phylm 3.0.7

Aggregrate useful data about films

PhYlm

Film data aggregation.

Motivation

When deciding which film to watch next, it can be helpful to have some key datapoints at your fingertips, for example, the genre, the cast, the Metacritic score and, perhaps most importantly, the runtime. This package provides a Phylm class to gather information from various sources for a given film.

Installation

pip install phylm

Usage

>>> from phylm import Phylm
>>> p = Phylm('The Matrix', 1999) # the year is optional
>>> p.imdb_score()
8.7
>>> p.genres(2)
['Action', 'Sci-Fi']

Available Datapoints

Methods

name	description	arguments (default)
genres	Return the genres	int(3) The number of genres returned
runtime	Return the runtime
cast	Return the cast	int(5) The number of cast members returned
directors	Return the directors	int(3) The number of directors returned
plot	Return the plot
imdb_title	Return the title from IMDb
imdb_year	Return the release year from IMDb
imdb_score	Return the IMDb score
imdb_low_confidence	Return the IMDb low confidence flag
mtc_title	Return the title from Metacritic
mtc_year	Return the release year from Metacritic
mtc_score	Return the Metacritic score
mtc_low_confidence	Return the Metacritic low confidence flag
rt_title	Return the title from Rotten Tomatoes
rt_year	Return the release year from Rotten Tomatoes
rt_tomato_score	Return the Rotten Tomatoes Tomatometer score
rt_audience_score	Return the Rotten Tomatoes Audience score
rt_low_confidence	Return the Rotten Tomatoes low confidence flag

Properties

name	description
title	Return the given title
year	Return the given year

Low Confidence

If the package can't find an exact match by title in one of the sources (IMDb, Metacritic, Rotten Tomatoes) then the first result from the search results will be used. In these instances the {source}_low_confidence flag will be set to True. Use the {source}_title and {source}_year values to cross reference with the given title to decide whether this is a worthwhile result or not.

Limitations

This package uses web scraping for the Rotten Tomatoes and Metacritic results and is therefore at the mercy of changes made to those webpages. Take the returned values with a healthy pinch of salt.