ecoutils - Ecosystem analytics

As a programming ecosystem grows, so do the chances of runtime variability.

Python boasts one of the widest deployments for a high-level programming environment, making it a viable target for all manner of application. But with breadth comes variance, so it’s important to know what you’re working with.

Some basic variations that are common among development machines:

  • Executable runtime: CPython, PyPy, Jython, etc., plus build date and compiler
  • Language version: 2.4, 2.5, 2.6, 2.7... 3.4, 3.5, 3.6
  • Host operating system: Windows, OS X, Ubuntu, Debian, CentOS, RHEL, etc.
  • Features: 64-bit, IPv6, Unicode character support (UCS-2/UCS-4)
  • Built-in library support: OpenSSL, threading, SQLite, zlib
  • User environment: umask, ulimit, working directory path
  • Machine info: CPU count, hostname, filesystem encoding

See the full example profile below for more.

ecoutils was created to quantify that variability. ecoutils quickly produces an information-dense description of critical runtime factors, with minimal side effects. In short, ecoutils is like browser and user agent analytics, but for Python environments.

Transmission and collection

The data is all JSON serializable, and is suitable for sending to a central analytics server. An HTTP-backed service for this can be found at:

Notable omissions

Due to space constraints (and possibly latency constraints), the following information is deemed not dense enough, and thus omitted:


So far ecoutils has has been tested on Python 2.4, 2.5, 2.6, 2.7, 3.4, 3.5, and PyPy. Various versions have been tested on Ubuntu, Debian, RHEL, OS X, FreeBSD, and Windows 7.


Boltons typically only support back to Python 2.6, but due to its nature, ecoutils extends backwards compatibility to Python 2.4 and 2.5.

Profile generation

Profiles are generated by ecoutils.get_profile().

When run as a module, ecoutils will call get_profile() and print a profile in JSON format:

$ python -m boltons.ecoutils
  "_eco_version": "1.0.0",
  "cpu_count": 4,
  "cwd": "/home/mahmoud/projects/boltons",
  "fs_encoding": "UTF-8",
  "guid": "6b139e7bbf5ad4ed8d4063bf6235b4d2",
  "hostfqdn": "mahmoud-host",
  "hostname": "mahmoud-host",
  "linux_dist_name": "Ubuntu",
  "linux_dist_version": "14.04",
  "python": {
    "argv": "boltons/",
    "bin": "/usr/bin/python",
    "build_date": "Jun 22 2015 17:58:13",
    "compiler": "GCC 4.8.2",
    "features": {
      "64bit": true,
      "expat": "expat_2.1.0",
      "ipv6": true,
      "openssl": "OpenSSL 1.0.1f 6 Jan 2014",
      "readline": true,
      "sqlite": "3.8.2",
      "threading": true,
      "tkinter": "8.6",
      "unicode_wide": true,
      "zlib": "1.2.8"
    "version": "2.7.6 (default, Jun 22 2015, 17:58:13) [GCC 4.8.2]",
    "version_info": [
  "time_utc": "2016-05-24 07:59:40.473140",
  "time_utc_offset": -8.0,
  "ulimit_hard": 4096,
  "ulimit_soft": 1024,
  "umask": "002",
  "uname": {
    "machine": "x86_64",
    "node": "mahmoud-host",
    "processor": "x86_64",
    "release": "3.13.0-85-generic",
    "system": "Linux",
    "version": "#129-Ubuntu SMP Thu Mar 17 20:50:15 UTC 2016"
  "username": "mahmoud"

pip install boltons and try it yourself!


The main entrypoint to ecoutils. Calling this will return a JSON-serializable dictionary of information about the current process.

It is very unlikely that the information returned will change during the lifetime of the process, and in most cases the majority of the information stays the same between runs as well.

get_profile() takes one optional keyword argument, scrub, a bool that, if True, blanks out identifiable information. This includes current working directory, hostname, Python executable path, command-line arguments, and username. Values are replaced with ‘-‘, but for compatibility keys remain in place.