I am trying to merge three dictionaries together.
I am receiving an unsupported operand types error.
Here is my code:
def add_student():
global Snumber
global iCode
global kCode
Snumber = Student_number.get()
Sname = Student_name.get()
Ssurnname = Student_surname.get()
Sdetail = Student_detail.get()
i = Students(Snumber,Sname,Ssurnname,Sdetail)
Sinfo[Snumber]=[Sname,Ssurnname,Sdetail]
iName = Student_subject.get()
iCode = Student_code.get()
iMark1 = Student_Mark1.get()
iMark2 = Student_Mark2.get()
iMark3 = Student_Mark3.get()
iProject = Student_project.get()
j = Subjects(iName,iCode,iMark1,iMark2,iMark3,iProject)
SSubject[iCode]=[iName,iMark1,iMark2,iMark3,iProject]
kCourse = Degree_course.get()
kCode = Degree_code.get()
kYear = Degree_year.get()
v = Degrees(kCourse,kCode,kYear)
SDegree[kCode]=[kCourse,kYear]
popup_add()
student_list = (Sinfo.items() + SSubject.items() + SDegree.items())
print(student_list)
I believe my problem is in:
student_list = (Sinfo.items() + SSubject.items() + SDegree.items())
print(student_list)
you can use dict.update()
>>> a = {1:1,2:2,3:3}
>>> a
{1: 1, 2: 2, 3: 3}
>>> b = {4:4,5:5}
>>> c = {6:6,7:7}
>>> a.update(b)
>>> a.update(c)
>>> a
{1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7}
if you dont want to modify the original you can use the following to copy it into a new variable
>>> new_dict = dict(a)
To merge multiple dictionary, lets say we have dict Sinfo, SSubject and SDegree
student_list = dict(Sinfo.items() + SSubject.items() + SDegree.items())
code above will works with python 2 only. for python 3, need to add list to convert dict.items into list first as shown below
student_list = dict(list(Sinfo.items()) + list(SSubject.items()) + list(SDegree.items()))
Related
So I created a helper function to help my main function in extracting stuff from a dictionary...
and here is my code and function
def rdict(recipes):
recipes_splitted = {}
for r in recipes:
recipe_name, parts = r.split(":")
recipe_parts = {}
for part in parts.split(','):
product, number = part.split('*')
recipe_parts[product] = int(number)
recipes_splitted[recipe_name] = recipe_parts
return recipes_splitted
def extract(recipes, data):
result = []
for r in recipes:
tmp = []
for key in data[r]:
tmp.append(f"{key}:{data[r][key]}")
final_string = ""
for i in range(len(tmp)):
if i < len(tmp) - 1:
final_string += tmp[i] + ", "
else:
final_string += tmp[i]
result.append(final_string)
return result
So what I'm trying to do is make sure data in extract(recipe, data) go through rdict(data) since rdict will convert data into a dictionary, which is what I need.. However, when I tried doing for key in rdict(data[r]): the output returns Error. String is not supscriptable..
what should I do to successfully implement the changes??
Edit
So from my current code, here is a sample input..
print(extract(recipes = ['T-Bone', 'Green Salad1'],data = ["Pork Stew:Cabbage*5,Carrot*1,Fatty Pork*10",
"Green Salad1:Cabbage*10,Carrot*2,Pineapple*5",
"T-Bone:Carrot*2,Steak Meat*1"]
))
and in order for my code to work, it has to be like this
print(extract(recipes = ['T-Bone', 'Green Salad1'], data = {'Pork Stew': {'Cabbage': 5, 'Carrot': 1, 'Fatty Pork': 10}, 'Green Salad1': {'Cabbage': 10, 'Carrot': 2, 'Pineapple': 5},'T-Bone': {'Carrot': 2, 'Steak Meat': 1}}))
So from the input, data should be changed from
data = ["Pork Stew:Cabbage*5,Carrot*1,Fatty Pork*10",
"Green Salad1:Cabbage*10,Carrot*2,Pineapple*5",
"T-Bone:Carrot*2,Steak Meat*1"]
to
data = {'Pork Stew': {'Cabbage': 5, 'Carrot': 1, 'Fatty Pork': 10}, 'Green Salad1': {'Cabbage': 10, 'Carrot': 2, 'Pineapple': 5},'T-Bone': {'Carrot': 2, 'Steak Meat': 1}}
Convert the data to dict in extract().
recipes = ['T-Bone', 'Green Salad1']
data = ["Pork Stew:Cabbage*5,Carrot*1,Fatty Pork*10",
"Green Salad1:Cabbage*10,Carrot*2,Pineapple*5",
"T-Bone:Carrot*2,Steak Meat*1"]
def rdict(recipes):
recipes_splitted = {}
for r in recipes:
recipe_name, parts = r.split(":")
recipe_parts = {}
for part in parts.split(','):
product, number = part.split('*')
recipe_parts[product] = int(number)
recipes_splitted[recipe_name] = recipe_parts
return recipes_splitted
def extract(recipes, data):
data = rdict(data) # convert data to dict first
result = []
for r in recipes:
tmp = []
for key in data[r]:
tmp.append(f"{key}:{data[r][key]}")
final_string = ""
for i in range(len(tmp)):
if i < len(tmp) - 1:
final_string += tmp[i] + ", "
else:
final_string += tmp[i]
result.append(final_string)
return result
print(extract(recipes, data))
Output:
['Carrot:2, Steak Meat:1', 'Cabbage:10, Carrot:2, Pineapple:5']
Renamed rdict to parse_recipe, and modified it to return a tuple that is lighter and easier to process
In extract:
a) Build a dict of recipes: data_recipes
b) Built result by getting the wanted recipes, with a guard against missing recipe (which be an empty dict:{} )
def parse_recipe(s):
recipe, ings_s = s.split(':')
ings_l = ings_s.split(',')
ings_d= {}
for ing in ings_l:
i,q = ing.split('*')
ings_d[i.strip()] = q.strip()
return recipe.strip(), ings_d
def extract(recipes, data):
data_recipes = {}
for s in data:
recipe, ings_d = parse_recipe(s)
data_recipes[recipe] = ings_d
return {r: data_recipes.get(r, dict()) for r in recipes}
Is there a quick way to combine word dictionaries(MapType) in a list?
word
[[word1 -> 2], [wor2 ->3] .... [word2 -> 4]]
--------------------------------------result-----------------------
word
[[word1 ->2] ,[wor2 -> 7]]
There is a problem that it takes a long time using the udf function.
def dictsum(keywords) :
dictlist = []
sumdict = {}
for wordcounts in keywords :
for k, v in wordcounts.items() :
print(wordcounts.items())
if k not in sumdict :
sumdict[k] = 1
else :
sumdict[k] += 1
dictlist.append(sumdict)
return dictlist
dict_df = noun_df.select("createDate","nounwords")
wordcountUdf = udf(wordcount, ArrayType(MapType(StringType(),IntegerType())))
dict_df = dict_df.withColumn("wordcount",wordcountUdf(dict_df['nounwords']))
#dict_df.show(100,False)
keyword_f = dict_df.select("createDate","wordcount")
keyword_f = keyword_f.groupby("createDate").agg(flatten(collect_list("wordcount")).alias("keywords"))
keyword_f = keyword_f.withColumn("statistic_type",lit("keyword_f"))
#keyword_f.show(10,False)
dictsumUdf = udf(dictsum, ArrayType(MapType(StringType(),IntegerType())))
keyword_f = keyword_f.withColumn("wordcounts",dictsumUdf(keyword_f['keywords']))
keyword_f = keyword_f.drop("keywords")
#keyword_f.show(100,False)
if filename not in dict1.keys():
dict1[filename] = {}
if transId not in dict1[filename].keys():
dict1[filename][transId] = {}
if error_type in dict1[filename][transId].keys():
count1 = dict1[filename][transId][error_type]
count1 = count1 + 1
dict1[filename][transId][error_type] = count1
dict data is :
{'abc': {'ACE12345678': {'ERR-2': 2}, {'ERR-3': 4}}}
where 'abc' is a filename, 'ACE12345678' a TransId, and 'ERR-2' an Error Type.
I would also like to add loglines for each transid(Eg: 'ACE12345678') so that the dict looks like as below :
{'abc': {'ACE12345678': {'ERR-2': 2, data1\n data2\n data3\n}, {'ERR-3': 4, data1\n data2\n data3\n}}}.
Can someone help me getting this output.
you can add a new key loglines that holds all the lines in a list:
dict1 = {'abc': {'ACE12345678': {'ERR-2': 2}}}
filename = 'abc'
transID = 'ACE12345678'
error_type = 'ERR-2'
logline = 'data1\n'
my_error = dict1.setdefault(filename, {}).setdefault(transID, {})
my_error[error_type] = my_error.get(error_type, 0) + 1
my_error.setdefault('loglines', []).append(logline)
print(dict1)
output:
{'abc': {'ACE12345678': {'ERR-2': 3, 'loglines': ['data1\n']}}}
I am extracting from the log file and print using the below code
for line in data:
g = re.findall(r'([\d.]+).*?(GET|POST|PUT|DELETE)', line)
print (g)
[('1.1.1.1', 'PUT')]
[('2.2.2.2', 'GET')]
[('1.1.1.1', 'PUT')]
[('2.2.2.2', 'POST')]
How to add to the output
output
1.1.1.1: PUT = 2
2.2.2.2: GET = 1,POST=1
You could use a dictionary to count:
# initialize the count dict
count_dict= dict()
for line in data:
g = re.findall(r'([\d.]+).*?(GET|POST|PUT|DELETE)', line)
for tup in g:
# get the counts for tuple tup if we don't have it yet
# use 0 (second argument to .get)
num= count_dict.get(tup, 0)
# increase the count and write it back
count_dict[tup]= num+1
# now iterate over the key (tuple) - value (counts)-pairs
# and print the result
for tup, count in count_dict.items():
print(tup, count)
Ok, I have to admit this doesn't give the exact output, you want, but from this you can do in a similar manner:
out_dict= dict()
for (comma_string, request_type), count in count_dict.items():
out_str= out_dict.get(comma_string, '')
sep='' if out_str == '' else ', '
out_str= f'{out_str}{sep}{request_type} = {count}'
out_dict[comma_string]= out_str
for tup, out_str in out_dict.items():
print(tup, out_str)
From your data that outputs:
1.1.1.1 PUT = 2
2.2.2.2 GET = 1, POST = 1
I would look towards Counter.
from collections import Counter
results = []
for line in data:
g = re.findall(r'([\d.]+).*?(GET|POST|PUT|DELETE)', line)
results.append(g[0])
ip_list = set(result[0] for result in results)
for ip in ip_list:
print(ip, Counter(result[1] for result in results if result[0] == ip ))
You can use collection.defaultdict
Ex:
from collections import defaultdict
result = defaultdict(list)
for line in data:
for ip, method in re.findall(r'([\d.]+).*?(GET|POST|PUT|DELETE)', line):
result[ip].append(method)
for k, v in result.items():
temp = ""
for i in set(v):
temp += " {} = {}".format(i, v.count(i))
print("{}{}".format(k, temp))
from collections import Counter
x = [[('1.1.1.1', 'PUT')],[('2.2.2.2', 'GET')],[('1.1.1.1', 'PUT')],[('2.2.2.2', 'POST')]]
# step 1: convert x into a dict.
m = {}
for i in x:
a, b = i[0]
if a not in m.keys():
m[a] = [b]
else:
x = m[a]
x.append(b)
m[a] = x
print('new dict is {}'.format(m))
# step 2 count frequency
m_values = list(m.values())
yy = []
for i in m_values:
x = []
k = list(Counter(i).keys())
v = list(Counter(i).values())
for i in range(len(k)):
x.append(k[i] + '=' + str(v[i]))
yy.append(x)
# step 3, update the value of the dict
m_keys = list(m.keys())
n = len(m_keys)
for i in range(n):
m[m_keys[i]] = yy[i]
print("final dict is{}".format(m))
Output is
new dict is {'1.1.1.1': ['PUT', 'PUT'], '2.2.2.2': ['GET', 'POST']}
final dict is{'1.1.1.1': ['PUT=2'], '2.2.2.2': ['GET=1', 'POST=1']}
Without dependencies and using a dict for counting, in a very basic way. Given the data_set:
data_set = [[('1.1.1.1', 'PUT')],
[('2.2.2.2', 'GET')],
[('2.2.2.2', 'POST')],
[('1.1.1.1', 'PUT')]]
Initialize the variables (manually, just few verbs) then iterate over the data:
counter = {'PUT': 0, 'GET': 0, 'POST': 0, 'DELETE': 0}
res = {}
for data in data_set:
ip, verb = data[0]
if not ip in res:
res[ip] = counter
else:
res[ip][verb] += 1
print(res)
#=> {'1.1.1.1': {'PUT': 1, 'GET': 0, 'POST': 1, 'DELETE': 0}, '2.2.2.2': {'PUT': 1, 'GET': 0, 'POST': 1, 'DELETE': 0}}
It's required to format the output to better fits your needs.
I have a data/character_data.py:
CHARACTER_A = { 1: {"level": 1, "name":"Ann", "skill_level" : 1},
2: {"level": 2, "name":"Tom", "skill_level" : 1}}
CHARACTER_B = { 1: {"level": 1, "name":"Kai", "skill_level" : 1},
2: {"level": 2, "name":"Mel", "skill_level" : 1}}
In main.py, I can do this:
from data import character_data as character_data
print character_data.CHARACTER_A[1]["name"]
>>> output: Ann
print character_data.CHARACTER_B[2]["name"]
>>> output: Mel
How do I achieve this?
from data import character_data as character_data
character_type = "CHARACTER_A"
character_id = 1
print character_data.character_type[character_id]["name"]
>>> correct output should be: Ann
I get AttributeError when try use character_type as "CHARACTER_A".
How about this
In [38]: from data import character_data as character_data
In [39]: character_type = "CHARACTER_A"
In [40]: character_id = 1
In [41]: getattr(character_data, character_type)[character_id]["name"]
Out[41]: 'Ann'
You can use locals():
>>> from data.character_data import CHARACTER_A, CHARACTER_B
>>> character_id = 1
>>> character_type = "CHARACTER_A"
>>> locals()[character_type][character_id]["name"]
Ann
Though, think about merging CHARACTER_A and CHARACTER_B into one dict and access this dict instead of locals().
Also, see Dive into Python: locals and globals.
You need to structure your data properly.
characters = {}
characters['type_a'] = {1: {"level": 1, "name":"Ann", "skill_level" : 1},
2: {"level": 2, "name":"Tom", "skill_level" : 1}}
characters['type_b'] = ...
Or, the better solution is to create your own "character" type, and use that instead:
class Character(object):
def __init__(self, type, level, name, skill):
self.type = type
self.level = level
self.name = name
self.skill = skill
characters = []
characters.append(Character('A',1,'Ann',1))
characters.append(Character('A',2,'Tom',1))
characters.append(Character('B',2,'Kai',1)) # and so on
Then,
all_type_a = []
looking_for = 'A'
for i in characters:
if i.type == looking_for:
all_type_a.append(i)
Or, the shorter way:
all_type_a = [i for i in characters if i.type == looking_for]