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Using MONGO DB IN PYTHON
Upcoming TEST 1: Mar 11, 2024 Monday
40 Questions: MCQ / 60 MINUTES
Let’s start by installing MONGODB
and
PYTHON MONGO Checklist:
Checklist for Creating a Colors Database in MongoDB using Python:
Install MongoDB:
Download and install MongoDB from the official website
*** Choose the Option to install MONGOD as a service.
Start the MongoDB server by running the command mongod in a terminal or command prompt.
Using Visual Studio code to get this application going:
START VSC and make a Directory for your work:
Install PyMongo: Ensure that Python is installed on your system.
Install the PyMongo library using pip by running the command
pip install pymongo in a terminal or command prompt.
Create a Python Script:
Open Visual Studion Code and create a new Python script (e.g., create_colors_database.py).
Connect to MongoDB:
Import the MongoClient class from the pymongo library.
Create a MongoClient instance to connect to the local MongoDB server.
Create a Database:
Add code to create a new MongoDB database using the MongoClient instance.
Verify Database Creation:
//
In order to work with `pymongo`, you must first ensure that you have the `pymongo` library installed. You can install it using the following pip command if it's not already installed:
```bash
pip install pymongo
```
Now, let's take a step-by-step look at creating a
MongoClient instance, creating a new database, and verifying its creation in Python.
**1. Create a MongoClient Instance**
First, you need to import `MongoClient` from `pymongo` and create an instance of `MongoClient` that will connect to your local MongoDB server.
Normally, MongoDB runs on port 27017 by default.
Here's how to establish the connection:
from pymongo import MongoClient
# Connect to the local MongoDB server
client = MongoClient('localhost', 27017)
```
Alternatively, the connection string can be used:
```python
# Connect to the local MongoDB server with connection string
client = MongoClient('mongodb://localhost:27017/')
```
2. Create a Database
MongoDB creates databases and collections automatically for you if they do not exist already. Here's how you would create a new database:
```python
# Create a new database called 'mydatabase'
db = client['mydatabase']
```
A database in MongoDB is not created until it gets content, so at this point, `mydatabase` is just a Python variable that will be mapped to a MongoDB database once content (like a collection) is added to it.
**3. Verify Database Creation**
Although databases in MongoDB are created lazily, you can still list all databases to verify whether or not your database name is registered as a part of the system.
Below is a simple code snippet to create a collection
and verify that the database has been created.
In MongoDB, a collection is analogous to a table in relational databases:
Assuming 'mydatabase' has no collections, let's create one to initialize the database
db.create_collection('mycollection')
# Now list all the databases in MongoDB
database_list = client.list_database_names()
print(database_list)
# Check if 'mydatabase' exists in the list of databases
if 'mydatabase' in database_list:
print("'mydatabase' exists.")
else:
print("'mydatabase' does not exist or has not been initialized with any data.")
```
In the above code, we tried to create a `collection` to ensure that the database is created.
Then we list all database names and check if our new database is in that list, even though the presence of a database in the list is not a definitive confirmation until at least one document is inserted into a collection.
Remember, a database in MongoDB stands up only upon insertion of the first document into a collection within that database (or, in some cases, when a collection is created explicitly). Thus, until you perform an actual insert operation, the new database may not show up in the server's database list.
In MongoDB, collections are analogous to tables in relational databases and can be created explicitly or implicitly.
When you add a document into a collection that does not exist, MongoDB automatically creates the collection.
Here's how to create a collection both implicitly and explicitly using PyMongo:
**Implicit Collection Creation**
When you insert a document into a collection that hasn't been created yet, MongoDB creates the collection automatically:
```python
from pymongo import MongoClient
# Establishing a connection to the MongoDB server
client = MongoClient('localhost', 27017)
# Selecting the database - it will be created if it does not exist
db = client['mydatabase']
# Inserting a document - the collection 'mycollection' will be created implicitly
result = db.mycollection.insert_one({'name': 'John', 'age': 30})
# You can now check that the 'mycollection' exists
print('Collection created:', 'mycollection' in db.list_collection_names())
```
**Explicit Collection Creation**
You can explicitly create a collection using the `create_collection` method. This is useful if you want to configure collection options, such as setting capped collections which limit the size or the number of documents a collection can have.
```python
from pymongo import MongoClient
# Establishing a connection
client = MongoClient('localhost', 27017)
# Selecting the database
db = client['mydatabase']
# Explicitly creating a collection named 'mycollection'
collection = db.create_collection('mycollection')
# Verifying that 'mycollection' exists
print('Collection created:', 'mycollection' in db.list_collection_names())
```
In the explicit creation, `create_collection` throws an error if the collection already exists unless you set the `strict` option to `False`.
Note that explicitly creating a collection without any options is not very common since MongoDB's philosophy embraces an implicit creation of collections and databases when they are first used.
To write to an existing "planetmars" database without re-creating it, you can follow these steps:
from pymongo import MongoClient
# Connect to the local MongoDB server
client = MongoClient('localhost', 27017)
# Select the 'planetmars' database
db = client['planetmars']
# Choose the collection
collection = db['mycollection']
# Insert a single document
result = collection.insert_one({'name': 'John', 'age': 30})
# Insert multiple documents
documents = [{'name': 'Alice', 'age': 25}, {'name': 'Bob', 'age': 35}]
result = collection.insert_many(documents)
# Print the inserted document's _id
print(result.inserted_id)
By following these steps, you should be able to write to the existing "planetmars" database without re-creating it.It's important to remember that a collection is not physically created until you actually insert some data into it.
So, when you call `create_collection` without defining any options, you're essentially telling MongoDB to prepare to create the collection once a document is inserted unless you specify options that take effect immediately, like capped collections.
>>>>>
To acquire the "my_collection" collection without trying to re-create it, you can modify your code as follows:
from pymongo import MongoClient
# Connect to the local MongoDB server
client = MongoClient('localhost', 27017)
# Select the 'planetmars' database
db = client['planetmars']
# Choose the collection 'my_collection'
collection = db['my_collection']
# Now you can use the 'collection' object to perform operations on the collection
# For example, you can insert a document
result = collection.insert_one({'name': 'John', 'age': 30})
# Print the result
print(result)
# You can also check if the collection exists
if 'my_collection' in db.list_collection_names():
print("'my_collection' exists.")
else:
print("'my_collection' does not exist or has not been initialized with any data.")
By using the db['my_collection'] syntax, you can directly access the "my_collection" collection without trying to re-create it. This way, you can perform operations on the existing collection, such as inserting documents.
Please note that if the collection does not exist, it will be created implicitly when you insert the first document.
>>>>>
Making the Bears Database
Add Collection (Optional):
If desired, include code to create a collection within the created database.
Finalize and Test:
Close the MongoClient connection to release resources.
Lab Activity:
Instruct students to run the Python script and observe the output to verify the successful creation of the database.
Encourage students to modify the script to perform additional interactions with the database, such as inserting sample data or querying the collection.
Additional Considerations:
Emphasize error handling and proper resource management in the Python script.
Guide students to organize the code and structure the database interactions for clean and efficient implementation.
By following this checklist, students can ensure a structured approach to creating a MongoDB database with Python, adhering to best practices in software writing and information architecture.
Exception handling if collection exists
To handle the situation where the collection already exists, you'll need to catch the `CollectionInvalid` exception that `create_collection` raises when it tries to create a collection that already exists. The `pymongo.errors` module provides this exception class. Amend the script as shown below:
```python
from pymongo import MongoClient
from pymongo.errors import CollectionInvalid
# Connect to the local MongoDB server
client = MongoClient('localhost', 27017)
# Select the database
db = client['TheBearCave']
try:
# Attempt to create the collection
collection = db.create_collection('mycollection')
print(f"Collection created: {collection}")
except CollectionInvalid:
print("Collection 'mycollection' already exists.")
# Since MongoDB lazy-creates databases, you can verify if 'TheBearCave'
# database is listed among the ones created after an interaction requiring its creation
database_list = client.list_database_names()
print("Database list:", database_list)
# Check if 'TheBearCave' exists in the list of databases
if 'TheBearCave' in database_list:
print("'TheBearCave' database exists.")
else:
print("'TheBearCave' database does not exist or has not been initialized with any data.")
```
In this updated version, the script will attempt to create the collection 'mycollection' within 'TheBearCave' database. If the collection already exists, the `CollectionInvalid` exception will be caught, and a message indicating that the collection already exists will be printed instead of the script failing with an exception.
It's important to note that `create_collection` will not only check for the existence of the collection by name but will also verify if the options match. If the collection already exists with different options, it will still raise `CollectionInvalid`. Therefore, use this feature when specific creation options are needed. Otherwise, letting MongoDB create the collection automatically when data is inserted might be more straightforward and error-tolerant.
Python works with MongoDB through drivers like PyMongo, which is the official MongoDB driver for synchronous Python applications.
PyMongo provides an intuitive API for accessing databases, collections, and documents in MongoDB.
It allows for easy manipulation, iteration, and printing of objects retrieved from MongoDB, as they are compatible with dictionaries and lists.
To work with MongoDB in Python, you need to install the PyMongo driver, which can be done using PIP.
Once installed, you can use PyMongo to connect to a MongoDB database, query, retrieve, write, and delete data, as well as run database commands
.If you encounter any issues when connecting to a MongoDB database locally using Python, ensure that the MongoDB server is running and that you are using the correct connection parameters. The connection string should specify the correct host, port, and database name.
Additionally, make sure that the necessary MongoDB driver, such as PyMongo, is installed in your Python environment
.Installing MONGODB:
When using MongoDB as the persistence layer for a Python MVC 3-tier application, it's recommended to set up a separate MongoDB database for the application. This allows for better isolation, management, and scalability of the application's data.
Setting up a separate MongoDB database provides the following advantages:
When teaching students, it's important to:
demonstrate the process of setting up a separate MongoDB database for their application and guide them on best practices for database naming conventions, user permissions, and data organization within the database.
This approach aligns with the principles of information architecture and ensures a structured and organized data storage for their applications.
Lesson Plan: Using MongoDB as the Persistence Layer for Python MVC 3-tier Application
Objective: To teach students how to integrate MongoDB as the persistence layer for a Python MVC 3-tier application.
Prerequisites:
Lesson Plan:
a. Explanation of MongoDB as a NoSQL database
b. Advantages of using MongoDB in web applications
c. Comparison with traditional SQL databases
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