paulonteri

paulonteri

paulonteri

git clone https://github.com/fastai/fastai

cd fastai

conda create -n fastai python=3.6 anaconda

conda env update

# bash include source 
# windows no source

paulonteri

from django.db import models


class Note(models.Model):
    title = models.CharField(max_length=20)
    description = models.CharField(max_length=255)
    note = models.TextField()  # Actual note

paulonteri

from rest_framework import serializers
from .models import Note


class NoteSerializer(serializers.ModelSerializer):
    class Meta:
        model = Note
        fields = ['id', 'title', 'description', 'note']

paulonteri

from rest_framework import status # provides identifiers for each status code
from rest_framework.response import Response # determines the correct content type to return
from rest_framework.views import APIView

from .models import Note
from .serializers import NoteSerializer


class NoteApi(APIView):
    # list or add Note instances

paulonteri

from django.contrib import admin
from django.urls import path, include

urlpatterns = [
    path('admin/', admin.site.urls),
    path('', include('myapiapp.urls')),
]

paulonteri

from django.urls import path
from .views import NoteApi

urlpatterns = [
    path('api/notes', NoteApi.as_view()),
]

paulonteri

# this Dockerfile starts with a Python 3.6 parent image
FROM python:3.6

# this means that Docker won’t buffer the output from your application; 
# instead, you will see your output in your console
ENV PYTHONUNBUFFERED 1 # environment variable

# create a directory for our project in the container
RUN mkdir /code
# Set the working directory to /code

paulonteri

# REACT PROJECT SETUP
# this Dockerfile starts with a Node 12.2.0 parent image
FROM node:12.2.0 AS build

# Set the working directory to /code
WORKDIR /code
# Copies package.json and package-lock.json to Docker environment
COPY package*.json ./
COPY yarn.lock ./
COPY . .