Data analysis

Document here the project: mlproject
Description: Project Description
Data Source:
Type of analysis:

Please document the project the better you can.

Stratup the project

The initial setup.

Create virtualenv and install the project:

  $ sudo apt-get install virtualenv python-pip python-dev
  $ deactivate; virtualenv ~/venv ; source ~/venv/bin/activate ;\
    pip install pip -U; pip install -r requirements.txt

Unittest test:

  $ make clean install test

Check for mlproject in gitlab.com/{group}. If your project is not set please add it:

Create a new project on gitlab.com/{group}/mlproject
Then populate it:

  $ ##   e.g. if group is "{group}" and project_name is "mlproject"
  $ git remote add origin git@gitlab.com:{group}/mlproject.git
  $ git push -u origin master
  $ git push -u origin --tags

Functionnal test with a script:

  $ cd /tmp
  $ mlproject-run

Install

Go to gitlab.com/{group}/mlproject to see the project, manage issues, setup you ssh public key, ...

Create a python3 virtualenv and activate it:

  $ sudo apt-get install virtualenv python-pip python-dev
  $ deactivate; virtualenv -ppython3 ~/venv ; source ~/venv/bin/activate

Clone the project and install it:

  $ git clone gitlab.com/{group}/mlproject
  $ cd mlproject
  $ pip install -r requirements.txt
  $ make clean install test                # install and test

Functionnal test with a script:

  $ cd /tmp
  $ mlproject-run

Continus integration

Github

Every push of master branch will execute .github/workflows/pythonpackages.yml docker jobs.

Gitlab

Every push of master branch will execute .gitlab-ci.yml docker jobs.

georgesms / mlproject