Merge pull request #166 from raphaelrpl/latest

📚 Improve documentation deploy and add compatibility table

CHANGES.rst

@@ -11,7 +11,7 @@ Changes
 =======
 
 
-Version 1.0.0a1 (2022-09-06)
+Version 1.0.0a1 (2022-09-12)
 ----------------------------
 
 - Implementation of STAC v1.0-rc.1 with the following extensions:

DEPLOY.rst

@@ -19,10 +19,17 @@ Requirements
 
 
 Besides Docker, you will need an instance of a PostgreSQL DBMS with a database prepared using `Brazil Data Cube Catalog Module <https://github.com/brazil-data-cube/bdc-catalog>`_.
-Before prepare database instance, just take a look in support mapping of BDC-STAC:
+Before prepare database instance, just take a look in support compatibility table:
 
-- STAC ``v0.9.0``  -> ``BDC-Catalog 0.8.x``
-- STAC ``v1.0.0+`` -> ``BDC-Catalog 1.0+``
++---------------------------+-----------+-------------+
+| STAC API Spec             | BDC-STAC  | BDC-Catalog |
++===========================+===========+=============+
+| 0.8.x                     | 0.8.x     | 0.4.x       |
++---------------------------+-----------+-------------+
+| 0.9.0        - 1.0.0-rc.1 | 0.9.x     | 0.8.x       |
++---------------------------+-----------+-------------+
+| 1.0.0-beta.1 - 1.0.0-rc.1 | 1.0.x     | 1.0.x       |
++---------------------------+-----------+-------------+
 
 
 Building the Docker Image
@@ -188,6 +195,11 @@ The output should be a JSON document similar to:
     }
 
 
+.. note::
+
+    Be aware that collections ``S2_L1C-1``, ``MYD13Q1-6`` and ``MOD13Q1-6`` described above are examples.
+    You should create a definition of Collection following `BDC-Catalog <https://github.com/brazil-data-cube/bdc-catalog>`_ module.
+
 .. rubric:: Footnotes
 
 .. [#f1] See the `Brazil Data Cube Catalog Module <https://github.com/brazil-data-cube/bdc-catalog>`_.

INSTALL.rst

@@ -1,6 +1,6 @@
 ..
     This file is part of Brazil Data Cube STAC Service.
-    Copyright (C) 2019-2020 INPE.
+    Copyright (C) 2019-2022 INPE.
 
     Brazil Data Cube STAC Service is free software; you can redistribute it and/or modify it
     under the terms of the MIT License; see LICENSE file for more details.
@@ -29,6 +29,22 @@ The Brazil Data Cube STAC implementation depends essentially on:
 - `Flask-Redoc <https://pypi.org/project/flask-redoc/>`_: a Flask extension for displaying OpenAPI/Swagger documentation using Redocs.
 
 
+STAC Versions
++++++++++++++
+
+Before installing the ``BDC-STAC`` server, please, take a look into compatibility table:
+
++---------------------------+-----------+-------------+
+| STAC API Spec             | BDC-STAC  | BDC-Catalog |
++===========================+===========+=============+
+| 0.8.x                     | 0.8.x     | 0.4.x       |
++---------------------------+-----------+-------------+
+| 0.9.0        - 1.0.0-rc.1 | 0.9.x     | 0.8.x       |
++---------------------------+-----------+-------------+
+| 1.0.0-beta.1 - 1.0.0-rc.1 | 1.0.x     | 1.0.x       |
++---------------------------+-----------+-------------+
+
+
 Clone the software repository
 +++++++++++++++++++++++++++++
 

bdc_stac/controller.py

@@ -11,7 +11,7 @@
 import warnings
 from datetime import datetime as dt
 from functools import lru_cache
-from typing import Optional
+from typing import List, Optional
 
 import shapely.geometry
 from bdc_catalog.models import (
@@ -264,27 +264,22 @@ def get_collection_crs(collection: Collection) -> str:
     return collection.grs.crs if collection.grs is not None else None
 
 
-def get_collection_timeline(collection_id):
-    """Retrieve a list of dates for a given collection.
+def format_timeline(timeline: Optional[List[Timeline]] = None):
+    """Format the collection timeline values with Dateformat
 
-    :param collection_id: collection identifier
-    :type collection_id: str
+    :param timeline: The collection timeline instance
+    :type timeline: Optional[List[Timeline]]
     :return: list of dates for the collection
     :rtype: list
     """
-    timeline = (
-        session.query(Timeline.time_inst)
-        .filter(Timeline.collection_id == collection_id)
-        .order_by(Timeline.time_inst.asc())
-        .all()
-    )
-
+    if timeline is None:
+        return []
     return [dt.fromisoformat(str(t.time_inst)).strftime("%Y-%m-%d") for t in timeline]
 
 
 @lru_cache()
 def get_collection_quicklook(collection_id):
-    """Retrieve a list of bands used to create the quicklooks for a given collection.
+    """Retrieve a list of bands used to create the quicklook for a given collection.
 
     :param collection_id: collection identifier
     :type collection_id: str
@@ -425,7 +420,7 @@ def get_collections(collection_id=None, roles=None, assets_kwargs=None):
             datacube = {
                 "x": dict(type="spatial", axis="x", extent=[bbox[0], bbox[2]], reference_system=proj4text),
                 "y": dict(type="spatial", axis="y", extent=[bbox[1], bbox[3]], reference_system=proj4text),
-                "temporal": dict(type="temporal", extent=[start, end], values=get_collection_timeline(r.Collection.id)),
+                "temporal": dict(type="temporal", extent=[start, end], values=format_timeline(r.Collection.timeline)),
             }
             if category == "eo":
                 datacube["bands"] = dict(type="bands", values=[band["name"] for band in collection_eo["eo:bands"]])