I have JSON file as mentioned below,
**test.json**
{
"header1" :
{
"header1_body1":
{
"some_key":"some_value",
.......................
},
"header1_body2":
{
"some_key":"some_value",
.......................
}
},
"header2":
{
"header2_body1":
{
"some_key":"some_value",
.......................
},
"header2_body2":
{
"some_key":"some_value",
.......................
}
}
}
Would like to group the JSON content into lists as below:
header1 = ['header1_body1','header1_body2']
header2 = ['header2_body1','header2_body2']
header1, header2 can be till ....header n. So dynamically lists has to be created containing it's values as shown above.
How can i achieve this ?
What's the best optimal way to approach ?
SOLUTION:
with open('test.json') as json_data:
d = json.load(json_data)
for k,v in d.iteritems():
if k == "header1" or k == "header2":
globals()['{}'.format(k)] = d[k].keys()
now, header1 and header2 can be accessed as list.
for i in header1:
print i
Assuming you read the JSON into a variable d (maybe using json.loads), you could iterate over the keys (sorted?) and build the lists with the keys of current value:
for key in sorted(d.keys()):
l = [x for x in sorted(d[key].keys())] # using list comprehension
print(key + ' = ' + str(l))
Fixing your json structure:
{
"header1" :
{
"header1_body1":
{
"some_key":"some_value"
},
"header1_body2":
{
"some_key":"some_value"
}
},
"header2":
{
"header2_body1":
{
"some_key":"some_value"
},
"header2_body2":
{
"some_key":"some_value"
}
}
}
And then loading and creating lists:
header = []
for key, value in dictdump.items():
header.append(list(value.keys()))
for header_num in range(0, len(header)):
print("header{} : {}".format(header_num + 1, header[header_num]))
Gives:
header1 : ['header1_body1', 'header1_body2']
header2 : ['header2_body1', 'header2_body2']
Once you load your json, you can get the list you want for any key by doing something like the following (headers variable below is a placeholder for your loaded json). You don't need to convert it to a list to work with it as an iterable but wrapped it in list(...) to match the output in your question.
list(headers['header1'].keys())
If you need to actually store the list of keys for each of your "header" dicts in some sort of accessible format, then you could create another dictionary that contains the lists you want. For example:
import json
data = """{
"header1" : {
"header1_body1": {
"some_key":"some_value"
},
"header1_body2": {
"some_key":"some_value"
}
},
"header2": {
"header2_body1": {
"some_key":"some_value"
},
"header2_body2": {
"some_key":"some_value"
}
}
}"""
headers = json.loads(data)
# get the list of keys for a specific header
header = list(headers['header1'].keys())
print(header)
# ['header1_body1', 'header1_body2']
# if you really want to store them in another dict
results = {h[0]: list(h[1].keys()) for h in headers.items()}
print(results)
# OUTPUT
# {'header1': ['header1_body1', 'header1_body2'], 'header2': ['header2_body1', 'header2_body2']}
You can use recursion:
d = {'header1': {'header1_body1': {'some_key': 'some_value'}, 'header1_body2': {'some_key': 'some_value'}}, 'header2': {'header2_body1': {'some_key': 'some_value'}, 'header2_body2': {'some_key': 'some_value'}}}
def flatten(_d):
for a, b in _d.items():
yield a
if isinstance(b, dict):
yield from flatten(b)
new_results = {a:[i for i in flatten(b) if i.startswith(a)] for a, b in d.items()}
Output:
{'header1': ['header1_body1', 'header1_body2'], 'header2': ['header2_body1', 'header2_body2']}
import json
with open('test.json') as json_data:
d = json.load(json_data)
for k,v in d.iteritems():
if k == "header1" or k == "header2":
globals()['{}'.format(k)] = d[k].keys()
now, `header1` and `header2` can be accessed as list.
for i in header1:
print i
Related
I want to remove some problematic $oid and everything that contains $ in a json file. I wrote:
import json
with open('C:\\Windows\\System32\\files\\news.json', 'r', encoding="utf8") as handle:
data = [json.loads(line) for line in handle]
for k,v in data[0].items():
#check if key has dict value
if type(v) == dict:
#find id with $
r = list(data[k].keys())[0]
#change value if $ occurs
if r[0] == '$':
data[k] = data[k][r]
print(data)
But I get TypeError: list indices must be integers or slices, not str. I know it is because the json dictionaries are made redeable for Python, but how do I fix it?
Edit: the .json file in my computer looks like this:
{
"_id": {
"$oid": "5e7511c45cb29ef48b8cfcff"
},
"description": "some text",
"startDate": {
"$date": "5e7511c45cb29ef48b8cfcff"
},
"completionDate": {
"$date": "2021-01-05T14:59:58.046Z"
}
}
I believe this is because your k is a str and you try to call data[k]?
It will be better if you show the format of the json as well.
Updating with answer.
This should work for the given json. But if you want to for a larger file. looping can be tricky, specially because you're trying to modify the keys of a dictionary.
import json
line = '{"_id": { "$oid": "5e7511c45cb29ef48b8cfcff" }, "description": "some text", "startDate": { "$date": "5e7511c45cb29ef48b8cfcff"},"completionDate": {"$date": "2021-01-05T14:59:58.046Z"}}'
data = [json.loads(line)]
for k,v in data[0].items():
if type(v) == dict:
for k2, v2 in data[0][k].items():
if k2[0] == '$':
formatted = k2[1:]
del data[0][k][k2]
data[0][k][formatted] = v2
print(data)
# import json
# with open('C:\\Windows\\System32\\files\\news.json', 'r', encoding="utf8") as handle:
# data = [json.loads(line) for line in handle]
data = [
{
"_id": {
"$oid": "5e7511c45cb29ef48b8cfcff"
},
"description": "some text",
"startDate": {
"$date": "5e7511c45cb29ef48b8cfcff"
},
"completionDate": {
"$date": "2021-01-05T14:59:58.046Z"
}
}
]
for d in data:
for k, v in d.items():
# check if key has dict value
del_keys = set()
if type(v) == dict:
# find id with $
del_keys.update([i for i in v if i.startswith("$")])
[v.pop(key) for key in del_keys]
print(data)
# [{'_id': {}, 'description': 'some text', 'startDate': {}, 'completionDate': {}}]
The question may be confusing I know however, I don't know how to ask this properly.
Let me explain the issue. I have a json file like this:
{
"0": "MyItem",
"1": "AnotherItem"
}
Then I am generating a dictionary with the same context above. Like this.
{
"UniqueId": "52355",
"AnotherUniqueId": "234235"
}
They have same length. What I want to do is I want to parse this dictionary to this json file at the same index as an object like:
{
{"0": "MyItem", "UniqueId": "52355"}
{"1": "AnotherItem", "AnotherUniqueId": "234235"}
}
How to achieve this ?
it takes item of each dict and combines them with { **dict1, **dict2 }
then stores each dict as key-value pairs of final dicts.
n = {
"0": "MyItem",
"1": "AnotherItem"
}
m = {
"UniqueId": "52355",
"AnotherUniqueId": "234235"
}
c = {}
for i, keys in enumerate(zip(n, m)):
a, b = keys
c[i] = { **{a:n[a]} , **{b:m[b]} }
print(c)
output :
{
0: {'0': 'MyItem', 'UniqueId': '52355'},
1: {'1': 'AnotherItem', 'AnotherUniqueId': '234235'}
}
Your dictionaries in the final dictionary need to be accompanied by some sort of key since a dictionary is a key-value pair, it wouldn't make sense to not have a key for a value. The output you should go after is this for example
{
0: {"0": "MyItem", "UniqueId": "52355"},
1: {"1": "AnotherItem", "AnotherUniqueId": "234235"}
}
Here's my solution
b = {
"UniqueId": "52355",
"AnotherUniqueId": "234235"
}
a = {
"0": "MyItem",
"1": "AnotherItem"
}
# Assuming a and b are of the same length
c = {} # will contain the final dictionaries
index = 0
for i,j in zip(a,b):
temp = {}
temp[i]=a[i]
temp[j]=b[j]
c[index] = temp
index+=1
print(c)
This question already has answers here:
How to remove all empty fields in a nested dict?
(5 answers)
Closed 4 years ago.
In a Python script I run json_decoded = json.load(file) that results in the following JSON data:
json_decoded = {
"data": {
"keyA": [
{
"subkeyA1": "valueA1",
"subkeyA2": "valueA2"
},
{
"subkeyA3": ""
}
],
"keyB": []
}
}
I would like to remove all the [] and "" ("empty") key-value pairs so to have:
json_decoded = {
"data": {
"keyA": [
{
"subkeyA1": "valueA1",
"subkeyA2": "valueA2"
}
]
}
}
How can I have that?
Note: I am pretty new to Python (v2.7.3).
You can use recursion to traverse the structure:
json_decoded = {'data': {'keyA': [{'subkeyA1': 'valueA1', 'subkeyA2': 'valueA2'}, {'subkeyA3': ''}], 'keyB': []}}
def remove_empty(d):
final_dict = {}
for a, b in d.items():
if b:
if isinstance(b, dict):
final_dict[a] = remove_empty(b)
elif isinstance(b, list):
final_dict[a] = list(filter(None, [remove_empty(i) for i in b]))
else:
final_dict[a] = b
return final_dict
print(remove_empty(json_decoded))
Output:
{'data':
{'keyA':
[{'subkeyA1': 'valueA1',
'subkeyA2': 'valueA2'}
]
}
}
With given script I am able to get output as I showed in a screenshot,
but there is a column named as cve.description.description_data which is again in json format. I want to extract that data as well.
import json
import pandas as pd
from pandas.io.json import json_normalize
#load json object
with open('nvdcve-1.0-modified.json') as f:
d = json.load(f)
#tells us parent node is 'programs'
nycphil = json_normalize(d['CVE_Items'])
nycphil.head(3)
works_data = json_normalize(data=d['CVE_Items'], record_path='cve')
works_data.head(3)
nycphil.to_csv("test4.csv")
If I change works_data = json_normalize(data=d['CVE_Items'], record_path='cve.descr') it gives this error:
"result = result[spec] KeyError: 'cve.description'"
JSON format as follows:
{
"CVE_data_type":"CVE",
"CVE_data_format":"MITRE",
"CVE_data_version":"4.0",
"CVE_data_numberOfCVEs":"1000",
"CVE_data_timestamp":"2018-04-04T00:00Z",
"CVE_Items":[
{
"cve":{
"data_type":"CVE",
"data_format":"MITRE",
"data_version":"4.0",
"CVE_data_meta":{
"ID":"CVE-2001-1594",
"ASSIGNER":"cve#mitre.org"
},
"affects":{
"vendor":{
"vendor_data":[
{
"vendor_name":"gehealthcare",
"product":{
"product_data":[
{
"product_name":"entegra_p&r",
"version":{
"version_data":[
{
"version_value":"*"
}
]
}
}
]
}
}
]
}
},
"problemtype":{
"problemtype_data":[
{
"description":[
{
"lang":"en",
"value":"CWE-255"
}
]
}
]
},
"references":{
"reference_data":[
{
"url":"http://apps.gehealthcare.com/servlet/ClientServlet/2263784.pdf?DOCCLASS=A&REQ=RAC&DIRECTION=2263784-100&FILENAME=2263784.pdf&FILEREV=5&DOCREV_ORG=5&SUBMIT=+ ACCEPT+"
},
{
"url":"http://www.forbes.com/sites/thomasbrewster/2015/07/10/vulnerable- "
},
{
"url":"https://ics-cert.us-cert.gov/advisories/ICSMA-18-037-02"
},
{
"url":"https://twitter.com/digitalbond/status/619250429751222277"
}
]
},
"description":{
"description_data":[
{
"lang":"en",
"value":"GE Healthcare eNTEGRA P&R has a password of (1) value."
}
]
}
},
"configurations":{
"CVE_data_version":"4.0",
"nodes":[
{
"operator":"OR",
"cpe":[
{
"vulnerable":true,
"cpe22Uri":"cpe:/a:gehealthcare:entegra_p%26r",
"cpe23Uri":"cpe:2.3:a:gehealthcare:entegra_p\\&r:*:*:*:*:*:*:*:*"
}
]
}
]
},
"impact":{
"baseMetricV2":{
"cvssV2":{
"version":"2.0",
"vectorString":"(AV:N/AC:L/Au:N/C:C/I:C/A:C)",
"accessVector":"NETWORK",
"accessComplexity":"LOW",
"authentication":"NONE",
"confidentialityImpact":"COMPLETE",
"integrityImpact":"COMPLETE",
"availabilityImpact":"COMPLETE",
"baseScore":10.0
},
"severity":"HIGH",
"exploitabilityScore":10.0,
"impactScore":10.0,
"obtainAllPrivilege":false,
"obtainUserPrivilege":false,
"obtainOtherPrivilege":false,
"userInteractionRequired":false
}
},
"publishedDate":"2015-08-04T14:59Z",
"lastModifiedDate":"2018-03-28T01:29Z"
}
]
}
I want to flatten all data.
Assuming the multiple URLs delineate between rows and all else meta data repeats, consider a recursive function call to extract every key-value pair in nested json object, d.
The recursive function will call global to update the needed global objects to be binded into a list of dictionaries for pd.DataFrame() call. Last loop at end updates the recursive function's dictionary, inner, to integrate the different urls (stored in multi)
import json
import pandas as pd
# load json object
with open('nvdcve-1.0-modified.json') as f:
d = json.load(f)
multi = []; inner = {}
def recursive_extract(i):
global multi, inner
if type(i) is list:
if len(i) == 1:
for k,v in i[0].items():
if type(v) in [list, dict]:
recursive_extract(v)
else:
inner[k] = v
else:
multi = i
if type(i) is dict:
for k,v in i.items():
if type(v) in [list, dict]:
recursive_extract(v)
else:
inner[k] = v
recursive_extract(d['CVE_Items'])
data_dict = []
for i in multi:
tmp = inner.copy()
tmp.update(i)
data_dict.append(tmp)
df = pd.DataFrame(data_dict)
df.to_csv('Output.csv')
Output (all columns the same except for URL, widened for emphasis)
As the question explains the problem, I've been trying to generate nested JSON object. In this case I have for loops getting the data out of dictionary dic. Below is the code:
f = open("test_json.txt", 'w')
flag = False
temp = ""
start = "{\n\t\"filename\"" + " : \"" +initial_filename+"\",\n\t\"data\"" +" : " +" [\n"
end = "\n\t]" +"\n}"
f.write(start)
for i, (key,value) in enumerate(dic.iteritems()):
f.write("{\n\t\"keyword\":"+"\""+str(key)+"\""+",\n")
f.write("\"term_freq\":"+str(len(value))+",\n")
f.write("\"lists\":[\n\t")
for item in value:
f.write("{\n")
f.write("\t\t\"occurance\" :"+str(item)+"\n")
#Check last object
if value.index(item)+1 == len(value):
f.write("}\n"
f.write("]\n")
else:
f.write("},") # close occurrence object
# Check last item in dic
if i == len(dic)-1:
flag = True
if(flag):
f.write("}")
else:
f.write("},") #close lists object
flag = False
#check for flag
f.write("]") #close lists array
f.write("}")
Expected output is:
{
"filename": "abc.pdf",
"data": [{
"keyword": "irritation",
"term_freq": 5,
"lists": [{
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 2
}]
}, {
"keyword": "bomber",
"lists": [{
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 2
}],
"term_freq": 5
}]
}
But currently I'm getting an output like below:
{
"filename": "abc.pdf",
"data": [{
"keyword": "irritation",
"term_freq": 5,
"lists": [{
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 2
},] // Here lies the problem "," before array(last element)
}, {
"keyword": "bomber",
"lists": [{
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 1
}, {
"occurance": 2
},], // Here lies the problem "," before array(last element)
"term_freq": 5
}]
}
Please help, I've trying to solve it, but failed. Please don't mark it duplicate since I have already checked other answers and didn't help at all.
Edit 1:
Input is basically taken from a dictionary dic whose mapping type is <String, List>
for example: "irritation" => [1,3,5,7,8]
where irritation is the key, and mapped to a list of page numbers.
This is basically read in the outer for loop where key is the keyword and value is a list of pages of occurrence of that keyword.
Edit 2:
dic = collections.defaultdict(list) # declaring the variable dictionary
dic[key].append(value) # inserting the values - useless to tell here
for key in dic:
# Here dic[x] represents list - each value of x
print key,":",dic[x],"\n" #prints the data in dictionary
What #andrea-f looks good to me, here another solution:
Feel free to pick in both :)
import json
dic = {
"bomber": [1, 2, 3, 4, 5],
"irritation": [1, 3, 5, 7, 8]
}
filename = "abc.pdf"
json_dict = {}
data = []
for k, v in dic.iteritems():
tmp_dict = {}
tmp_dict["keyword"] = k
tmp_dict["term_freq"] = len(v)
tmp_dict["lists"] = [{"occurrance": i} for i in v]
data.append(tmp_dict)
json_dict["filename"] = filename
json_dict["data"] = data
with open("abc.json", "w") as outfile:
json.dump(json_dict, outfile, indent=4, sort_keys=True)
It's the same idea, I first create a big json_dict to be saved directly in json. I use the with statement to save the json avoiding the catch of exception
Also, you should have a look to the doc of json.dumps() if you need future improve in your json output.
EDIT
And just for fun, if you don't like tmp var, you can do all the data for loop in a one-liner :)
json_dict["data"] = [{"keyword": k, "term_freq": len(v), "lists": [{"occurrance": i} for i in v]} for k, v in dic.iteritems()]
It could gave for final solution something not totally readable like this:
import json
json_dict = {
"filename": "abc.pdf",
"data": [{
"keyword": k,
"term_freq": len(v),
"lists": [{"occurrance": i} for i in v]
} for k, v in dic.iteritems()]
}
with open("abc.json", "w") as outfile:
json.dump(json_dict, outfile, indent=4, sort_keys=True)
EDIT 2
It looks like you don't want to save your json as the desired output, but be abble to read it.
In fact, you can also use json.dumps() in order to print your json.
with open('abc.json', 'r') as handle:
new_json_dict = json.load(handle)
print json.dumps(json_dict, indent=4, sort_keys=True)
There is still one problem here though, "filename": is printed at the end of the list because the d of data comes before the f.
To force the order, you will have to use an OrderedDict in the generation of the dict. Be careful the syntax is ugly (imo) with python 2.X
Here is the new complete solution ;)
import json
from collections import OrderedDict
dic = {
'bomber': [1, 2, 3, 4, 5],
'irritation': [1, 3, 5, 7, 8]
}
json_dict = OrderedDict([
('filename', 'abc.pdf'),
('data', [ OrderedDict([
('keyword', k),
('term_freq', len(v)),
('lists', [{'occurrance': i} for i in v])
]) for k, v in dic.iteritems()])
])
with open('abc.json', 'w') as outfile:
json.dump(json_dict, outfile)
# Now to read the orderer json file
with open('abc.json', 'r') as handle:
new_json_dict = json.load(handle, object_pairs_hook=OrderedDict)
print json.dumps(json_dict, indent=4)
Will output:
{
"filename": "abc.pdf",
"data": [
{
"keyword": "bomber",
"term_freq": 5,
"lists": [
{
"occurrance": 1
},
{
"occurrance": 2
},
{
"occurrance": 3
},
{
"occurrance": 4
},
{
"occurrance": 5
}
]
},
{
"keyword": "irritation",
"term_freq": 5,
"lists": [
{
"occurrance": 1
},
{
"occurrance": 3
},
{
"occurrance": 5
},
{
"occurrance": 7
},
{
"occurrance": 8
}
]
}
]
}
But be carefull, most of the time, it is better to save a regular .json file in order to be cross languages.
Your current code is not working because the loop iterates through the before-last item adding the }, then when the loop runs again it sets the flag to false, but the last time it ran it added a , since it thought that there will be another element.
If this is your dict: a = {"bomber":[1,2,3,4,5]} then you can do:
import json
file_name = "a_file.json"
file_name_input = "abc.pdf"
new_output = {}
new_output["filename"] = file_name_input
new_data = []
i = 0
for key, val in a.iteritems():
new_data.append({"keyword":key, "lists":[], "term_freq":len(val)})
for p in val:
new_data[i]["lists"].append({"occurrance":p})
i += 1
new_output['data'] = new_data
Then save the data by:
f = open(file_name, 'w+')
f.write(json.dumps(new_output, indent=4, sort_keys=True, default=unicode))
f.close()