Collections

Anytime your results return multiple values then an instance of Collection is returned. This allows you to iterate over your values and has a lot of shorthand methods.

When using collections as a query result you can iterate over it as if the collection with a normal list:

users = User.get() #== <masoniteorm.collections.Collection>
users.count() #== 50
users.pluck('email') #== <masoniteorm.collections.Collection> of emails

for user in users:
  user.email #== '[e-mail]'

Available Methods

all

Returns the underlying list or dict represented by the collection:

users = User.get().all() #== [<app.User.User>, <app.User.User>]

Collection([1, 2, 3]).all() #== [1, 2, 3]

avg

Returns the average of all items in the collection:

Collection([1, 2, 3, 4, 5]).avg() #== 3

If the collection contains nested objects or dictionaries (e.g. for a collection of models), you must pass a key to use for determining which values to calculate the average:

average_price = Product.get().avg('price')

chunk

Chunks a collection into multiple, smaller collections of a given size. Uses a generator to keep each chunk small. Useful for chunking large data sets where pulling too many results in memory will overload the application.

collection = Collection([1, 2, 3, 4, 5, 6, 7])
chunks = collection.chunk(2).serialize() #== [[1, 2], [3, 4], [5, 6], [7]]

collapse

Collapses a collection of lists into a flat collection:

collection = Collection([[1, 2, 3], [4, 5, 6])
collection.collapse().serialize() #== [1, 2, 3, 4, 5, 6]

contains

Determines whether the collection contains a given item:

collection = Collection(['foo', 'bar'])
collection.contains('foo') #== True

You can also pass a key / value pair to the contains method, which will determine if the given pair exists in the collection.

Finally, you may also pass a callback to the contains method to perform your own truth test:

collection = Collection([1, 2, 3, 4, 5])
collection.contains(lambda item: item > 5) #== False

count

Returns the total number of items in the collection. len() standard python method can also be used.

diff

Returns the difference as a collection against another collection

collection = Collection([1, 2, 3, 4, 5])
diff = collection.diff([2, 4, 6, 8])
diff.all() #== [1, 3, 5]

each

Iterates over the items in the collection and passes each item to a given callback:

posts.each(lambda post: post.author().save(author))

every

Creates a new collection by applying a given callback on every element:

collection = Collection([1, 2, 3])
collection.every(lambda x: x*2 ).all() #== [2, 4, 6]

filter

Filters the collection by a given callback, keeping only those items that pass a given truth test:

collection = Collection([1, 2, 3, 4])
filtered = collection.filter(lambda item: item > 2)
filtered.all() #== [3, 4]

first

Returns the first item of the collection, if no arguments are given.

When given a truth test as callback, it returns the first element in the collection that passes the test:

collection = Collection([1, 2, 3, 4])
collection.first(lambda item: item > 2)

flatten

Flattens a multi-dimensional collection into a single dimension:

collection = Collection([1, 2, [3, 4, 5, {'foo': 'bar'}]])
flattened = collection.flatten().all() #== [1, 2, 3, 4, 5, 'bar']

forget

Removes an item from the collection by its key:

collection = Collection([1, 2, 3, 4, 5])
collection.forget(1).all() #== [1,3,4,5]
collection.forget(0,2).all() #== [3,5]

Unlike most other collection methods, forget does not return a new modified collection; it modifies the collection it is called on.

for_page

Paginates the collection by returning a new collection containing the items that would be present on a given page number:

collection = Collection([1, 2, 3, 4, 5, 6, 7, 8, 9])
chunk = collection.for_page(2, 4).all() #== 4, 5, 6, 7

for_page(page, count) takes the page number and the number of items to show per page.

get

Returns the item at a given key or index. If the key does not exist, None is returned. An optional default value can be passed as the second argument:

collection = Collection([1, 2, 3])
collection.get(0) #== 1
collection.get(4) #== None
collection.get(4, 'default') #== 'default'

collection = Collection({"apples": 1, "cherries": 2})
collection.get("apples") #== 1

group_by

Returns a collection where items are grouped by the given key:

collection = Collection([
  {"id": 1, "type": "a"},
  {"id": 2, "type": "b"},
  {"id": 3, "type": "a"}
])
collection.implode("type").all()
#== {'a': [{'id': 1, 'type': 'a'}, {'id': 4, 'type': 'a'}],
#    'b': [{'id': 2, 'type': 'b'}]}

implode

Joins the items in a collection with , or the given glue string.

collection = Collection(['foo', 'bar', 'baz'])
collection.implode() #== foo,bar,baz
collection.implode('-') #== foo-bar-baz

If the collection contains dictionaries or objects, you must pass the key of the attributes you wish to join:

collection = Collection([
    {'account_id': 1, 'product': 'Desk'},
    {'account_id': 2, 'product': 'Chair'}
])
collection.implode(key='product') #== Desk,Chair
collection.implode(" - ", key='product') #== Desk - Chair

is_empty

Returns True if the collection is empty; otherwise, False is returned:

Collection([]).is_empty() #== True

last

Returns the last element in the collection if no arguments are given.

Returns the last element in the collection that passes the given truth test:

collection = Collection([1, 2, 3, 4])
last = collection.last(lambda item: item < 3) #== 2

map

Iterates through the collection and passes each value to the given callback. The callback is free to modify the item and return it, thus forming a new collection of modified items:

collection = Collection([1, 2, 3, 4])
multiplied = collection.map(lambda item: item * 2).all() #== [2, 4, 6, 8]

If you want to transform the original collection, use the transform method.

map_into

Iterates through the collection and cast each value into the given class:

collection = Collection([1,2])
collection.map_into(str).all() #== ["1", "2"]

A class method can also be specified. Some additional keywords arguments can be passed to this method:

class Point:
    @classmethod
    def as_dict(cls, coords, one_dim=False):
        if one_dim:
            return {"X": coords[0]}
        return {"X": coords[0], "Y": coords[1]}

collection = Collection([(1,2), (3,4)])
collection.map_into(Point, "as_dict") #== [{'X': 1, 'Y': 2}, {'X': 3, 'Y': 4}]
collection.map_into(Point, "as_dict", one_dim=True) #== [{'X': 1}, {'X': 3}]

max

Retrieves max value of the collection:

collection = Collection([1,2,3])
collection.max() #== 3

If the collection contains dictionaries or objects, you must pass the key on which to compute max value:

collection = Collection([
    {'product_id': 1, 'product': 'Desk'},
    {'product_id': 2, 'product': 'Chair'}
    {'product_id': 3, 'product': 'Table'}
])
collection.max("product_id") #== 3

merge

Merges the given list into the collection:

collection = Collection(['Desk', 'Chair'])
collection.merge(['Bookcase', 'Door'])
collection.all() #== ['Desk', 'Chair', 'Bookcase', 'Door']

Unlike most other collection methods, merge does not return a new modified collection; it modifies the collection it is called on.

pluck

Retrieves all of the collection values for a given key:

collection = Collection([
    {'product_id': 1, 'product': 'Desk'},
    {'product_id': 2, 'product': 'Chair'}
    {'product_id': 3, 'product': None}
])

plucked = collection.pluck('product').all() #== ['Desk', 'Chair', None]

A key can be given to pluck the collection into a dictionary with the given key

collection.pluck("product", "product_id") #== {1: 'Desk', 2: 'Chair', 3: None}

You can pass keep_nulls=False to remove None value in the collection.

collection.pluck("product", keep_nulls=False) #== ['Desk', 'Chair']

pop

Removes and returns the last item from the collection:

collection = Collection([1, 2, 3, 4, 5])
collection.pop() #== 5
collection.all() #== [1, 2, 3, 4]

prepend

Adds an item to the beginning of the collection:

collection = Collection([1, 2, 3, 4])
collection.prepend(0)
collection.all() #== [0, 1, 2, 3, 4]

pull

Removes and returns an item from the collection by its key:

collection = Collection([1, 2, 3, 4])
collection.pull(1) #== 2
collection.all() #== [1, 3, 4]

collection = Collection({'apple': 1, 'cherry': 3, 'lemon': 2})
collection.pull('cherry') #== 3
collection.all() #== {'apple': 1, 'lemon': 2}

push

Appends an item to the end of the collection:

collection = Collection([1, 2, 3, 4])
collection.push(5)
collection.all() #== [1, 2, 3, 4, 5]

put

Sets the given key and value in the collection:

collection = Collection([1, 2, 3, 4])
collection.put(1, 5)
collection.all() #== [1, 5, 3, 4]

collection = Collection({'apple': 1, 'cherry': 3, 'lemon': 2})
collection.put('cherry', 0)
collection.all() #== {'apple': 1, 'cherry': 0, 'lemon': 2}

random

Returns a random item from the collection

user = User.all().random() #== returns a random User instance

An integer count can be given to random method to specify how many items you would like to randomly retrieve from the collection. A collection will always be returned when the items count is specified

users = User.all().random(3) #== returns a Collection of 3 users
users.count() #== 3
users.all() #== returns a list of 3 users

If the collection length is smaller than specified count a ValueError will be raised.

reduce

Reduces the collection to a single value, passing the result of each iteration into the subsequent iteration.

collection = Collection([1, 2, 3])
collection.reduce(lambda result, item: (result or 0) + item) #== 6

Initial value is 0 by default but can be overridden:

collection.reduce(lambda result, item: (result or 0) + item, 4) #== 10

reject

It's the inverse of filter method. It filters the collection using the given callback. The callback should return True for any items to remove from the resulting collection:

collection = Collection([1, 2, 3, 4])
filtered = collection.reject(lambda item: item > 2)
filtered.all() #== [1, 2]

Unlike most other collection methods, reject does not return a new modified collection; it modifies the collection it is called on.

reverse

Reverses the order of the items in the collection:

collection = Collection([1, 2, 3])
collection.reverse().all() #== [3, 2, 1]

Unlike most other collection methods, reverse does not return a new modified collection; it modifies the collection it is called on.

serialize

Converts the collection into a list. If the collection’s values are ORM models, the models will also be converted to dictionaries:

collection = Collection([1, 2, 3])
collection.serialize() #== [1, 2, 3]

collection = Collection([User.find(1)])
collection.serialize() #== [{'id': 1, 'name': 'John', 'email': '[e-mail]'}]

Be careful, serialize also converts all of its nested objects. If you want to get the underlying items as is, use the all method instead.

shift

Removes and returns the first item from the collection:

collection = Collection([1, 2, 3, 4, 5])
collection.shift() #== 1
collection.all() #== [2, 3, 4, 5]

sort

Sorts the collection:

collection = Collection([5, 3, 1, 2, 4])
sorted = collection.sort()
sorted.all() #== [1, 2, 3, 4, 5]

sum

Returns the sum of all items in the collection:

Collection([1, 2, 3, 4, 5]).sum() #== 15

If the collection contains dictionaries or objects, you must pass a key to use for determining which values to sum:

collection = Collection([
    {'name': 'JavaScript: The Good Parts', 'pages': 176},
    {'name': 'JavaScript: The Defnitive Guide', 'pages': 1096}
])
collection.sum('pages') #== 1272

take

Returns a new collection with the specified number of items:

collection = Collection([0, 1, 2, 3, 4, 5])
chunk = collection.take(3)
chunk.all() #== [0, 1, 2]

You can also pass a negative integer to take the specified amount of items from the end of the collection:

chunk = collection.chunk(-2)
chunk.all() #== [4, 5]

to_json

Converts the collection into JSON:

collection = Collection([{'name': 'Desk', 'price': 200}])
collection.to_json() #== '[{"name": "Desk", "price": 200}]'

transform

Iterates over the collection and calls the given callback with each item in the collection. The items in the collection will be replaced by the values returned by the callback:

collection = Collection([1, 2, 3, 4, 5])
collection.transform(lambda item: item * 2)
collection.all() #== [2, 4, 6, 8, 10]

If you wish to create a new collection instead, use the map method.

unique

Returns all of the unique items in the collection:

collection = Collection([1, 1, 2, 2, 3, 4, 2])
unique = collection.unique()
unique.all() #== [1, 2, 3, 4]

When dealing with dictionaries or objects, you can specify the key used to determine uniqueness:

collection = Collection([
    {'name': 'Sam', 'role': 'admin'},
    {'name': 'Joe', 'role': 'basic'},
    {'name': 'Joe', 'role': 'admin'},
])
unique = collection.unique('name')
unique.all()
# [
#     {'name': 'Sam', 'role': 'admin'},
#     {'name': 'Joe', 'role': 'basic'}
# ]

where

Filters the collection by a given key / value pair:

collection = Collection([
    {'name': 'Desk', 'price': 200},
    {'name': 'Chair', 'price': 100},
    {'name': 'Bookcase', 'price': 150},
    {'name': 'Door', 'price': 100},
])
filtered = collection.where('price', 100)
filtered.all()
# [
#     {'name': 'Chair', 'price': 100},
#     {'name': 'Door', 'price': 100}
# ]

zip

Merges together the values of the given list with the values of the collection at the corresponding index:

collection = Collection(['Chair', 'Desk'])
zipped = collection.zip([100, 200])
zipped.all() #== [('Chair', 100), ('Desk', 200)]