Beauty Advisor - knowing the client!

Matuy Unisex & SPA

• Description:

  We are a company dedicated to the manufacture of perfumes for all genders and ages. Our goal is to collect data from our customers to predict future information about them via machine learning, in addition to knowing them better and understanding who consumes our brand.

• Data Source:

  Random fake data, created and manipulated by us

• Type of analysis:

  Marketing Inbound, Business model, Databases, Dashboards

We have tried to document the project as best as possible, enjoy our Readme...

Startup the project

Create a python3 virtualenv and activate it:

mkdir backend-beautyAdvisor
cd backend-beautyAdvisor
# create new env
pyenv virtualenv beautyAdvisor
# activate new env
pyenv activate beautyAadvisor
# update pip
pip install --upgrade pip

Git |Github Repository:

Create a new repository on the command line

Go to see the project, manage issues, setup you ssh public key, ...

git init 
git add README.md 
git commit -m "first commit" 
git branch -M main 

or Push an existing repository from the command line

git remote add origin https://github.com/USERNAME/REPOSITORYNAME.git
git branch -M main
git push -u origin main

Let's install Docker

The installation is fairly straightforward, In order to use Docker you first need to install it. You can either install Docker on a Desktop machine (both Windows and Mac), or on a server (Linux based installations).

psycopg2 :

Installation:

pip install psycopg2

How to create a Postgres database:

docker run --name matui-db -it -e POSTGRES_PASSWORD=pass123 -p 5432:5432 -d postgres

But what does it do?

Last section of the command grabs the latest 'postgres' Docker image from the Docker Hub

• -d: means that you enable Docker to run the container in the background

• -p: plus the port numbers means you map the containers port 5432 to the external port 5432 - this allows you to connect to it from the outside

• -it: run it interactively

• POSTGRES_PASSWORD: sets the password to docker. This is the password that gives you access to your database

• —name: property gives your container a name and means you can easily find it back

Run docker compose:

docker-compose up --build

Now you can connect to this brand new Postgres database in any tool that allows you to communicate with databases. I tend to use PgAdmin or DBeaver.

You need to use the following connection details to actually connect to the DB:

• Host: localhost
• Port: 5432
• User: postgres
• Password: pass123

Create a python3 virtualenv and activate it:

#create new env
pyenv virtualenv beautyAdvisor
# activate new env
pyenv activate beautyAadvisor
# update pip
pip install --upgrade pip

Clone the project and install it:

git clone [email protected]:{group}/backend-BeautyAdvisor.git
cd backend-BeautyAdvisor
pip install -r requirements.txt

Used Libraries:

fastapi:

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.

Documentation: https://fastapi.tiangolo.com Source Code: https://github.com/tiangolo/fastapi

Installation:

pip install fastapi

Create a FastAPI "instance":

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def root():
    return {"message": "Hello World"}

You will also need an ASGI server, for production, we choose Uvicorn

uvicorn:

Uvicorn is an ASGI web server implementation for Python.

Documentation: https://www.uvicorn.org/ Source Code: https://github.com/encode/uvicorn

Installation:

This will install uvicorn with minimal (pure Python) dependencies.

pip install "uvicorn[standard]"

Now Run it!

Run the live server with:

uvicorn main:app --reload

INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [28720]
INFO:     Started server process [28722]
INFO:     Waiting for application startup.
INFO:     Application startup complete.

The command uvicorn main:app refers to:

• main: the file main.py (the Python "module").
• app: the object created inside of main.py with the line app = FastAPI().
• --reload: make the server restart after code changes. Only do this for development.

In the output, there's a line with something like:

INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)

Check it!!!

Open your browser at http://127.0.0.1:8000.

Interactive API docs...

Now go to http://127.0.0.1:8000/docs.

peewee:

Peewee is a simple and small ORM (Object-Relational mapping). It has few (but expressive) concepts, making it easy to learn and intuitive to use.

Documentation: https://docs.peewee-orm.com/en/latest/index.html

Source Code: https://github.com/coleifer/peewee

• a small, expressive ORM
• python 2.7+ and 3.4+ (developed with 3.6)
• supports sqlite, mysql, postgresql and cockroachdb
• tons of extensions

from peewee import *

db = PostgresqlDatabase('mydatabase', host='localhost', port=5432, user='postgres', password='postgres')
class MyUser (Model):
   name=TextField()
   city=TextField(constraints=[SQL("DEFAULT 'Mumbai'")])
   age=IntegerField()
   class Meta:
      database=db
      db_table='MyUser'

db.connect()
db.create_tables([MyUser])

FastAPIwee : Optional!

Made for FastAPI web framework and PeeWee ORM.

A fast and simple (I hope) way to create REST API based on PeeWee models.

Documentation: https://fastapiwee.qqmber.wtf/

Source Code: https://github.com/Ignisor/FastAPIwee/

Requirements:

• Python 3.6+
• FastAPI
• Peewee

Installation:

pip install FastAPIwee

Define Peewee models in example.py:

import peewee as pw

DB = pw.SqliteDatabase('/tmp/fastapiwee_example.db')


class TestModel(pw.Model):
    id = pw.AutoField()
    text = pw.TextField()
    number = pw.IntegerField(null=True)
    is_test = pw.BooleanField(default=True)

    class Meta:
        database = DB


class AnotherModel(pw.Model):
    id = pw.AutoField()
    text = pw.TextField(default='Cucumber')

    class Meta:
        database = DB