Release v0.8.4 (#742)

* release: v0.8.4 * fix: keep hvplot.pandas import * fix: another import
stac-utils · Oct 16, 2024 · e666078 · e666078
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diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -3,12 +3,12 @@
 
 repos:
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: "v0.5.0"
+    rev: "v0.6.9"
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]
   - repo: https://github.com/psf/black
-    rev: 24.4.2
+    rev: 24.10.0
     hooks:
       - id: black
   - repo: https://github.com/codespell-project/codespell
@@ -18,14 +18,14 @@ repos:
         args: [--ignore-words=.codespellignore]
         types_or: [jupyter, markdown, python, shell]
   - repo: https://github.com/PyCQA/doc8
-    rev: v1.1.1
+    rev: v1.1.2
     hooks:
       - id: doc8
         args: [--ignore=D004]
         additional_dependencies:
           - importlib_metadata < 5; python_version == "3.7"
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.10.1
+    rev: v1.12.0
     hooks:
       - id: mypy
         files: ".*\\.py$"

diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -7,6 +7,8 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 
 ## [Unreleased]
 
+## [v0.8.4] - 2024-10-16
+
 ### Added
 
 - Support for collection search via `CollectionSearch` class and associated client methods [#735](https://github.com/stac-utils/pystac-client/pull/735)
@@ -393,7 +395,8 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 
 Initial release.
 
-[Unreleased]: https://github.com/stac-utils/pystac-client/compare/v0.8.3...main
+[Unreleased]: https://github.com/stac-utils/pystac-client/compare/v0.8.4...main
+[v0.8.4]: https://github.com/stac-utils/pystac-client/compare/v0.8.3...v0.8.4
 [v0.8.3]: https://github.com/stac-utils/pystac-client/compare/v0.8.2...v0.8.3
 [v0.8.2]: https://github.com/stac-utils/pystac-client/compare/v0.8.1...v0.8.2
 [v0.8.1]: https://github.com/stac-utils/pystac-client/compare/v0.8.0...v0.8.1

diff --git a/docs/tutorials/aoi-coverage.ipynb b/docs/tutorials/aoi-coverage.ipynb
@@ -17,13 +17,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pystac_client import Client\n",
+    "from typing import Any, Dict\n",
     "\n",
     "import matplotlib.pyplot as plt\n",
-    "from shapely.geometry import shape\n",
-    "from pystac_client import Client\n",
     "from pystac.item import Item\n",
-    "from typing import Dict, Any"
+    "from shapely.geometry import shape\n",
+    "\n",
+    "from pystac_client import Client"
    ]
   },
   {
@@ -34,9 +34,9 @@
    "outputs": [],
    "source": [
     "def intersection_percent(item: Item, aoi: Dict[str, Any]) -> float:\n",
-    "    '''The percentage that the Item's geometry intersects the AOI. An Item that\n",
+    "    \"\"\"The percentage that the Item's geometry intersects the AOI. An Item that\n",
     "    completely covers the AOI has a value of 100.\n",
-    "    '''\n",
+    "    \"\"\"\n",
     "    geom_item = shape(item.geometry)\n",
     "    geom_aoi = shape(aoi)\n",
     "\n",
@@ -48,7 +48,7 @@
     "\n",
     "\n",
     "# STAC API root URL\n",
-    "URL = 'https://planetarycomputer.microsoft.com/api/stac/v1'\n",
+    "URL = \"https://planetarycomputer.microsoft.com/api/stac/v1\"\n",
     "\n",
     "# geometry of the AOI to search over\n",
     "intersects_geometry = {\n",
@@ -79,7 +79,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "print([f\"{intersection_percent(item, intersects_geometry):.2f}\" for item in item_search.items()])"
+    "print(\n",
+    "    [\n",
+    "        f\"{intersection_percent(item, intersects_geometry):.2f}\"\n",
+    "        for item in item_search.items()\n",
+    "    ]\n",
+    ")"
    ]
   },
   {
@@ -105,19 +110,20 @@
     "# Render the AOI and Item results\n",
     "# The green shape is the AOI\n",
     "# The blue shapes are the Item geometries\n",
-    "# If there are no blue shapes, adjust the intersection percent filter above until there are\n",
+    "# If there are no blue shapes, adjust the intersection percent filter above\n",
+    "# until there are\n",
     "\n",
-    "cm = plt.get_cmap('RdBu')\n",
+    "cm = plt.get_cmap(\"RdBu\")\n",
     "fig, axs = plt.subplots()\n",
-    "axs.set_aspect('equal', 'datalim')\n",
+    "axs.set_aspect(\"equal\", \"datalim\")\n",
     "\n",
     "for item in items_gt_5_percent:\n",
-    "  xs, ys = shape(item.geometry).exterior.xy\n",
-    "  axs.fill(xs, ys, alpha=0.5, fc='b', ec='none')\n",
+    "    xs, ys = shape(item.geometry).exterior.xy\n",
+    "    axs.fill(xs, ys, alpha=0.5, fc=\"b\", ec=\"none\")\n",
     "\n",
     "geom_intersects = shape(intersects_geometry)\n",
     "xs, ys = geom_intersects.exterior.xy\n",
-    "axs.fill(xs, ys, alpha=0.5, fc='g', ec='none')\n",
+    "axs.fill(xs, ys, alpha=0.5, fc=\"g\", ec=\"none\")\n",
     "\n",
     "plt.show()"
    ]

diff --git a/docs/tutorials/cql2-filter.ipynb b/docs/tutorials/cql2-filter.ipynb
@@ -20,32 +20,33 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pystac_client import Client\n",
-    "\n",
     "# set pystac_client logger to DEBUG to see API calls\n",
     "import logging\n",
-    "logging.basicConfig()\n",
-    "logger = logging.getLogger('pystac_client')\n",
-    "logger.setLevel(logging.INFO)\n",
-    "\n",
-    "# function for creating GeoDataFrame from Items\n",
     "from copy import deepcopy\n",
+    "\n",
     "import geopandas as gpd\n",
     "import pandas as pd\n",
     "from shapely.geometry import shape\n",
     "\n",
+    "from pystac_client import Client\n",
+    "\n",
+    "logging.basicConfig()\n",
+    "logger = logging.getLogger(\"pystac_client\")\n",
+    "logger.setLevel(logging.INFO)\n",
+    "\n",
+    "\n",
     "# convert a list of STAC Items into a GeoDataFrame\n",
     "def items_to_geodataframe(items):\n",
     "    _items = []\n",
     "    for i in items:\n",
     "        _i = deepcopy(i)\n",
-    "        _i['geometry'] = shape(_i['geometry'])\n",
+    "        _i[\"geometry\"] = shape(_i[\"geometry\"])\n",
     "        _items.append(_i)\n",
     "    gdf = gpd.GeoDataFrame(pd.json_normalize(_items))\n",
-    "    for field in ['properties.datetime', 'properties.created', 'properties.updated']:\n",
+    "    for field in [\"properties.datetime\", \"properties.created\", \"properties.updated\"]:\n",
     "        if field in gdf:\n",
     "            gdf[field] = pd.to_datetime(gdf[field])\n",
-    "    gdf.set_index('properties.datetime', inplace=True)\n",
+    "    gdf.set_index(\"properties.datetime\", inplace=True)\n",
     "    return gdf"
    ]
   },
@@ -57,7 +58,7 @@
    "outputs": [],
    "source": [
     "# STAC API root URL\n",
-    "URL = 'https://planetarycomputer.microsoft.com/api/stac/v1'\n",
+    "URL = \"https://planetarycomputer.microsoft.com/api/stac/v1\"\n",
     "\n",
     "# custom headers\n",
     "headers = []\n",
@@ -82,33 +83,22 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import json\n",
+    "\n",
+    "import hvplot.pandas  # noqa: F401\n",
+    "\n",
     "# AOI around Delfzijl, in the north of The Netherlands\n",
     "geom = {\n",
     "    \"type\": \"Polygon\",\n",
     "    \"coordinates\": [\n",
-    "      [\n",
-    "        [\n",
-    "          6.42425537109375,\n",
-    "          53.174765470134616\n",
-    "        ],\n",
-    "        [\n",
-    "          7.344360351562499,\n",
-    "          53.174765470134616\n",
-    "        ],\n",
-    "        [\n",
-    "          7.344360351562499,\n",
-    "          53.67393435835391\n",
-    "        ],\n",
-    "        [\n",
-    "          6.42425537109375,\n",
-    "          53.67393435835391\n",
-    "        ],\n",
     "        [\n",
-    "          6.42425537109375,\n",
-    "          53.174765470134616\n",
+    "            [6.42425537109375, 53.174765470134616],\n",
+    "            [7.344360351562499, 53.174765470134616],\n",
+    "            [7.344360351562499, 53.67393435835391],\n",
+    "            [6.42425537109375, 53.67393435835391],\n",
+    "            [6.42425537109375, 53.174765470134616],\n",
     "        ]\n",
-    "      ]\n",
-    "    ]\n",
+    "    ],\n",
     "}\n",
     "\n",
     "params = {\n",
@@ -118,20 +108,20 @@
     "    \"datetime\": \"2018-01-01/2020-12-31\",\n",
     "}\n",
     "\n",
-    "import hvplot.pandas\n",
-    "import json\n",
     "\n",
     "# reusable search function\n",
     "def search_fetch_plot(params, filt):\n",
     "    # limit sets the # of items per page so we can see multiple pages getting fetched\n",
-    "    params['filter'] = filt\n",
+    "    params[\"filter\"] = filt\n",
     "    search = cat.search(**params)\n",
-    "    items = list(search.items_as_dicts()) # safe b/c we set max_items = 100\n",
+    "    items = list(search.items_as_dicts())  # safe b/c we set max_items = 100\n",
     "    # DataFrame\n",
     "    items_df = pd.DataFrame(items_to_geodataframe(items))\n",
     "    print(f\"{len(items_df.index)} items found\")\n",
-    "    field = 'properties.eo:cloud_cover'\n",
-    "    return items_df.hvplot(y=field, label=json.dumps(filt), frame_height=500, frame_width=800)    "
+    "    field = \"properties.eo:cloud_cover\"\n",
+    "    return items_df.hvplot(\n",
+    "        y=field, label=json.dumps(filt), frame_height=500, frame_width=800\n",
+    "    )"
    ]
   },
   {
@@ -151,10 +141,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "filt = {\n",
-    "    \"op\": \"lte\",\n",
-    "    \"args\": [{\"property\": \"eo:cloud_cover\"}, 10]\n",
-    "}\n",
+    "filt = {\"op\": \"lte\", \"args\": [{\"property\": \"eo:cloud_cover\"}, 10]}\n",
     "\n",
     "search_fetch_plot(params, filt)"
    ]
@@ -166,10 +153,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "filt = {\n",
-    "    \"op\": \"gte\",\n",
-    "    \"args\" : [{\"property\": \"eo:cloud_cover\"}, 80]\n",
-    "}\n",
+    "filt = {\"op\": \"gte\", \"args\": [{\"property\": \"eo:cloud_cover\"}, 80]}\n",
     "\n",
     "search_fetch_plot(params, filt)"
    ]
@@ -181,18 +165,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "filt = { \n",
+    "filt = {\n",
     "    \"op\": \"and\",\n",
     "    \"args\": [\n",
-    "      { \n",
-    "          \"op\":\"lte\", \n",
-    "          \"args\": [{\"property\": \"eo:cloud_cover\"}, 60]\n",
-    "      },\n",
-    "      { \n",
-    "          \"op\": \"gte\", \n",
-    "          \"args\": [{\"property\": \"eo:cloud_cover\"}, 40]\n",
-    "      }\n",
-    "    ]\n",
+    "        {\"op\": \"lte\", \"args\": [{\"property\": \"eo:cloud_cover\"}, 60]},\n",
+    "        {\"op\": \"gte\", \"args\": [{\"property\": \"eo:cloud_cover\"}, 40]},\n",
+    "    ],\n",
     "}\n",
     "\n",
     "search_fetch_plot(params, filt)"