Interesting question, This will do the trick

     db.multiArr.find({&#39;Keys&#39;:{$elemMatch:{$elemMatch:{$in:[&#39;carrot&#39;]}}}})

`$elemMatch` used to check if an element in an array matches the specified match expression.
so nested `$elemMatch` will go deeper into nested arrays

Test data
&#160; &#160; 

    db.multiArr.insert({&quot;ID&quot; : &quot;fruit1&quot;,&quot;Keys&quot; : [[&quot;apple&quot;, &quot;carrot&quot;, &quot;banana&quot;]]})
    db.multiArr.insert({&quot;ID&quot; : &quot;fruit2&quot;,&quot;Keys&quot; : [[&quot;apple&quot;, &quot;orange&quot;, &quot;banana&quot;]]})
    
    
    db.multiArr.find({&#39;Keys&#39;:{$elemMatch:{$elemMatch:{$in:[&#39;carrot&#39;]}}}})
    { &quot;_id&quot; : ObjectId(&quot;506555212aeb79b5f7374cbf&quot;), &quot;ID&quot; : &quot;fruit1&quot;, &quot;Keys&quot; : [ [ &quot;apple&quot;, &quot;carrot&quot;, &quot;banana&quot; ] ] }
    
    db.multiArr.find({&#39;Keys&#39;:{$elemMatch:{$elemMatch:{$in:[&#39;banana&#39;]}}}})
    
    { &quot;_id&quot; : ObjectId(&quot;506555212aeb79b5f7374cbf&quot;), &quot;ID&quot; : &quot;fruit1&quot;, &quot;Keys&quot; : [ [ &quot;apple&quot;, &quot;carrot&quot;, &quot;banana&quot; ] ] }
    { &quot;_id&quot; : ObjectId(&quot;5065587e2aeb79b5f7374cc0&quot;), &quot;ID&quot; : &quot;fruit2&quot;, &quot;Keys&quot; : [ [ &quot;apple&quot;, &quot;orange&quot;, &quot;banana&quot; ] ] }





if you want to find array of first position data, use 0 as reference index to get data in nested array.

    db.getCollection(&#39;routes&#39;).find({&quot;routeId&quot; : 12,&#39;routes._id&#39;:ObjectId(&quot;598da27a713f3e6acd72287f&quot;),&#39;routes.0.stops.0.orders.0._id&#39;:ObjectId(&quot;598da27a713f3e6acd722887&quot;)})

I am designing a RESTful API using Python and Flask. As expected, the API needs to receive an API request and return data if all goes well, but in the instance of an error, it needs to fail softly and return the proper error. I typically raise exceptions when an error results, but in this case I need to return the error message to the user (try-catch block?).

The way I am currently dealing with errors is to have my functions return both the data and an error, and to check for the data at each level, finally returning either the data or the error to the caller of the API function.

The problem with this is that it can get cumbersome when there are several levels of function calls, requiring my functions to pass data and errors several times and perform checks each time.

Is there a better way to do this? What are some improvements I could make to make the error propagation more simple and elegant?

Here is an example of the way I&#39;m currently returning errors:

    def get_data()
        data1, error = get_some_data() # function not shown
        if data1 is None:
             return None, &quot;could not retrieve data1&quot;
        data2, error = get_some_other_data() # function not shown
        if data2 is None:
             return None, &quot;could not retrieve data2&quot;
        return (data1, data2), None

    @app.route(&quot;/api/method&quot;, methods=[&#39;GET&#39;])
    def method():
        data, error = get_data()
        if data is None:
            if error is None:
                error = &quot;unknown error&quot;
            return json.dumps({ &quot;error&quot;: error }), 500
        return json.dumps({ &quot;data&quot;: data }), 200


Returning API Error Messages with Python and Flask

I am trying to clone a remote repository on Windows, but when I did this:

    git clone git@github.com:organization/xxx.git

I got this error:


    error: cannot run ssh: No such file or directory
    fatal: unable to fork

Am I missing something?


error: cannot run ssh: No such file or directory when trying to clone on windows

Say, I have a document like this..

    &quot;ID&quot; : &quot;fruit1&quot;,
    &quot;Keys&quot; : [[&quot;apple&quot;, &quot;carrot&quot;, &quot;banana&quot;]]

How do I query for Keys = &quot;carrot&quot;. None of the following syntax works.

    db.myColl.results.find({ &quot;Keys&quot; : &quot;carrot&quot; });
    db.myColl.results.find({ &quot;Keys&quot; : [[&quot;carrot&quot;]] });

Following works though, but not helpful.

    db.myColl.results.find({ &quot;Keys&quot; : [[&quot;apple&quot;, &quot;carrot&quot;, &quot;banana]]});

Any pointer to this query will be helpful. Thanks.

Querying an array of arrays in MongoDB

Say, I have a document like this..
<pre><code class="hljs language-lua">"ID" : "fruit1",
"Keys" : [["apple", "carrot", "banana"]]
</code></pre>
How do I query for Keys = "carrot". None of the following syntax works.
<pre><code class="hljs language-lua">db.myColl.results.find({ "Keys" : "carrot" });
db.myColl.results.find({ "Keys" : [["carrot"]] });
</code></pre>
Following works though, but not helpful.
<pre><code class="hljs language-lua">db.myColl.results.find({ "Keys" : [["apple", "carrot", "banana]]});
</code></pre>
Any pointer to this query will be helpful. Thanks.

Is there a way to add created_at and `updated_at` fields to a mongoose schema, without having to pass them in everytime new `MyModel()` is called?

The `created_at` field would be a date and only added when a document is created.
The `updated_at` field would be updated with new date whenever `save()` is called on a document.

I have tried this in my schema, but the field does not show up unless I explicitly add it:

    var ItemSchema = new Schema({
        name    : { type: String, required: true, trim: true },
        created_at    : { type: Date, required: true, default: Date.now }
    });



add created_at and updated_at fields to mongoose schemas

&lt;!-- language-all: lang-js --&gt;

Is there an explain function for the Aggregation framework in MongoDB? I can&#39;t see it in the documentation.

If not is there some other way to check, how a query performs within the aggregation framework?

I know with find you just do 

    db.collection.find().explain()

But with the aggregation framework I get an error

    db.collection.aggregate(
    	{ $project : { &quot;Tags._id&quot; : 1 }},
    	{ $unwind : &quot;$Tags&quot; },
    	{ $match: {$or: [{&quot;Tags._id&quot;:&quot;tag1&quot;},{&quot;Tags._id&quot;:&quot;tag2&quot;}]}},
    	{ 
    		$group: 
    		{ 
    			_id : { id: &quot;$_id&quot;},
    			&quot;count&quot;: { $sum:1 } 
    		}
    	},
    	{ $sort: {&quot;count&quot;:-1}}
    ).explain()

Mongodb Explain for Aggregation framework

This question is about making an architectural choice prior to delving into the details of experimentation and implementation. It&#39;s about the suitability, in scalability and performance terms, of elasticsearch v.s. MongoDB, for a somewhat specific purpose. 

Hypothetically both store data objects that have fields and values, and allow querying that body of objects. So presumably filtering out subsets of the objects according to fields selected ad-hoc, is something fit for both. 

My application will revolve around selecting objects according to criteria.
It would select objects by filtering simultaneously by more than a single field, put differently, its query filtering criteria would typically comprise anywhere between 1 and 5 fields, maybe more in some cases. Whereas the fields chosen as filters would be a subset of a much larger amount of fields. Picture some 20 field names existing, and each query is an attempt to filter the objects by few fields out of those overall 20 fields (It can be less or more than 20 overall field names existing, I just used this number to demonstrate the ratio of fields to fields used as filters in every discrete query). The filtering can be by the existence of the chosen fields, as well as by the field values, e.g. filtering out objects that have field A, and their field B is between x and y, and their field C is equal to w. 

My application will be continuously doing this sort of filtering, whereas there would be nothing or very little constant in terms of which fields are used for the filtering at any moment. Perhaps in elasticsearch indexes need to be defined, but maybe even without indexes speed is at par with that of MongoDB. 

As per the data getting into the store, there are no special details about that.. the objects would be almost never changed after having been inserted. Perhaps old objects would need to be dropped, I&#39;d like to assume both data stores support expire deleting stuff internally or by an application made query. (Less frequently, objects that fit a certain query would need to be dropped as well).

What do you think?
And, have you experimented this aspect?

I am interested in the performance and the scalability of it, of each of the two data stores, for this kind of task. This is the sort of an architectural desing question, and details of store-specific options or query cornerstones that should make it well architected are welcome as a demonstration of a fully thought-out suggestion.

Thanks!

elasticsearch v.s. MongoDB for filtering application

I got an error about `dbpath (/data/db/) does not exist`, but `/etc/mongodb.conf` named it `dbpath = /var/lib/mongodb.
 `
So, which is the default dbpath for MongoDB?


What is the default database path for MongoDB?

Just a simple query, for example with a double ref in the model.

**Schema / Model**

    var OrderSchema = new Schema({

        user: {
            type    : Schema.Types.ObjectId,
            ref     : &#39;User&#39;,
            required: true
        },

        meal: {
            type    : Schema.Types.ObjectId,
            ref     : &#39;Meal&#39;,
            required: true
        },
    });

    var OrderModel = db.model(&#39;Order&#39;, OrderSchema);


**Query**

    OrderModel.find()
        .populate(&#39;user&#39;) // works
        .populate(&#39;meal&#39;) // dont works
        .exec(function (err, results) {
             // callback
        });

I already tried something like

    .populate(&#39;user meal&#39;)
    .populate([&#39;user&#39;, &#39;meal&#39;])

In fact only one of the populates works.

So, how do is get two populates working ? 

Multiple populates - mongoosejs

Are there good ways to &quot;expand&quot; a numpy ndarray? Say I have an ndarray like this:

    [[1 2]
     [3 4]]

And I want each row to contains more elements by filling zeros:

    [[1 2 0 0 0]
     [3 4 0 0 0]]

I know there must be some brute-force ways to do so (say construct a bigger array with zeros then copy elements from old smaller arrays), just wondering are there pythonic ways to do so. Tried `numpy.reshape` but didn&#39;t work:

    import numpy as np
    a = np.array([[1, 2], [3, 4]])
    np.reshape(a, (2, 5))

Numpy complains that: `ValueError: total size of new array must be unchanged`



Good ways to &quot;expand&quot; a numpy ndarray?

    $array1 = array(&quot;$name1&quot; =&gt; &quot;$id1&quot;);
    
    $array2 = array(&quot;$name2&quot; =&gt; &quot;$id2&quot;, &quot;$name3&quot; =&gt; &quot;$id3&quot;);

I need a new array combining all together, i.e. it would be

    $array3 = array(&quot;$name1&quot; =&gt; &quot;$id1&quot;, &quot;$name2&quot; =&gt; &quot;$id2&quot;, &quot;$name3&quot; =&gt; &quot;$id3&quot;);

What is the best way to do this?

Sorry, I forgot, the ids will never match each other, but technically the names could, yet would not be likely, and they all need to be listed in one array.  I looked at array_merge but wasn&#39;t sure if that was best way to do this.  Also, how would you unit test this?

PHP combine two associative arrays into one array

How do I create an empty mutable two dimensional array in Rust?

This is what I have tried so far:

    let mut state[[u8 * 4] * 4];

This produces the error

&lt;!-- language: none --&gt;

    error: expected one of `:`, `;`, `=`, or `@`, found `[`
     --&gt; src/main.rs:2:18
      |
    2 |     let mut state[[u8 * 4] * 4];
      |                  ^ expected one of `:`, `;`, `=`, or `@` here



Creating two dimensional arrays in Rust

Hi I&#39;m Trying to merge two arrays and also want to remove duplicate values from final Array.

Here is my Array 1:

    Array
        (
        [0] =&gt; stdClass Object
        (
        [ID] =&gt; 749
        [post_author] =&gt; 1
        [post_date] =&gt; 2012-11-20 06:26:07
        [post_date_gmt] =&gt; 2012-11-20 06:26:07
    )

And this is my array 2:

    Array
    (
    [0] =&gt; stdClass Object
    (
    [ID] =&gt; 749
    [post_author] =&gt; 1
    [post_date] =&gt; 2012-11-20 06:26:07
    [post_date_gmt] =&gt; 2012-11-20 06:26:07
    
    )

I&#39;m using ``array_merge`` for merging both arrays into one array. it is giving output like this

    Array
    (
    [0] =&gt; stdClass Object
    (
    [ID] =&gt; 749
    [post_author] =&gt; 1
    [post_date] =&gt; 2012-11-20 06:26:07
    [post_date_gmt] =&gt; 2012-11-20 06:26:07
       
    [1] =&gt; stdClass Object
    (
    [ID] =&gt; 749
    [post_author] =&gt; 1
    [post_date] =&gt; 2012-11-20 06:26:07
    [post_date_gmt] =&gt; 2012-11-20 06:26:07
        
    )

I want to remove these duplicate entries or can I remove these before merging...
Pleas help.. 
Thanks!!!!!!!

PHP - Merging two arrays into one array (also Remove Duplicates)

Should be a simple question, but I&#39;m unable to find an answer anywhere. The `~` operator in python is a documented as a bitwise inversion operator.  Fine. I have noticed seemingly schizophrenic behavior though, to wit:

    ~True -&gt; -2
    ~1 -&gt; -2
    ~False -&gt; -1
    ~0 -&gt; -1
    ~numpy.array([True,False],dtype=int) -&gt; array([-2,-1])
    ~numpy.array([True,False],dtype=bool) -&gt; array([False,True])

In the first 4 examples, I can see that python is implementing (as documented) `~x = -(x+1)`, with the input treated as an int *even if it&#39;s boolean*. Hence, for a scalar boolean, `~` is not treated as a logical negation. Not that the behavior is identical on a numpy array defined with boolean values by with an int type.

Why does `~` then work as a logical negation operator on a boolean array (Also notice: `~numpy.isfinite(numpy.inf) -&gt; True`?)?

It is extremely annoying that I must use `not()` on a scalar, but `not()` won&#39;t work to negate an array. Then for an array, I must use `~`, but `~` won&#39;t work to negate a scalar...

Content Type	Original Author	Original Content on Stackoverflow
Question	rajibdotnet	View Question on Stackoverflow
Solution 1 - Mongodb	RameshVel	View Answer on Stackoverflow
Solution 2 - Mongodb	KARTHIKEYAN.A	View Answer on Stackoverflow

Querying an array of arrays in MongoDB

Mongodb Problem Overview

Mongodb Solutions

Solution 1 - Mongodb

Solution 2 - Mongodb

error: cannot run ssh: No such file or directory when trying to clone on windows

Returning API Error Messages with Python and Flask

Attributions