Tomato Timer with Spotify
Project description
Spomato
Welcome!
This project is intended to be a way to generate playlists through the Spotify API. The main purpose was to create a Tomato Timer length playlist in Spotify (Spotify + Tomato = Spomato).
Installation
You can install via pypi:
pip install spomato
You can pip install it straight from git:
pip install git+git://github.com/pm8k/spomato.git
Spotify Access Token
You need to have a Spotify Access token in order to access the Spotify API. The API scopes used by this library are playlist-read-private, playlist-modify-private, and user-library-read.
You can find the Spotify Authorization flow here and you can find the Spotipy implementation here.
Using Spomato
Create a Spomato object with a Spotify Access Token:
Create a Spomato object providing your token.
from spomato import spomato
sp = spomato.Spomato(access_token='your-token')
Creating a Dataset
The first step is to create one or more datasets to use as a source for your playlist.
Creating a Dataset from Your Saved Tracks
You can use the user's saved tracks as your dataset. This is the default, or you can specify it as below:
sp.get_api_data(data_key='your_dataset_name',
source={'savedtracks':None})
Creating a Dataset from Your Playlist(s)
You can use the user's playlist(s) as your dataset.
sp.get_api_data(data_key='your_dataset_name',
source={'playlist':['playlistid1','playlistid2']})
Creating a Dataset from an Artist
You can use any number of artists to create your dataset.
sp.get_api_data(data_key='your_dataset_name',
source={'artist':['artistid1','artistid2']})
Creating a Dataset from Multiple Sources
You can use any of the above sources to create a dataset.
sp.get_api_data(data_key='your_dataset_name',
source={'artist':['artistid1','artistid2'], 'playlist':['playlistid4', 'savedtracks':None]})
Additional Arguments
There are a few more arguments you can pass to generate a dataset:
- file_path: If you want to save the dataset to file, pass in a path to a file to save a csv of your dataset
- reset: A boolean to determine if you want to overwrite a dataset you've previously created
- market: The Spotify market to filter the songs that can be added to a playlist
Read the Dataset from File
If you saved the file, you can also use that to load it back into a dataset:
sp.get_file_data(data_key='default',
file_path='/my/path/data.csv',
overwrite=False)
Searching Data
You can find an artist or playlist id you're looking for with a couple builtin functions.
playlist_df = sp.get_playlists()
The get_playlists()
function returns all of your playlists by name and id.
artist_search_df = sp.artist_id_search(artist='Foo Fighters')
The artist_id_search
function will search a given string for artists of that name, returning DataFrame of artists and their ids.
You can alternatively go through Spotify and find the corresponding id in the web url when you click on the corresponding playlist or artist.
Creating a Playlist
Get the Song List to Create a playlist
You can use our built in function to select tracks from a dataset to make your playlist.
my_song_df = sp.pick_tracks(data_key='my_dataset', time=25, extra=5)
This example will create a playlist between 25 and 30 minutes. It selects tracks until the total time is greater than
or equal to the time
argument in minutes but not that it exceeds time + extra
(also in minutes). You can
also specify a maximum song length with the time_limit
argument (the default is one-third of time
).
You can also generate you own dataframe using your own logic. You can access a dataset by:
dataset_df = sp['data']['my_dataset']
Create the Playlist
Once you have the dataframe of your songs generated, you can create the playlist.
sp.make_playlist(playlist_name='New_Playlist_Name', song_df=my_song_df)
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