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 #== '[email protected]'
Available Methods
​
​
​
​all​
​avg​
​chunk​
​collapse​
​contains​
​count​
​diff​
​each​
​every​
​filter​
​first​
​flatten​
​for_page​
​forget​
​get​
​group_by​
​implode​
​is_empty​
​last​
​map_into​
​map​
​max​
​merge​
​pluck​
​pop​
​prepend​
​pull​
​push​
​put​
​random​
​reduce​
​reject​
​reverse​
​serialize​
​shift​
​sort​
​sum​
​take​
​to_json​
​transform​
​unique​
​where​
​zip​
​
​
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': '[email protected]'}]
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)]
Models
Schema & Migrations
Last updated 2 months ago

all	avg	chunk
collapse	contains	count
diff	each	every
filter	first	flatten
for_page	forget	get
group_by	implode	is_empty
last	map_into	map
max	merge	pluck
pop	prepend	pull
push	put	random
reduce	reject	reverse
serialize	shift	sort
sum	take	to_json
transform	unique	where
zip