Multiprocessing search in a dict in python - python

I got a huge dict adding data in it. I am trying to search if already a key exists in the dict but takes to long when the dictionary grows. how can I get this search in parallel in a multiprocesser system?
def __getVal(self, key, val):
ret= 0
if key in self.mydict:
ret= val + self.mydict[key]
else:
ret = val
return ret

Perhaps before trying to split in multiprocess, you should try this:
Instead of looking if the key is in the dictionnary, access it, in a try...catch block.
On my various computer, it's so far faster than looking in the key list.
So your final code would be something like:
try:
ret = val + self.mydict[key]
catch:
ret = val

Just use .get with `a default value of 0
return self.mydict.get(key, 0) + val
Using ret = 0 and adding to it is pointless, just return as above.

The problem is how Nick Bastin said, "it is not search speed, but the cost of making the dictionary larger as you continue to add elements".
The cost is caused by the hashmap that creates for a new item. Due the hashmap is a short eventually collision and makes other proccesses to insert.
One solution is recompile the Hashmap to make the hashmap larger.
In this case changing for a List was sufficient, this grows without the inconvenient of the collision.

Related

Iterate over Python list with clear code - rewriting functions

I've followed a tutorial to write a Flask REST API and have a special request about a Python code.
The offered code is following:
# data list is where my objects are stored
def put_one(name):
list_by_id = [list for list in data_list if list['name'] == name]
list_by_id[0]['name'] = [new_name]
print({'list_by_id' : list_by_id[0]})
It works, which is nice, and even though I understand what line 2 is doing, I would like to rewrite it in a way that it's clear how the function iterates over the different lists. I already have an approach but it returns Key Error: 0
def put(name):
list_by_id = []
list = []
for list in data_list:
if(list['name'] == name):
list_by_id = list
list_by_id[0]['name'] = request.json['name']
return jsonify({'list_by_id' : list_by_id[0]})
My goal with this is also to be able to put other elements, that don't necessarily have the type 'name'. If I get to rewrite the function in an other way I'll be more likely to adapt it to my needs.
I've looked for tools to convert one way of coding into the other and answers in forums before coming here and couldn't find it.
It may not be beatiful code, but it gets the job done:
def put(value):
for i in range(len(data_list)):
key_list = list(data_list[i].keys())
if data_list[i][key_list[0]] == value:
print(f"old value: {key_list[0], data_list[i][key_list[0]]}")
data_list[i][key_list[0]] = request.json[test_key]
print(f"new value: {key_list[0], data_list[i][key_list[0]]}")
break
Now it doesn't matter what the key value is, with this iteration the method will only change the value when it finds in the data_list. Before the code breaked at every iteration cause the keys were different and they played a role.

For loops and conditionals in Python

I am new to Python and I was wondering if there was a way I could shorten/optimise the below loops:
for breakdown in data_breakdown:
for data_source in data_source_ids:
for camera in camera_ids:
if (camera.get("id") == data_source.get("parent_id")) and (data_source.get("id") == breakdown.get('parent_id')):
for res in result:
if res.get("camera_id") == camera.get("id"):
res.get('data').update({breakdown.get('name'): breakdown.get('total')})
I tried this oneliner, but it doesn't seem to work:
res.get('data').update({breakdown.get('name'): breakdown.get('total')}) for camera in camera_ids if (camera.get("id") == data_source.get("parent_id")) and (data_source.get("id") == breakdown.get('parent_id'))
You can use itertools.product to handle the nested loops for you, and I think (although I'm not sure because I can't see your data) you can skip all the .get and .update and just use the [] operator:
from itertools import product
for b, d, c in product(data_breakdown, data_source_ids, camera_ids):
if c["id"] != d["parent_id"] or d["id"] != b["parent_id"]:
continue
for res in result:
if res["camera_id"] == c["id"]:
res['data'][b['name']] = b['total']
If anything, to optimize the performance of those loops, you should make them longer and more nested, with the data_source.get("id") == breakdown.get('parent_id') happening outside of the camera loop.
But there is perhaps an alternative, where you could change the structure of your data so that you don't need to loop nearly as much to find matching ID values. Convert each of your current lists (of dicts) into a single dict with its keys equal to the 'id' value you'll be trying to match in that loop, and the value being whole dict.
sources_dict = {source.get("id"): source for source in data_source_ids}
cameras_dict = {camera.get("id"): camera for camera in camera_ids}
results_dict = {res.get("camera_id"): res for res in result}
Now the whole loop only needs one level:
for breakdown in data_breakdown:
source = sources_dict[breakdown["parent_id"]]
camera = cameras_dict[source["parent_id"]]
res = results_dict[camera["id"]]
res.data[breakdown["name"]] = breakdown["total"]
This code assumes that all the lookups with get in your current code were going to succeed in getting a value. You weren't actually checking if any of the values you were getting from a get call was None, so there probably wasn't much benefit to it.
I'd further note that it's not clear if the camera loop in your original code was at all necessary. You might have been able to skip it and just directly compare data_source['parent_id'] against res['camera_id'] without comparing them both to a camera['id'] in between. In my updated version, that would translate to leaving out the creation of the cameras_dict and just directly indexing results_dict with source["parent_id"] rather than indexing to find camera first.

pop operation on dictionary in python 3.8 [duplicate]

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.

Weird Python dictionary behavior [duplicate]

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.

Check if Dictionary Values exist in a another Dictionary in Python

I am trying to compare values from 2 Dictionaries in Python. I want to know if a value from one Dictionary exists anywhere in another Dictionary. Here is what i have so far. If it exists I want to return True, else False.
The code I have is close, but not working right.
I'm using VS2012 with Python Plugin
I'm passing both Dictionary items into the functions.
def NameExists(best_guess, line):
return all (line in best_guess.values() #Getting Generator Exit Error here on values
for value in line['full name'])
Also, I want to see if there are duplicates within best_guess itself.
def CheckDuplicates(best_guess, line):
if len(set(best_guess.values())) != len(best_guess):
return True
else:
return False
As error is about generator exit, I guess you use python 3.x. So best_guess.values() is a generator, which exhaust for the first value in line['full name'] for which a match will not be found.
Also, I guess all usage is incorrect, if you look for any value to exist (not sure, from which one dictinary though).
You can use something like follows, providing line is the second dictionary:
def NameExists(best_guess, line):
vals = set(best_guess.values())
return bool(set(line.values()).intersection(vals))
The syntax in NameExists seems wrong, you aren't using the value and best_guess.values() is returning an iterator, so in will only work once, unless we convert it to a list or a set (you are using Python 3.x, aren't you?). I believe this is what you meant:
def NameExists(best_guess, line):
vals = set(best_guess.values())
return all(value in vals for value in line['full name'])
And the CheckDuplicates function can be written in a shorter way like this:
def CheckDuplicates(best_guess, line):
return len(set(best_guess.values())) != len(best_guess)

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