Jewish Historical Migration

An interface for creating and curating a dataset to study Jewish Historical Migration. See project description.

Usage notes

This application contains a Django backend and an Angular frontend, but currently only the backend is used. The task of the backend is to allow import and editing of the dataset using the default Django admin interface, and to make it accessible to I-Analyzer through a REST API (using django-rest-framework).

The only endpoint of the REST API is /api/records/, which is a read-only viewset that is accessible to any authenticated user. Authentication works via session authentication or via token authentication. To get a token for a given user, run the admin command manage.py token <username>. The user will be created if it does not yet exist.

Importing the dataset from the original Excel dataset happens through an admin command as well: manage.py import_dataset <path>.

Before you start

You need to install the following software:

• PostgreSQL >= 10, client, server and C libraries
• Python >= 3.8, <= 3.11
• virtualenv
• WSGI-compatible webserver (deployment only)
• Visual C++ for Python (Windows only)
• Node.js >= 14.20.0
• Yarn
• WebDriver for at least one browser (only for functional testing)

Setup with Docker

Alternatively, you can run the application via Docker:

1. Install Docker Desktop and start it.
2. Make an .env file next to this README, which defines the configuration for the Postgres database, as well as the directory in which the source (Excel) data is located.

SQL_HOST=db
SQL_PORT=5432
SQL_USER=jewishmigration
SQL_DATABASE=jewishmigration
SQL_PASSWORD=topsecret
DATA_DIR=/location/of/source/data/on/your/machine

3. Run docker-compose up from the directory of this README. This will pull images from the Docker registry and start containers based on these images. This will take a while to set up the first time. To stop, hit ctrl-c, run docker-compose down in another terminal, or use the Docker Desktop dashboard.
4. If you need to reinstall libraries via pip or yarn, use docker-compose up --build.

Note: you can also call the .env file .myenv and specify this during startup: docker-compose --env-file .myenv up

How it works

This project integrates three isolated subprojects, each inside its own subdirectory with its own code, package dependencies and tests:

• backend: the server side web application based on Django and DRF

• frontend: the client side web application based on Angular

• functional-tests: the functional test suite based on Selenium and pytest

Each subproject is configurable from the outside. Integration is achieved using "magic configuration" which is contained inside the root directory together with this README. In this way, the subprojects can stay truly isolated from each other.

If you are reading this README, you'll likely be working with the integrated project as a whole rather than with one of the subprojects in isolation. In this case, this README should be your primary source of information on how to develop or deploy the project. However, we recommend that you also read the "How it works" section in the README of each subproject.

Development

Quickstart

First time after cloning this project:

$ python bootstrap.py

Running the application in development mode (hit ctrl-C to stop):

$ yarn start

This will run the backend and frontend applications, as well as their unittests, and watch all source files for changes. You can visit the frontend on http://localhost:8000/, the browsable backend API on http://localhost:8000/api/ and the backend admin on http://localhost:8000/admin/. On every change, unittests rerun, frontend code rebuilds and open browser tabs refresh automatically (livereload).

Recommended order of development

For each new feature, we suggested that you work through the steps listed below. This could be called a back-to-front or "bottom up" order. Of course, you may have reasons to choose otherwise. For example, if very precise specifications are provided, you could move step 8 to the front for a more test-driven approach.

Steps 1–5 also include updating the unittests. Only functions should be tested, especially critical and nontrivial ones.

1. Backend model changes including migrations.
2. Backend serializer changes and backend admin changes.
3. Backend API endpoint changes.
4. Frontend model changes.
5. Other frontend unit changes (templates, views, routers, FSMs).
6. Frontend integration (globals, event bindings).
7. Run functional tests, repair broken functionality and broken tests.
8. Add functional tests for the new feature.
9. Update technical documentation.

For release branches, we suggest the following checklist.

1. Bump the version number in the package.json next to this README.
2. Run the functional tests in production mode, fix bugs if necessary.
3. Try using the application in production mode, look for problems that may have escaped the tests.
4. Add regression tests (unit or functional) that detect problems from step 3.
5. Work on the code until new regression tests from step 4 pass.
6. Optionally, repeat steps 2–5 with the application running in a real deployment setup (see Deployment).

Commands for common tasks

The package.json next to this README defines several shortcut commands to help streamline development. In total, there are over 30 commands. Most may be regarded as implementation details of other commands, although each command could be used directly. Below, we discuss the commands that are most likely to be useful to you. For full details, consult the package.json.

Install the pinned versions of all package dependencies in all subprojects:

$ yarn

Run backend and frontend in production mode:

$ yarn start-p

Run the functional test suite:

$ yarn test-func [FUNCTIONAL TEST OPTIONS]

The functional test suite by default assumes that you have the application running locally in production mode (i.e., on port 4200). See Configuring the browsers and Configuring the base address in functional-tests/README for options.

Run all tests (mostly useful for continuous integration):

$ yarn test [FUNCTIONAL TEST OPTIONS]

Run an arbitrary command from within the root of a subproject:

$ yarn back  [ARBITRARY BACKEND COMMAND HERE]
$ yarn front [ARBITRARY FRONTEND COMMAND HERE]
$ yarn func  [ARBITRARY FUNCTIONAL TESTS COMMAND HERE]

For example,

$ yarn back less README.md

is equivalent to

$ cd backend
$ less README.md
$ cd ..

Run python manage.py within the backend directory:

$ yarn django [SUBCOMMAND] [OPTIONS]

yarn django is a shorthand for yarn back python manage.py. This command is useful for managing database migrations, among other things.

Manage the frontend package dependencies:

$ yarn fyarn (add|remove|upgrade|...) (PACKAGE ...) [OPTIONS]

Notes on Python package dependencies

Both the backend and the functional test suite are Python-based and package versions are pinned using pip-tools in both subprojects. For ease of development, you most likely want to use the same virtualenv for both and this is also what the bootstrap.py assumes.

This comes with a small catch: the subprojects each have their own separate requirements.txt. If you run pip-sync in one subproject, the dependencies of the other will be uninstalled. In order to avoid this, you run pip install -r requirements.txt instead. The yarn command does this correctly by default.

Another thing to be aware of, is that pip-compile takes the old contents of your requirements.txt into account when building the new version based on your requirements.in. You can use the following trick to keep the requirements in both projects aligned so the versions of common packages don't conflict:

$ yarn back pip-compile
# append contents of backend/requirements.txt to functional-tests/requirements.txt
$ yarn func pip-compile

Development mode vs production mode

The purpose of development mode is to facilitate live development, as the name implies. The purpose of production mode is to simulate deployment conditions as closely as possible, in order to check whether everything still works under such conditions. A complete overview of the differences is given below.

dimension	Development mode	Production mode
command	yarn start	yarn start-p
base address	http://localhost:8000	http://localhost:4200
backend server (Django)	in charge of everything	serves backend only
frontend server (angular-cli)	serves	watch and build
static files	served directly by Django's staticfiles app	collected by Django, served by gulp-connect
backend DEBUG setting	True	False
backend ALLOWED_HOSTS	-	restricted to localhost
frontend sourcemaps	yes	no
frontend optimization	no	yes

Deployment

Both the backend and frontend applications have a section dedicated to deployment in their own READMEs. You should read these sections entirely before proceeding. All instructions in these sections still apply, though it is good to know that you can use the following shorthand commands from the integrated project root:

# collect static files of both backend and frontend, with overridden settings
$ yarn django collectstatic --settings SETTINGS --pythonpath path/to/SETTINGS.py

You should build the frontend before collecting all static files.