chore: change default postgres version to 17 in deployment template

The Docker container image for Postgres 18 made a breaking change:
docker-library/postgres#1259. As a short-term fix, we change the default
Postgres version to 17. In the longer term, logic will need to be added to the template to support
Postgres images
>=18 and <18.

Author: jkglasbrenner

cookiecutter-templates/cookiecutter-dioptra-deployment/cookiecutter.json

@@ -8,7 +8,7 @@
     "systemd_required_mounts": "",
     "nginx_server_name": "dioptra.example.org",
     "nginx_expose_ports_on_localhost_only": ["True", "False"],
-    "postgres_container_tag": "18",
+    "postgres_container_tag": "17",
     "__restapi_http_port": "80",
     "__restapi_https_port": "443",
     "__db_admin_username": "postgres",

docs/source/how-to/setup-dioptra/reference/deployment-template-reference.rst

@@ -213,7 +213,7 @@ Press Enter to accept the default, or type a new value.
    1 - True
    2 - False
    Choose from 1, 2 [1]: 1
-   postgres_container_tag [18]: 18
+   postgres_container_tag [17]: 17
    pgadmin_default_email [dioptra@example.com]: dioptra@example.com
    num_tensorflow_cpu_workers [1]: 1
    num_tensorflow_gpu_workers [0]: 0

tests/cookiecutter_dioptra_deployment/conftest.py

@@ -29,7 +29,7 @@ def context():
         "systemd_required_mounts": "",
         "nginx_server_name": "dioptra.example.org",
         "nginx_expose_ports_on_localhost_only": "True",
-        "postgres_container_tag": "18",
+        "postgres_container_tag": "17",
         "__restapi_http_port": "80",
         "__restapi_https_port": "443",
         "__db_admin_username": "postgres",

tests/cookiecutter_dioptra_deployment/test_cruft_no_prompt.py

@@ -35,7 +35,7 @@
     "docker_compose_path": "docker compose",
     "nginx_server_name": "dioptra.example.org",
     "nginx_expose_ports_on_localhost_only": "True",
-    "postgres_container_tag": "18",
+    "postgres_container_tag": "17",
     "pgadmin_default_email": "dioptra@example.com",
     "num_tensorflow_cpu_workers": "1",
     "num_tensorflow_gpu_workers": "0",