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Install BentoML from source code

Download the source code to local file system:

$ git clone https://github.com/bentoml/BentoML.git
$ cd BentoML

Ensure you have python and pip installed, BentoML supports python 3.6, and 3.7

$ python --version
$ pip --version

And install BentoML with pip in editable mode:

pip install --editable .

This will make bentoml available on your system which links to the sources of your local clone and pick up changes you made locally.

Now you can test your BentoML installation by running the following in terminal:

$ bentoml --version

How to run unit tests

  1. Install all test dependencies:
pip install .[test]

# For zsh users, use:
$ pip install -e .\[test\]
  1. Run all unit tests with current python version and environment
$ pytest tests

Optional: Run unit test with all supported python versions

Make sure you have conda installed:

$ conda --version

Bentoml tox file is configured to run in muiltple python versions:

$ tox

If you want to run tests under conda for specific version, use -e option:

$ tox -e py37
// or
$ tox -e py36

Optional: Run BentoML with verbose/debug logging

Add the following lines to the Python code that invokes BentoML:

import bentoml
import logging
bentoml.config().set('core', 'debug', 'true')
bentoml.utils.log.configure_logging(logging.DEBUG)

And/or use the --verbose option when running bentoml CLI command, e.g.:

bentoml get IrisClassifier --verbose

Installing BentoML from forks/branches

When trying new BentoML feature that has not been released, testing a fork of BentoML on Google Colab or trying out changes in a pull request, an easy way of doing so is to use pip install git+... command, for example to install BentoML from its master branch with all latest changes:

pip install git+https://github.com/bentoml/BentoML.git

Or to install from your own fork of BentoML:

pip install git+https://github.com/{your_github_username}/BentoML.git

You can also specify what branch to install from:

pip install git+https://github.com/{your_github_username}/BentoML.git@{branch_name}

Style check and auto-formatting your code

Make sure to install all dev dependencies:

$ pip install -e .[dev]

# For zsh users, use:
$ pip install -e .\[dev\]

Run linter/format script:

./dev/format.sh

./dev/lint.sh

How to edit, run, build documentation site

Install all dev dependencies:

$ pip install -e .[dev]

To build documentation for locally:

$ ./docs/build.sh

Modify *.rst files inside the docs folder to update content, and to view your changes, run the following command:

$ python -m http.server --directory ./docs/build/html

And go to your browser at http://localhost:8000

If you are developing under macOS, we also made a script that watches docs file changes, automatically rebuild the docs html files, and refresh the browser tab to show the change:

Make sure you have fswatch command installed:

brew install fswatch

Run the watch.sh script to start watching docs changes:

$ ./docs/watch.sh

How to debug YataiService GRPC server

Instll all dev dependenci:

$ pip install -e .[dev]

Install grpcui:

$ go get github.com/fullstorydev/grpcui
$ go install github.com/fullstorydev/grpcui/cmd/grpcui

Start Yatai server in debug mode:

$ bentoml yatai-service-start --debug

In another terminal session run grpcui:

$ grpcui -plain text localhost:50051

gRPC Web UI available at http://127.0.0.1:60551/...

Navigate to the URL from above

How to run and develop BentoML Web UI

Make sure you have yarn installed: https://classic.yarnpkg.com/en/docs/install

Install all npm packages required by BentoML Web UI:

# install npm packages required by BentoML's Node.js Web Server
cd {PROJECT_ROOT}/bentoml/yatai/web/
yarn

# install npm packages required by BentoML web frontend
cd {PROJECT_ROOT}/bentoml/yatai/web/client/
yarn

Build the Web Server and frontend UI code:

cd {PROJECT_ROOT}/bentoml/yatai/web/
npm run build

Creating Pull Request on Github

  1. Fork BentoML project on github and add upstream to local BentoML clone:
$ git remote add upstream [email protected]:YOUR_USER_NAME/BentoML.git

  1. Make the changes either to fix a known issue or adding new feature

  2. Push changes to your fork and follow this article on how to create a pull request on github

  3. Once your pull request created, an automated test run will be triggered on your branch and the BentoML authors will be notified to review your code changes. Once tests are passed and reviewer has signed off, we will merge your pull request.