I have a list of dictionaries in the django template. I wish to use its values in a form.
[
{
"movie_id": 1950,
"title": "In the Heat of the Night (1967)"
},
{
"movie_id": 3741,
"title": "Badlands (1973)"
},
{
"movie_id": 3959,
"title": "Time Machine, The (1960)"
},
{
"movie_id": 4101,
"title": "Dogs in Space (1987)"
},
{
"movie_id": 8572,
"title": "Littlest Rebel, The (1935)"
},
{
"movie_id": 65230,
"title": "Marley & Me (2008)"
},
{
"movie_id": 105954,
"title": "All Is Lost (2013)"
}
]
In my template, I want to get values of each field by index. ie. for the
list[0]['movieId'], I would like to get the value 1950. Is that possible?
You can access it via dot (.) notation.
From the documentation
Technically, when the template system encounters a dot, it tries the following lookups, in this order:
Dictionary lookup
Attribute or method lookup
Numeric index lookup
So you can use list.0.movieId. The 0 dot attribute will access the list element and movieId will do the dictionary lookup.
Related
How to loop through a JSON object in Django template?
JSON:
"data": {
"node-A": {
"test1A": "val1A",
"test2A": "val2A",
"progress": {
"conf": "conf123A"
"loc": "loc123A"
},
"test3A": "val3A"
},
"node-B": {
"test1B": "val1B",
"test2B": "val2B",
"progress": {
"conf": "conf123B"
"loc": "loc123B"
},
"test3B": "val3B"
}
}
I am having trouble accessing the nested values "conf" and "lock" inside "progress". How can I access them in Django template if the data is passed as context i.e. return (request, 'monitor.html', {"data_context": json_data['data']})?
they way you have it set up, your data is in a dictionary called 'data_context'. To access what you need in the template it would be {{data_context.test1A}}.
to not have to use 'data_context.' try this instead,
return (request, 'monitor.html', json_data['data'].to_dict())
Dictionary lookup, attribute lookup and list-index lookups are implemented with a dot notation:
{{ my_dict.key.key_nested }}
As the JSON format behaves like a dictionary in Python, the data stored with the specified keys conf and loc should be accessible with the python notation for dictionaries. Since the provided JSON can be seen as a nested dictionary, you need to "concat" the keys respectively to get your desired data.
Your return statement returns a dictionary which I will call ret so the structure should be:
{"data_context": {
"node-A": {
"test1": "val1A",
"test2": "val2A",
"progress": {
"conf": "conf123A",
"loc": "loc123A"
},
"test3": "val3A"
},
"node-B": {
"test1B": "val1B",
"test2B": "val2B",
"progress": {
"conf": "conf123B",
"loc": "loc123B"
},
"test3": "val3B"
}
}
}
Therefor to access conf and loc:
ret["data_context"]["node-A"]["progress"]["conf"]
will get you the value stored at conf in node-A
I'm hustling with regex, and trying to get the id's from this body.
But only the id´s in the members list, and not the id in the verified key. :)
To clarify, I'm using Regular Expression Extractor in JMeter
{
"id": "9c40ffca-0f1a-4f93-b068-1f6332707d02", //<--not this
"me": {
"id": "38a2b866-c8a9-424f-a5d4-93b379f080ce", //<--not this
"isMe": true,
"user": {
"verified": {
"id": "257e30f4-d001-47b3-9e7f-5772e591970b" //<--not this
}
}
},
"members": [
{
"id": "88a2b866-c8a9-424f-a5d4-93b379f780ce", //<--this
"isMe": true,
"user": {
"verified": {
"id": "223e30f4-d001-47b3-9e7f-5772e781970b" //<--not this
}
}
},
{
"id": "53cdc218-4784-4e55-a784-72e6a3ffa9bc", //<--this
"isMe": false,
"user": {
"unverified": {
"verification": "XYZ"
}
}
}
]
}
at the moment I have this regex :
("id": )("[\w-]+")
But as you can see here it returns every guid
Any ideas on how to go on?
Thanks in advance.
Since the input data type is JSON, it is recommended to use the JMeter's JSON Path Extractor Plugin.
Once you add it, use the
$.members[*].id
JSON path expression to match all id values of each members in the document that are the top nodes.
If you may have nested memebers, you may get them all using
$..members[*].id
You may test these expressions at https://jsonpath.com/, see a test:
I am searching a term "john" in a list of dict ,
I have a list of dict like this :
"response": [
{
"name": "Alex T John"
},
{
"name": "Ajo John"
},
{
"name": "John",
}]
I am using :
response_query = sorted(response, key = lambda i: i['name'])
response_query return ascending order of result only but I need a result with first name as a priority.
Expected result:
{
"name": "John"
},
{
"name": "Ajo John"
},
{
"name": "Alex T John",
}
The first name containing search term should appear first.
If you need to sort with priorities you can try a key-function that returns tuple. In your particular case, as far as I got the question, this function will work fine:
response_query = sorted(
response,
key=lambda i: (len(i['name'].split()) > 1, i['name'])
)
In other words, I added the condition len(i['name'].split()) > 1 that return False (it will go first) if the name consists of one word only, else True.
For the case, if you need the priority condition as the name starts with the term you used in the search, the result would be:
term = 'john'
...
response_query = sorted(
response,
key=lambda i: (not i['name'].lower().startswith(term), i['name'])
)
I have a json object contaning currencies as listed below which I need to convert it into my model and save it into the DB. Also is there a way to save the list of models in one go?
{
"results": {
"ALL": {
"currencyName": "Albanian Lek",
"currencySymbol": "Lek",
"id": "ALL"
},
"KWD": {
"currencyName": "Kuwaiti Dinar",
"id": "KWD"
},
"LSL": {
"currencyName": "Lesotho Loti",
"id": "LSL"
},
"MYR": {
"currencyName": "Malaysian Ringgit",
"currencySymbol": "RM",
"id": "MYR"
},
"MUR": {
"currencyName": "Mauritian Rupee",
"currencySymbol": "₨",
"id": "MUR"
}
}
}
I tried this :
for key,value in currencies.results :
#print(currency)
#print(value)
However, I get the following error :
"Too many attribures to unpack, expected 2
Can someone help me with this?
I think it should be like this:
results = currencies.get('results')
for key, value in results.items(): # for python3
print(key, value)
for key, value in results.iteritems(): # python2.7
print(key, value)
You should iterate as
for result in results:
for currency in result:
print(result)
I want to create a small MongoDB Search Query where I want to sort the result set based exact match followed by no. of matches.
For eg. if I have following labels
Physics
11th-Physics
JEE-IIT-Physics
Physics-Physics
Then, if I search for "Physics" it should sort as
Physics
Physics-Physics
11th-Physics
JEE-IIT-Physics
Looking for the sort of "scoring" you are talking about here is an excercise in "imperfect solutions". In this case, the "best fit" here starts with "text search", and "imperfect" is the term to consider first when working with the text search capabilties of MongoDB.
MongoDB is "not" a dedicated "text search" product, nor is it ( like most databases ) trying to be one. Full capabilites of "text search" is reserved for dedicated products that do that as there area of expertise. So maybe not the best fit, but "text search" is given as an option for those who can live with the limitations and don't want to implement another engine. Or Yet! At least.
With that said, let's look at what you can do with the data sample as given. First set up some data in a collection:
db.junk.insert([
{ "data": "Physics" },
{ "data": "11th-Physics" },
{ "data": "JEE-IIT-Physics" },
{ "data": "Physics-Physics" },
{ "data": "Something Unrelated" }
])
Then of course to "enable" the text search capabilties, then you need to index at least one of the fields in the document with the "text" index type:
db.junk.createIndex({ "data": "text" })
Now that is "ready to go", let's have a look at a first basic query:
db.junk.find(
{ "$text": { "$search": "\"Physics\"" } },
{ "score": { "$meta": "textScore" } }
).sort({ "score": { "$meta": "textScore" } })
That is going to give results like this:
{
"_id" : ObjectId("55af83b964876554be823f33"),
"data" : "Physics-Physics",
"score" : 1.5
}
{
"_id" : ObjectId("55af83b964876554be823f30"),
"data" : "Physics",
"score" : 1
}
{
"_id" : ObjectId("55af83b964876554be823f31"),
"data" : "11th-Physics",
"score" : 0.75
}
{
"_id" : ObjectId("55af83b964876554be823f32"),
"data" : "JEE-IIT-Physics",
"score" : 0.6666666666666666
}
So that is "close" to your desired result, but of course there is no "exact match" component. In addition, the logic here used by the text search capabilities with the $text operator means that "Physics-Physics" is the preferred match here.
This is because then engine does not recognize "non words" such as the "hyphen" in between. To it, the word "Physics" appears several times in the indexed content for the document, therefore it has a higher score.
Now the rest of your logic here depends on the application of "exact match" and what you mean by that. If you are looking for "Physics" in the string and "not" surrounded by "hyphens" or other characters then the following does not suit. But you can just match a field "value" that is "exactly" just "Physics":
db.junk.aggregate([
{ "$match": {
"$text": { "$search": "Physics" }
}},
{ "$project": {
"data": 1,
"score": {
"$add": [
{ "$meta": "textScore" },
{ "$cond": [
{ "$eq": [ "$data", "Physics" ] },
10,
0
]}
]
}
}},
{ "$sort": { "score": -1 } }
])
And that will give you a result that both looks at the "textScore" produced by the engine and then applies some math with a logical test. In this case where the "data" is exactly equal to "Physics" then we "weight" the score by an additional factor using $add:
{
"_id": ObjectId("55af83b964876554be823f30"),
"data" : "Physics",
"score" : 11
}
{
"_id" : ObjectId("55af83b964876554be823f33"),
"data" : "Physics-Physics",
"score" : 1.5
}
{
"_id" : ObjectId("55af83b964876554be823f31"),
"data" : "11th-Physics",
"score" : 0.75
}
{
"_id" : ObjectId("55af83b964876554be823f32"),
"data" : "JEE-IIT-Physics",
"score" : 0.6666666666666666
}
That is what the aggregation framework can do for you, by allowing manipulation of the returned data with additional conditions. The end result is passed to the $sort stage ( notice it is reversed in descending order ) to allow that new value to be to sorting key.
But the aggregation framework can really only deal with "exact matches" like this on strings. There is no facility at present to deal with regular expression matches or index positions in strings that return a meaningful value for projection. Not even a logical match. And the $regex operation is only used to "filter" in queries, so not of use here.
So if you were looking for something in a "phrase" thats was a bit more invovled than a "string equals" exact match, then the other option is using mapReduce.
This is another "imperfect" approach as the limitations of the mapReduce command mean that the "textScore" from such a query by the engine is "completely gone". While the actual documents will be selected correctly, the inherrent "ranking data" is not available to the engine. This is a by-product of how MongoDB "projects" the "score" into the document in the first place, and "projection" is not a feature available to mapReduce.
But you can "play with" the strings using JavaScript, as in my "imperfect" sample:
db.junk.mapReduce(
function() {
var _id = this._id,
score = 0;
delete this._id;
score += this.data.indexOf(search);
score += this.data.lastIndexOf(search);
emit({ "score": score, "id": _id }, this);
},
function() {},
{
"out": { "inline": 1 },
"query": { "$text": { "$search": "Physics" } },
"scope": { "search": "Physics" }
}
)
Which gives results like this:
{
"_id" : {
"score" : 0,
"id" : ObjectId("55af83b964876554be823f30")
},
"value" : {
"data" : "Physics"
}
},
{
"_id" : {
"score" : 8,
"id" : ObjectId("55af83b964876554be823f33")
},
"value" : {
"data" : "Physics-Physics"
}
},
{
"_id" : {
"score" : 10,
"id" : ObjectId("55af83b964876554be823f31")
},
"value" : {
"data" : "11th-Physics"
}
},
{
"_id" : {
"score" : 16,
"id" : ObjectId("55af83b964876554be823f32")
},
"value" : {
"data" : "JEE-IIT-Physics"
}
}
My own "silly little algorithm" here is basically taking both the "first" and "last" index position of the matched string here and adding them together to produce a score. It's likely not what you really want, but the point is that if you can code your logic in JavaScript, then you can throw it at the engine to produce the desired "ranking".
The only real "trick" here to remember is that the "score" must be the "preceeding" part of the grouping "key" here, and that if including the orginal document _id value then that composite key part must be renamed, otherwise the _id will take precedence of order.
This is just part of mapReduce where as an "optimization" all output "key" values are sorted in "ascending order" before being processed by the reducer. Which of course does nothing here since we are not "aggregating", but just using the JavaScript runner and document reshaping of mapReduce in general.
So the overall note is, those are the available options. None of them perfect, but you might be able to live with them or even just "accept" the default engine result.
If you want more then look at external "dedicated" text search products, which would be better suited.
Side Note: The $text searches here are preferred over $regex because they can use an index. A "non-anchored" regular expression ( without the caret ^ ) cannot use an index optimally with MongoDB. Therefore the $text searches are generally going to be a better base for finding "words" within a phrase.
One more way is using the $indexOfCp aggregation operator to get the index of matched string and then apply sort on the indexed field
Data insertion
db.junk.insert([
{ "data": "Physics" },
{ "data": "11th-Physics" },
{ "data": "JEE-IIT-Physics" },
{ "data": "Physics-Physics" },
{ "data": "Something Unrelated" }
])
Query
const data = "Physics";
db.junk.aggregate([
{ "$match": { "data": { "$regex": data, "$options": "i" }}},
{ "$addFields": { "score": { "$indexOfCP": [{ "$toLower": "$data" }, { "$toLower": data }]}}},
{ "$sort": { "score": 1 }}
])
Here you can test the output
[
{
"_id": ObjectId("5a934e000102030405000000"),
"data": "Physics",
"score": 0
},
{
"_id": ObjectId("5a934e000102030405000003"),
"data": "Physics-Physics",
"score": 0
},
{
"_id": ObjectId("5a934e000102030405000001"),
"data": "11th-Physics",
"score": 5
},
{
"_id": ObjectId("5a934e000102030405000002"),
"data": "JEE-IIT-Physics",
"score": 8
}
]