I have the following code:
import json
data_sample = [{
"name":"John",
"age":30,
"cars":[ {
"temp":{
"sum":"20",
"for":12,
}
,
"id":30,
"element":[ {"model":"Taurus1", "doors":{"id":"1", "id2":101}}, {"model":"T1", "doors":{"id":"2", "id2":12}}, {"model":"As", "doors":{"id":"Mo", "id2":4}} ]
}, {
"temp":{
"sum":"10",
"for":12,
}
,
"id":31,
"element":[ {"model":"Taurus2", "doors":{"id":"2", "id2":102}}, {"model":"T2", "doors":{"id":"5", "id2":12}}, {"model":"Thing", "doors":{"id":"Fo", "id2":4}} ]
}, {
"temp":{
"sum":"20",
"for":10,
}
,
"id":32,
"element":[ {"model":"Taurus3", "doors":{"id":"3", "id2":103}}, {"model":"T3", "doors":{"id":"15", "id2":62}}, {"model":"By", "doors":{"id":"Log", "id2":4}} ]
} ]
}]
def flat_list(z):
x = []
for i, data_obj in enumerate(z):
if type(data_obj) is dict or type(data_obj) is list:
x.extend([flatten_data(data_obj)])
else:
x.extend([data_obj])
return x
def flatten_data(y):
out = {}
def flatten(x, name=''):
if type(x) is dict:
for a in x:
flatten(x[a], name + a + '_')
elif type(x) is list:
out[name[:-1]] = flat_list(x)
else:
out[name[:-1]] = x
flatten(y)
return out
def generatejson(response2):
# response 2 is [(first data set), (second data set)] convert it to dictionary {0: (first data set), 1: (second data set)}
sample_object = {i: data_response for i, data_response in enumerate(response2)}
flat = {k: flatten_data(v) for k, v in sample_object.items()}
return json.dumps(flat, sort_keys=True)
print generatejson(data_sample)
This code takes data from the following format:
[(first data set), (second data set)]
and begin to look for nesting dicts. If nesting dict is detected the code flats it to the parent level.
For example the code detects this:
doors is nested dict so it converts it to:
Note that it doesn't change the lists/arrays. They are not being flattened.
My issue:
On small amount of data the code works great however handling large amount of sets (1000+) the performance is very low... And sometimes even crash.
How can I improve and optimize the performance of this code?
The data_sample contains only 1 data set (I assume that's enough for checking).
Related
I have a config file that I've been working out of, Ex:
"Preprocessing": {
"BOW":{"ngram_range":[1,2], "max_features":[100, 200]},
"RemoveStopWords": {"Parameter1": ["..."]}
}
The idea is to take this data and run every iteration between the two preprocessing steps and pass it into a Preprocessing object. The output I'm looking for is:
[{"BOW":{"ngram_range":1, "max_features":100}, "RemoveStopWords":{"Parameter1": "..."},
{"BOW":{"ngram_range":2, "max_features":100}, "RemoveStopWords":{"Parameter1": "..."},
{"BOW":{"ngram_range":1, "max_features":200}, "RemoveStopWords":{"Parameter1": "..."},
{"BOW":{"ngram_range":2, "max_features":200}, "RemoveStopWords":{"Parameter1": "..."}]
Current code:
def unpack_preprocessing_steps(preprocessing: dict):
"""
This script will take the Preprocessing section of the config file
and produce a list of preprocessing combinations.
"""
preprocessing_steps = [] # save for all steps bow, w2v, etc.
preprocessing_params = [] # individual parameters for each preprocessing step
for key, values in preprocessing.items():
for key2, values2 in values.items():
preprocessing_steps.append(key2)
preprocessing_params.append(values2)
iterables = product(*preprocessing_params) # Creates a matrix of every combination
iterable_of_params = [i for i in iterables]
exploded_preprocessing_list = []
for params in iterable_of_params:
individual_objects = {} # store each object as an unpackable datatype
for step, param in zip(preprocessing_steps, params):
individual_objects[step] = param # This stores ever iteration as it's own set of preprocesses
exploded_preprocessing_list.append(individual_objects)
return exploded_preprocessing_list
Current output (and wrong) output is:
[{"ngram_range":1, "max_features":100, "Parameter1":"..."},
{"ngram_range":2, "max_features":200, "Parameter1":"..."},
{"ngram_range":1, "max_features":100, "Parameter1":"..."},
{"ngram_range":2, "max_features":200, "Parameter1":"..."}]
This should work for you - assuming you always want that same RemoveStopWords section. It generates the product of all feature keys and values:
from itertools import product
# pprint just to make output clearer
from pprint import pprint
config = {
"Preprocessing": {
"BOW": {"ngram_range":[1,2]},
"RemoveStopWords": {"Parameter1": ["..."]},
}
}
features, values = zip(*config["Preprocessing"]["BOW"].items())
bows = [dict(zip(features, v)) for v in product(*values)]
newconf = []
for bow in bows:
newconf.append({
"BOW": bow,
"RemoveStopWords": config["Preprocessing"]["RemoveStopWords"],
})
print(newconf)
Result:
[{'BOW': {'max_features': 100, 'ngram_range': 1}, 'RemoveStopWords': {'Parameter1': ['...']}},
{'BOW': {'max_features': 200, 'ngram_range': 1}, 'RemoveStopWords': {'Parameter1': ['...']}},
{'BOW': {'max_features': 100, 'ngram_range': 2}, 'RemoveStopWords': {'Parameter1': ['...']}},
{'BOW': {'max_features': 200, 'ngram_range': 2}, 'RemoveStopWords': {'Parameter1': ['...']}}]
I am trying to use binance api for my project I would like to list top gainers and sort them from high to small I tried couple of things but those did not work.
I would like to print only "symbol" and "priceChangePercent".
Is there any way to get these two values?
This is my output:
[
{
"symbol":"FIDABUSD",
"priceChange":"0.41800000",
"priceChangePercent":"6.375",
"weightedAvgPrice":"6.95111809",
"prevClosePrice":"6.54400000",
"lastPrice":"6.97500000",
"lastQty":"28.30000000",
"bidPrice":"6.97400000",
"bidQty":"74.80000000",
"askPrice":"6.97900000",
"askQty":"3.30000000",
"openPrice":"6.55700000",
"highPrice":"7.20000000",
"lowPrice":"6.47700000",
"volume":"354812.40000000",
"quoteVolume":"2466342.89060000",
"openTime":1633166019175,
"closeTime":1633252419175,
"firstId":78716,
"lastId":88805,
"count":10090
},
{
"symbol":"FIDABNB",
"priceChange":"0.00093000",
"priceChangePercent":"6.008",
"weightedAvgPrice":"0.01614960",
"prevClosePrice":"0.01546000",
"lastPrice":"0.01641000",
"lastQty":"109.10000000",
"bidPrice":"0.01643000",
"bidQty":"97.50000000",
"askPrice":"0.01649000",
"askQty":"140.60000000",
"openPrice":"0.01548000",
"highPrice":"0.01663000",
"lowPrice":"0.01533000",
"volume":"75225.50000000",
"quoteVolume":"1214.86161500",
"openTime":1633166016671,
"closeTime":1633252416671,
"firstId":8400,
"lastId":9840,
"count":1441
},
]
Here's what I tried:
class BinanceConnection:
def __init__(self, file):
self.connect(file)
""" Creates Binance client """
def connect(self, file):
lines = [line.rstrip('\n') for line in open(file)]
key = lines[0]
secret = lines[1]
self.client = Client(key, secret)
if __name__ == '__main__':
connection = BinanceConnection(filename)
prices = connection.client.get_ticker()
print(prices)
see below - a 1 liner
data = [
{
"symbol":"FIDABUSD",
"priceChange":"0.41800000",
"priceChangePercent":"6.375",
"weightedAvgPrice":"6.95111809",
"prevClosePrice":"6.54400000",
"lastPrice":"6.97500000",
"lastQty":"28.30000000",
"bidPrice":"6.97400000",
"bidQty":"74.80000000",
"askPrice":"6.97900000",
"askQty":"3.30000000",
"openPrice":"6.55700000",
"highPrice":"7.20000000",
"lowPrice":"6.47700000",
"volume":"354812.40000000",
"quoteVolume":"2466342.89060000",
"openTime":1633166019175,
"closeTime":1633252419175,
"firstId":78716,
"lastId":88805,
"count":10090
},
{
"symbol":"FIDABNB",
"priceChange":"0.00093000",
"priceChangePercent":"6.008",
"weightedAvgPrice":"0.01614960",
"prevClosePrice":"0.01546000",
"lastPrice":"0.01641000",
"lastQty":"109.10000000",
"bidPrice":"0.01643000",
"bidQty":"97.50000000",
"askPrice":"0.01649000",
"askQty":"140.60000000",
"openPrice":"0.01548000",
"highPrice":"0.01663000",
"lowPrice":"0.01533000",
"volume":"75225.50000000",
"quoteVolume":"1214.86161500",
"openTime":1633166016671,
"closeTime":1633252416671,
"firstId":8400,
"lastId":9840,
"count":1441
}
]
data = sorted([{'symbol':x['symbol'],'priceChangePercent':x['priceChangePercent']} for x in data],key = lambda k: float(k['priceChangePercent']), reverse=True)
print(data)
output
[{'symbol': 'FIDABUSD', 'priceChangePercent': '6.375'}, {'symbol': 'FIDABNB', 'priceChangePercent': '6.008'}]
try this:
data = *your data*
newlist = list()
for item in data:
newlist.append({key:item[key] for key in ['symbol', 'priceChange']})
print(sorted(newlist, key=lambda k: k['priceChange'], reverse=True) )
I'm looking for any suggestions to resolve an issue I'm facing. It might seem as a simple problem, but after a few days trying to find an answer - I think it is not anymore.
I'm receiving data (StringType) in a following JSON-like format, and there is a requirement to turn it into flat key-value pair dictionary. Here is a payload sample:
s = """{"status": "active", "name": "{\"first\": \"John\", \"last\": \"Smith\"}", "street_address": "100 \"Y\" Street"}"""
and the desired output should look like this:
{'status': 'active', 'name_first': 'John', 'name_last': 'Smith', 'street_address': '100 "Y" Street'}
The issue is I can't find a way to turn original string (s) into a dictionary. If I can achieve that the flattening part is working perfectly fine.
import json
import collections
import ast
#############################################################
# Flatten complex structure into a flat dictionary
#############################################################
def flatten_dictionary(dictionary, parent_key=False, separator='_', value_to_str=True):
"""
Turn a nested complex json into a flattened dictionary
:param dictionary: The dictionary to flatten
:param parent_key: The string to prepend to dictionary's keys
:param separator: The string used to separate flattened keys
:param value_to_str: Force all returned values to string type
:return: A flattened dictionary
"""
items = []
for key, value in dictionary.items():
new_key = str(parent_key) + separator + key if parent_key else key
try:
value = json.loads(value)
except BaseException:
value = value
if isinstance(value, collections.MutableMapping):
if not value.items():
items.append((new_key,None))
else:
items.extend(flatten_dictionary(value, new_key, separator).items())
elif isinstance(value, list):
if len(value):
for k, v in enumerate(value):
items.extend(flatten_dictionary({str(k): (str(v) if value_to_str else v)}, new_key).items())
else:
items.append((new_key,None))
else:
items.append((new_key, (str(value) if value_to_str else value)))
return dict(items)
# Data sample; sting and dictionary
s = """{"status": "active", "name": "{\"first\": \"John\", \"last\": \"Smith\"}", "street_address": "100 \"Y\" Street"}"""
d = {"status": "active", "name": "{\"first\": \"John\", \"last\": \"Smith\"}", "street_address": "100 \"Y\" Street"}
# Works for dictionary type
print(flatten_dictionary(d))
# Doesn't work for string type, for any of the below methods
e = eval(s)
# a = ast.literal_eval(s)
# j = json.loads(s)
Try:
import json
import re
def jsonify(s):
s = s.replace('"{','{').replace('}"','}')
s = re.sub(r'street_address":\s+"(.+)"(.+)"(.+)"', r'street_address": "\1\2\3"',s)
return json.loads(s)
If you must keep the quotes around Y, try:
def jsonify(s):
s = s.replace('"{','{').replace('}"','}')
search = re.search(r'street_address":\s+"(.+)"(.+)"(.+)"',s)
if search:
s = re.sub(r'street_address":\s+"(.+)"(.+)"(.+)"', r'street_address": "\1\2\3"',s)
dict_version = json.loads(s)
dict_version['street_address'] = dict_version['street_address'].replace(search.group(2),'"'+search.group(2)+'"')
return dict_version
A more generalized attempt:
def jsonify(s):
pattern = r'(?<=[,}])\s*"(.[^\{\}:,]+?)":\s+"([^\{\}:,]+?)"([^\{\}:,]+?)"([^\{\}:,]+?)"([,\}])'
s = s.replace('"{','{').replace('}"','}')
search = re.search(pattern,s)
matches = []
if search:
matches = re.findall(pattern,s)
s = re.sub(pattern, r'"\1": "\2\3\4"\5',s)
dict_version = json.loads(s)
for match in matches:
dict_version[match[0]] = dict_version[match[0]].replace(match[2],'"'+match[2]+'"')
return dict_version
I am novice with Python and currently I am trying to use it to parse some custom output formated string. In fact format contains named lists of float and lists of tuples of float. I wrote a function but it looks excessive. How can it be done in more suitable way for Python?
import re
def extract_line(line):
line = line.lstrip('0123456789# ')
measurement_list = list(filter(None, re.split(r'\s*;\s*', line)))
measurement = {}
for elem in measurement_list:
elem_list = list(filter(None, re.split(r'\s*=\s*', elem)))
name = elem_list[0]
if name == 'points':
points = list(filter(None, re.split(r'\s*\(\s*|\s*\)\s*',elem_list[1].strip(' {}'))))
for point in points:
p = re.match(r'\s*(\d+(?:\.\d+)?)\s*,\s*(\d+(?:\.\d+)?)\s*', point).groups()
if 'points' not in measurement.keys():
measurement['points'] = []
measurement['points'].append(tuple(map(float,p)))
else:
values = list(filter(None, elem_list[1].strip(' {}').split(' ')))
for value in values:
if name not in measurement.keys():
measurement[name] = []
measurement[name].append(float(value))
return measurement
to_parse = '#10 points = { ( 2.96296 , 0.822213 ) ( 3.7037 , 0.902167 ) } ; L = { 5.20086 } ; P = { 3.14815 3.51852 } ;'
print(extract_line(to_parse))
You can do it using re.findall:
import re
to_parse = '#10 points = { ( 2.96296 , 0.822213 ) ( 3.7037 , 0.902167 ) } ; L = { 5.20086 } ; P = { 3.14815 3.51852 } ;'
m_list = re.findall(r'(\w+)\s*=\s*{([^}]*)}', to_parse)
measurements = {}
for k,v in m_list:
if k == 'points':
elts = re.findall(r'([0-9.]+)\s*,\s*([0-9.]+)', v)
measurements[k] = [tuple(map(float, elt)) for elt in elts]
else:
measurements[k] = [float(x) for x in v.split()]
print(measurements)
Feel free to put it in a function and to check if keys don't already exists.
This:
import re
a=re.findall(r' ([\d\.eE-]*) ',to_parse)
map(float, a)
>> [2.96296, 0.822213, 3.7037, 0.902167, 5.20086, 3.14815]
Will give you your list of numbers, is that what you look for?
Search for a value and get the parent dictionary names (keys):
Dictionary = {dict1:{
'part1': {
'.wbxml': 'application/vnd.wap.wbxml',
'.rl': 'application/resource-lists+xml',
},
'part2':
{'.wsdl': 'application/wsdl+xml',
'.rs': 'application/rls-services+xml',
'.xop': 'application/xop+xml',
'.svg': 'image/svg+xml',
},
'part3':{...}, ...
dict2:{
'part1': { '.dotx': 'application/vnd.openxmlformats-..'
'.zaz': 'application/vnd.zzazz.deck+xml',
'.xer': 'application/patch-ops-error+xml',}
},
'part2':{...},
'part3':{...},...
},...
In above dictionary I need to search values like: "image/svg+xml". Where, none of the values are repeated in the dictionary. How to search the "image/svg+xml"? so that it should return the parent keys in a dictionary { dict1:"part2" }.
Please note: Solutions should work unmodified for both Python 2.7 and Python 3.3.
Here's a simple recursive version:
def getpath(nested_dict, value, prepath=()):
for k, v in nested_dict.items():
path = prepath + (k,)
if v == value: # found value
return path
elif hasattr(v, 'items'): # v is a dict
p = getpath(v, value, path) # recursive call
if p is not None:
return p
Example:
print(getpath(dictionary, 'image/svg+xml'))
# -> ('dict1', 'part2', '.svg')
To yield multiple paths (Python 3 only solution):
def find_paths(nested_dict, value, prepath=()):
for k, v in nested_dict.items():
path = prepath + (k,)
if v == value: # found value
yield path
elif hasattr(v, 'items'): # v is a dict
yield from find_paths(v, value, path)
print(*find_paths(dictionary, 'image/svg+xml'))
This is an iterative traversal of your nested dicts that additionally keeps track of all the keys leading up to a particular point. Therefore as soon as you find the correct value inside your dicts, you also already have the keys needed to get to that value.
The code below will run as-is if you put it in a .py file. The find_mime_type(...) function returns the sequence of keys that will get you from the original dictionary to the value you want. The demo() function shows how to use it.
d = {'dict1':
{'part1':
{'.wbxml': 'application/vnd.wap.wbxml',
'.rl': 'application/resource-lists+xml'},
'part2':
{'.wsdl': 'application/wsdl+xml',
'.rs': 'application/rls-services+xml',
'.xop': 'application/xop+xml',
'.svg': 'image/svg+xml'}},
'dict2':
{'part1':
{'.dotx': 'application/vnd.openxmlformats-..',
'.zaz': 'application/vnd.zzazz.deck+xml',
'.xer': 'application/patch-ops-error+xml'}}}
def demo():
mime_type = 'image/svg+xml'
try:
key_chain = find_mime_type(d, mime_type)
except KeyError:
print ('Could not find this mime type: {0}'.format(mime_type))
exit()
print ('Found {0} mime type here: {1}'.format(mime_type, key_chain))
nested = d
for key in key_chain:
nested = nested[key]
print ('Confirmation lookup: {0}'.format(nested))
def find_mime_type(d, mime_type):
reverse_linked_q = list()
reverse_linked_q.append((list(), d))
while reverse_linked_q:
this_key_chain, this_v = reverse_linked_q.pop()
# finish search if found the mime type
if this_v == mime_type:
return this_key_chain
# not found. keep searching
# queue dicts for checking / ignore anything that's not a dict
try:
items = this_v.items()
except AttributeError:
continue # this was not a nested dict. ignore it
for k, v in items:
reverse_linked_q.append((this_key_chain + [k], v))
# if we haven't returned by this point, we've exhausted all the contents
raise KeyError
if __name__ == '__main__':
demo()
Output:
Found image/svg+xml mime type here: ['dict1', 'part2', '.svg']
Confirmation lookup: image/svg+xml
Here is a solution that works for a complex data structure of nested lists and dicts
import pprint
def search(d, search_pattern, prev_datapoint_path=''):
output = []
current_datapoint = d
current_datapoint_path = prev_datapoint_path
if type(current_datapoint) is dict:
for dkey in current_datapoint:
if search_pattern in str(dkey):
c = current_datapoint_path
c+="['"+dkey+"']"
output.append(c)
c = current_datapoint_path
c+="['"+dkey+"']"
for i in search(current_datapoint[dkey], search_pattern, c):
output.append(i)
elif type(current_datapoint) is list:
for i in range(0, len(current_datapoint)):
if search_pattern in str(i):
c = current_datapoint_path
c += "[" + str(i) + "]"
output.append(i)
c = current_datapoint_path
c+="["+ str(i) +"]"
for i in search(current_datapoint[i], search_pattern, c):
output.append(i)
elif search_pattern in str(current_datapoint):
c = current_datapoint_path
output.append(c)
output = filter(None, output)
return list(output)
if __name__ == "__main__":
d = {'dict1':
{'part1':
{'.wbxml': 'application/vnd.wap.wbxml',
'.rl': 'application/resource-lists+xml'},
'part2':
{'.wsdl': 'application/wsdl+xml',
'.rs': 'application/rls-services+xml',
'.xop': 'application/xop+xml',
'.svg': 'image/svg+xml'}},
'dict2':
{'part1':
{'.dotx': 'application/vnd.openxmlformats-..',
'.zaz': 'application/vnd.zzazz.deck+xml',
'.xer': 'application/patch-ops-error+xml'}}}
d2 = {
"items":
{
"item":
[
{
"id": "0001",
"type": "donut",
"name": "Cake",
"ppu": 0.55,
"batters":
{
"batter":
[
{"id": "1001", "type": "Regular"},
{"id": "1002", "type": "Chocolate"},
{"id": "1003", "type": "Blueberry"},
{"id": "1004", "type": "Devil's Food"}
]
},
"topping":
[
{"id": "5001", "type": "None"},
{"id": "5002", "type": "Glazed"},
{"id": "5005", "type": "Sugar"},
{"id": "5007", "type": "Powdered Sugar"},
{"id": "5006", "type": "Chocolate with Sprinkles"},
{"id": "5003", "type": "Chocolate"},
{"id": "5004", "type": "Maple"}
]
},
...
]
}
}
pprint.pprint(search(d,'svg+xml','d'))
>> ["d['dict1']['part2']['.svg']"]
pprint.pprint(search(d2,'500','d2'))
>> ["d2['items']['item'][0]['topping'][0]['id']",
"d2['items']['item'][0]['topping'][1]['id']",
"d2['items']['item'][0]['topping'][2]['id']",
"d2['items']['item'][0]['topping'][3]['id']",
"d2['items']['item'][0]['topping'][4]['id']",
"d2['items']['item'][0]['topping'][5]['id']",
"d2['items']['item'][0]['topping'][6]['id']"]
Here are two similar quick and dirty ways of doing this type of operation. The function find_parent_dict1 uses list comprehension but if you are uncomfortable with that then find_parent_dict2 uses the infamous nested for loops.
Dictionary = {'dict1':{'part1':{'.wbxml':'1','.rl':'2'},'part2':{'.wbdl':'3','.rs':'4'}},'dict2':{'part3':{'.wbxml':'5','.rl':'6'},'part4':{'.wbdl':'1','.rs':'10'}}}
value = '3'
def find_parent_dict1(Dictionary):
for key1 in Dictionary.keys():
item = {key1:key2 for key2 in Dictionary[key1].keys() if value in Dictionary[key1][key2].values()}
if len(item)>0:
return item
find_parent_dict1(Dictionary)
def find_parent_dict2(Dictionary):
for key1 in Dictionary.keys():
for key2 in Dictionary[key1].keys():
if value in Dictionary[key1][key2].values():
print {key1:key2}
find_parent_dict2(Dictionary)
Traverses a nested dict looking for a particular value. When success is achieved the full key path to the value is printed. I left all the comments and print statements for pedagogical purposes (this isn't production code!)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 24 17:16:46 2022
#author: wellington
"""
class Tree(dict):
"""
allows autovivification as in Perl hashes
"""
def __missing__(self, key):
value = self[key] = type(self)()
return value
# tracking the key sequence when seeking the target
key_list = Tree()
# dict storing the target success result
success = Tree()
# example nested dict of dicts and lists
E = {
'AA':
{
'BB':
{'CC':
{
'DD':
{
'ZZ':'YY',
'WW':'PP'
},
'QQ':
{
'RR':'SS'
},
},
'II':
{
'JJ':'KK'
},
'LL':['MM', 'GG', 'TT']
}
}
}
def find_keys_from_value(data, target):
"""
recursive function -
given a value it returns all the keys in the path to that value within
the dict "data"
there are many paths and many false routes
at the end of a given path if success has not been achieved
the function discards keys to get back to the next possible path junction
"""
print(f"the number of keys in the local dict is {len(data)}")
key_counter = 0
for key in data:
key_counter += 1
# if target has been located stop iterating through keys
if success[target] == 1:
break
else:
# eliminate prior key from path that did not lead to success
if key_counter > 1:
k_list.pop()
# add key to new path
k_list.append(key)
print(f"printing k_list after append{k_list}")
# if target located set success[target] = 1 and exit
if key == target or data[key] == target:
key_list[target] = k_list
success[target] = 1
break
# if the target has not been located check to see if the value
# associated with the new key is a dict and if so return to the
# recursive function with the new dict as "data"
elif isinstance(data[key], dict):
print(f"\nvalue is dict\n {data[key]}")
find_keys_from_value(data[key], target)
# check to see if the value associated with the new key is a list
elif isinstance(data[key], list):
# print("\nv is list\n")
# search through the list
for i in data[key]:
# check to see if the list element is a dict
# and if so return to the recursive function with
# the new dict as "data
if isinstance(i, dict):
find_keys_from_value(i, target)
# check to see if each list element is the target
elif i == target:
print(f"list entry {i} is target")
success[target] = 1
key_list[target] = k_list
elif i != target:
print(f"list entry {i} is not target")
print(f"printing k_list before pop_b {k_list}")
print(f"popping off key_b {key}")
# so if value is not a key and not a list and not the target then
# discard the key from the key list
elif data[key] != target:
print(f"value {data[key]} is not target")
print(f"printing k_list before removing key_before {k_list}")
print(f"removing key_c {key}")
k_list.remove(key)
# select target values
values = ["PP", "SS", "KK", "TT"]
success = {}
for target in values:
print(f"\nlooking for target {target}")
success[target] = 0
k_list = []
find_keys_from_value(E, target)
print(f"\nprinting key_list for target {target}")
print(f"{key_list[target]}\n")
print("\n****************\n\n")