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INSTALL.rst

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Installation

First, create a virtualenv using virtualenvwrapper in order to sandbox our Python environment for development:

$ mkvirtualenv my-site

Start all dependent services using docker-compose (this will start PostgreSQL, Elasticsearch 6, RabbitMQ and Redis):

$ docker-compose up -d

Note

Make sure you have enough virtual memory for Elasticsearch in Docker:

# Linux
$ sysctl -w vm.max_map_count=262144

# macOS
$ screen ~/Library/Containers/com.docker.docker/Data/com.docker.driver.amd64-linux/tty
<enter>
linut00001:~# sysctl -w vm.max_map_count=262144

Next, bootstrap the instance (this will install all Python dependencies and build all static assets):

$ ./scripts/bootstrap

Next, create database tables, search indexes and message queues:

$ ./scripts/setup

Running

Start the webserver:

$ ./scripts/server

Start the a background worker:

$ celery -A invenio_app.celery worker -l INFO

Start a Python shell:

$ ./scripts/console

Upgrading

In order to upgrade an existing instance simply run:

$ ./scripts/update

Testing

Run the test suite via the provided script:

$ ./scripts/test

By default, end-to-end tests are skipped. You can include the E2E tests like this:

$ env E2E=yes ./scripts/test

For more information about end-to-end testing see pytest-invenio

Documentation

You can build the documentation with:

$ python setup.py build_sphinx

Production environment

You can use simulate a full production environment using the docker-compose.full.yml. You can start it like this:

$ docker-compose -f docker-compose.full.yml up -d

In addition to the normal docker-compose.yml, this one will start:

  • HAProxy (load balancer)
  • Nginx (web frontend)
  • UWSGI (application container)
  • Celery (background task worker)
  • Flower (Celery monitoring)