I need your help to count all array from all my "doc" documents.
sample this i have 4 document with different array list:
[{
"uid": "111",
"data": [{
"eid": "111a",
"ori": ""
},
{
"eid": "111b",
"ori": ""
}]
},
{
"uid": "222",
"data": [{
"eid": "222a",
"ori": ""
}]
},
{
"uid": "333",
"data": [{
"eid": "333a",
"ori": ""
}]
},
{
"uid": "444",
"data": [{
"eid": "444a",
"ori": ""
},
{
"eid": "444b",
"ori": ""
}]
}]
how i can count total data on all my documents ? in this sample is 6 by ori. Already this:
db.doc.find({"data.ori": ""}).count()
try many methods from stackoverflow, but not luck.. if you have any idea to do this or have tutorial for this, let me know and thanks.
I've cleaned up your input by assuming each dictionary is held in a list as follows:
doc = [
{
"uid": "111",
"data": [{
"eid": "111a",
"ori": ""
},
{
"eid": "111b",
"ori": ""
}]
},
{
"uid": "222",
"data": [{
"eid": "222a",
"ori": ""
}]
},
{
"uid": "333",
"data": [{
"eid": "333a",
"ori": ""
}]
},
{
"uid": "444",
"data": [{
"eid": "444a",
"ori": ""
},
{
"eid": "444b",
"ori": ""
}]
}]
found = 0
for d in doc:
data = d['data']
for x in data:
if 'ori' in x:
found += 1
print(found)
Pymongo $count(aggregation) may help:
docs = db.doc.aggregate( [
{ $group: { _id: null, myCount: { $sum: 1 } } },
{ $project: { _id: 0 } }
] )
The operation returns the following results:
{
"myCount": 4
}
Related
I have a json file name input which as follows
{
"abc": {
"dbc": {
"type": "string",
"metadata": {
"description": "Name of the namespace"
}
},
"fgh": {
"type": "string",
"metadata": {
"description": "Name of the Topic"
}
}
},
"resources": [
{
"sku": {
"name": "[parameters('sku')]"
},
"properties": {},
"resources": [
{
"resources": [
{
"resources": [
{
"properties": {
"filterType": "SqlFilter",
"sqlFilter": {
"sqlExpression": "HAI"
}
}
}
]
}
]
}
]
}
]
}
I want "sqlExpression": "HAI" value to be replaced with BYE as below
"sqlExpression": "BYE"
I want python code to do it, I tried the below code but not working
input['resources'][0]['resources'][0]['resources'][0]['resources'][0][properties][0][sqlFilter][0][sqlExpression][0]='BYE'
inp = {
"abc": {
"dbc": {
"type": "string",
"metadata": {
"description": "Name of the namespace"
}
},
"fgh": {
"type": "string",
"metadata": {
"description": "Name of the Topic"
}
}
},
"resources": [
{
"sku": {
"name": "[parameters('sku')]"
},
"properties": {},
"resources": [
{
"resources": [
{
"resources": [
{
"properties": {
"filterType": "SqlFilter",
"sqlFilter": {
"sqlExpression": "HAI"
}
}
}
]
}
]
}
]
}
]
}
inp['resources'][0]['resources'][0]['resources'][0]['resources'][0]['properties']['sqlFilter']['sqlExpression']='BYE'
print(inp)
Result
{'abc': {'dbc': ...truncated... {'sqlExpression': 'BYE'}}}]}]}]}]}
I am trying to extract data from the json file I got from a get request.
{
"data": [
{
"type": "Projects",
"id": "102777c7-50a7-592d-1b65-621d5850a5bb",
"attributes": {
"name": "Hydroelectric Project Updated from Postman",
"projectid": "001"
},
"relationships": {
"Accounts": "Account1"
"Notes": "Note1"
}
},
{
"type": "Projects",
"id": "102c7131-d797-c085-d248-621d5820494f",
"attributes": {
"name": "Ana Hydroelectric Project",
"projectid": "002"
},
"relationships": {
"Accounts": "Account1"
"Notes": "Note1"
}
},
{
"type": "Projects",
"id": "1041f300-5acf-4bd9-2ec4-621d58bbe6bc",
"attributes": {
"name": "Methane Capture Project",
"projectid": "003"
},
"relationships": {
"Accounts": "Account1"
"Notes": "Note1"
}
}
]
}
I have an empty dictionary that stores projectid as Key.
projectids = {
001:"",
002:"",
003:"",
004:"",
}
I was looking for a way to find "projectid" inside "attributes" and the corresponding value for "id" and populate the dictionary projectids with the key(['attributes']['projectid']) and values(id):
{
"001": "102777c7-50a7-592d-1b65-621d5850a5bb",
"002": "102c7131-d797-c085-d248-621d5820494f",
"003": "1041f300-5acf-4bd9-2ec4-621d58bbe6bc",
"004": ""
}
You can try this, assuming data is your variable for the response from the GET request
# this solution will populate for all project ids
projectids = {}
for item in data['data']:
projectids[item['attributes']['projectid']] = item['id']
Output:
{
'001': '102777c7-50a7-592d-1b65-621d5850a5bb',
'002': '102c7131-d797-c085-d248-621d5820494f',
'003': '1041f300-5acf-4bd9-2ec4-621d58bbe6bc'
}
if you're trying to match with already existing projectids in a dict then try
# this solution will search for only pre-specified project ids
projectids = {
"001": "",
"002": "",
"003": "",
"004": "",
}
for idx in projectids.keys():
# find the index of matching dict from data['data']
# will return None if match is not found
matching_index = next((i for i, item in enumerate(data['data']) if
item["attributes"]["projectid"] == idx), None)
if matching_index is not None:
projectids[idx] = data['data'][matching_index]['id']
If data is your input data from the question, then:
projectids = {f"{i:>03}": "" for i in range(1, 5)}
out = {
**projectids,
**{d["attributes"]["projectid"]: d["id"] for d in data["data"]},
}
print(out)
Prints:
{
"001": "102777c7-50a7-592d-1b65-621d5850a5bb",
"002": "102c7131-d797-c085-d248-621d5820494f",
"003": "1041f300-5acf-4bd9-2ec4-621d58bbe6bc",
"004": "",
}
Simply try this:
json_data = {
"data": [
{
"type": "Projects",
"id": "102777c7-50a7-592d-1b65-621d5850a5bb",
"attributes": {
"name": "Hydroelectric Project Updated from Postman",
"projectid": "001"
},
"relationships": {
"Accounts": "Account1",
"Notes": "Note1"
}
},
{
"type": "Projects",
"id": "102c7131-d797-c085-d248-621d5820494f",
"attributes": {
"name": "Ana Hydroelectric Project",
"projectid": "002"
},
"relationships": {
"Accounts": "Account1",
"Notes": "Note1"
}
},
{
"type": "Projects",
"id": "1041f300-5acf-4bd9-2ec4-621d58bbe6bc",
"attributes": {
"name": "Methane Capture Project",
"projectid": "003"
},
"relationships": {
"Accounts": "Account1",
"Notes": "Note1"
}
}
]
}
Just asumme the above json data and try the following code:
project_ids = {item['attributes']['projectid']:item['id'] for item in json_data['data']}
expected output:
{'001': '102777c7-50a7-592d-1b65-621d5850a5bb',
'002': '102c7131-d797-c085-d248-621d5820494f',
'003': '1041f300-5acf-4bd9-2ec4-621d58bbe6bc'}
I got a resultant json from an API in the following format
[{
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Name": "Kiran"
}
}, {
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Age": "24"
}
},
{
"Uid": "196f5865-e9fe-4847-86ae-97d0bf57b816",
"Id": "84909ecb-c92e-48a7-bcaa-d478bf3a9220",
"Details": {
"Name": "Shreyas"
}
}
]
since the Uid and Id are same for multiple entires, can I club them togeather with Details key being the comma seperate key,value pair? Something like mentioned below
[{
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Name": "Kiran",
"Age": "24"
}
},
{
"Uid": "196f5865-e9fe-4847-86ae-97d0bf57b816",
"Id": "84909ecb-c92e-48a7-bcaa-d478bf3a9220",
"Details": {
"Name": "Shreyas"
}
}]
Please Guide me on this for the approach to be followed. Thanks
What you need is the dictionary function update(). Here's an example:
A = [{
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Name": "Kiran"
}
}, {
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Age": "24"
}
},
{
"Uid": "196f5865-e9fe-4847-86ae-97d0bf57b816",
"Id": "84909ecb-c92e-48a7-bcaa-d478bf3a9220",
"Details": {
"Name": "Shreyas"
}
}
]
B = []
def find(uid, id_):
for i, d in enumerate(B):
if d['Uid'] == uid and d['Id'] == id_:
return i
return -1
for d in A:
if (i := find(d['Uid'], d['Id'])) < 0:
B.append(d)
else:
B[i]['Details'].update(d['Details'])
print(B)
Prettyfied output:
[
{
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Name": "Kiran",
"Age": "24"
}
},
{
"Uid": "196f5865-e9fe-4847-86ae-97d0bf57b816",
"Id": "84909ecb-c92e-48a7-bcaa-d478bf3a9220",
"Details": {
"Name": "Shreyas"
}
}
]
Note:
This could be very inefficient if your API response contains very large numbers of dictionaries. You might need a completely different approach
You should iterate over the list and merge with accumulator with (Uid, Id) as key:
from typing import Dict, List
l = [{
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Name": "Kiran"
}
}, {
"Uid": "40cc6103-1cf0-4735-b882-d14d32018e58",
"Id": "9e1a0057-4570-4a6e-8ff5-88b2facbaf4e",
"Details": {
"Age": "24"
}
},
{
"Uid": "196f5865-e9fe-4847-86ae-97d0bf57b816",
"Id": "84909ecb-c92e-48a7-bcaa-d478bf3a9220",
"Details": {
"Name": "Shreyas"
}
}
]
def mergeItem(it: Dict, acc: Dict) -> Dict:
uid = it["Uid"]
id = it["Id"]
if (uid, id) in acc:
acc[(uid, id)] = {"Uid": uid, "Id": id, "Details": {**acc[(uid, id)]["Details"], **it["Details"]}}
else:
acc[(uid, id)] = {"Uid": uid, "Id": id, "Details": it["Details"]}
return acc
def mergeList(a:List) -> Dict:
acc = {}
for v in a:
acc = mergeItem(v, acc)
return acc
print(list(mergeList(l).values()))
# [
# {
# 'Uid': '40cc6103-1cf0-4735-b882-d14d32018e58',
# 'Id': '9e1a0057-4570-4a6e-8ff5-88b2facbaf4e',
# 'Details': {'Name': 'Kiran', 'Age': '24'}},
# {
# 'Uid': '196f5865-e9fe-4847-86ae-97d0bf57b816',
# 'Id': '84909ecb-c92e-48a7-bcaa-d478bf3a9220',
# 'Details': {'Name': 'Shreyas'}
# }
# ]
Relatively new to Python here, coming from a node.js background, having quite a few issues parsing the output I get from get_query_results()
Documentation Link
I have been at this for some hours, i have tried iterating through the ['ResultSetMetadata']['ColumnInfo'] to grab the column names, but i don't know how to tie the ['ResultSet']['Data'] to these items so the code knows which name to apply to each dataValue.
I know i need to select the row headers then add the associated objects to those rows, but the logic on how to do such a thing in python escapes me.
I can see that the first column name always lines up with the first ['Data']['VarCharValue'] so I can get all the values in order, but if I loop through ['ResultSet']['Rows'] how do I isolate the first iteration as the column names to then populate with each other row?
Or is there a better way to do this?
Here is my json.dumps(ATHENAoutput)
{
"ResultSet": {
"Rows": [{
"Data": [{
"VarCharValue": "postcode"
}, {
"VarCharValue": "CountOf"
}]
}, {
"Data": [{
"VarCharValue": "1231"
}, {
"VarCharValue": "2"
}]
}, {
"Data": [{
"VarCharValue": "1166"
}, {
"VarCharValue": "2"
}]
}, {
"Data": [{
"VarCharValue": "3651"
}, {
"VarCharValue": "3"
}]
}, {
"Data": [{
"VarCharValue": "2171"
}, {
"VarCharValue": "2"
}]
}, {
"Data": [{
"VarCharValue": "4697"
}, {
"VarCharValue": "2"
}]
}, {
"Data": [{
"VarCharValue": "4450"
}, {
"VarCharValue": "2"
}]
}, {
"Data": [{
"VarCharValue": "4469"
}, {
"VarCharValue": "1"
}]
}],
"ResultSetMetadata": {
"ColumnInfo": [{
"Scale": 0,
"Name": "postcode",
"Nullable": "UNKNOWN",
"TableName": "",
"Precision": 2147483647,
"Label": "postcode",
"CaseSensitive": true,
"SchemaName": "",
"Type": "varchar",
"CatalogName": "hive"
}, {
"Scale": 0,
"Name": "CountOf",
"Nullable": "UNKNOWN",
"TableName": "",
"Precision": 19,
"Label": "CountOf",
"CaseSensitive": false,
"SchemaName": "",
"Type": "bigint",
"CatalogName": "hive"
}]
}
},
"ResponseMetadata": {
"RetryAttempts": 0,
"HTTPStatusCode": 200,
"RequestId": "18190e7c-901c-40b4-b6ef-10a5013b1a70",
"HTTPHeaders": {
"date": "Mon, 01 Oct 2018 04:51:14 GMT",
"x-amzn-requestid": "18190e7c-901c-40b4-b6ef-10a5013b1a70",
"content-length": "1464",
"content-type": "application/x-amz-json-1.1",
"connection": "keep-alive"
}
}
}
My desired Result is a JSON Array like the following:
[{
"postcode": "2171",
"CountOf": "2"
}, {
"postcode": "4697",
"CountOf": "2"
}, {
"postcode": "1166",
"CountOf": "2"
},
...
]
>>> def get_var_char_values(d):
... return [obj['VarCharValue'] for obj in d['Data']]
...
...
... header, *rows = input_data['ResultSet']['Rows']
... header = get_var_char_values(header)
... result = [dict(zip(header, get_var_char_values(row))) for row in rows]
>>> import json; print(json.dumps(result, indent=2))
[
{
"postcode": "4450",
"CountOf": "2"
},
{
"postcode": "1231",
"CountOf": "2"
},
{
"postcode": "4469",
"CountOf": "1"
},
{
"postcode": "3651",
"CountOf": "3"
},
{
"postcode": "1166",
"CountOf": "2"
},
{
"postcode": "4697",
"CountOf": "2"
},
{
"postcode": "2171",
"CountOf": "2"
}
]
In elastic search aggregation query I need to get all the movies watched by the user who watches the movie "Frozen". This is how my Result source
{
"_index": "user",
"_type": "user",
"_id": "ovUowmUBREWOv-CU-4RT",
"_version": 4,
"_score": 1,
"_source": {
"movies": [
"Angry birds 1",
"PINNOCCHIO",
"Frozen",
"Hotel Transylvania 3"
],
"user_id": 86
}
}
This is the query I'm using.
{
"query": {
"match": {
"movies": "Frozen"
}
},
"size": 0,
"aggregations": {
"movies_like_Frozen": {
"terms": {
"field": "movies",
"min_doc_count": 1
}
}
}
}
The result I got in the bucket is correct, but the movie names are splits by white space like this
"buckets": [
{
"key": "3",
"doc_count": 2
},
{
"key": "hotel",
"doc_count": 2
},
{
"key": "transylvania",
"doc_count": 2
},
{
"key": "1",
"doc_count": 1
},
{
"key": "angry",
"doc_count": 1
},
{
"key": "birds",
"doc_count": 1
}
]
How can I get buckets with "Angry birds 1", "Hotel Transylvania 3" as result.
Please help.
In elasticsearch 6.x, every text field is analyzed implicitly. To override this, you need to create a mapping for text type fields as not_analyzed in an index, then insert documents in it.
In your case,
{
"mappings": {
"user": {
"properties": {
"movies": {
"type": "text",
"index": "not_analyzed",
"fields": {
"keyword": {
"type": "text",
"index": "not_analyzed"
}
}
},
"user_id": {
"type": "long"
}
}
}
}
}
Hope it works.