alex gaynor's blago-blog

PyPI Download Statistics

Posted January 3rd, 2014.

For the past few weeks, I've been spending a bunch of time on a side project, which is to get better insight into who uses packages from PyPI. I don't mean what people, I mean what systems: how many users are on Windows, how many still use Python 2.5, do people install with pip or easy_install, questions like these; which come up all the time for open source projects.

Unfortunately until now there's been basically no way to get this data. So I sat down to solve this, and to do that I went straight to the source. PyPI! Downloads of packages are probably our best source of information about users of packages. So I set up a simple system: process log lines from the web server, parse any information I could out of the logs (user agents have tons of great stuff), and then insert it into a simple PostgreSQL database.

We don't yet have the system in production, but I've started playing with sample datasets, here's my current one:

pypi=> select count(*), min(download_time), max(download_time) from downloads;
  count  |         min         |         max
---------+---------------------+---------------------
 1981765 | 2014-01-02 14:46:42 | 2014-01-03 17:40:04
(1 row)

All of the downloads over the course of about 27 hours. There's a few caveats to the data: it only covers PyPI, packages installed with things like apt-get on Ubuntu/Debian aren't counted. Things like CI servers which frequently install the same package can "inflate" the download count, this isn't a way of directly measuring users. As with all data, knowing how to interpret it and ask good questions is at least as important as having the data.

Eventually I'm looking forwards to making this dataset available to the community; both as a way to ask one off queries ("What version of Python do people install my package with?") and as a whole dataset for running large analysis on ("How long does it take after a release before a new version of Django has widespread uptake?").

Here's a sample query:

pypi=> SELECT
pypi->     substring(python_version from 0 for 4),
pypi->     to_char(100 * COUNT(*)::numeric / (SELECT COUNT(*) FROM downloads), 'FM999.990') || '%' as percent_of_total_downloads
pypi-> FROM downloads
pypi-> GROUP BY
pypi->     substring(python_VERSION from 0 for 4)
pypi-> ORDER BY
pypi->     count(*) DESC;
 substring | percent_of_total_downloads
-----------+----------------------------
 2.7       | 75.533%
 2.6       | 15.960%
           | 5.840%
 3.3       | 2.079%
 3.2       | .350%
 2.5       | .115%
 1.1       | .054%
 2.4       | .052%
 3.4       | .016%
 3.1       | .001%
 2.1       | .000%
 2.0       | .000%
(12 rows)

Here's the schema to give you a sense of what data we have:

                                   Table "public.downloads"
          Column          |            Type             |              Modifiers
--------------------------+-----------------------------+-------------------------------------
 id                       | uuid                        | not null default uuid_generate_v4()
 package_name             | text                        | not null
 package_version          | text                        |
 distribution_type        | distribution_type           |
 python_type              | python_type                 |
 python_release           | text                        |
 python_version           | text                        |
 installer_type           | installer_type              |
 installer_version        | text                        |
 operating_system         | text                        |
 operating_system_version | text                        |
 download_time            | timestamp without time zone | not null
 raw_user_agent           | text                        |

Let your imagination run wild with the questions you can answer now that we have data!

This entry was tagged with python.
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