In the information age we live in, we can see how much data the world is exchanging. We are basically creating, storing and retrieving data on a broad scale! There should be a way to handle all this - there's no way it could spread everywhere without any management, right? This is a database management system (DBMS).
A DBMS is a software system that allows you to create, store, modify, retrieve, and otherwise manipulate data in a database. Such systems also vary in size, from small systems running only on personal computers to large systems running on mainframes.
The focus of this tutorial is Python, not database design. Yes, Python is very capable of interacting with databases, and that's what I'm going to show you in this tutorial. You'll learn how to use Python to work with SQLite and Redis databases.
let's start!
As mentioned above, Python can interact with databases. But how can it do this? Python uses what is called the Python Database API to interact with databases. This API allows us to program different database management systems (DBMS). However, the process followed at the code level is the same for different DBMSs as follows:
SQLite is an open source, full-featured, standalone (needs little support from external libraries), serverless (no server is required to run the database engine, and is a locally stored database), zero-configuration (no installation or configuration required), A lightweight database management system based on SQL (can run SQL queries on SQLite tables) and uses a data file to store data.
It is worth mentioning that SQLite is used by large companies such as Google, Apple, Microsoft, etc., which makes it very reliable. In this tutorial we will use SQLite to interact with a database, more specifically we will use the sqlite3 module in Python.
As mentioned above, using a database involves five major steps. Let's see these steps in action.
This step is implemented as follows:
conn = sqlite3.connect('company.db')
As stated in the sqlite3 documentation:
To use this module, you must first create a Connection object that represents the database.
In the above code, please note that the data will be stored in the file company.db.
The next step in working with the database is to create a cursor, as shown below:
curs = conn.cursor()
After connecting to the database and creating the cursor, we can now process (interact with) the data. In other words, we can now run SQL commands on database company.db.
Suppose we want to create a new table employee in database company. In this case, we need to run a SQL command. To do this, we will use the execute() method of the sqlite3 module. Therefore, the Python statement will look like this:
curs.execute('Create table employee (name, age)')
This statement will run a SQL command that will create a table named employee with two columns (fields) name and age .
We can now run a new SQL command to insert data into the table as follows:
curs.execute("Insert employee value ('Ali', 28)")
You can also insert multiple values at once, as shown below:
Values = [('Brad',54), ('Ross', 34), ('Muhammad', 28), ('Bilal', 44)]
In this case, instead of using the method executemany(), we will use the method execute() to execute the above multiple values.
curs.executemany('Insert employee value (?,?)', value)
In this step we want to apply (commit) the changes we made in the previous step. It's simple and looks like this:
conn.commit()
After performing the operation and committing the changes, the final step is to close the connection:
conn.close()
Let's put all the steps in a script. The program will look like this (note that we must first import the sqlite3 module):
import sqlite3
conn = sqlite3.connect('company.db')
curs = conn.cursor()
curs.execute('create table employee (name, age)')
curs.execute("insert into employee values ('Ali', 28)")
values = [('Brad',54), ('Ross', 34), ('Muhammad', 28), ('Bilal', 44)]
curs.executemany('insert into employee values(?,?)', values)
conn.commit()
conn.close()
If you run the script, you should get a file named company.db in the current directory. Download this file as we will use it in the next step.
After creating the database and tables and adding some data, let's see what's inside company.db (the file you downloaded in the previous section). For this we will use a great tool: DB Browser for SQLite. Go ahead and download the tool to your computer. After opening the program, you should see a screen like this:
Open the database using the Open Database button at the top, in which case you should get the database structure as shown below:
Please note that we listed the table employee, which contains two fields: name and age.
To confirm that the code above works and that the data has been added to the table, click the Browse Data tab. You should see something similar to the following:
You can see that the database (company) and table (employee) have been created, and data has been successfully added to the table.
Remote Dictionary Server, referred to as Redis, is a powerful NoSQL database that can also act as an in-memory cache. Redis was developed by Salvatore Sanfilippo and is currently maintained by Redis Labs. The software is written in the C programming language and is open source (BSD license).
One of the most notable features of Redis is its data structure storage mechanism. You can store data in Redis using the same data types in Python (strings, sets, integers, lists, dictionaries, etc.). This makes Redis a popular choice among Python developers.
In addition to its data structure storage mechanism, Python developers also prefer Redis over other NoSQL databases because of its large number of Python clients, the most popular choice of which is probably redis-py. Redis-py provides built-in commands for storing various data in a Redis server.
Now that we have a basic understanding of Redis, let's learn how to store data in it. Before proceeding, make sure you have a Redis server installed on your computer.
First, create a new folder called redis-python for your Python script. Next, cd to the folder using Command Terminal and run the following command to install the Redis client:
pip install redis
Then, create a file named app.py in redis-python and open the file with a text editor. The next step is to create a Python script to add data to the database.
First, in app.py, import redis and set the variables of the Redis server host and port address:
import redis redis_host = 'localhost' redis_port = 6379
Next, define the data to be added to the database. In this example we will create a simple Python dictionary:
user = {
'ID': 1,
'name': 'Kingsley Ubah',
'email': 'ubahthebuilder@gmail.com',
'role': 'Tech Writing',
}
Next, define the add_to_db function using try... except. In the try block we connect to the local Redis server and store the above dictionary in the database and then print the values on the console. If the code fails, we print the error object in a except block. The last part will run the function:
def add_to_db():
try:
r = redis.StrictRedis(host = redis_host, port = redis_port, decode_responses=True)
r.hmset("newUserOne", user)
msg = r.hgetall("newUserOne")
print(msg)
except Exception as e:
print(f"Something went wrong {e}")
# Runs the function:
if __name__ == "__main__":
add_to_db()
First, run the Redis server by executing the following command on the command terminal:
redis-cli
Once the server is active, you can run the Python script using the following command:
python app.py
如果一切顺利，包含用户配置文件的字典将使用 newUserOne 键添加到 Redis。此外，您应该在终端控制台上看到以下输出：
{
'ID': '1',
'name': 'Kingsley Ubah',
'email': 'ubahthebuilder@gmail.com',
'role': 'Tech Writing',
}
这就是 Redis 的全部内容！
本教程仅触及使用 Python 处理数据库的皮毛。您可以从 sqlite3 模块了解更多方法，您可以在其中执行不同的数据库操作，例如更新和查询数据库。
要了解有关 redis-py 的更多信息，请立即阅读其完整文档。玩得开心！
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