A clean realtime way to handle MongoDB documents in Pythonic way
Project description
MongoGetterSetter - A Clean Realtime MongoDB Getter Setter API for Python
MongoGetterSetter is a metaclass that provides a convenient getter and setter API for instances of the classes that use it, allowing natural operations in Python objects to easily reflect in MongoDB documents.
The idea is to convert MongoDB Document into Python Object of Type MongoGetterSetter in High Level, and all other document's sub documents are treated as dict wrapped with MongoDictWrapper and other datatypes like int, bool float and list are all handled by MongoDataWrapper.
Here, we initialize Employee and EmployeeCollection class with _collection and _filter_query as mandatory attributes for MongoGetterSetter to function properly. These 2 attributes are used internally to do further manipulations to MongoDB documents. You can change the _filter_query attribute to customize the filter query as per your needs. _collection should point to the MongoDB collection.
Usage of MongoGetterSetter metaclass
from pymongo import MongoClient
from mongogettersetter import MongoGetterSetter
# Connect to the MongoDB database and collection
client = MongoClient("mongodb://localhost:27017/")
db = client["example_db"]
collection = db["employee"]
# Wrapper for MongoDB Collection with metaclass, use this inside your actual class.
class EmployeeCollection(metaclass=MongoGetterSetter):
def __init__(self, _id):
self._filter_query = {"id": _id} # or the ObjectID, at your convinence
self._collection = collection # Should be a pymongo.MongoClient[database].collection
class Employee:
def __init__(self, _id):
self._filter_query = {"id": _id}
self._collection = collection
self.collection = EmployeeCollection(_id)
# Create a new document if it doesn't exist
if self.collection.get() is None:
self._collection.insert_one(self._filter_query)
def someOtherOperation(self):
self.collection.hello = "Hello World"
Now, save the above code in a file named employee.py and run the following command in the same directory:
$ python3 -i employee.py
This will run the contents of employee.py in interactive mode. Now, you can create an instance of EmployeeCollection in Employee class and do operations on it.
Before that, assume you have a MongoDB Collection called employee with an object like this:
{'_id': ObjectId('640311ab0469a9c4eaf3d2bd'), 'id': 4051, 'email': 'manoj123@gmail.com', 'password': 'SomeNew SecurePassword', 'about': None, 'token': '7f471974-ae46-4ac0-a882-1980c300c4d6', 'country': 'India', 'location': None, 'lng': 0, 'lat': 0, 'dob': None, 'gender': 0, 'userType': 1, 'userStatus': 1, 'profilePicture': 'Images/9b291404-bc2e-4806-88c5-08d29e65a5ad.png', 'coverPicture': 'Images/44af97d9-b8c9-4ec1-a099-010671db25b7.png', 'enablefollowme': False, 'sendmenotifications': False, 'sendTextmessages': False, 'enabletagging': False, 'createdAt': '2020-01-01T11:13:27.1107739', 'updatedAt': '2020-01-02T09:16:49.284864', 'livelng': 77.389849, 'livelat': 28.6282231, 'liveLocation': 'Unnamed Road, Chhijarsi, Sector 63, Noida, Uttar Pradesh 201307, India', 'creditBalance': 130, 'myCash': 0, 'data': {'name': 'array_test', 'arr': [1, 2, 3, 4, 5, 6, 7, 8], 'hobies': {'composer': ['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan'], 'music': 'helo'}}, 'scores': [{'subject': 'math', 'score': 100}, {'subject': 'physics', 'score': 85}, {'subject': 'chemistry', 'score': 95}], 'fix': 1, 'hello': 1, 'recent_views': [200], 'exam': '', 'subject': '', 'arr': {'name': 'sibidharan', 'pass': 'hello', 'score': {'subject': {'minor': 'zoology', 'major': 'biology', 'others': ['evs', {'name': 'shiro', 'inarr': [200, 2, 3, {'sub': 'testsub', 'newsu': 'aksjdad', 'secret': 'skdjfnsdkfjnsdfsdf'}, 4, 12]}]}, 'score': 40, 'new': 'not7', 'hello': {'arr': [5, 2]}}}, 'name': 'ManojKumar', 'd': [1, 3, 4, 5], 'score': {}, 'hgf': 5}
This can be accessed by creating an instance of EmployeeCollection class with the proper id as given in the self._filter_query. If such ID doesn't exist, it will create a new document with the given id.
For example:
>>> e = EmployeeCollection(4051)
Now this e object is an instance of EmployeeCollection class, which is a subclass of MongoGetterSetter metaclass. This object is a wrapper around the MongoDB document, which is fetched from the MongoDB collection using the self._filter_query from the self._collection attribute. You can access the MongoDB document and do CURD essential operations just by accessing this object's attributes/indexes. For the available methods, see the MongoDataWrapper and MongoDictWrapper methods. For example:
>>> e = EmployeeCollection(4051)
>>> e
{'_id': ObjectId('640311ab0469a9c4eaf3d2bd'), 'id': 4051, 'email': 'manoj123@gmail.com', 'password': 'SomeNew SecurePassword', 'about': None, 'token': '7f471974-ae46-4ac0-a882-1980c300c4d6', 'country': 'India', 'location': None, 'lng': 0, 'lat': 0, 'dob': None, 'gender': 0, 'userType': 1, 'userStatus': 1, 'profilePicture': 'Images/9b291404-bc2e-4806-88c5-08d29e65a5ad.png', 'coverPicture': 'Images/44af97d9-b8c9-4ec1-a099-010671db25b7.png', 'enablefollowme': False, 'sendmenotifications': False, 'sendTextmessages': False, 'enabletagging': False, 'createdAt': '2020-01-01T11:13:27.1107739', 'updatedAt': '2020-01-02T09:16:49.284864', 'livelng': 77.389849, 'livelat': 28.6282231, 'liveLocation': 'Unnamed Road, Chhijarsi, Sector 63, Noida, Uttar Pradesh 201307, India', 'creditBalance': 130, 'myCash': 0, 'data': {'name': 'array_test', 'arr': [1, 2, 3, 4, 5, 6, 7, 8], 'hobies': {'composer': ['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan'], 'music': 'helo'}}, 'scores': [{'subject': 'math', 'score': 100}, {'subject': 'physics', 'score': 85}, {'subject': 'chemistry', 'score': 95}], 'fix': 1, 'hello': 1, 'recent_views': [200], 'exam': '', 'subject': '', 'arr': {'name': 'sibidharan', 'pass': 'hello', 'score': {'subject': {'minor': 'zoology', 'major': 'biology', 'others': ['evs', {'name': 'shiro', 'inarr': [200, 2, 3, {'sub': 'testsub', 'newsu': 'aksjdad', 'secret': 'skdjfnsdkfjnsdfsdf'}, 4, 12]}]}, 'score': 40, 'new': 'not7', 'hello': {'arr': [5, 2]}}}, 'name': 'ManojKumar', 'd': [1, 3, 4, 5], 'score': {}, 'hgf': 5}
>>> e.id
4051
>>> e.id.get()
4051
>>> e.name
ManojKumar
>>> e.name.get()
ManojKumar
The MongoDB Document's root level attributes are directly accessible as the attributes of the MongoGetterSetter object. For example, e.id can also be accessible as e['id'] and e.name can also be accessible as e['name']. The e.id.get() and e.name.get() methods are used to get the original datatype of the MongoDB document's root level attributes. For example, e.id is an int datatype, so e.id.get() will return the original int datatype. Similarly, e.data is a dict datatype wrapped in MongoDictWrapper, e.data.get() will return the original dict datatype.
For Example:
>>> e.name = "S. Manoj Kumar"
>>> e.name
S. Manoj Kumar
>>> e.data
{'name': 'array_test', 'arr': [1, 2, 3, 4, 5, 6, 7, 8], 'hobies': {'composer': ['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan'], 'music': 'helo'}}
>>> type(e.data)
<class 'mongogettersetter.MongoDataWrapper'>
>>> e.data.name = "ThisIsAwesmoe"
>>> e.data
{'name': 'ThisIsAwesmoe', 'arr': [1, 2, 3, 4, 5, 6, 7, 8], 'hobies': {'composer': ['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan'], 'music': 'helo'}}
>>>
The MongoDataWrapper class is used to wrap the MongoDB document datatypes to provide MongoDB Array/List Operations over a simple, straightforward API to perform various operations on the MongoDB collection.
You can perform almost all basic array operations MongoDB supports. For example, you can use e.data.arr.push(9) to append a new element to the arr array. Similarly, you can use e.data.arr.pop() to pop the last element from the arr array. You can also use e.data.arr.remove(2) to remove the element 2 from the arr array. You can also use e.data.arr.insert(0, [1,2,3]) to insert the element [1,2,3] at the beginning of the arr array. You can also use e.data.arr[0] = 0 to set the first element of the arr array to 0. You can also use e.data.arr[0] to get the first element of the arr array. You can also use e.data.arr[0].get() to get the original datatype of the first element of the arr array.
>>> e.data
{'name': 'ThisIsAwesmoe', 'arr': [1, 2, 3, 4, 5, 6, 7, 8], 'hobies': {'composer': ['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan'], 'music': 'helo'}}
>>> type(e.data)
<class 'mongogettersetter.MongoDataWrapper'>
>>> type(e.data.get())
<class 'dict'>
>>> e.data.arr.push(9)
True
>>> e.data
{'name': 'ThisIsAwesmoe', 'arr': [1, 2, 3, 4, 5, 6, 7, 8, 9], 'hobies': {'composer': ['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan'], 'music': 'helo'}}
>>> e.data.arr[1] = 100
>>> e.data.arr
[1, 100, 3, 4, 5, 6, 7, 8, 9]
>>> e.data.arr[1]
100
Access documents in any depth, either as attributes or as keys, to access nested data. For example, e.data.hobies is a nested dictionary, so you can access the hobies dictionary as e.data.hobies or e.data['hobies']. Similarly, e.data.hobies.composer is a nested list, so you can access the composer list as e.data.hobies.composer or e.data.hobies['composer']. Similarly, e.data.hobies.composer[1] is a nested dictionary, so you can access the co_singer list as e.data.hobies.composer[1].co_singer or e.data.hobies.composer[1]['co_singer']. Perform all possible operations on all the nested data, limited to the MongoDB supported operations.
>>> e.data.hobies
{'composer': ['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan'], 'music': 'helo'}
>>> e.data.hobies.composer
['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan']
>>> e.data.hobies.composer.push('rahman')
True
>>> e.data.hobies.composer
['anirudh', {'co_singer': ['rakshitha', 'divagar', 'sibi']}, 'yuvan', 'rahman']
>>> e.data.hobies.composer[1]
{'co_singer': ['rakshitha', 'divagar', 'sibi']}
>>> e.data.hobies.composer[1].co_singer
['rakshitha', 'divagar', 'sibi']
>>> e.data.hobies.composer[1].co_singer.pop()
True
>>> e.data.hobies.composer[1].co_singer
['rakshitha', 'divagar']
>>> e.data.hobies.composer[1].co_singer.insert(0, 'sushila')
True
>>> e.data.hobies.composer[1].co_singer
['sushila', 'rakshitha', 'divagar']
>>> e.data.hobies
{'composer': ['anirudh', {'co_singer': ['sushila', 'rakshitha', 'divagar']}, 'yuvan', 'rahman'], 'music': 'helo'}
>>> e.data.hobies.music = 'melody'
>>> e.data.hobies
{'composer': ['anirudh', {'co_singer': ['sushila', 'rakshitha', 'divagar']}, 'yuvan', 'rahman'], 'music': 'melody'}
>>> e.data.hobies.composer[1].main_singer = 'SPB'
>>> e.data.hobies
{'composer': ['anirudh', {'co_singer': ['sushila', 'rakshitha', 'divagar'], 'main_singer': 'SPB'}, 'yuvan', 'rahman'], 'music': 'melody'}
>>> e.data.hobies.composer
['anirudh', {'co_singer': ['sushila', 'rakshitha', 'divagar'], 'main_singer': 'SPB'}, 'yuvan', 'rahman']
>>> e.data.hobies.composer[1].main_singer
'SPB'
>>> type(e.data.hobies.composer[1].main_singer)
<class 'str'>
>>> type(e.data.hobies.composer)
<class 'mongogettersetter.MongoDataWrapper'>
>>> type(e.data.hobies.composer[1])
<class 'mongogettersetter.MongoDictWrapper'>
>>> e.data.hobies.composer[1].get('co_singer')
['sushila', 'rakshitha', 'divagar']
>>> e.data.hobies.composer[1].get()
{'co_singer': ['sushila', 'rakshitha', 'divagar'], 'main_singer': 'SPB'}
>>> type(e.data.hobies.composer[1].get())
<class 'dict'>
>>>
MongoGetterSetter
MongoGetterSetter is a metaclass that provides a convenient getter and setter API for instances of the classes that use it, allowing natural operations in Python objects to easily reflect in MongoDB documents.
Methods
-
__getattr__(self, key): Returns aMongoDataWrapperinstance for the givenkey. See below for the capabalities ofMongoDataWrapperExample:
obj = EmployeeCollection(_id) result = obj.some_key -
__getitem__(self, key, value): Gets the value of the specifiedkeyfrom the MongoDB document.Example:
print(obj['some_key']) -
__setattr__(self, key, value): Sets the value of the specifiedkeyin the MongoDB document.Example:
obj.some_key = "new_value" -
__setitem__(self, key, value): Sets the value of the specifiedkeyin the MongoDB document.Example:
obj['some_key'] = "new_value" -
__contains__(self, key): Checks if the MongoDB document contains the specifiedkey.Example:
if "some_key" in obj: print("Key exists") -
__str__(self): Returns a string representation of the MongoDB document.Example:
print(obj) -
__delitem__(self, key): Removes the specified key from the MongoDB document.Example:
del obj['some_key'] -
__delattr__(self, key): Removes the specified key from the MongoDB document.Example:
del obj.some_key -
delete(self): Removes document itself from the MongoDBExample:
obj.delete() -
get(self): Returns the MongoDB document.Example:
print(obj.get()) -
set(self, data): Sets the given updated document in the MongoDB collectionExample:
obj.set({ "password": "$2$somenewpassword", "country": "Malaysia" })
MongoDataWrapper
MongoDataWrapper is a subscriptable class, which wraps MongoDB document datatypes to provide MongoDB Array/List Operations over a simple, straightforward API to perform various operations on the MongoDB collection. Check the list of methods for the allowed operations.
Methods
-
__init__(self, _id, key, collection): Initialize the instance with the given_id,key, andcollection. -
get(self): Returns the value of the key in the MongoDB document. -
inArray(self, value): Checks if the givenvalueis present in the array of the document's key. -
push(self, *values, maximum=-1): Pushes one or morevaluesinto the array of the document's key. Ifmaximumis specified, it will limit the array size to themaximumvalue. -
addToSet(self, value): Adds avalueto the array of the document's key only if it doesn't exist in the array. -
pop(self, direction=1): Removes the first (direction=-1) or the last (direction=1) element from the array of the document's key. -
pull(self, value): Removes the specifiedvaluefrom the array of the document's key. -
pullAll(self, *values): Removes all occurrences of the specifiedvaluesfrom the array of the document's key. -
matchSize(self, value): Checks if the size of the array of the document's key is equal to the givenvalue. -
elemMatch(self, **kvalues): Checks if the array of the document's key contains at least one element that matches the specified key-value pairs inkvalues. -
matchAll(self, *values): Checks if the array of the document's key contains all the specifiedvalues. -
update(self, field, match, **kvalues): Updates the nested fieldfieldof the document's key where thefieldvalue matchesmatch, with the key-value pairs provided inkvalues. -
insert(self, index, value): Inserts the givenvalueat the specifiedindexin the array of the document's key. -
index(self, value): Find the index of the given value in array. It will return -1 if the value is not present in the list. -
delete(self): Delets the key from MongoDB Document -
__getitem__(self, index): Returns the value of the array of the document's key at the specifiedindex. -
__setitem__(self, index, value): Sets the value of the array of the document's key at the specifiedindexto the givenvalue. -
__delitem__(self, index): Removes the value of the array of the document's key at the specifiedindex. -
__len__(self): Returns the length of the array of the document's key. -
__str__(self): Returns a string representation of the value of the document's key. -
__repr__(self): Returns a string representation of the value of the document's key.
MongoDictWrapper
MongoDictWrapper is a class that inherits from the dict class and extends its functionalities to access dictionary keys as attributes. It allows you to access, modify, and manipulate MongoDB documents using Python dictionaries. When a MongoDataWrapper returns a dict, it automatically is wrapped with MongoDictWrapper, when it returns a list, it automatically is wrapped with MongoDataWrapper to allow manipulation of MongoDB object inside a MongoDB object, like a dict inside a dict. If you wish to access the value as default datatype, consider get() method.
Methods
-
__init__(self, *args, **kwargs): Constructor method that initializes the basedictclass. -
prepare(self, _id, key, collection, filter_query): This method initializes the internal data structure that stores information about the document's location in the MongoDB collection. -
__getitem__(self, key): Overrides the basedictmethod to return a wrapped MongoDictWrapper when accessing a nested dictionary. -
__setitem__(self, key, value): Overrides the basedictmethod to update the MongoDB document when setting a key-value pair. -
__delattr__(self, key): Overrides the basedictmethod to delete a key-value pair from the MongoDB document when deleting an attribute. -
__getattr__(self, key): Overrides the basedictmethod to return a wrapped MongoDictWrapper when accessing a nested dictionary. -
__setattr__(self, key, value): Overrides the basedictmethod to update the MongoDB document when setting a key-value pair. -
__delitem__(self, key): Overrides the basedictmethod to delete a key-value pair from the MongoDB document when deleting an item. -
get(self, key, default=None): Overrides the basedictmethod to return the value of the key in the MongoDB document, or thedefaultvalue if the key is not present. -
pop(self, key, default=None): Overrides the basedictmethod to remove and return the value of the key in the MongoDB document, or thedefaultvalue if the key is not present. -
update(self, other): Overrides the basedictmethod to update the MongoDB document with the key-value pairs from theotherdictionary or iterable. -
delete(self): Delets the key from MongoDB Document -
clear(self): Overrides the basedictmethod to remove all key-value pairs from the MongoDB document. -
__len__(self): Overrides the basedictmethod to return the number of key-value pairs in the MongoDB document. -
__str__(self): Overrides the basedictmethod to return a string representation of the MongoDB document. -
__repr__(self): Overrides the basedictmethod to return a string representation of the MongoDB document.
Examples
To provide a more detailed example, let's assume you have a MongoDB collection named people with the following documents:
[
{
"id": 1,
"name": "Alice",
"age": 30,
"skills": ["Python", "Django", "JavaScript"],
"contact": {
"email": "alice@example.com",
"phone": "555-1234"
},
"projects": [
{
"title": "Project A",
"status": "completed"
},
{
"title": "Project B",
"status": "in progress"
}
]
},
{
"id": 2,
"name": "Bob",
"age": 25,
"skills": ["Java", "Spring", "JavaScript"],
"contact": {
"email": "bob@example.com",
"phone": "555-5678"
},
"projects": [
{
"title": "Project X",
"status": "completed"
},
{
"title": "Project Y",
"status": "in progress"
}
]
}
]
Now, let's create a class called People and PeopleCollection with MongoGetterSetter as its metaclass.
from pymongo import MongoClient
from mongogettersetter import MongoGetterSetter
# Connect to the MongoDB database and collection
client = MongoClient("mongodb://localhost:27017/")
db = client["example_db"]
people_collection = db["people"]
# Wrapper for MongoDB Collection with metaclass, use this inside your actual class.
class PeopleCollection(metaclass=MongoGetterSetter):
def __init__(self, _id):
self._filter_query = {"id": _id} # or the ObjectID, at your convenience
self._collection = people_collection # Should be a pymongo.MongoClient[database].collection
class People():
def __init__(self, _id):
self.collection = PeopleCollection(_id)
self._filter_query = {"id": _id}
self._collection = people_collection
if self.collection.get() is None:
self._collection.insert_one(self._filter_query)
def someOtherOperation(self):
self.collection.hello = "Hello World"
Create a PeopleCollection object for Alice with id = 1
alice = PeopleCollection(1)
Access and modify Alice's name
print(alice.name) # Output: 'Alice'
alice.name = "Alice Johnson"
print(alice.name) # Output: 'Alice Johnson'
Check if Alice's document has a 'contact' field
if 'contact' in alice:
print("Contact field exists")
Access and modify Alice's email
print(alice.contact) # Output: {'email': 'alice@example.com', 'phone': '555-1234'}
alice.contact.email = "alice.johnson@example.com"
print(alice.contact.email) # Output: 'alice.johnson@example.com'
Access and modify Alice's skills
print(alice.skills)# Output: ['Python', 'Django', 'JavaScript']
print(alice.skills.get()) # Output: ['Python', 'Django', 'JavaScript']
alice.skills.push("React", maximum=4)
print(alice.skills.get()) # Output: ['Python', 'Django', 'JavaScript', 'React']
alice.skills.pop(direction=-1)
print(alice.skills.get()) # Output: ['Python', 'Django', 'JavaScript']
Access and modify Alice's projects
print(alice.projects.get()) # Output: [{'title': 'Project A', 'status': 'completed'}, {'title': 'Project B', 'status': 'in progress'}]
alice.projects.update("title", "Project A", status="archived")
print(alice.projects.get()) # Output: [{'title': 'Project A', 'status': 'archived'}, {'title': 'Project B', 'status': 'in progress'}]
More MongoDataWrapper examples
Create a People object for Alice with id = 1
alice = People(1)
Create MongoDataWrapper instances for Alice's skills and projects
alice_skills = alice.skills
alice_projects = alice.projects
Examples for each method of the MongoDataWrapper class
get()
print(alice_skills.get()) # Output: ['Python', 'Django', 'JavaScript']
inArray()
print(alice_skills.inArray("Python")) # Output: True
push()
alice_skills.push("React", "Java", maximum=5)
print(alice_skills.get()) # Output: ['Python', 'Django', 'JavaScript', 'React', 'Java']
addToSet()
alice_skills.addToSet("C++")
print(alice_skills.get()) # Output: ['Python', 'Django', 'JavaScript', 'React', 'Java', 'C++']
pop()
alice_skills.pop(direction=-1)
print(alice_skills.get()) # Output: ['Python', 'Django', 'JavaScript', 'React', 'Java']
pull()
alice_skills.pull("Java")
print(alice_skills.get()) # Output: ['Python', 'Django', 'JavaScript', 'React']
pullAll()
alice_skills.pullAll("Python", "React")
print(alice_skills.get()) # Output: ['Django', 'JavaScript']
matchSize()
print(alice_skills.size(2)) # Output: True
elemMatch()
print(alice_projects.elemMatch(title="Project A", status="completed")) # Output: True
matchAll()
print(alice_skills.all("Django", "JavaScript")) # Output: True
update()
alice_projects.update("title", "Project A", status="archived")
print(alice_projects.get()) # Output: [{'title': 'Project A', 'status': 'archived'}, {'title': 'Project B', 'status': 'in progress'}]
__len__()
print(len(alice_skills)) # Output: 2
__str__() and __repr__()
print(alice_skills) # Output: ['Django', 'JavaScript']
print(repr(alice_skills)) # Output: ['Django', 'JavaScript']
More MongoDictWrapper examples
>>> e = Employee(4051)
>>> e
{'_id': ObjectId('640311ab0469a9c4eaf3d2bd'), 'id': 4051, 'name': 'Manoj', 'email': 'manoj123@gmail.com', 'password': 'different password', 'about': None, 'token': '7f471974-ae46-4ac0-a882-1980c300c4d6', 'country': None, 'location': None, 'lng': 0, 'lat': 0, 'dob': None, 'gender': 0, 'userType': 1, 'userStatus': 1, 'profilePicture': 'Images/9b291404-bc2e-4806-88c5-08d29e65a5ad.png', 'coverPicture': 'Images/44af97d9-b8c9-4ec1-a099-010671db25b7.png', 'enablefollowme': False, 'sendmenotifications': False, 'sendTextmessages': False, 'enabletagging': False, 'createdAt': '2020-01-01T11:13:27.1107739', 'updatedAt': '2020-01-02T09:16:49.284864', 'livelng': 77.389849, 'livelat': 28.6282231, 'liveLocation': 'Unnamed Road, Chhijarsi, Sector 63, Noida, Uttar Pradesh 201307, India', 'creditBalance': 127, 'myCash': 0, 'data': [4, 3, 4, 5, 7], 'arr': {'name': 'shiro', 'pass': 'hello', 'score': {'subject': {'minor': 'physics', 'major': 'science'}, 'score': 95}}, 'scores': [{'subject': 'math', 'score': 95}, {'subject': 'physics', 'score': 85}, {'subject': 'chemistry', 'score': 95}], 'recent_views': [4, 4, 4, 4, 4, 4, 4, 4, 4], 'fix': 1, 'hello': 1}
>>> e.arr
{'name': 'shiro', 'pass': 'hello', 'score': {'subject': {'minor': 'physics', 'major': 'science'}, 'score': 95}}
>>> e.arr['name'] = 'sibidharan' # MongoDataWrapper is also Subscriptable
>>> e.arr
{'name': 'sibidharan', 'pass': 'hello', 'score': {'subject': {'minor': 'physics', 'major': 'science'}, 'score': 95}}
>>> e.arr.score # Queried from the MongoDB directly
{'subject': {'minor': 'physics', 'major': 'science'}, 'score': 95}
>>> e.arr.score['subject']
{'minor': 'physics', 'major': 'science'}
>>> e.arr.score.subject
{'minor': 'physics', 'major': 'science'}
>>> e.arr.score.subject.minor = 'chemistry'
{'minor': 'physics', 'major': 'science'}
# is same as the following
>>> e.arr.score['subject']['minor'] = 'chemistry' # All change are reflected in MongoDB Document
>>> e.arr
{'name': 'sibidharan', 'pass': 'hello', 'score': {'subject': {'minor': 'chemistry', 'major': 'science'}, 'score': 95}}
>>> del e.arr.score['subject'] # Can delete any key in dictionary
>>> del e.arr # Can delete a key itself from the MongoDB Document
>>> e.delete() # Delete the document itself
High-level Overview of the code for contributors to better understand the implementation
Any and all contributions are welcome ❤️
-
MongoDictWrapper: A wrapper for dictionaries that provides additional methods for interaction with MongoDB documents.Methods:
prepare__getitem____setitem____delitem__getpopupdatecleardelete
-
MongoDataWrapper: A wrapper class for the data stored in MongoDB documents.Methods:
getinArraypushaddToSetpoppullpullAllsizeelemMatchallupdatedelete__len____str____repr____getattr____getitem____setattr____setitem____delitem____delattr__
-
MongoGetterSetter: A metaclass that provides a way to override the default behavior of__getattr__,__setattr__,__contains__,__str__,__repr__, and__delattr__to work with MongoDB documents.Nested class:
PyMongoGetterSetterMethods:
__getattr____getitem____setattr____setitem____contains____str____repr____delattr____delitem__delete
Credits
Thanks to GPT-4 for helping me write this documentation. If you find any errors or something doesn't work as the documentation says, raise an issue here https://git.selfmade.ninja/sibidharan/pymongogettersetter
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