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dcyd model performance monitoring client

Project description

MPM Model Performance Monitoring client


$ pip3 install dcyd
$ export DCYD_CONFIG_FILE=/some/path/dcyd-key.json


Barebones decorator of your predict function:

from dcyd.mpm import mpm

def my_predict_function(some args, some kwargs):

    return some response

Decorate your predict function, but include some metadata (e.g. customer_id, experiment_group, model_version) for helpful tracking:

from dcyd.mpm import mpm

@mpm(optional kwargs for tracking/filtering)
def my_other_predict_function(some args, some kwargs):

    return some response

Decorate a method as well:

from dcyd.mpm import mpm

class MyModel(object):

  @mpm(optional kwargs for tracking/filtering)
  def my_predict_method(self, *args, **kwargs):
    return some response


  1. Clone the repo locally, and switch to a branch other than master.
  2. Create and activate a virtual environment:
$ python3 -m venv my_env_name
  1. From the directory containing
$ pip3 install .


$ pip3 install -e .

(These are in place of python3 install and python3 develop, for reasons explained here.

Distributing the package in PyPI

This process comes from this turorial.

  1. Increment the version in, using these rules (or newer).
  2. Install/update some modules:
$ pip3 install --user --upgrade setuptools wheel twine
  1. From the directory containing (and not in a virtual environment), create the wheel:
$ python3 sdist bdist_wheel
  1. Upload the wheel to PyPI:
$ python3 -m twine upload dist/*

Project details

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