Initial commit of all files

LICENSE

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+BSD 3-Clause License
+
+Copyright (c) 2023-2024, Centre of Environmental Data Analysis Developers,
+Scientific and Technical Facilities Council (STFC),
+UK Research and Innovation (UKRI).
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without 
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this 
+list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice, this 
+list of conditions and the following disclaimer in the documentation and/or other 
+materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its contributors 
+may be used to endorse or promote products derived from this software without 
+specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS”
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE 
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL 
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR 
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

README.md

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+# DataPoint package
+
+A package to be installed into Jaspy that enables the use of CEDA search and cloud data services:
+ - Search the CEDA STAC catalog for relevant data.
+ - Port the data into an Xarray object from multiple sources.

datapoint/__init__.py

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+from .core import DataPoint

datapoint/core.py

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+
+class DataPoint:
+
+    def __init__(self):
+        pass
+
+    def search(self, **kwargs):
+        return None
+
+    def to_xarray(self, **kwargs):
+        return None

demo/datapoint.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# CEDA DataPoint - Demonstration\n",
+    "\n",
+    "The CEDA DataPoint module wraps both the ``pystac_client`` and ``xarray`` packages into a single container for searching and accessing data. This notebook shows how methods function in DataPoint."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from datapoint import DataPoint\n",
+    "\n",
+    "client = DataPoint() # All public connection kwargs are known by default for CEDA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Same as normal for pystac_client\n",
+    "\n",
+    "for coll in client.get_collections():\n",
+    "    print(f\"{coll.id}: {coll.description}\")\n",
+    "\n",
+    "# Return a new client with a specified collection to search for - or results from pystac_client? (Could load lazily?)\n",
+    "sentinel2_ard = client.get_collection('sentinel2_ard')\n",
+    "\n",
+    "# Make this a function or similar.\n",
+    "sentinel2_ard.extent.spatial.bboxes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Returns a new datapoint.SearchResult object. Inheritance for DataPoint, SearchResult from a general object type.\n",
+    "item_search = client.search(\n",
+    "    collections=['sentinel2_ard'],\n",
+    "    datetime=\"2023-01-01/2023-02-28\",\n",
+    "    max_items=10,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "items = list(item_search.items())\n",
+    "items"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Make all the properties into actual class properties?\n",
+    "for item in items:\n",
+    "    print(item.properties[\"start_datetime\"], item.properties[\"end_datetime\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Useful method for matching to catalog\n",
+    "item_search.url_with_parameters()\n",
+    "item_search.get_dois() # List item DOIs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Assemble xarray and other datasets\n",
+    "item_search.get_datasets()\n",
+    "\n",
+    "# Could have datasets from multiple sources in the same Xarray object?"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}