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https://github.com/geoadmin/service-stac
STAC API service
https://github.com/geoadmin/service-stac
django docker managed-by-tf postgres
Last synced: 4 days ago
JSON representation
STAC API service
- Host: GitHub
- URL: https://github.com/geoadmin/service-stac
- Owner: geoadmin
- License: other
- Created: 2020-08-13T14:23:45.000Z (over 4 years ago)
- Default Branch: develop
- Last Pushed: 2024-11-11T08:03:18.000Z (5 days ago)
- Last Synced: 2024-11-11T08:28:59.588Z (5 days ago)
- Topics: django, docker, managed-by-tf, postgres
- Language: Python
- Homepage:
- Size: 23.8 MB
- Stars: 12
- Watchers: 18
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# service-stac
| Branch | Status |
|--------|-----------|
| develop | ) |
| master |  |
## Table of Content
- [Table of Content](#table-of-content)
- [Summary of the project](#summary-of-the-project)
- [SPEC](#spec)
- [Local development](#local-development)
- [Dependencies](#dependencies)
- [Python3.12](#python312)
- [pipenv](#pipenv)
- [Using Postgres on local host](#using-postgres-on-local-host)
- [Creating the local environment](#creating-the-local-environment)
- [Setting up the local database](#setting-up-the-local-database)
- [Using a local PostGres database instead of a container](#using-a-local-postgres-database-instead-of-a-container)
- [Starting dev server](#starting-dev-server)
- [Running tests](#running-tests)
- [Unit test logging](#unit-test-logging)
- [Test Conformance](#test-conformance)
- [Linting and formatting your work](#linting-and-formatting-your-work)
- [Using Django shell](#using-django-shell)
- [vs code Integration](#vs-code-integration)
- [Debug from vs code](#debug-from-vs-code)
- [Attach debugger to the tests](#attach-debugger-to-the-tests)
- [Run tests from within vs code](#run-tests-from-within-vs-code)
- [Migrate DB with Django](#migrate-db-with-django)
- [How to generate a db migrations script?](#how-to-generate-a-db-migrations-script)
- [How to put the database to the state of a previous code base?](#how-to-put-the-database-to-the-state-of-a-previous-code-base)
- [How to create a clean PR with a single migration script?](#how-to-create-a-clean-pr-with-a-single-migration-script)
- [How to get a working database when migrations scripts screw up?](#how-to-get-a-working-database-when-migrations-scripts-screw-up)
- [Initial Setup up the RDS database and the user](#initial-setup-up-the-rds-database-and-the-user)
- [Deploying the project and continuous integration](#deploying-the-project-and-continuous-integration)
- [Docker](#docker)
- [Configuration](#configuration)
- [**General settings**](#general-settings)
- [**Database settings**](#database-settings)
- [**Asset Storage settings (AWS S3)**](#asset-storage-settings-aws-s3)
- [**Development settings (only for local environment and DEV staging)**](#development-settings-only-for-local-environment-and-dev-staging)
- [Utility scripts](#utility-scripts)
- ["update\_to\_latest.sh" script](#update_to_latestsh-script)
## Summary of the project
`service-stac` provides and manages access to packaged geospatial data and their metadata. It implements and extends the **STAC API** specification version 0.9.0 [radiantearth/stac-spec/tree/v0.9.0/api-spec](https://github.com/radiantearth/stac-spec/tree/v0.9.0/api-spec). Currently the **STAC API** has been split from the main **STAC SPEC** repository into [radiantearth/stac-api-spec](https://github.com/radiantearth/stac-api-spec), which is under active development until the release 1.0-beta.
## SPEC
See [SPEC](./spec/README.md)
## Local development
### Dependencies
Prerequisites on host for development and build:
- python version 3.12
- libgdal-dev
- [pipenv](https://pipenv-fork.readthedocs.io/en/latest/install.html)
- `docker` and `docker compose`
#### Python3.12
If your Ubuntu distribution is missing Python 3.12, you may use the `deadsnakes` PPA and install it:
```bash
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt-get update
sudo apt-get install python3.12
```
#### pipenv
Generally, all modern distributions have already a [pipenv](https://pipenv-fork.readthedocs.io) package.
However, the version may be dated, which could result in problems during the installation. In this case,
uninstall the version from apt and install it manually like this:
```bash
pip install --user pipenv
```
At the time of writing, version `2022.11.30`, should be working fine.
The other services that are used (Postgres with PostGIS extension for metadata and [MinIO](https://www.min.io) as local S3 replacement) are wrapped in a docker compose.
Starting postgres and MinIO is done with a simple
```bash
docker compose up
```
in the source root folder (this is automatically done if you `make setup`). Make sure to run `make setup` before to ensure the necessary folders `.volumes/*` are in place. These folders are mounted in the services and allow data persistency over restarts of the containers.
### Using Postgres on local host
If you wish to use a local postgres instance rather than the dockerised one, you'll also need the following :
- a local postgres (>= 12.0) running
- postgis extension installed (>= 3.0)
### Creating the local environment
These steps will ensure you have everything needed to start working locally.
- Clone the repo
```bash
git clone [email protected]:geoadmin/service-stac.git
cd service-stac
```
- You can create and adapt your local environment variable in `.env.local`. This files is not under source control and if it doesn't exists during `make setup` it will be created from `.env.default`.
- Install and prepare all the dependencies (pip packages, minio, postgresql, .env.local, ...) by running
```bash
make setup
```
- The command above has generated the following for you
- python virtual environment with all dependencies (inclusive dev dependencies), you can locate the `venv` with `pipenv --venv`
- started a `minio` docker container as S3 storage for the assets
- started a PostGIS DB docker container
- You manually stop/start the minio and PostGIS DB with (see also [Setting up the local database](#setting-up-the-local-database))
```bash
docker compose down
docker compose up
```
- Finally you can do the initial DB setup using django management commands
```bash
# activate the python virtual environment
pipenv shell
# prepare the DB
./app/manage.py migrate
# Populate some test data in the DB
./app/manage.py populate_testdb
# Create a superuser for the admin page
./app/manage.py createsuperuser
```
- Now you are ready to work with a full setup and 2 samples colletions
### Setting up the local database
The service use two other services to run, Postgres with a PostGIS extension and S3.
For local development, we recommend using the services given through the [docker-compose.yml](docker-compose.yml) file, which will
instantiate a Postgres container and a [MinIO](https://www.min.io/) container which act as a local S3 replacement.
If you used the ```make setup``` command during the local environment creation, those two services
should be already be up. You can check with
```bash
docker ps -a
```
which should give you a result like this :
```text
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
a63582388800 minio/mc "/bin/sh -c '\n set …" 39 hours ago Exited (0) 40 seconds ago service-stac_s3-client_1
33deededf690 minio/minio "/usr/bin/docker-ent…" 39 hours ago Up 41 seconds 0.0.0.0:9090->9000/tcp service-stac_s3_1
d158be863ac1 kartoza/postgis:12.0 "/bin/sh -c /docker-…" 39 hours ago Up 41 seconds 0.0.0.0:15432->5432/tcp service-stac_db_1
```
As you can see, MinIO is using two containers, one is the local S3 server, the other is a S3 client used to set the
download policy of the bucket which allows anonymous downloads, and exits once its job is done. You should also have a postGIS container.
`make setup` also creates some necessary directories : `.volumes/minio` and `.volumes/postgresql`, which are mounted to the
corresponding containers in order to allow data persistency.
Another way to start these containers (if, for example, they stopped) is with a simple
```bash
docker compose up
```
### Using a local PostGres database instead of a container
To use a local postgres instance rather than a container, once you've ensured you've the needed dependencies, you should :
- Create a new superuser (required to create/destroy the test-databases) and a new database.
*Note: the user/password and database name in the example below can be changed if required, these names reflects the one in `.env.default`.*
```bash
sudo su - postgres
psql
# create a new user, for simplicity make it a superuser
# this allows the user to automatically create/destroy
# databases (used for testing)
psql> CREATE USER service_stac WITH PASSWORD 'service_stac';
psql> ALTER ROLE service_stac WITH SUPERUSER;
# We need a database with utf8 encoding (for jsonfield) and utf8 needs template0
psql> CREATE DATABASE service_stac_local WITH OWNER service_stac ENCODING 'UTF8' TEMPLATE template0;
```
The PostGIS extension will be installed automatically by Django.
**Note: this is a local development setup and not suitable for production!**
You might have to change your .env.local file especially the DB_PORT, if you're using this setup.
### Starting dev server
```bash
# enable first your virtual environment
pipenv shell
cd app
./manage.py runserver
```
### Running tests
```bash
./manage.py test
```
You can choose to create a new test-db on every run or to keep the db, which speeds testing up:
```bash
./manage.py test --keepdb
```
You can uses `--parallel=20` which also speed up tests.
You can use `--failfast` to stop at the first error.
You can add the test python module to test as well
```bash
./manage.py test tests.test_asset_model
```
Alternatively you can use `make` to run the tests which will run all tests in parallel.
```bash
make test
```
or use the container environment like on the CI.
```bash
docker compose -f docker-compose-ci.yml up --build --abort-on-container-exit
```
**NOTE:** the `--build` option is important otherwise the container will not be rebuild and you don't have the latest modification
of the code.
#### Unit test logging
By default only `WARNING` logs of the `tests` module is printed in the console during unit testing.
All logs are also added to two logs files; `app/tests/logs/unittest-json-logs.json` and `app/tests/logs/unittest-standard-logs.txt`.
Alternatively for a finer logging granularity during unit test, a new logging configuration base on `app/config/logging-cfg-unittest.yml` can be generated and set via `LOGGING_CFG` environment variable or logging can be completely disabled by setting `LOGGING_CFG=0`.
### Test Conformance
Use [stac-api-validator](https://github.com/stac-utils/stac-api-validator) to validate against the [STAC API](https://github.com/radiantearth/stac-api-spec) family of specifications.
```bash
make test-conformance
```
### Linting and formatting your work
In order to have a consistent code style the code should be formatted using `yapf`. Also to avoid syntax errors and non
pythonic idioms code, the project uses the `pylint` linter. Both formatting and linter can be manually run using the
following command:
```bash
make format
```
```bash
make lint
```
**Formatting and linting should be at best integrated inside the IDE, for this look at
[Integrate yapf and pylint into IDE](https://github.com/geoadmin/doc-guidelines/blob/master/PYTHON.md#yapf-and-pylint-ide-integration)**
****
### Using Django shell
Django shell can be use for development purpose (see [Django: Playing with the API](https://docs.djangoproject.com/en/3.1/intro/tutorial02/#playing-with-the-api))
```bash
./manage.py shell
```
Logging is then redireted by default to the log files `logs/management-standard-logs.txt` and `logs/management-json-logs.json`. Only error logs are printed to the console. You can disable totally logging while playing with the shell as follow:
```bash
LOGGING_CFG=0 ./manage.py shell
```
**NOTE:** the environment variable can also be set in the `.venv.local` file.
For local development (or whenever you have a `*-dev` docker image deployed), there's `shell_plus` available (part of the package `django_extensions`), a shell on steroids that automatically pre-imports e.g. all model definitions and makes working with the Django API much easier
```bash
./manage.py shell_plus
```
### vs code Integration
There are some possibilities to debug this codebase from within visual studio code.
#### Debug from vs code
In order to debug the service from within vs code, you need to create a launch-configuration. Create
a folder `.vscode` in the root folder if it doesn't exist and put a file `launch.json` with this content
in it:
```json
{
"version": "0.2.0",
"configurations": [
{
"name": "Python Debugger: Attach",
"type": "debugpy",
"request": "attach",
"justMyCode": false,
"connect": {
"host": "localhost",
"port": 5678
}
}
]
}
```
Now you can start the server with `make serve-debug`. The bootup will wait with the execution until
the debugger is attached, which can most easily done by hitting f5.
#### Attach debugger to the tests
The same process described above can be used to debug tests. Simply run `make test-debug`, they will
then wait until the debugger is attached.
#### Run tests from within vs code
The unit tests can also be invoked inside vs code directly. To do this you need to have following
settings locally to your workspace:
```json
"python.testing.pytestArgs": [
"app"
],
"python.testing.unittestEnabled": false,
"python.testing.pytestEnabled": true,
"python.testing.debugPort": 5678
```
They can either be in `.vscode/settings.json` or in your workspace settings. Now the tests can be
run and debugged with the testing tab of vscode (beaker icon).
## Migrate DB with Django
With the Django shell ist is possible to migrate the state of the database according to the code base. Please consider following principles:
In general, the code base to setup the according state of the database ist stored here:
```bash
stac_api/migrations/
├── 0001_initial.py
├── 0002_auto_20201016_1423.py
├── 0003_auto_20201022_1346.py
├── 0004_auto_20201028.py
```
Please make sure, that per PR only one migrations script gets generated (*if possible*).
### How to generate a db migrations script?
1. First of all this will only happen, when a model has changed
1. Following command will generate a new migration script:
```bash
./manage.py makemigrations
```
### How to put the database to the state of a previous code base?
With the following command of the Django shell a specific state of the database can be achieved:
```bash
.manage.py migrate stac_api 0003_auto_20201022_1346
```
### How to create a clean PR with a single migration script?
Under a clean PR, we mean that only one migration script comes along a PR.
This can be obtained with the following steps (*only if more than one migration script exist for this PR*):
```bash
# 1. migrate back to the state before the PR
./manage.py migrate stac_api 0016_auto_20201022_1346
# 2. remove the migration scripts that have to be put together
cd stac_api/migrations && rm 0017_har.py 0018_toto.py 0019_final.py
./manage.py makemigrations
# 3. add the generated migration script to git
git add stac_api/migrations 0017_the_new_one.py
```
**NOTE:** When going back to a certain migration step, you have to pay attention, that this also involves deleting fields, that have not been added yet.
Which, of course, involves that its content will be purged as well.
### How to get a working database when migrations scripts screw up?
With the following commands it is possible to get a proper state of the database:
```bash
./manage.py reset_db
./manage.py migrate
```
**Warning:** ```reset_db``` a destructive command and will delete all structure and content of the database.
## Initial Setup up the RDS database and the user
Right now the initial setup on the RDS database for the stagings *dev*, *int* and *prod* can be obtained
with the helper script `scripts/setup_rds_db.sh`. The credentials come from `ssm`. To
setup the RDS database on int, run following command (the PROFILE variable denotes in what account the
parameters are stored):
```bash
summon -p `ssm` -D APP_ENV=int -D PROFILE=swisstopo-bgdi-dev scripts/setup_rds_db.sh
```
**Note:** The script won't delete the existing database.
## Deploying the project and continuous integration
When creating a PR, terraform should run a codebuild job to test and build automatically your PR as a tagged container. This container will only be pushed to dockerhub when the PR is accepted and merged.
This service is to be deployed to the Kubernetes cluster once it is merged.
## Docker
The service is encapsulated in a Docker image. Images are pushed on the AWS elastic container registry (ECR).
From each github PR that is merged into develop branch, two Docker images are built and pushed with the following tags:
- develop.latest (prod image)
- develop.latest-dev (dev image)
From each github PR that are merged into master, one Docker image is built an pushed with the following tag:
- master.GIT_HASH
Each images contains the following metadata:
- author
- target
- git.branch
- git.hash
- git.dirty
- version
These metadata can be seen directly on the dockerhub registry in the image layers or can be read with the following command
```bash
# NOTE: jq is only used for pretty printing the json output,
# you can install it with `apt install jq` or simply enter the command without it
docker image inspect --format='{{json .Config.Labels}}' swisstopo/service-stac:develop.latest-dev | jq
```
You can also check these metadata on a running container as follow
```bash
docker ps --format="table {{.ID}}\t{{.Image}}\t{{.Labels}}"d
```
### Configuration
The service is configured by Environment Variable:
#### **General settings**
| Env | Default | Description |
|-------------|-----------------------|----------------------------------------|
| LOGGING_CFG | `'app/config/logging-cfg-local.yml'` | Logging configuration file or '0' to disable logging |
| LOGS_DIR | `''` | Relative path to log directory to use if logging is configured to logs into files. NOTE: the default value for local development is `logs`. :warning: This should only be used for local development. |
| SECRET_KEY | - | Secret key for django |
| ALLOWED_HOSTS | `''` | See django ALLOWED_HOSTS. On local development and DEV staging this is overwritten with `'*'` |
| THIS_POD_IP | No default | The IP of the POD the service is running on |
| HTTP_CACHE_SECONDS | `600` | Sets the `Cache-Control: max-age` and `Expires` headers of the GET and HEAD requests to the api views. |
| HTTP_STATIC_CACHE_SECONDS | `3600` | Sets the `Cache-Control: max-age` header of GET, HEAD requests to the static files. |
| STORAGE_ASSETS_CACHE_SECONDS | `7200` | Sets the `Cache-Control: max-age` and `Expires` headers of the GET and HEAD on the assets file uploaded via admin page. |
| DJANGO_STATIC_HOST | `''` | See [Whitenoise use CDN](http://whitenoise.evans.io/en/stable/django.html#use-a-content-delivery-network). |
| PAGE_SIZE | `100` | Default page size |
| PAGE_SIZE_LIMIT | `100` | Maximum page size allowed |
| STAC_BROWSER_HOST | `None` | STAC Browser host (including HTTP schema). When `None` it takes the same host as the STAC API. |
| STAC_BROWSER_BASE_PATH | `browser/index.html` | STAC Browser base path. |
| GUNICORN_WORKERS | `2` | Number of Gunicorn workers |
| GUNICORN_WORKER_TMP_DIR | `None` | Path to a tmpfs directory for Gunicorn. If `None` let gunicorn decide which path to use. See https://docs.gunicorn.org/en/stable/settings.html#worker-tmp-dir. |
#### **Database settings**
| Env | Default | Description |
|-------------|-----------------------|----------------------------------------|
| DB_NAME | service_stac | Database name |
| DB_USER | service_stac | Database user (used by django for DB connection) |
| DB_PW | service_stac | Database password (used by django for DB connection) |
| DB_HOST | service_stac | Database host |
| DB_PORT | 5432 | Database port |
| DB_NAME_TEST | test_service_stac | Database name used for unittest |
#### **Asset Storage settings (AWS S3)**
| Env | Default | Description |
|-------------|-----------------------|----------------------------------------|
| LEGACY_AWS_ACCESS_KEY_ID | - | |
| LEGACY_AWS_SECRET_ACCESS_KEY | - | |
| LEGACY_AWS_S3_BUCKET_NAME | - | The name of the legacy bucket |
| LEGACY_AWS_S3_REGION_NAME | `"eu-west-1"` | |
| LEGACY_AWS_S3_ENDPOINT_URL | `None` | |
| LEGACY_AWS_S3_CUSTOM_DOMAIN | `None` | |
| AWS_S3_BUCKET_NAME | - | The name of the managed bucket |
| AWS_S3_REGION_NAME | `"eu-central-1"` | The region of the managed bucket |
| AWS_S3_ENDPOINT_URL | `None` | |
| AWS_S3_CUSTOM_DOMAIN | `None` | |
| AWS_PRESIGNED_URL_EXPIRES | 3600 | AWS presigned url for asset upload expire time in seconds |
| MANAGED_BUCKET_COLLECTION_PATTERNS | - | A list of regex patterns for collections that go to the managed bucket |
| EXTERNAL_URL_REACHABLE_TIMEOUT | `5` | How long the external asset URL validator should try to connect to given asset in seconds |
#### **Development settings (only for local environment and DEV staging)**
These settings are read from `settings_dev.py`
| Env | Default | Description |
|-------------|-----------------------|----------------------------------------|
| DEBUG | `False` | Set django DEBUG flag |
| DEBUG_PROPAGATE_API_EXCEPTIONS | `False` | When `True` the API exception are treated as in production, using a JSON response. Otherwise in DEBUG mode the API exception returns an HTML response with backtrace. |
| EXTERNAL_TEST_ASSET_URL | `"https://prod-[...].jpg"` | The URL of an externally hosted jpg file that's used in the external asset tests |
## Utility scripts
The folder `scripts` contains several utility scripts that can be used for setting up local DBs,
filling it with random data and the like and also for uploading files via the API.
## "update_to_latest.sh" script
In the main directory, there is a script named "update_to_latest.sh" which can be used to
automatically update the version strings of the dependencies in the Pipfile. See the comment at
the top of the script to learn how to use it.