Any resemblance to real persons or names is purely coincidental.
Simple REST API - a basic movie database interacting with external API.
There are 3 endpoints:
/movies- to search for details about particular movie or get list of all movies present in application database,/comments- to add comments for movies already present in application database,/top- to get ranking of movies in application database based on number of comments.
Details about movies are retrieved from OMDb - The Open Movie Database. Application tries to limit queries to external API by saving made queries that point to given movie so consecutive requests with the same title use data already stored in application database.
Details about application's possibilities are documented in Endpoints section.
Why? Well, let's take a look at Django's main page:
Django makes it easier to build better Web apps more quickly and with less code.
and
The web framework for perfectionists with deadlines.
Django makes it easy to implement and control web app without much boilerplate. With it's ORM defining domain objects and controlling them is straightforward and butter-smooth.
If Django and REST API, then DRF is a given. It build on top of Django for even better and more robust approach for creating web apps implementing REST API.
The World's Most Advanced Open Source Relational Database
Battle tested database system with performance and robustness in mind. It scales well and works perfectly with Django.
'Strange, it works on my machine.' killer. Makes deployment easy and platform independent. Ideal for work on web apps which can have parts of the system running on different servers. Allows isolation of assets and portability of code.
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries.
Unit testing in python was never easier. Ties in with django nicely by
pytest-django with mocking sponsored by pytest-mock which enables easy use
of mock library in pytest context.
You have to create docker/env/dev.env file in existing docker/ directory.
File should have following environmental variables defined:
POSTGRES_HOST=postgres_dev
POSTGRES_DB=<postgres_db_name>
POSTGRES_USER=<postgres_user>
POSTGRES_PASSWORD=<postgres_password>
ALLOW_IP_RANGE=0.0.0.0/0
DJANGO_SECRET=<your_secret_value>
OMDB_KEY=<your_omdb_api_key>
Specific values are left to you. POSTGRES_HOST value can be changed but it
has to match docker container with PostgreSQL. (If you have no idea about
docker leave it as it is). You can get free OMDB API key at
www.omdbapi.com that allows 1,000
requests per day.
Provided Docker images and scripts allow easy start with:
$ ./docker/run-manage.sh createsuperuser
$ ./docker/run-manage.sh makemigrations
$ ./docker/run-manage.sh migrate
$ ./docker/run-server.shTo access bash use:
$ ./docker/run-bash.shTo run tests:
$ ./docker/run-pytest.shBased on passed title, movie details are fetched from
www.omdbapi.com and saved to application database.
Title does not have to be exact, it is case insensitive. OMDB API returns best
match. Queried title is saved in database in Movie.tags for later retrieval
of similar queries without calling external OMDB API.
Request body has to contain movie title as JSON, example:
{
"title": "Scott Pilgrim"
}Returned when movie details were fetched correctly and saved in database.
Response includes movie object as JSON with id, tags and with all data
fetched from external API as details.
{
"id": 7,
"tags": [
"scott pilgrim"
],
"details": {
"title": "Scott Pilgrim vs. the World",
"year": "2010",
"rated": "PG-13",
"released": "13 Aug 2010",
"runtime": "112 min",
"genre": "Action, Comedy, Fantasy, Romance",
"director": "Edgar Wright",
"writer": "Michael Bacall (screenplay), Edgar Wright (screenplay), Bryan Lee O'Malley (Oni Press graphic novels)",
"actors": "Michael Cera, Kieran Culkin, Anna Kendrick, Alison Pill",
"plot": "Scott Pilgrim must defeat his new girlfriend's seven evil exes in order to win her heart.",
"language": "English",
"country": "USA, UK, Canada, Japan",
"awards": "17 wins & 62 nominations.",
"poster": "https://m.media-amazon.com/images/M/MV5BMTkwNTczNTMyOF5BMl5BanBnXkFtZTcwNzUxOTUyMw@@._V1_SX300.jpg",
"ratings": [
{
"source": "Internet Movie Database",
"value": "7.5/10"
},
{
"source": "Rotten Tomatoes",
"value": "81%"
},
{
"source": "Metacritic",
"value": "69/100"
}
],
"metascore": "69",
"imdb_rating": "7.5",
"imdb_votes": "334,787",
"imdb_id": "tt0446029",
"type": "movie",
"dvd": "09 Nov 2010",
"box_office": "$31,494,270",
"production": "Universal Pictures",
"website": "http://www.scottpilgrimthemovie.com",
"response": "True"
}
}Returned if movie matching query already exists in database. Response includes
the same data as for HTTP 201 Created response.
Returned when there is no title value in request body or when it's value is
empty.
{
"detail": "title required in request body"
}Returned when OMDB API did not return any movie for given title.
{
"detail": "no movie matching 'whatever some long meaningless title' found"
}Fetches list of all movies already present in application database. Allows filtering with query parameters by:
tags: string,released: date (YYYY-MM-DD format),country: string,metascore: int (0-100),imdb_rating: float (0.0-10.0).
Allows adding comments to movies. Request has to contain ID of movie already present in database, and comment text body.
Request has to contain movie_id and text as JSON:
{
"text": "That was very pleasant screening, 10/10 would recommend.",
"movie_id": 1
}Returned when movie for given ID was found and comment was saved. Response
contains comment object with movie_id, text and creation date as created.
{
"text": "That was very pleasant screening, 10/10 would recommend.",
"created": "2019-04-12",
"movie_id": 1
}Returned when no movie with given ID exists in database:
{
"movie_id": [
"Invalid pk \"21435264\" - object does not exist."
]
}or when request body does not contain one or both of required values:
{
"text": [
"This field is required."
],
"movie_id": [
"This field is required."
]
}Fetches list of all comments present in application database. Allows filtering with query parameters by:
movie_id: int,created: date (YYYY-MM-DD format)
Returns ranking of movies present in the database based on a number of comments added to the movies in the specified date range. Movies with the same number of comments have the same rank. Movies without comments are also included with last rank.
Request requires date range query parameters:
from_date: date (YYYY-MM-DD format),to_date: date (YYYY-MM-DD format).
Response includes
movie_id, total_comments count and rank.
Example response:
[
{
"movie_id": 1,
"total_comments": 4,
"rank": 1
},
{
"movie_id": 4,
"total_comments": 2,
"rank": 2
},
{
"movie_id": 2,
"total_comments": 2,
"rank": 2
},
{
"movie_id": 6,
"total_comments": 0,
"rank": 3
},
{
"movie_id": 3,
"total_comments": 0,
"rank": 3
}
]