I am attempting to wrap an API with the following function. The API has end points that look similar to this:
/users/{ids}
/users/{ids}/permissions
The idea is that I'll be able to pass a dictionary to my function that contains a list of ids and those will be formatted as the API expects:
users = {'ids': [1, 2, 3, 5]}
call_api('/users/{ids}/permissions', users)
Then in call_api, I currently do something like this
def call_api(url, data):
for k, value in data.items():
if "{" + key + "}" in url:
url = url.replace("{"+k+"}", ';'.join(str(x) for x in value))
data.pop(k, None)
This works, but I can't imagine that if statement is efficient.
How can I improve it and have it work in both Python 2.7 and Python 3.5?
I've also been told that changing the dictionary while iterating is bad, but in my tests I've never had an issue. I am poping the value, because I later check if there are unexpected parameters (ie. anything left in data). Is what I'm doing now the right way?
Instead of modifying a dictionary as you iterate over it, creating another object to hold the unused keys is probably the way to go. In Python 3.4+, at least, removing keys during iteration will raise a
RuntimeError: dictionary changed size during iteration.
def call_api(url, data):
unused_keys = set()
for k, value in data.items():
key_pattern = "{" + k + "}"
if key_pattern in url:
formatted_value = ';'.join(map(str, value))
url = url.replace(key_pattern, formatted_value)
else:
unused_keys.add(k)
Also, if you think that you're more likely to run into an unused key, reversing the conditions might be the way to go.
Here is the way to do it. First, the string is parsed for the keys. It then remembers all keys not used in the url and saves it in the side. Lastly, it formats the url with the given parameters of the dict. The function returns the unused variables and the formatted url. If you wish you can remove the unused variables from the dict by iterating over them and deleting from the dict.
Here's some documentation with examples regarding the format syntax.
import string
users = {'ids': [1, 2, 3, 5]}
def call_api(url, data):
data_set = set(data)
formatter = string.Formatter()
used_set = {f[1] for f in formatter.parse(url) if f[1] is not None}
unused_set = data_set - used_set
formatted = url.format(**{k: ";".join(str(x) for x in v)
for k, v in data.items()})
return unused_set, formatted
print(call_api('/users/{ids}/permissions', users))
You could use re.subn which returns the number of replacements made:
import re
def call_api(url, data):
for k, value in list(data.items()):
url, n = re.subn(r'\{%s\}' % k, ';'.join(str(x) for x in value), url)
if n:
del data[k]
Note that for compatibilty with both python2 and python3, it is also necessary to create a copy of the list of items when destructively iterating over the dict.
EDIT:
It seems the main bottleneck is checking that the key is in the url. The in operator is easily the most efficient way to do this, and is much faster than a regex for the simple pattern that is being used here. Recording the unused keys separately is also more efficient than destructive iteration, but it doesn't make as much difference (relatively speaking).
So: there's not much wrong with the original solution, but the one given by #wegry is the most efficient.
The formatting keys can be found with a RegEx and then compared to the keys in the dictionary. Your string is already setup to use str.format, so you apply a transformation to the values in data, and then apply that transformation.
import re
from toolz import valmap
def call_api(url, data):
unused = set(data) - set(re.findall('\{(\w+)\}', url))
url = url.format_map(valmap(lambda v: ';'.join(map(str, v)), data))
return url, unused
The usage looks like:
users = {'ids': [1, 2, 3, 5], 'unused_key': 'value'}
print(call_api('/users/{ids}/permissions', users))
# ('/users/1;2;3;5/permissions', {'unused_key'})
This isn't going to time that well, but it's concise. As noted in one of the comments, it seems unlikely that this method is be a bottleneck.
Related
Let's say we have a Python dictionary d, and we're iterating over it like so:
for k, v in d.iteritems():
del d[f(k)] # remove some item
d[g(k)] = v # add a new item
(f and g are just some black-box transformations.)
In other words, we try to add/remove items to d while iterating over it using iteritems.
Is this well defined? Could you provide some references to support your answer?
See also How to avoid "RuntimeError: dictionary changed size during iteration" error? for the separate question of how to avoid the problem.
Alex Martelli weighs in on this here.
It may not be safe to change the container (e.g. dict) while looping over the container.
So del d[f(k)] may not be safe. As you know, the workaround is to use d.copy().items() (to loop over an independent copy of the container) instead of d.iteritems() or d.items() (which use the same underlying container).
It is okay to modify the value at an existing index of the dict, but inserting values at new indices (e.g. d[g(k)] = v) may not work.
It is explicitly mentioned on the Python doc page (for Python 2.7) that
Using iteritems() while adding or deleting entries in the dictionary may raise a RuntimeError or fail to iterate over all entries.
Similarly for Python 3.
The same holds for iter(d), d.iterkeys() and d.itervalues(), and I'll go as far as saying that it does for for k, v in d.items(): (I can't remember exactly what for does, but I would not be surprised if the implementation called iter(d)).
You cannot do that, at least with d.iteritems(). I tried it, and Python fails with
RuntimeError: dictionary changed size during iteration
If you instead use d.items(), then it works.
In Python 3, d.items() is a view into the dictionary, like d.iteritems() in Python 2. To do this in Python 3, instead use d.copy().items(). This will similarly allow us to iterate over a copy of the dictionary in order to avoid modifying the data structure we are iterating over.
I have a large dictionary containing Numpy arrays, so the dict.copy().keys() thing suggested by #murgatroid99 was not feasible (though it worked). Instead, I just converted the keys_view to a list and it worked fine (in Python 3.4):
for item in list(dict_d.keys()):
temp = dict_d.pop(item)
dict_d['some_key'] = 1 # Some value
I realize this doesn't dive into the philosophical realm of Python's inner workings like the answers above, but it does provide a practical solution to the stated problem.
The following code shows that this is not well defined:
def f(x):
return x
def g(x):
return x+1
def h(x):
return x+10
try:
d = {1:"a", 2:"b", 3:"c"}
for k, v in d.iteritems():
del d[f(k)]
d[g(k)] = v+"x"
print d
except Exception as e:
print "Exception:", e
try:
d = {1:"a", 2:"b", 3:"c"}
for k, v in d.iteritems():
del d[f(k)]
d[h(k)] = v+"x"
print d
except Exception as e:
print "Exception:", e
The first example calls g(k), and throws an exception (dictionary changed size during iteration).
The second example calls h(k) and throws no exception, but outputs:
{21: 'axx', 22: 'bxx', 23: 'cxx'}
Which, looking at the code, seems wrong - I would have expected something like:
{11: 'ax', 12: 'bx', 13: 'cx'}
Python 3 you should just:
prefix = 'item_'
t = {'f1': 'ffw', 'f2': 'fca'}
t2 = dict()
for k,v in t.items():
t2[k] = prefix + v
or use:
t2 = t1.copy()
You should never modify original dictionary, it leads to confusion as well as potential bugs or RunTimeErrors. Unless you just append to the dictionary with new key names.
This question asks about using an iterator (and funny enough, that Python 2 .iteritems iterator is no longer supported in Python 3) to delete or add items, and it must have a No as its only right answer as you can find it in the accepted answer. Yet: most of the searchers try to find a solution, they will not care how this is done technically, be it an iterator or a recursion, and there is a solution for the problem:
You cannot loop-change a dict without using an additional (recursive) function.
This question should therefore be linked to a question that has a working solution:
How can I remove a key:value pair wherever the chosen key occurs in a deeply nested dictionary? (= "delete")
Also helpful as it shows how to change the items of a dict on the run: How can I replace a key:value pair by its value wherever the chosen key occurs in a deeply nested dictionary? (= "replace").
By the same recursive methods, you will also able to add items as the question asks for as well.
Since my request to link this question was declined, here is a copy of the solution that can delete items from a dict. See How can I remove a key:value pair wherever the chosen key occurs in a deeply nested dictionary? (= "delete") for examples / credits / notes.
import copy
def find_remove(this_dict, target_key, bln_overwrite_dict=False):
if not bln_overwrite_dict:
this_dict = copy.deepcopy(this_dict)
for key in this_dict:
# if the current value is a dict, dive into it
if isinstance(this_dict[key], dict):
if target_key in this_dict[key]:
this_dict[key].pop(target_key)
this_dict[key] = find_remove(this_dict[key], target_key)
return this_dict
dict_nested_new = find_remove(nested_dict, "sub_key2a")
The trick
The trick is to find out in advance whether a target_key is among the next children (= this_dict[key] = the values of the current dict iteration) before you reach the child level recursively. Only then you can still delete a key:value pair of the child level while iterating over a dictionary. Once you have reached the same level as the key to be deleted and then try to delete it from there, you would get the error:
RuntimeError: dictionary changed size during iteration
The recursive solution makes any change only on the next values' sub-level and therefore avoids the error.
I got the same problem and I used following procedure to solve this issue.
Python List can be iterate even if you modify during iterating over it.
so for following code it will print 1's infinitely.
for i in list:
list.append(1)
print 1
So using list and dict collaboratively you can solve this problem.
d_list=[]
d_dict = {}
for k in d_list:
if d_dict[k] is not -1:
d_dict[f(k)] = -1 # rather than deleting it mark it with -1 or other value to specify that it will be not considered further(deleted)
d_dict[g(k)] = v # add a new item
d_list.append(g(k))
Today I had a similar use-case, but instead of simply materializing the keys on the dictionary at the beginning of the loop, I wanted changes to the dict to affect the iteration of the dict, which was an ordered dict.
I ended up building the following routine, which can also be found in jaraco.itertools:
def _mutable_iter(dict):
"""
Iterate over items in the dict, yielding the first one, but allowing
it to be mutated during the process.
>>> d = dict(a=1)
>>> it = _mutable_iter(d)
>>> next(it)
('a', 1)
>>> d
{}
>>> d.update(b=2)
>>> list(it)
[('b', 2)]
"""
while dict:
prev_key = next(iter(dict))
yield prev_key, dict.pop(prev_key)
The docstring illustrates the usage. This function could be used in place of d.iteritems() above to have the desired effect.
In a directory images, images are named like - 1_foo.png, 2_foo.png, 14_foo.png, etc.
The images are OCR'd and the text extract is stored in a dict by the code below -
data_dict = {}
for i in os.listdir(images):
if str(i[1]) != '_':
k = str(i[:2]) # Get first two characters of image name and use as 'key'
else:
k = str(i[:1]) # Get first character of image name and use 'key'
# Intiates a list for each key and allows storing multiple entries
data_dict.setdefault(k, [])
data_dict[k].append(pytesseract.image_to_string(i))
The code performs as expected.
The images can have varying numbers in their name ranging from 1 to 99.
Can this be reduced to a dictionary comprehension?
No. Each iteration in a dict comprehension assigns a value to a key; it cannot update an existing value list. Dict comprehensions aren't always better--the code you wrote seems good enough. Although maybe you could write
data_dict = {}
for i in os.listdir(images):
k = i.partition("_")[0]
image_string = pytesseract.image_to_string(i)
data_dict.setdefault(k, []).append(image_string)
Yes. Here's one way, but I wouldn't recommend it:
{k: d.setdefault(k, []).append(pytesseract.image_to_string(i)) or d[k]
for d in [{}]
for k, i in ((i.split('_')[0], i) for i in names)}
That might be as clean as I can make it, and it's still bad. Better use a normal loop, especially a clean one like Dennis's.
Slight variation (if I do the abuse once, I might as well do it twice):
{k: d.setdefault(k, []).append(pytesseract_image_to_string(i)) or d[k]
for d in [{}]
for i in names
for k in i.split('_')[:1]}
Edit: kaya3 now posted a good one using a dict comprehension. I'd recommend that over mine as well. Mine are really just the dirty results of me being like "Someone said it can't be done? Challenge accepted!".
In this case itertools.groupby can be useful; you can group the filenames by the numeric part. But making it work is not easy, because the groups have to be contiguous in the sequence.
That means before we can use groupby, we need to sort using a key function which extracts the numeric part. That's the same key function we want to group by, so it makes sense to write the key function separately.
from itertools import groupby
def image_key(image):
return str(image).partition('_')[0]
images = ['1_foo.png', '2_foo.png', '3_bar.png', '1_baz.png']
result = {
k: list(v)
for k, v in groupby(sorted(images, key=image_key), key=image_key)
}
# {'1': ['1_foo.png', '1_baz.png'],
# '2': ['2_foo.png'],
# '3': ['3_bar.png']}
Replace list(v) with list(map(pytesseract.image_to_string, v)) for your use-case.
I need to parse a json file which unfortunately for me, does not follow the prototype. I have two issues with the data, but i've already found a workaround for it so i'll just mention it at the end, maybe someone can help there as well.
So i need to parse entries like this:
"Test":{
"entry":{
"Type":"Something"
},
"entry":{
"Type":"Something_Else"
}
}, ...
The json default parser updates the dictionary and therfore uses only the last entry. I HAVE to somehow store the other one as well, and i have no idea how to do this. I also HAVE to store the keys in the several dictionaries in the same order they appear in the file, thats why i am using an OrderedDict to do so. it works fine, so if there is any way to expand this with the duplicate entries i'd be grateful.
My second issue is that this very same json file contains entries like that:
"Test":{
{
"Type":"Something"
}
}
Json.load() function raises an exception when it reaches that line in the json file. The only way i worked around this was to manually remove the inner brackets myself.
Thanks in advance
You can use JSONDecoder.object_pairs_hook to customize how JSONDecoder decodes objects. This hook function will be passed a list of (key, value) pairs that you usually do some processing on, and then turn into a dict.
However, since Python dictionaries don't allow for duplicate keys (and you simply can't change that), you can return the pairs unchanged in the hook and get a nested list of (key, value) pairs when you decode your JSON:
from json import JSONDecoder
def parse_object_pairs(pairs):
return pairs
data = """
{"foo": {"baz": 42}, "foo": 7}
"""
decoder = JSONDecoder(object_pairs_hook=parse_object_pairs)
obj = decoder.decode(data)
print obj
Output:
[(u'foo', [(u'baz', 42)]), (u'foo', 7)]
How you use this data structure is up to you. As stated above, Python dictionaries won't allow for duplicate keys, and there's no way around that. How would you even do a lookup based on a key? dct[key] would be ambiguous.
So you can either implement your own logic to handle a lookup the way you expect it to work, or implement some sort of collision avoidance to make keys unique if they're not, and then create a dictionary from your nested list.
Edit: Since you said you would like to modify the duplicate key to make it unique, here's how you'd do that:
from collections import OrderedDict
from json import JSONDecoder
def make_unique(key, dct):
counter = 0
unique_key = key
while unique_key in dct:
counter += 1
unique_key = '{}_{}'.format(key, counter)
return unique_key
def parse_object_pairs(pairs):
dct = OrderedDict()
for key, value in pairs:
if key in dct:
key = make_unique(key, dct)
dct[key] = value
return dct
data = """
{"foo": {"baz": 42, "baz": 77}, "foo": 7, "foo": 23}
"""
decoder = JSONDecoder(object_pairs_hook=parse_object_pairs)
obj = decoder.decode(data)
print obj
Output:
OrderedDict([(u'foo', OrderedDict([(u'baz', 42), ('baz_1', 77)])), ('foo_1', 7), ('foo_2', 23)])
The make_unique function is responsible for returning a collision-free key. In this example it just suffixes the key with _n where n is an incremental counter - just adapt it to your needs.
Because the object_pairs_hook receives the pairs exactly in the order they appear in the JSON document, it's also possible to preserve that order by using an OrderedDict, I included that as well.
Thanks a lot #Lukas Graf, i got it working as well by implementing my own version of the hook function
def dict_raise_on_duplicates(ordered_pairs):
count=0
d=collections.OrderedDict()
for k,v in ordered_pairs:
if k in d:
d[k+'_dupl_'+str(count)]=v
count+=1
else:
d[k]=v
return d
Only thing remaining is to automatically get rid of the double brackets and i am done :D Thanks again
If you would prefer to convert those duplicated keys into an array, instead of having separate copies, this could do the work:
def dict_raise_on_duplicates(ordered_pairs):
"""Convert duplicate keys to JSON array."""
d = {}
for k, v in ordered_pairs:
if k in d:
if type(d[k]) is list:
d[k].append(v)
else:
d[k] = [d[k],v]
else:
d[k] = v
return d
And then you just use:
dict = json.loads(yourString, object_pairs_hook=dict_raise_on_duplicates)
Let's say we have a Python dictionary d, and we're iterating over it like so:
for k, v in d.iteritems():
del d[f(k)] # remove some item
d[g(k)] = v # add a new item
(f and g are just some black-box transformations.)
In other words, we try to add/remove items to d while iterating over it using iteritems.
Is this well defined? Could you provide some references to support your answer?
See also How to avoid "RuntimeError: dictionary changed size during iteration" error? for the separate question of how to avoid the problem.
Alex Martelli weighs in on this here.
It may not be safe to change the container (e.g. dict) while looping over the container.
So del d[f(k)] may not be safe. As you know, the workaround is to use d.copy().items() (to loop over an independent copy of the container) instead of d.iteritems() or d.items() (which use the same underlying container).
It is okay to modify the value at an existing index of the dict, but inserting values at new indices (e.g. d[g(k)] = v) may not work.
It is explicitly mentioned on the Python doc page (for Python 2.7) that
Using iteritems() while adding or deleting entries in the dictionary may raise a RuntimeError or fail to iterate over all entries.
Similarly for Python 3.
The same holds for iter(d), d.iterkeys() and d.itervalues(), and I'll go as far as saying that it does for for k, v in d.items(): (I can't remember exactly what for does, but I would not be surprised if the implementation called iter(d)).
You cannot do that, at least with d.iteritems(). I tried it, and Python fails with
RuntimeError: dictionary changed size during iteration
If you instead use d.items(), then it works.
In Python 3, d.items() is a view into the dictionary, like d.iteritems() in Python 2. To do this in Python 3, instead use d.copy().items(). This will similarly allow us to iterate over a copy of the dictionary in order to avoid modifying the data structure we are iterating over.
I have a large dictionary containing Numpy arrays, so the dict.copy().keys() thing suggested by #murgatroid99 was not feasible (though it worked). Instead, I just converted the keys_view to a list and it worked fine (in Python 3.4):
for item in list(dict_d.keys()):
temp = dict_d.pop(item)
dict_d['some_key'] = 1 # Some value
I realize this doesn't dive into the philosophical realm of Python's inner workings like the answers above, but it does provide a practical solution to the stated problem.
The following code shows that this is not well defined:
def f(x):
return x
def g(x):
return x+1
def h(x):
return x+10
try:
d = {1:"a", 2:"b", 3:"c"}
for k, v in d.iteritems():
del d[f(k)]
d[g(k)] = v+"x"
print d
except Exception as e:
print "Exception:", e
try:
d = {1:"a", 2:"b", 3:"c"}
for k, v in d.iteritems():
del d[f(k)]
d[h(k)] = v+"x"
print d
except Exception as e:
print "Exception:", e
The first example calls g(k), and throws an exception (dictionary changed size during iteration).
The second example calls h(k) and throws no exception, but outputs:
{21: 'axx', 22: 'bxx', 23: 'cxx'}
Which, looking at the code, seems wrong - I would have expected something like:
{11: 'ax', 12: 'bx', 13: 'cx'}
Python 3 you should just:
prefix = 'item_'
t = {'f1': 'ffw', 'f2': 'fca'}
t2 = dict()
for k,v in t.items():
t2[k] = prefix + v
or use:
t2 = t1.copy()
You should never modify original dictionary, it leads to confusion as well as potential bugs or RunTimeErrors. Unless you just append to the dictionary with new key names.
This question asks about using an iterator (and funny enough, that Python 2 .iteritems iterator is no longer supported in Python 3) to delete or add items, and it must have a No as its only right answer as you can find it in the accepted answer. Yet: most of the searchers try to find a solution, they will not care how this is done technically, be it an iterator or a recursion, and there is a solution for the problem:
You cannot loop-change a dict without using an additional (recursive) function.
This question should therefore be linked to a question that has a working solution:
How can I remove a key:value pair wherever the chosen key occurs in a deeply nested dictionary? (= "delete")
Also helpful as it shows how to change the items of a dict on the run: How can I replace a key:value pair by its value wherever the chosen key occurs in a deeply nested dictionary? (= "replace").
By the same recursive methods, you will also able to add items as the question asks for as well.
Since my request to link this question was declined, here is a copy of the solution that can delete items from a dict. See How can I remove a key:value pair wherever the chosen key occurs in a deeply nested dictionary? (= "delete") for examples / credits / notes.
import copy
def find_remove(this_dict, target_key, bln_overwrite_dict=False):
if not bln_overwrite_dict:
this_dict = copy.deepcopy(this_dict)
for key in this_dict:
# if the current value is a dict, dive into it
if isinstance(this_dict[key], dict):
if target_key in this_dict[key]:
this_dict[key].pop(target_key)
this_dict[key] = find_remove(this_dict[key], target_key)
return this_dict
dict_nested_new = find_remove(nested_dict, "sub_key2a")
The trick
The trick is to find out in advance whether a target_key is among the next children (= this_dict[key] = the values of the current dict iteration) before you reach the child level recursively. Only then you can still delete a key:value pair of the child level while iterating over a dictionary. Once you have reached the same level as the key to be deleted and then try to delete it from there, you would get the error:
RuntimeError: dictionary changed size during iteration
The recursive solution makes any change only on the next values' sub-level and therefore avoids the error.
I got the same problem and I used following procedure to solve this issue.
Python List can be iterate even if you modify during iterating over it.
so for following code it will print 1's infinitely.
for i in list:
list.append(1)
print 1
So using list and dict collaboratively you can solve this problem.
d_list=[]
d_dict = {}
for k in d_list:
if d_dict[k] is not -1:
d_dict[f(k)] = -1 # rather than deleting it mark it with -1 or other value to specify that it will be not considered further(deleted)
d_dict[g(k)] = v # add a new item
d_list.append(g(k))
Today I had a similar use-case, but instead of simply materializing the keys on the dictionary at the beginning of the loop, I wanted changes to the dict to affect the iteration of the dict, which was an ordered dict.
I ended up building the following routine, which can also be found in jaraco.itertools:
def _mutable_iter(dict):
"""
Iterate over items in the dict, yielding the first one, but allowing
it to be mutated during the process.
>>> d = dict(a=1)
>>> it = _mutable_iter(d)
>>> next(it)
('a', 1)
>>> d
{}
>>> d.update(b=2)
>>> list(it)
[('b', 2)]
"""
while dict:
prev_key = next(iter(dict))
yield prev_key, dict.pop(prev_key)
The docstring illustrates the usage. This function could be used in place of d.iteritems() above to have the desired effect.
This question already has answers here:
Destructuring-bind dictionary contents
(17 answers)
Closed 1 year ago.
I am studying Python and currently going through some more learning with dictionaries.
I was wondering;
If I have a dictionary like: d = {'key_1': 'value_a', 'key_2': 'value_b'} and I want separate/divide this dictionary into variables where each variable is a key from the dictionary and each variables value is the value of that key in the dictionary.
What would be the best pythonic way to achieve this?
d = {'key_1': 'value_a', 'key_2': 'value_b'}
#perform the command and get
key_1 = 'value_a'
key_2 = 'value_b'
I tried: key_1, key_2 = d but it did not work.
Basically I am seeking expert's wisdom to find out if there is a better way to reduce 2 lines of code into one.
Note: This is not a dynamic variable creation.
The existing answers will work, but they're all essentially re-implementing a function that already exists in the Python standard library: operator.itemgetter()
From the docs:
Return a callable object that fetches item from its operand using the operand’s __getitem__() method. If multiple items are specified, returns a tuple of lookup values. For example:
After f = itemgetter(2), the call f(r) returns r[2].
After g = itemgetter(2, 5, 3), the call g(r) returns (r[2], r[5], r[3]).
In other words, your destructured dict assignment becomes something like:
from operator import itemgetter
d = {'key_1': 'value_a', 'key_2': 'value_b'}
key_1, key_2 = itemgetter('key_1', 'key_2')(d)
# prints "Key 1: value_a, Key 2: value_b"
print("Key 1: {}, Key 2: {}".format(key_1, key_2))
Problem is that dicts are unordered, so you can't use simple unpacking of d.values(). You could of course first sort the dict by key, then unpack the values:
# Note: in python 3, items() functions as iteritems() did
# in older versions of Python; use it instead
ds = sorted(d.iteritems())
name0, name1, name2..., namen = [v[1] for v in ds]
You could also, at least within an object, do something like:
for k, v in dict.iteritems():
setattr(self, k, v)
Additionally, as I mentioned in the comment above, if you can get all your logic that needs your unpacked dictionary as variables in to a function, you could do:
def func(**kwargs):
# Do stuff with labeled args
func(**d)
A solution which has not been mentionned before would be
dictget = lambda d, *k: [d[i] for i in k]
and then use it:
key_1, key_2 = dictget(d, 'key_1', 'key_2')
whose advantage is that it is quite readable even with more variables to be retrieved.
Even more readable, however, would be a "real" function such as
def dictget(d, *k):
"""Get the values corresponding to the given keys in the provided dict."""
return [d[i] for i in k]
# or maybe
return (d[i] for i in k) # if we suppose that we have bigger sets of result
# or, equivalent to this
for i in k:
yield d[i]
which as well supports commenting with a docstring and is to be preferred.
var1, var2 = (lambda key1, key2: (key1, key2))(**d)
If you want to give anyone reading your code a headache you can use anonymous function to unpack values like this.
You can do this, if you're brave:
for k, v in d.items():
locals()[k] = v
But being brave might not be enough - you might also have to be reckless etc.
If you want to be a reckless hero like #ecatmur, you can do this:
locals().update(d)
But now that OP has updated his question and answered comments, it seems, this isn't what he really wants to do. Just for the record: There are good reasons for dynamically creating variables - even if everyone here agrees that it's not pythonic. A lot of interpreter style problems can be solved neetly with dynamic altering of your scope. Just do this in a controlled fashion. And... uh, don't deploy this to some production site ;)
I actually have a usecase, where i pull all the arguments of an __init__ method into the self namespace on object construction:
vars(self).update(somedict)
The vars function gets you a dict of the “namespace” associated with the object passed. However, this will not work with locals in a function, due to CPython implementation details. So it's not supposed to work on all interpreters.
For global namespace you would substitute vars(self) with globals(), but this is really a sign that something is wrong with your logic. As said, for local variables this won't work anyways (It'll NameError even if you assigned a value to the dict).
i think this should solve your problem
d = {'key_1': 'value_a', 'key_2': 'value_b'}
for k,v in d.items():
exec '%s=%s'%(k,v)
#glglgl's answer is not most voted, that answer worked for me,
solution1={'variable': np.array([75, 74]), 'function': 0}
def dict_get(d, *k):
for i in k:
yield d[i]
variables, obj_func = dict_get(solution1, 'variable', 'function')
a, b=variables
print(a)
reference: #glglgl
It's not recommended to ever declare variables dynamically, because it becomes very difficult to find the source of a variable name. That said, it's possible to hack together a solution Dynamic variable name in python but I wouldn't recommend it. Probably better off using a plain old dictionary.
Here is a solution that uses Python's inspect module on the calling stack frame to determine how to extract the right values from a supplied dictionary. Right now the only check is to make sure that there is a value available for each of the output variables, but feel free to add additional checks if you need them.
import inspect
def update(src):
result = []
cprev = inspect.currentframe().f_back
#print(cprev.f_code.co_names)
for v in cprev.f_code.co_names[1:]:
if src is cprev.f_locals[v]: continue
if v in src:
result.append(src[v])
else:
raise NameError(v + " has no source for update")
return result
Usage looks like this:
src={'a': 1, 'b': 2, 'c': 3}
a,b,c = update(src)