Develop Reference

Returning data that is not in ElasticSearch as 0 in doc_count

I am filtering in ElasticSearch. I want doc_count to return 0 on non-data dates, but it doesn't print those dates at all, only dates with data are returned to me. do you know how i can do it? Here is the Python output:
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
...
33479 {'date': '2022-04-13T08:08:00.000Z', 'value': 7}
33480 {'date': '2022-04-13T08:08:00.000Z', 'value': 7}
33481 {'date': '2022-04-13T08:08:00.000Z', 'value': 7}
33482 {'date': '2022-04-13T08:08:00.000Z', 'value': 7}
33483 {'date': '2022-04-13T08:08:00.000Z', 'value': 7}
And here is my ElasticSearch filter:
"from": 0,
"size": 0,
"query": {
"bool": {
"must":
[
{
"range": {
"#timestamp": {
"gte": "now-1M",
"lt": "now"
}
}
}
]
}
},
"aggs": {
"continent": {
"terms": {
"field": "source.geo.continent_name.keyword"
},
"aggs": {
"_source": {
"date_histogram": {
"field": "#timestamp", "interval": "8m"
}}}}}}

You need to set min_doc_count value to 0 for aggregation where you want result with zero doc_count.
{
"from": 0,
"size": 0,
"query": {
"bool": {
"must": [
{
"range": {
"#timestamp": {
"gte": "now-1M",
"lt": "now"
}
}
}
]
}
},
"aggs": {
"continent": {
"terms": {
"field": "source.geo.continent_name.keyword",
"min_doc_count": 0
},
"aggs": {
"_source": {
"date_histogram": {
"field": "#timestamp",
"interval": "8m",
"min_doc_count": 0
}
}
}
}
}
}

update_many objects by reference to objects in same documents

Let's say I have a collection like the following. For every document that contains animals.horse, I want to set animals.goat equal to animals.horse (so the horses don't get lonely or outnumbered).
[
{
"_id": 1,
"animals": {
"goat": 1
}
},
{
"_id": 2,
"animals": {
"cow": 1,
"horse": 2,
"goat": 1
}
},
{
"_id": 3,
"animals": {
"horse": 5
}
},
{
"_id": 4,
"animals": {
"cow": 1
}
}
]
In Mongo shell, this works as desired:
db.collection.update(
{"animals.horse": { "$gt": 0 }},
[ { "$set": { "animals.goat": "$animals.horse" } } ],
{ "multi": true }
)
which achieves the desired result:
[
{
"_id": 1,
"animals": {
"goat": 1
}
},
{
"_id": 2,
"animals": {
"cow": 1,
"goat": 2,
"horse": 2
}
},
{
"_id": 3,
"animals": {
"goat": 5,
"horse": 5
}
},
{
"_id": 4,
"animals": {
"cow": 1
}
}
]
However, this doesn't work in pymongo -- the collection is unaltered.
db.collection.update_many( filter = {'animals.horse': {'$gt':0} },
update = [ {'$set': {'animals.goat': '$animals.horse' } } ],
upsert = True
)
What am I doing wrong?

How to map the dictionary values to another dictionary

I have dictionary which is below
{
"aggregations": {
"A": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{ "key": "ADL", "doc_count": 1 },
{ "key": "SDD", "doc_count": 1 },
{ "key": "JJD", "doc_count": 1 }
]
},
"B": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{ "key": "ABC", "doc_count": 1 },
{ "key": "CDE", "doc_count": 1 },
{ "key": "FGH", "doc_count": 1 }
]
},
"C": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{ "key": "XYX", "doc_count": 1 },
{ "key": "NXS", "doc_count": 1 }
]
}
}
}
aggregations.keys will be aggregationfilters.fieldName
aggregations.buckets.key will be aggregationfilters.values.title
aggregationfilters.values.paragraph is null everytime
aggregations.buckets.doc_count will be aggregationfilters.values.count
Basically I need to extract aggregations.keys and aggregations.bucket values and put into different dictionary.
Need to write a general code structure to do that.
I cannot do with .pop(rename) the dictioanry
My expected out
{
"aggregationfilters": [
{
"name": "ABC",
"fieldName": "A",
"values": [
{ "title": "ADL", "paragraph": null, "count": 1 },
{ "title": "SDD", "paragraph": null, "count": 1 },
{ "title": "JJD", "paragraph": null, "count": 1 }
]
}, {
"name": "CDE",
"fieldName": "B",
"values": [
{ "title": "ABC", "paragraph": null, "count": 1 },
{ "title": "CDE", "paragraph": null, "count": 1 },
{ "title": "FGH", "paragraph": null, "count": 1 }
]
}, {
"name": "FGH",
"fieldName": "C",
"values": [
{ "title": "XYX", "paragraph": null, "count": 1 },
{ "title": "NXS", "paragraph": null, "count": 1 }
]
}
]
}

Well, this works, but even with my best effort this still doesn't look that clean.
import json
source = {
"aggregations": {
"A": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{"key": "ADL", "doc_count": 1},
{"key": "SDD", "doc_count": 1},
{"key": "JJD", "doc_count": 1},
],
},
"B": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{"key": "ABC", "doc_count": 1},
{"key": "CDE", "doc_count": 1},
{"key": "FGH", "doc_count": 1},
],
},
"C": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [{"key": "XYX", "doc_count": 1}, {"key": "NXS", "doc_count": 1}],
},
}
}
convert_map = {
"buckets": "values",
"doc_count": "count",
"key": "title",
}
remove_map = {"sum_other_doc_count", "doc_count_error_upper_bound"}
add_map = {"name": "Changed VAL_", "fieldName": "VAL_"}
def converting_generator(
source_: dict, convert_map_: dict, remove_map_: set, add_map_: dict
):
working_dict = {k: v for k, v in source_.items()}
variable_identifier = "VAL_"
for key, inner_dic in working_dict.items():
inner_dic: dict
for rm_key in remove_map_:
try:
inner_dic.pop(rm_key)
except KeyError:
pass
for add_key, add_val in add_map_.items():
inner_dic[add_key] = add_val.replace(variable_identifier, key)
dumped = json.dumps(inner_dic, indent=2)
for original, target in convert_map_.items():
dumped = dumped.replace(original, target)
yield json.loads(dumped)
converted = {
"aggregation_filters": list(
converting_generator(source["aggregations"], convert_map, remove_map, add_map)
)
}
for inner_dict in converted["aggregation_filters"]:
for even_inner_dict in inner_dict["values"]:
even_inner_dict["paragraph"] = None
print(json.dumps(converted, indent=2))
Output:
{
"aggregation_filters": [
{
"values": [
{
"title": "ADL",
"count": 1,
"paragraph": null
},
{
"title": "SDD",
"count": 1,
"paragraph": null
},
{
"title": "JJD",
"count": 1,
"paragraph": null
}
],
"name": "Changed A",
"fieldName": "A"
},
{
"values": [
{
"title": "ABC",
"count": 1,
"paragraph": null
},
{
"title": "CDE",
"count": 1,
"paragraph": null
},
{
"title": "FGH",
"count": 1,
"paragraph": null
}
],
"name": "Changed B",
"fieldName": "B"
},
{
"values": [
{
"title": "XYX",
"count": 1,
"paragraph": null
},
{
"title": "NXS",
"count": 1,
"paragraph": null
}
],
"name": "Changed C",
"fieldName": "C"
}
]
}
Always show your code, would be nice if that's a working one - to show that you've put at least that worth of the effort on your problem.
I don't bother it as this feels like puzzle solving, but others may not.

Get names of keys in objectpath

How would I get the names of the keys, for example [800, 801] (the key names are unknown) with objectpath.
It is easy in jmespath: keys(#).
"groups": {
"800": {
"short_name": "22",
"oname": "11",
"group": 8,
"title": "SS",
"name": "33",
"onames": [""],
"alt_name": False,
"waytype": 1,
"multiple": 1,
"primary": 1
},
"801": {
"short_name": "ss",
"oname": "zz",
"group": 8,
"title": "ss",
"name": "bbb",
"onames": [""],
"alt_name": False,
"waytype": 1,
"multiple": 1,
"primary": 0
},

let your object is assigned to name variable
const name = { "groups": {
"800": {
"short_name": "22",
"oname": "11",
"group": 8,
"title": "SS",
"name": "33",
"onames": [""],
"alt_name": false,
"waytype": 1,
"multiple": 1,
"primary": 1
},
"801": {
"short_name": "ss",
"oname": "zz",
"group": 8,
"title": "ss",
"name": "bbb",
"onames": [""],
"alt_name": false,
"waytype": 1,
"multiple": 1,
"primary": 0
} } }
Use for loop to get the key name as
for(var num in name.groups) {
console.log(num);
}
and to get the values of key
for(var num in name.groups) {
console.log(name.groups[num]);
}

Parsing and creating nested dictionaries

I would like to create a dictionary containing a nested structure of dictionaries, like bellow :
{
"Jaque": {
"ES": {
"Madrid": [
{
"experience": 9
}
]
},
"FR": {
"Lyon": [
{
"experience": 11.4
}
],
"Paris": [
{
"experience": 20
}
]
}
},
"James": {
"UK": {
"London": [
{
"experience": 10.9
}
]
}
},
"Henry": {
"UK": {
"London": [
{
"experience": 15
}
]
}
},
"Joe": {
"US": {
"Boston": [
{
"experience": 100
}
]
}
}
}
}
My input is a list of dictionaries of this format:
c = [{
"country": "US",
"city": "Boston",
"name": "Joe",
"experience": 100
},
{
"country": "FR",
"city": "Paris",
"name": "Jaque",
"experience": 20
},
{
"country": "FR",
"city": "Lyon",
"name": "Jaque",
"experience": 11.4
},
{
"country": "ES",
"city": "Madrid",
"name": "Jaque",
"experience": 9
},
{
"country": "UK",
"city": "London",
"name": "Henry",
"experience": 15
},
{
"country": "UK",
"city": "London",
"name": "James",
"experience": 10.9
}
]
My first approach was to create the nested dict, step by step:
dd = dict.fromkeys([i.get("name") for i in c],defaultdict(dict))
#will create
# dd = {'Joe': defaultdict(<class 'dict'>, {}), 'Jaque': defaultdict(<class 'dict'>, {}), 'James': defaultdict(<class 'dict'>, {}), 'Henry': defaultdict(<class 'dict'>, {})}
for i in dd:
for j in c:
#verify if name from d is in dict j
if i in j.values():
dd[i]=dict(zip([a.get("country") for a in c if i in a.values() ],[b.get("city") for b in c if i in b.values() ]))
# dd will become
#{'Joe': {'US': 'Boston'}, 'Jaque': {'FR': 'Lyon', 'ES': 'Madrid'}, 'Henry': {'UK': 'London'}, 'James': {'UK': 'London'}}
Now I can't figure a way to create/update the nested structure of dict dd. Is there a more dynamic way to create dict? Thx

You could use itertools.groupby to organize the list similarly to your expected output and then loop to convert to a dict.
from itertools import groupby
from operator import itemgetter
data = [{"country": "US", "city": "Boston", "name": "Joe", "experience": 100 }, {"country": "FR", "city": "Paris", "name": "Jaque", "experience": 20 }, {"country": "FR", "city": "Lyon", "name": "Jaque", "experience": 11.4 }, {"country": "ES", "city": "Madrid", "name": "Jaque", "experience": 9 }, {"country": "UK", "city": "London", "name": "Henry", "experience": 15 }, {"country": "UK", "city": "London", "name": "James", "experience": 10.9 } ]
result = {}
for key, values in groupby(sorted(data, key=itemgetter('name')), key=itemgetter('name')):
result[key] = {
v['country']: {v['city']: [{'experience': v['experience']}]} for v in values
}
print(result)
# {'Henry': {'UK': {'London': [{'experience': 15}]}}, 'James': {'UK': {'London': [{'experience': 10.9}]}}, 'Jaque': {'FR': {'Lyon': [{'experience': 11.4}]}, 'ES': {'Madrid': [{'experience': 9}]}}, 'Joe': {'US': {'Boston': [{'experience': 100}]}}}

You can use recursion with itertools.groupby:
from itertools import groupby
def group(d, keys = None):
key, *keys = keys
new_d = {a:list(b) for a, b in groupby(sorted(d, key=lambda x:x[key]), key=lambda x:x[key])}
t = {a:[{c:d for c, d in k.items() if c != key} for k in b] for a, b in new_d.items()}
return {a:group(b, keys) if not all(len(i) == 1 for i in b) else b for a, b in t.items()}
result = group(data, keys = ['name', 'country', 'city', 'experience'])
import json
print(json.dumps(result, indent=4)))
Output:
{
"Henry": {
"UK": {
"London": [
{
"experience": 15
}
]
}
},
"James": {
"UK": {
"London": [
{
"experience": 10.9
}
]
}
},
"Jaque": {
"ES": {
"Madrid": [
{
"experience": 9
}
]
},
"FR": {
"Lyon": [
{
"experience": 11.4
}
],
"Paris": [
{
"experience": 20
}
]
}
},
"Joe": {
"US": {
"Boston": [
{
"experience": 100
}
]
}
}
}