billboard.py

billboard.py is a Python API for accessing music charts from Billboard.com.

Installation

Install with pip:

pip install billboard.py

Or clone this repo and run python setup.py install.

Quickstart

To download a Billboard chart, we use the ChartData() constructor.

Let's fetch the current Hot 100 chart.

>>> import billboard
>>> chart = billboard.ChartData('hot-100')
>>> chart.title
'The Hot 100'

Now we can look at the chart entries, which are of type ChartEntry and have attributes like artist and title:

>>> song = chart[0]  # Get no. 1 song on chart
>>> song.title
'Nice For What'
>>> song.artist
'Drake'
>>> song.weeks  # Number of weeks on chart
2

We can also print the entire chart:

>>> print(chart)
hot-100 chart from 2018-04-28
-----------------------------
1. 'Nice For What' by Drake
2. 'God's Plan' by Drake
3. 'Meant To Be' by Bebe Rexha & Florida Georgia Line
4. 'Psycho' by Post Malone Featuring Ty Dolla $ign
5. 'The Middle' by Zedd, Maren Morris & Grey
# ...

Guide

What charts exist?

This page shows all charts grouped by category.

Year-end charts are here.

Downloading a chart

Use the ChartData constructor to download a chart:

ChartData(name, date=None, year=None, fetch=True, timeout=25)

The arguments are:

• name – The chart name, e.g. 'hot-100' or 'pop-songs'.
• date – The chart date as a string, in YYYY-MM-DD format. By default, the latest chart is fetched.
• year – The chart year, if requesting a year-end chart. Must be a string in YYYY format. Cannot supply both date and year.
• fetch – A boolean indicating whether to fetch the chart data from Billboard.com immediately (at instantiation time). If False, the chart data can be populated at a later time using the fetchEntries() method.
• max_retries – The max number of times to retry when requesting data (default: 5).
• timeout – The number of seconds to wait for a server response. If None, no timeout is applied.

For example, to download the Alternative Songs year-end chart for 2006:

>>> chart = billboard.ChartData('alternative-songs', year=2006)

Accessing chart entries

If chart is a ChartData instance, we can ask for its entries attribute to get the chart entries (see below) as a list.

For convenience, chart[x] is equivalent to chart.entries[x], and ChartData instances are iterable.

Chart entry attributes

A chart entry (typically a single track) is of type ChartEntry. A ChartEntry instance has the following attributes:

• title – The title of the track.
• artist – The name of the artist, as formatted on Billboard.com.
• image – The URL of the image for the track.
• peakPos – The track's peak position on the chart as of the chart date, as an int (or None if the chart does not include this information).
• lastPos – The track's position on the previous week's chart, as an int (or None if the chart does not include this information). This value is 0 if the track was not on the previous week's chart.
• weeks – The number of weeks the track has been or was on the chart, including future dates (up until the present time).
• rank – The track's current position on the chart.
• isNew – Whether the track is new to the chart.

More resources

For additional documentation, look at the file billboard.py, or use Python's interactive help feature.

Think you found a bug? Create an issue here.

Contributing

Pull requests are welcome! Please adhere to the following style guidelines:

• We use Black for formatting.
  • If you have pre-commit installed, run pre-commit install to install a pre-commit hook that runs Black.
• Variable names should be in mixedCase.

Running tests

To run the test suite locally, install nose and run

nosetests

To run the test suite locally on both Python 2.7 and 3.4, install tox and run

tox

Made with billboard.py

Projects and articles that use billboard.py:

• "What Makes Music Pop?" by Zach Loery
• "How Has Hip Hop Changed Over the Years?" by Rohan Kshirsagar
• "Spotify and billboard.py" by Allen Guo
• chart_success.py by 3ngthrust
• "Top Billboard Streaks" and "Drake's Hot-100 Streak" by James Wenzel @ Polygraph
• "Determining the 'Lifecycle' of Each Music Genre" by Jack Beckwith @ The Data Face
• "Splunking the Billboard Hot 100 with Help from the Spotify API" by Karthik Subramanian
• "Predicting Movement on 70s & 80s Billboard R&B Charts" by Andy Friedman
• "Billboard Trends" by Tom Johnson
• "Billboard Charts Alexa Skill" by Cameron Ezell
• "In the Mix: What's the Secret Formula Behind the Hottest Tracks?" by Jason Kibozi-Yocka
• "MUHSIC: An Open Dataset with Temporal Musical Success Information" by Gabriel P. Oliveira et al.

Have an addition? Make a pull request!

Dependencies

• Beautiful Soup 4
• Requests

License

• This project is licensed under the MIT License.
• The Billboard charts are owned by Prometheus Global Media LLC. See Billboard.com's Terms of Use for more information.