Python-REST-APIs-with-Flask-Docker-MongoDB-and-AWS

Used ubuntu for demo, so summarize some of the common Linux commands here

ls: list files in a directory

cd: change directory

cat: show the content of file, or merge several files

sudo: allows users to run programs with the security privileges of another user, by default the superuser

apt: Advanced Package Tool, handle the installation and removal of software on Debian, Ubuntu, and related Linux distributions

apt install, apt update, apt remove...

mkdir xxx: make a directory called xxx

cp: copy, sudo cp ../app.py . cope app.py into a directory

touch: create or modify a file

How to dockerizing an application:

Code (refer to Dockerizing application demo https://github.com/duozhanggithub/Python-REST-APIs-with-Flask-Docker-MongoDB-and-AWS/tree/master/Dockerizing%20application%20demo)

1. Docker file (with detailed explanations)

#download python 3 from docker hub FROM python:3 #download not only python 3, but also ubuntu operating system

#Tell the image(ubuntu OS with python 3 installed), the working directory is /usr/src/app WORKDIR /usr/src/app

#copy requirements.txt from local machine (the directory include the docker file) #to current working directory /usr/src/app COPY requirements.txt .

#install libraries listed in the requirements.txt on the Ubuntu machine RUN pip install --no-cache-dir -r requirements.txt

#copy all the files from local machine to the ubuntu COPY . .

#run python app.py CMD ["python", "app.py"]

2. Docker compose file:

#wpecify docker compose version version: '3'

#services provided services: #specify the service of web web: #web is a services, you can build this services from the directory ./web #wehre the docker file located, it means in this direc you must have a docker file build: ./web # ports: "5000: 5000"

3. Run the docker compose file:

sudo docker-compose build

sudo docker-compoase up

MongoDB

MongoDB server > Database > Collections > Documents

Database is a physical container for collections where each database gets its own set of files of the file system.

Collection is a group of Mongo documents and it's equivalent of an RDBMS table. Collections do not enforce schema.

Document is a set of key value pairs and the documents have dynamic schema. Very similar to JSON

Relational database has a typical schema design that shows a number of tables and the relationships between these tables while in MongoDB there is no concept of relationship.

Create or switch to the database: use mydb

Write documents into db: db.movie.insert({"name":"xyz"})

Delete database: db.dropDatabase()

Create a collection: db.createColelction(name, options), options is a documents, and optional

Drop collection: db.collection.drop(), db.COLLECTION_NAME.drop()

Insert document into collection: db.COLLECTION_NAME.insert(document)

Query documents: df.COLLECTION_NAME.find().pretty(), the pretty function make the query easy to read

More queries:

We can also use $AND, $OR etc.

Update: db.COLLECTION_NAME.update(SECTION_CRITERIA, UPDATED_DATA), set 'multi' parameter to 'True' if we want to update multiple documents

Deleting documents: db.COLLECTION_NAME.remove(DELETION_CRITERIA)

Projection: selecting only the necessary data rather than selecting the whole data of the document. Need to set a list of fields with value 1 or 0 and this is used to show the fields while 0 is used to hide the field.

Limiting records: db.COLLECTION_NAME.find().limit(NUMBER)

Sorting: db.COLLECTION_NAME.find().sort({KEY: 1}), 1 is ascending

Use MongoDB in web application

Code (https://github.com/duozhanggithub/Python-REST-APIs-with-Flask-Docker-MongoDB-and-AWS/tree/master/MongoDB-Building-a-Simple-Application-to-Keep-Track-of-Number-of-Users)

Links in the dockerfile, connect the web services with db services

pymongo