MongoDB - Multi Level Nested Array Update() using Flask [duplicate] - python

This question already has answers here:
Updating a Nested Array with MongoDB
(2 answers)
Closed 3 years ago.
i'm trying to update data on MongoDB using python-Flask but i found an error. I have followed the documentation how to implement it but the error still there. Could anyone help me to fix this?
#app.route('/updateData', methods=['POST'])
def updateData():
dataList = mongo.db.warehouse
old_Data = {
"name": "Pulo Gebang Warehouse"
}
new_Data = {
'$push':{"racks":{"rack columns":{"rack objects":{"items":{'$each':[{"index":4, "item":{"SKU": "HD 2179/3",
"arrivalDate": "2019-10-22",
"brand": "Philips",
"maxQty": 30,
"name": "Playstatus 10",
"qty": 10}}]}}}}}
}
dataList.update(old_Data, new_Data)
return "Update Success!"
This is my Database
[
{
"floorRacks": [
{
"adjacentRackID": "A1",
"floorColumn": [
{
"floorObjects": [
{
"index": 0,
"item": {
"SKU": "HD 1179/3",
"arrivalDate": "2019-10-22",
"brand": "Philips",
"maxQty": 30,
"name": "Blender Super mewah",
"qty": 10
}
},
{
"index": 1,
"item": "null"
}
],
"index": 0
}
]
}
],
"name": "Pulo Gebang Warehouse",
"racks": [
{
"code": "A",
"rack_columns": [
{
"columnID": 0,
"rack_objects": [
{
"items": [
{
"index": 0,
"item": {
"SKU": "HD 1179/3",
"arrivalDate": "2019-10-22",
"brand": "Philips",
"maxQty": 30,
"name": "Blender Super mewah",
"qty": 10
}
},
{
"index": 1,
"item": {
"SKU": "HD 1179/3",
"arrivalDate": "2019-10-22",
"brand": "Philips",
"maxQty": 30,
"name": "Blender Super mewah",
"qty": 10
}
},
{
"index": 2,
"item": "null"
},
{
"index": 3,
"item": {
"SKU": "HD 1189/3",
"arrivalDate": "2019-10-22",
"brand": "Philips",
"maxQty": 35,
"name": "Blender Super mewah Eksklusif",
"qty": 10
}
}
],
"level": 0
}
]
}
]
}
]
}
]
and here is the full ERROR Message
pymongo.errors.WriteError: The dollar ($) prefixed field '$each' in
'racks..rack columns.rack objects.items.$each' is not valid for
storage.


Try changing the query to below:
{
"$push": {
"racks.rack columns.rack objects.items": {
"$each": [
{
"index": 4,
"item": {
"SKU": "HD 2179/3",
"arrivalDate": "2019-10-22",
"brand": "Philips",
"maxQty": 30,
"name": "Playstatus 10",
"qty": 10
}
}
]
}
}
}

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Here is the python script I used. have been trying different variations but no luck getting different errors in all other instances
filename = Path('fre.json')
data = []
with open(filename,'r') as json_file:
data_str = json_file.read()
data_str = data_str.split('[',1)[-1]
data_str = data_str.rsplit(']',1)[0]
data_str = data_str.split('][')
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{
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{
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"productStockAlert": {
"entity": "69825",
"map": {
"203": {
"label": "52,5",
"": "",
"6610": "6610",
"6498": "6498",
"6582": "6582",
"6516": "6516",
"6501": "6501",
"6518": "6518",
"6504": "6504",
"6395": "6395",
"6404": "6404",
"6533": "6533",
"6407": "6407",
"6530": "6530",
"6410": "6410",
"6413": "6413",
"6416": "6416",
"6534": "6534",
"6419": "6419",
"6422": "6422",
"6425": "6425",
"6398": "6398",
"6401": "6401",
"6531": "6531",
"6431": "6431",
"6443": "6443",
"6446": "6446",
"6495": "6495",
"6449": "6449",
"6452": "6452",
"6455": "6455",
"6458": "6458",
"6461": "6461",
"6807": "6807",
"6464": "6464",
"6434": "6434",
"6437": "6437",
"6558": "6558",
"6440": "6440",
"6480": "6480",
"6481": "6481",
"6382": "6382",
"6465": "6465",
"6631": "6631",
"6332": "6332",
"6466": "6466",
"6348": "6348",
"6634": "6634",
"6320": "6320",
"6351": "6351",
"6384": "6384",
"6659": "6659",
"6335": "6335",
"6388": "6388",
"6508": "6508",
"6354": "6354",
"6338": "6338",
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"6357": "6357",
"6390": "6390",
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"6637": "6637",
"6326": "6326",
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"6640": "6640",
"6341": "6341",
"6392": "6392",
"6560": "6560",
"6365": "6365",
"6344": "6344",
"6385": "6385",
"6838": "6838",
"6368": "6368",
"6386": "6386",
"6370": "6370",
"6643": "6643",
"6628": "6628",
"6329": "6329",
"6529": "6529",
"6387": "6387",
"6843": "6843",
"6347": "6347",
"6470": "6470",
"6360": "6360",
"6646": "6646",
"6472": "6472",
"6323": "6323",
"6564": "6564",
"6593": "6593",
"6474": "6474",
"6376": "6376",
"6565": "6565",
"6561": "6561",
"6567": "6567",
"6604": "6604",
"6607": "6607"
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"205": {
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"": "",
"6513": "6513",
"6497": "6497",
"6583": "6583",
"6500": "6500",
"6821": "6821",
"6503": "6503",
"6532": "6532",
"6394": "6394",
"6403": "6403",
"6406": "6406",
"6409": "6409",
"6412": "6412",
"6415": "6415",
"6418": "6418",
"6421": "6421",
"6424": "6424",
"6397": "6397",
"6400": "6400",
"6430": "6430",
"6442": "6442",
"6445": "6445",
"6448": "6448",
"6451": "6451",
"6454": "6454",
"6457": "6457",
"6460": "6460",
"6463": "6463",
"6433": "6433",
"6436": "6436",
"6439": "6439",
"6555": "6555",
"6468": "6468",
"6507": "6507",
"6632": "6632",
"6331": "6331",
"6319": "6319",
"6635": "6635",
"6372": "6372",
"6334": "6334",
"6661": "6661",
"6350": "6350",
"6337": "6337",
"6663": "6663",
"6353": "6353",
"6619": "6619",
"6325": "6325",
"6621": "6621",
"6638": "6638",
"6356": "6356",
"6340": "6340",
"6623": "6623",
"6641": "6641",
"6364": "6364",
"6343": "6343",
"6625": "6625",
"6840": "6840",
"6367": "6367",
"6328": "6328",
"6644": "6644",
"6371": "6371",
"6346": "6346",
"6842": "6842",
"6359": "6359",
"6322": "6322",
"6647": "6647",
"6373": "6373",
"6566": "6566",
"6375": "6375",
"6562": "6562",
"6605": "6605",
"6608": "6608"
},
"204": {
"label": "17,0",
"": "",
"6611": "6611",
"6514": "6514",
"6496": "6496",
"6515": "6515",
"6499": "6499",
"6517": "6517",
"6502": "6502",
"6393": "6393",
"6505": "6505",
"6402": "6402",
"6405": "6405",
"6408": "6408",
"6411": "6411",
"6414": "6414",
"6417": "6417",
"6420": "6420",
"6423": "6423",
"6396": "6396",
"6399": "6399",
"6429": "6429",
"6745": "6745",
"6441": "6441",
"6444": "6444",
"6447": "6447",
"6450": "6450",
"6453": "6453",
"6456": "6456",
"6459": "6459",
"6462": "6462",
"6432": "6432",
"6435": "6435",
"6438": "6438",
"6467": "6467",
"6381": "6381",
"6633": "6633",
"6330": "6330",
"6349": "6349",
"6636": "6636",
"6318": "6318",
"6352": "6352",
"6660": "6660",
"6333": "6333",
"6743": "6743",
"6744": "6744",
"6355": "6355",
"6662": "6662",
"6336": "6336",
"6620": "6620",
"6361": "6361",
"6622": "6622",
"6639": "6639",
"6324": "6324",
"6363": "6363",
"6624": "6624",
"6642": "6642",
"6339": "6339",
"6366": "6366",
"6626": "6626",
"6839": "6839",
"6342": "6342",
"6627": "6627",
"6369": "6369",
"6645": "6645",
"6327": "6327",
"6358": "6358",
"6841": "6841",
"6345": "6345",
"6471": "6471",
"6648": "6648",
"6321": "6321",
"6473": "6473",
"6374": "6374",
"6563": "6563",
"6606": "6606",
"6609": "6609"
}
},
"child": {
"6320_6319_6318_": {
"entity": "69813",
"stock_number": 0,
"stock_status": false,
"productId": "69813",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6365_6364_6339_": {
"entity": "69814",
"stock_number": 5,
"stock_status": true,
"productId": "69814",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6344_6343_6366_": {
"entity": "69815",
"stock_number": 3,
"stock_status": true,
"productId": "69815",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6370_6328_6369_": {
"entity": "69816",
"stock_number": 1,
"stock_status": true,
"productId": "69816",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6351_6372_6352_": {
"entity": "69817",
"stock_number": 0,
"stock_status": false,
"productId": "69817",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6335_6334_6743_": {
"entity": "69818",
"stock_number": 0,
"stock_status": false,
"productId": "69818",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6354_6350_6744_": {
"entity": "69819",
"stock_number": 0,
"stock_status": false,
"productId": "69819",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6338_6337_6355_": {
"entity": "69820",
"stock_number": 0,
"stock_status": false,
"productId": "69820",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6357_6353_6336_": {
"entity": "69821",
"stock_number": 3,
"stock_status": true,
"productId": "69821",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6326_6325_6361_": {
"entity": "69822",
"stock_number": 4,
"stock_status": true,
"productId": "69822",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6362_6356_6324_": {
"entity": "69823",
"stock_number": 6,
"stock_status": true,
"productId": "69823",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
},
"6341_6340_6363_": {
"entity": "69824",
"stock_number": 6,
"stock_status": true,
"productId": "69824",
"parent_url": "https://www.bstn.com/eu_en/p/jordan-jordan-why-not-zer0-4-dd4889-006-0250549"
}
}
}
}
)
So what I did is that I created two dicts within a list:
first_loop = []
second_loop = []
total_stock = 0
for idx, sizes in json_value["attributes"].items():
for getId in sizes["options"]:
first_loop.append({getId["label"]: getId["products"][0]})
break
for idx, test in json_value["productStockAlert"]["child"].items():
total_stock += test["stock_number"]
second_loop.append({test["productId"]: test["stock_number"]})
print("first_loop", first_loop)
print("second_loop", second_loop)
print("total_stock", total_stock)
which returns:
first_loop [{'38': '69813'}, {'38,5': '69817'}, {'39': '69818'}, {'40': '69819'}, {'40,5': '69820'}, {'41': '69821'}, {'42': '69822'}, {'42,5': '69823'}, {'43': '69824'}, {'44': '69814'}, {'44,5': '69815'}, {'45,5': '69816'}]
second_loop [{'69813': 0}, {'69814': 5}, {'69815': 3}, {'69816': 1}, {'69817': 0}, {'69818': 0}, {'69819': 0}, {'69820': 0}, {'69821': 3}, {'69822': 4}, {'69823': 6}, {'69824': 6}]
total_stock 28
My issue is how can I compare from first_loop where I check the ID (etc 69816) is in second_loop and has the value above 0, if its above 0 then I want to add it to a append it to a new list etc: 45,5 (1) (Which is the size number from first_loop and the number (value) from second_loop.
Output would end up:
>>> ["41 (3)", "42 (4)", "42,5 (6)", "43 (6)", "44 (5)", "44,5 (3)", "45,5 (1)"]

Basically, you just need to create id-label mapping, id-count mapping and merge them:
id_label_mapping = {o["products"][0]: o["label"] for o in next(iter(json_value["attributes"].values()))["options"]}
id_count_mapping = {o["productId"]: o["stock_number"] for o in json_value["productStockAlert"]["child"].values()}
result = [f"{l} ({id_count_mapping[k]})" for k, l in id_label_mapping.items() if id_count_mapping.get(k)]
In your code you've done 2 major mistakes which makes implementation of last step (merging) much harder.
You're creating list of dicts instead of single dict with different keys;
In first_loop you're using label as key, but in second_loop you're using productId.
If we will fix this 2 gaps, your code will work:
first_loop = {}
second_loop = {}
total_stock = 0
for idx, sizes in json_value["attributes"].items():
for getId in sizes["options"]:
first_loop[getId["products"][0]] = getId["label"]
break
for idx, test in json_value["productStockAlert"]["child"].items():
total_stock += test["stock_number"]
second_loop[test["productId"]] = test["stock_number"]
result = []
for product_id, label in first_loop.items():
count = second_loop.get(product_id)
if count: # filters both None (key doesn't exit) and 0
result.append(f"{label} ({count})")
print("result", result)
print("total_stock", total_stock)

Not sure if it's the most efficient way, but you could:
make dicts not lists, does it need to be a list?
swap the key-value of the first_loop
intersect the sets
get the values from original, print only if > 0
[Code not tested]
first_loop = {}
second_loop = {}
total_stock = 0
for idx, sizes in json_value["attributes"].items():
for getId in sizes["options"]:
first_loop[getId["products"][0]] = getId["label"]
break
for idx, test in json_value["productStockAlert"]["child"].items():
total_stock += test["stock_number"]
second_loop[test["productId"]] = test["stock_number"]
matching = set(first_loop.keys()).intersection(second_loop.keys())
for prod_id in matching:
stock = second_loop.get(prod_id)
if stock > 0:
print(f"{first_loop.get(prod_id) ({stock})")
Lastly, you have a break statement, that will make it run only one time... In which case you do not need a for loop...
It's quite too case specific, but hope it helps...

Elasticsearch bool query sort by date if status is true

I have a JSON file like as follows in an Elasticsearch index. I need to sort data if the advertisement does not expire and status is true, and then sort them as desc. How can I achieve this?
I tried using end_date sort, but it did not work. Also I need to show all expired data which end_date are expired.
advertisement = [
{
"id": 1,
"name": "test",
"status": True,
"start_date": "2020-08-09",
"end_date": "2020-09-09",
},
{
"id": 2,
"name": "test2",
"status": False,
"start_date": "2020-08-09",
"end_date": "2020-08-09",
}]
This is my elastic search method.
def elastic_search(category=None):
client = Elasticsearch(host="localhost", port=9200)
query_all = {
'size': 10000,
'query': {
"bool": {
"filter": [
{
"match": {
"name": "test"
}
}]
},
},
"sort": [
{
"end_date": {
"type": "date",
"order": 'desc'
}
}
]
}
resp = client.search(
index="my-index",
body=query_all
)
return resp
This is my es response
http://localhost:9200/my-index/_search
{
"took":96,
"timed_out":false,
"_shards":{
"total":5,
"successful":5,
"skipped":0,
"failed":0
},
"hits":{
"total":36,
"max_score":1.0,
"hits":[
{
"_index":"my-index",
"_type":"doc",
"_id":"52",
"_score":1.0,
"_source":{
"id": 1,
"name": "test",
"status": True,
"start_date": "2020-08-09",
"end_date": "2020-09-09",
}
},
{
"_index":"my-index",
"_type":"doc",
"_id":"60",
"_score":1.0,
"_source":{
"id": 1,
"name": "English test",
"status": True,
"start_date": "2020-08-09",
"end_date": "2020-09-09",
}
},
{
"_index":"my-index",
"_type":"doc",
"_id":"40",
"_score":1.0,
"_source":{
"id": 1,
"name": "Designw test",
"status": false,
"start_date": "2020-08-09",
"end_date": "2020-09-09",
}
},
{
"_index":"my-index",
"_type":"doc",
"_id":"41",
"_score":1.0,
"_source":{
"id": 1,
"name": "Designw New",
"status": false,
"start_date": "2020-08-09",
"end_date": "2020-09-09",
}
},
{
"_index":"my-index",
"_type":"doc",
"_id":"59",
"_score":1.0,
"_source":{
"id": 1,
"name": "Designw New",
"status": false,
"start_date": "2020-08-09",
"end_date": "2020-09-09",
}
},
{
"_index":"my-index",
"_type":"doc",
"_id":"62",
"_score":1.0,
"_source":{
"id": 1,
"name": "Designw New",
"status": false,
"start_date": "2020-08-09",
"end_date": "2020-09-09",
}
}
]
}
}
This is my mapping http://localhost:9200/my-index/_mapping response.
"my-index":{
"mappings":{
"_doc":{
"properties":{
"address":{
"properties":{
"name":{
"type":"text",
"fields":{
"keyword":{
"type":"keyword",
"ignore_above":256
}
}
},
"start_date":{
"type":"text",
"fields":{
"keyword":{
"type":"keyword",
"ignore_above":256
}
}
},
"end_date":{
"type":"text",
"fields":{
"keyword":{
"type":"keyword",
"ignore_above":256
}
}
},
"id":{
"type":"long"
},
"status":{
"type":"text",
"fields":{
"keyword":{
"type":"keyword",
"ignore_above":256
}
}
}
}
}
}
}
}
}
}

Two things regarding the mapping:
There's an address field there that's not found in your actual documents. Remove it.
Your dates should be mapped correctly using the date datatype.
A correct mapping would look like this:
{
"properties":{
"end_date":{
"type":"date",
"format":"yyyy-MM-dd"
},
"start_date":{
"type":"date",
"format":"yyyy-MM-dd"
},
//...other properties
}
}
Once you get the mapping right, this query looks for all non-expired ads w/ a true status and sorts by the longest running:
{
"query": {
"bool": {
"must": [
{
"range": {
"end_date": {
"gt": "now"
}
}
},
{
"term": {
"status": {
"value": true
}
}
}
]
}
},
"sort": [
{
"end_date": {
"order": "desc"
}
}
]
}
Alternatively, if you're looking for the expired ones, change gt to lt which stands for less-than.

issue in Elastic Search Term Aggregation

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.

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