you want to find the next and prev in O(1) here's how you do that.
>>> from collections import OrderedDict
>>> d = OrderedDict([('aaaa', 'a',), ('bbbb', 'b'), ('cccc', 'c'), ('dddd', 'd'), ('eeee', 'e'), ('ffff', 'f')])
>>> i = 'eeee'
>>> link_prev, link_next, key = d._OrderedDict__map['eeee']
>>> print 'nextKey: ', link_next[2], 'prevKey: ', link_prev[2]
nextKey: ffff prevKey: dddd
This will give you next and prev by insertion order. If you add items in random order then just keep track of your items in sorted order.
You could also use the list.index() method.
This function is more generic (you can check positions +n and -n), it will catch attempts at searching a key that's not in the dict, and it will also return None if there's nothing before of after the key:
def keyshift(dictionary, key, diff):
if key in dictionary:
token = object()
keys = [token]*(diff*-1) + sorted(dictionary) + [token]*diff
newkey = keys[keys.index(key)+diff]
if newkey is token:
print None
else:
print {newkey: dictionary[newkey]}
else:
print 'Key not found'
keyshift(d, 'bbbb', -1)
keyshift(d, 'eeee', +1)
Try:
pos = 0
d = {'aaaa': 'a', 'bbbb':'b', 'cccc':'c', 'dddd':'d', 'eeee':'e', 'ffff':'f'}
for i in d:
pos+=1
if i == 'eeee':
listForm = list(d.values())
print(listForm[pos-1])
print(listForm[pos+1])
As in #AdamKerz's answer enumerate seems pythonic, but if you are a beginner this code might help you understand it in an easy way.
And I think its faster + smaller compared to sorting followed by building list & then enumerating
You could use a generic function, based on iterators, to get a moving window (taken from this question):
import itertools
def window(iterable, n=3):
it = iter(iterable)
result = tuple(itertools.islice(it, n))
if len(result) == n:
yield result
for element in it:
result = result[1:] + (element,)
yield result
l = range(8)
for i in window(l, 3):
print i
Using the above function with OrderedDict.items() will give you three (key, value) pairs, in order:
d = collections.OrderedDict(...)
for p_item, item, n_item in window(d.items()):
p_key, p_value = p_item
key, value = item
# Or, if you don't care about the next value:
n_key, _ = n_item
Of course using this function the first and last values will never be in the middle position (although this should not be difficult to do with some adaptation).
I think the biggest advantage is that it does not require table lookups in the previous and next keys, and also that it is generic and works with any iterable.
Maybe it is an overkill, but you can keep Track of the Keys inserted with a Helper Class and according to that list, you can retrieve the Key for Previous or Next. Just don't forget to check for border conditions, if the objects is already first or last element. This way, you will not need to always resort the ordered list or search for the element.
from collections import OrderedDict
class Helper(object):
"""Helper Class for Keeping track of Insert Order"""
def __init__(self, arg):
super(Helper, self).__init__()
dictContainer = dict()
ordering = list()
#staticmethod
def addItem(dictItem):
for key,value in dictItem.iteritems():
print key,value
Helper.ordering.append(key)
Helper.dictContainer[key] = value
#staticmethod
def getPrevious(key):
index = (Helper.ordering.index(key)-1)
return Helper.dictContainer[Helper.ordering[index]]
#Your unordered dictionary
d = {'aaaa': 'a', 'bbbb':'b', 'cccc':'c', 'dddd':'d', 'eeee':'e', 'ffff':'f'}
#Create Order over keys
ordered = OrderedDict(sorted(d.items(), key=lambda t: t[0]))
#Push your ordered list to your Helper class
Helper.addItem(ordered)
#Get Previous of
print Helper.getPrevious('eeee')
>>> d
You can store the keys and values in temp variable in prior, and can access previous and next key,value pair using index.
It is pretty dynamic, will work for any key you query. Please check this code :
d = {'1234': '8.8.8.8', '2345':'0.0.0.0', '3213':'4.4.4.4', '4523':'1.1.1.1', '7654':'1.3.3.7', '9999':'127.0.0.1'}
ch = raw_input('Pleasure Enter your choice : ')
keys = d.keys()
values = d.values()
#print keys, values
for k,v in d.iteritems():
if k == ch:
ind = d.keys().index(k)
print keys[ind-1], ':',values[ind-1]
print keys[ind+1], ':',values[ind+1]
I think this is a nice Pythonic way of resolving your problem using a lambda and list comprehension, although it may not be optimal in execution time:
import collections
x = collections.OrderedDict([('a','v1'),('b','v2'),('c','v3'),('d','v4')])
previousItem = lambda currentKey, thisOrderedDict : [
list( thisOrderedDict.items() )[ z - 1 ] if (z != 0) else None
for z in range( len( thisOrderedDict.items() ) )
if (list( thisOrderedDict.keys() )[ z ] == currentKey) ][ 0 ]
nextItem = lambda currentKey, thisOrderedDict : [
list( thisOrderedDict.items() )[ z + 1 ] if (z != (len( thisOrderedDict.items() ) - 1)) else None
for z in range( len( thisOrderedDict.items() ) )
if (list( thisOrderedDict.keys() )[ z ] == currentKey) ][ 0 ]
assert previousItem('c', x) == ('b', 'v2')
assert nextItem('c', x) == ('d', 'v4')
assert previousItem('a', x) is None
assert nextItem('d',x) is None
Another way that seems simple and straight forward: this function returns the key which is offset positions away from k
def get_shifted_key(d:dict, k:str, offset:int) -> str:
l = list(d.keys())
if k in l:
i = l.index(k) + offset
if 0 <= i < len(l):
return l[i]
return None
i know how to get next key:value of a particular key in a dictionary:
flag = 0
for k, v in dic.items():
if flag == 0:
code...
flag += 1
continue
code...{next key and value in for}
if correct :
d = { "a": 1, "b":2, "c":3 }
l = list( d.keys() ) # make a list of the keys
k = "b" # the actual key
i = l.index( k ) # get index of the actual key
for the next :
i = i+1 if i+1 < len( l ) else 0 # select next index or restart 0
n = l [ i ]
d [ n ]
for the previous :
i = i-1 if i-1 >= 0 else len( l ) -1 # select previous index or go end
p = l [ i ]
d [ p ]
I have the following 2 lists in python:
ll = [500,500,500,501,500,502,500]
mm = [499,501,502]
I want to find out the position of last occurence of any item in mm, in the list ll. I can do this for a single element like this:
len(ll) - 1 - ll[::-1].index(502)
>> 5
Here ll[::-1].index(502) provides position of last occurence of 502 and len(ll) - 1 gives the total length.
How do I extend this to work for the entire list mm? I know I can write a function, but is there a more pythonic way
If you want all the last indices of each item in ll present in mm, then:
ll = [500,500,500,501,500,502,500]
mm = [499,501,502]
d = {v:k for k,v in enumerate(ll) if v in mm}
# {501: 3, 502: 5}
It's probably worth creating a set from mm first to make it an O(1) lookup, instead of O(N), but for three items, it's really not worth it.
Following #Apero's concerns about retaining missing indices as None and also using a hash lookup to make it an O(1) lookup...
# Build a key->None dict for all `mm`
d = dict.fromkeys(mm)
# Update `None` values with last index using a gen-exp instead of dict-comp
d.update((v,k) for k,v in enumerate(ll) if v in d)
# {499: None, 501: 3, 502: 5}
results = {}
reversed = ll[::-1]
for item in mm:
try:
index = ((len(ll) - 1) - reversed.index(item))
except ValueError:
index = None
finally:
results[item] = index
print results
Output:
{499: None, 501: 3, 502: 5}
You can do this with a list comprehension and the max function. In particular, for each element in ll, iterate through mm to create a list of indices where ll[i] = mm[i], and take the max of this list.
>>> indices = [ max([-1] + [i for i, m in enumerate(mm) if m == n]) for n in ll ]
>>> indices
[-1, -1, -1, 1, -1, 2, -1]
Note that you need to add [-1] in case there are no matching indices in mm.
All this being said, I don't think it's more Python-ic than writing a function and using a list comprehension (as you alluded to in your question).
I'm creating a class where one of the methods inserts a new item into the sorted list. The item is inserted in the corrected (sorted) position in the sorted list. I'm not allowed to use any built-in list functions or methods other than [], [:], +, and len though. This is the part that's really confusing to me.
What would be the best way in going about this?
Use the insort function of the bisect module:
import bisect
a = [1, 2, 4, 5]
bisect.insort(a, 3)
print(a)
Output
[1, 2, 3, 4, 5]
Hint 1: You might want to study the Python code in the bisect module.
Hint 2: Slicing can be used for list insertion:
>>> s = ['a', 'b', 'd', 'e']
>>> s[2:2] = ['c']
>>> s
['a', 'b', 'c', 'd', 'e']
You should use the bisect module. Also, the list needs to be sorted before using bisect.insort_left
It's a pretty big difference.
>>> l = [0, 2, 4, 5, 9]
>>> bisect.insort_left(l,8)
>>> l
[0, 2, 4, 5, 8, 9]
timeit.timeit("l.append(8); l = sorted(l)",setup="l = [4,2,0,9,5]; import bisect; l = sorted(l)",number=10000)
1.2235019207000732
timeit.timeit("bisect.insort_left(l,8)",setup="l = [4,2,0,9,5]; import bisect; l=sorted(l)",number=10000)
0.041441917419433594
I'm learning Algorithm right now, so i wonder how bisect module writes.
Here is the code from bisect module about inserting an item into sorted list, which uses dichotomy:
def insort_right(a, x, lo=0, hi=None):
"""Insert item x in list a, and keep it sorted assuming a is sorted.
If x is already in a, insert it to the right of the rightmost x.
Optional args lo (default 0) and hi (default len(a)) bound the
slice of a to be searched.
"""
if lo < 0:
raise ValueError('lo must be non-negative')
if hi is None:
hi = len(a)
while lo < hi:
mid = (lo+hi)//2
if x < a[mid]:
hi = mid
else:
lo = mid+1
a.insert(lo, x)
If there are no artificial restrictions, bisect.insort() should be used as described by stanga. However, as Velda mentioned in a comment, most real-world problems go beyond sorting pure numbers.
Fortunately, as commented by drakenation, the solution applies to any comparable objects. For example, bisect.insort() also works with a custom dataclass that implements __lt__():
from bisect import insort
#dataclass
class Person:
first_name: str
last_name: str
age: int
def __lt__(self, other):
return self.age < other.age
persons = []
insort(persons, Person('John', 'Doe', 30))
insort(persons, Person('Jane', 'Doe', 28))
insort(persons, Person('Santa', 'Claus', 1750))
# [Person(first_name='Jane', last_name='Doe', age=28), Person(first_name='John', last_name='Doe', age=30), Person(first_name='Santa', last_name='Claus', age=1750)]
However, in the case of tuples, it would be desirable to sort by an arbitrary key. By default, tuples are sorted by their first item (first name), then by the next item (last name), and so on.
As a solution you can manage an additional list of keys:
from bisect import bisect
persons = []
ages = []
def insert_person(person):
age = person[2]
i = bisect(ages, age)
persons.insert(i, person)
ages.insert(i, age)
insert_person(('John', 'Doe', 30))
insert_person(('Jane', 'Doe', 28))
insert_person(('Santa', 'Claus', 1750))
Official solution: The documentation of bisect.insort() refers to a recipe how to use the function to implement this functionality in a custom class SortedCollection, so that it can be used as follows:
>>> s = SortedCollection(key=itemgetter(2))
>>> for record in [
... ('roger', 'young', 30),
... ('angela', 'jones', 28),
... ('bill', 'smith', 22),
... ('david', 'thomas', 32)]:
... s.insert(record)
>>> pprint(list(s)) # show records sorted by age
[('bill', 'smith', 22),
('angela', 'jones', 28),
('roger', 'young', 30),
('david', 'thomas', 32)]
Following is the relevant extract of the class required to make the example work. Basically, the SortedCollection manages an additional list of keys in parallel to the items list to find out where to insert the new tuple (and its key).
from bisect import bisect_left
class SortedCollection(object):
def __init__(self, iterable=(), key=None):
self._given_key = key
key = (lambda x: x) if key is None else key
decorated = sorted((key(item), item) for item in iterable)
self._keys = [k for k, item in decorated]
self._items = [item for k, item in decorated]
self._key = key
def __getitem__(self, i):
return self._items[i]
def __iter__(self):
return iter(self._items)
def insert(self, item):
'Insert a new item. If equal keys are found, add to the left'
k = self._key(item)
i = bisect_left(self._keys, k)
self._keys.insert(i, k)
self._items.insert(i, item)
Note that list.insert() as well as bisect.insort() have O(n) complexity. Thus, as commented by nz_21, manually iterating through the sorted list, looking for the right position, would be just as good in terms of complexity. In fact, simply sorting the array after inserting a new value will probably be fine, too, since Python's Timsort has a worst-case complexity of O(n log(n)). For completeness, however, note that a binary search tree (BST) would allow insertions in O(log(n)) time.
This is a possible solution for you:
a = [15, 12, 10]
b = sorted(a)
print b # --> b = [10, 12, 15]
c = 13
for i in range(len(b)):
if b[i] > c:
break
d = b[:i] + [c] + b[i:]
print d # --> d = [10, 12, 13, 15]
# function to insert a number in an sorted list
def pstatement(value_returned):
return print('new sorted list =', value_returned)
def insert(input, n):
print('input list = ', input)
print('number to insert = ', n)
print('range to iterate is =', len(input))
first = input[0]
print('first element =', first)
last = input[-1]
print('last element =', last)
if first > n:
list = [n] + input[:]
return pstatement(list)
elif last < n:
list = input[:] + [n]
return pstatement(list)
else:
for i in range(len(input)):
if input[i] > n:
break
list = input[:i] + [n] + input[i:]
return pstatement(list)
# Input values
listq = [2, 4, 5]
n = 1
insert(listq, n)
Well there are many ways to do this, here is a simple naive program to do the same using inbuilt Python function sorted()
def sorted_inserter():
list_in = []
n1 = int(input("How many items in the list : "))
for i in range (n1):
e1 = int(input("Enter numbers in list : "))
list_in.append(e1)
print("The input list is : ",list_in)
print("Any more items to be inserted ?")
n2 = int(input("How many more numbers to be added ? : "))
for j in range (n2):
e2= int(input("Add more numbers : "))
list_in.append(e2)
list_sorted=sorted(list_in)
print("The sorted list is: ",list_sorted)
sorted_inserter()
The output is
How many items in the list : 4
Enter numbers in list : 1
Enter numbers in list : 2
Enter numbers in list : 123
Enter numbers in list : 523
The input list is : [1, 2, 123, 523]
Any more items to be inserted ?
How many more numbers to be added ? : 1
Add more numbers : 9
The sorted list is: [1, 2, 9, 123, 523]
To add to the existing answers: When you want to insert an element into a list of tuples where the first element is comparable and the second is not you can use the key parameter of the bisect.insort function as follows:
import bisect
class B:
pass
a = [(1, B()), (2, B()), (3, B())]
bisect.insort(a, (3, B()), key=lambda x: x[0])
print(a)
Without the lambda function as the third parameter of the bisect.insort function the code would throw a TypeError as the function would try to compare the second element of a tuple as a tie breaker which isn't comparable by default.
This is the best way to append the list and insert values to sorted list:
a = [] num = int(input('How many numbers: ')) for n in range(num):
numbers = int(input('Enter values:'))
a.append(numbers)
b = sorted(a) print(b) c = int(input("enter value:")) for i in
range(len(b)):
if b[i] > c:
index = i
break d = b[:i] + [c] + b[i:] print(d)`