Merge pull request #2412 from Esri/update_item_properties_dataclass

Update guides to use type over item_type for 2.4.3

Author: jyaistMap

.github/workflows/DockerBuild.NotebookImage.yaml

@@ -11,15 +11,27 @@ on:
       version:
         description: "Version of ArcGIS API for Python to install in the image"
         type: string
-        default: "2.4.1"
+        default: "2.4.2"
+      arcgis_mapping_version:
+        description: "Version of arcgis-mapping to install in the image (only used if version >= 2.4.0)"
+        type: string
+        default: "4.33.0"
       python_version:
         description: "Python version to base image on"
         type: string
-        default: "3.11"
+        default: "3.13"
       is_latest_release:
         description: "Version of ArcGIS API for Python is Latest current release"
         type: boolean
         default: false
+      arcgis_wheel_url:
+        description: "Use a custom version of ArcGIS API for Python from this wheel URL, if empty, use pypi.org; if provided, `-prerelease` will be appended to the image tag"
+        type: string
+        default: ""
+      arcgis_mapping_wheel_url:
+        description: "Use a custom version of arcgis-mapping from this wheel URL, if empty, install from pypi.org; if provided, `-prerelease` will be appended to the image tag"
+        type: string
+        default: ""
       is_default_supported_python:
         description: "Python version is default supported version (i.e. python used by Pro and Enterprise)"
         type: boolean
@@ -52,10 +64,10 @@ jobs:
           images: |
             ghcr.io/esri/arcgis-python-api-notebook
           tags: |
-            type=raw,value=${{ inputs.version }}-python${{ inputs.python_version }}
-            type=raw,value=${{ inputs.version }},enable=${{ inputs.is_default_supported_python && github.ref_name == github.event.repository.default_branch }}
-            type=raw,value=latest,enable=${{ inputs.is_latest_release && inputs.is_default_supported_python && github.ref_name == github.event.repository.default_branch }}
-            type=schedule,pattern={{date 'YY.MM'}},enable=${{ inputs.is_latest_release && inputs.is_default_supported_python && github.ref_name == github.event.repository.default_branch }}
+            type=raw,value=${{ inputs.version }}-python${{ inputs.python_version }}${{ inputs.arcgis_wheel_url != '' && '-prerelease' || '' }}
+            type=raw,value=${{ inputs.version }},enable=${{ inputs.is_default_supported_python && inputs.arcgis_wheel_url == '' && github.ref_name == github.event.repository.default_branch }}
+            type=raw,value=latest,enable=${{ inputs.arcgis_wheel_url == '' && inputs.is_latest_release && inputs.is_default_supported_python && github.ref_name == github.event.repository.default_branch }}
+            type=schedule,pattern={{date 'YY.MM'}},enable=${{ inputs.arcgis_wheel_url == '' && inputs.is_latest_release && inputs.is_default_supported_python && github.ref_name == github.event.repository.default_branch }}
 
       - id: docker_build
         name: Build image and push to GitHub Container Registry
@@ -67,6 +79,9 @@ jobs:
           build-args: |
             python_version=${{ inputs.python_version }}
             arcgis_version=${{ inputs.version }}
+            arcgis_mapping_version=${{ inputs.arcgis_mapping_version }}
+            arcgis_wheel_url=${{ inputs.arcgis_wheel_url }}
+            arcgis_mapping_wheel_url=${{ inputs.arcgis_mapping_wheel_url }}
           tags: ${{ steps.meta.outputs.tags }}
           provenance: false
           platforms: linux/amd64

docker/NotebookImage.Dockerfile

@@ -1,9 +1,14 @@
-ARG python_version="3.11"
+ARG python_version="3.13"
 FROM quay.io/jupyter/minimal-notebook:python-${python_version}
 
 ARG python_version
-ARG arcgis_version="2.4.1"
-ARG gdal_version="3.10.2"
+ARG arcgis_version="2.4.2"
+ARG arcgis_mapping_version="4.33.0"
+ARG gdal_version="3.11.4"
+# If arcgis_wheel_url is provided, the Dockerfile will attempt to install the ArcGIS API for Python from that URL
+ARG arcgis_wheel_url=""
+ARG arcgis_mapping_wheel_url=""
+
 ARG sampleslink="https://github.com/Esri/arcgis-python-api/releases/download/v${arcgis_version}/samples.zip"
 ARG githubfolder="arcgis-python-api"
 ARG env_name=arcgis
@@ -25,17 +30,20 @@ RUN conda install -n ${env_name} -c conda-forge gdal=${gdal_version} -y --quiet
     && conda clean --all -f -y \
     && find /opt/conda -name __pycache__ -type d -exec rm -rf {} +
 
+RUN echo "${arcgis_wheel_url:-arcgis==${arcgis_version}.*}" > /tmp/arcgis_source.txt
+
 # Install ArcGIS API for Python from pypi
 RUN . activate ${env_name} \
-    # adding .* ensures the latest patch version is installed
-    && python -m pip install "arcgis==${arcgis_version}.*" \
+    && python -m pip install "$(cat /tmp/arcgis_source.txt)" \
     && conda clean --all -f -y \
     && find /opt/conda -name __pycache__ -type d -exec rm -rf {} +
 
+RUN echo "${arcgis_mapping_wheel_url:-arcgis-mapping==${arcgis_mapping_version}.*}" > /tmp/arcgis_mapping_source.txt
+
 # Install arcgis-mapping if arcgis_version >= 2.4.0
 RUN (dpkg --compare-versions $arcgis_version ge 2.4.0 \
     && . activate ${env_name} \
-    && python -m pip install arcgis-mapping \
+    && python -m pip install "$(cat /tmp/arcgis_mapping_source.txt)" \
     && conda clean --all -f -y \
     && find /opt/conda -name __pycache__ -type d -exec rm -rf {} +;) \
     || echo "[INFO] Skipped installing arcgis-mapping for version $arcgis_version (>= 2.4.0 required for arcgis-mapping)"

guide/02-api-overview/release_notes_242.ipynb

@@ -16,7 +16,7 @@
     "    * [Working with Branch Versioning](../guide/working-with-branch-versioning/)  \n",
     "* [Deep Learning](../)\n",
     "  * [3D Computer Vision](../)\n",
-    "    * [Point cloud object detection using SECOND](../guide/point-cloud-classification-using-second)\n",
+    "    * [Point cloud object detection using SECOND](../guide/point-cloud-object-detection-using-second)\n",
     "    * [Point cloud classification using Point Transformer](../guide/point-cloud-classification-using-point-transformer/)\n",
     "* [Content Management](../)\n",
     "  * **Note:** Available since July '25\n",
@@ -32,7 +32,7 @@
     "* [Deep Learning](/python/samples)\n",
     "  * [2D Computer Vision](/python/samples)\n",
     "    * [Object Detection](/python/samples)\n",
-    "      * [Detecting airplanes in satellite imagery using deep learning](/python/latest/samples/detecting-airplanes-on-satellite-imagery-using-deep-learning/\") \n",
+    "      * [Detecting airplanes in satellite imagery using deep learning](/python/latest/samples/detecting-airplanes-on-satellite-imagery-using-deep-learning/) \n",
     "  * [Tabular Data Forecasting](/python/samples)\n",
     "    * [Leveraging TabPFN for Human Activity Recognition Using Mobile Dataset](/python/latest/samples/classifying-human-activity-using-tabPFN-classifier) \n",
     "\n",

guide/04-feature-data-and-analysis/working-with-feature-layers-and-features.ipynb

@@ -490,7 +490,9 @@
    "source": [
     "<a id=\"querying-layers\"></a>\n",
     "## Querying feature layers\n",
-    "Querying is a powerful operation that can be performed on a `FeatureLayer` object. Let's take a closer look here. To write meaningful queries, we need to know the names of fields present in the layer. This can be determined by calling the `fields` property:"
+    "Querying is a powerful operation that can be performed on a [`FeatureLayer`](/python/latest/api-reference/arcgis.features.toc.html#arcgis.features.FeatureLayer) object. Let's take a closer look here. To write meaningful queries, we need to know the names of fields present in the layer. This can be determined by calling the `fields` property:\n",
+    "\n",
+    "> **Note:** When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems."
    ]
   },
   {
@@ -1503,7 +1505,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.13.2"
   },
   "toc": {
    "base_numbering": 1,

guide/05-working-with-the-spatially-enabled-dataframe/introduction-to-the-spatially-enabled-dataframe.ipynb

@@ -52,7 +52,11 @@
     "\n",
     "The SEDF integrates with Esri's [`ArcPy` site-package](http://pro.arcgis.com/en/pro-app/arcpy/get-started/what-is-arcpy-.htm) as well as the open source [`pyshp`](https://github.com/GeospatialPython/pyshp/), [`shapely`](https://github.com/Toblerity/Shapely) and [`fiona`](https://github.com/Toblerity/Fiona) packages. This means the ArcGIS API for Python SEDF can use either of these geometry engines to provide you options for easily working with geospatial data regardless of your platform. The SEDF transforms data into the formats you desire so you can use Python functionality to analyze and visualize geographic information.\n",
     "\n",
-    "Data can be read and scripted to automate workflows and just as easily visualized on maps in [`Jupyter Lab notebooks`](../using-the-jupyter-notebook-environment/). The SEDF can export data as feature classes or publish them directly to servers for sharing according to your needs. Let's explore some of the different options available with the versatile `Spatial Enabled DataFrame` namespaces:\n"
+    "Data can be read and scripted to automate workflows and just as easily visualized on maps in [`Jupyter Lab notebooks`](../using-the-jupyter-notebook-environment/). The SEDF can export data as feature classes or publish them directly to servers for sharing according to your needs. \n",
+    "\n",
+    "> **_Note:_** When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems.\n",
+    "\n",
+    "Let's explore some of the different options available with the versatile `Spatial Enabled DataFrame` namespaces:"
    ]
   },
   {
@@ -1418,7 +1422,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.13.2"
   },
   "toc": {
    "base_numbering": 1,

guide/05-working-with-the-spatially-enabled-dataframe/part1_introduction_to_sedf.ipynb

@@ -39,7 +39,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "> _Note:_ Spatial Data Engineering using SeDF builds on top of core Data Engineering concepts in Python. If you are new to Pandas, NumPy and related libraries, we recommend you start with the [Introduction to Data Engineering](../part1-introduction-to-dataengineering) guide series and then come here.\n"
+    "> _**Note:**_ Spatial Data Engineering using SeDF builds on top of core Data Engineering concepts in Python. If you are new to Pandas, NumPy and related libraries, we recommend you start with the [Introduction to Data Engineering](../part1-introduction-to-dataengineering) guide series and then come here.\n",
+    "\n",
+    "> **_Note:_** When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems."
    ]
   },
   {
@@ -1543,7 +1545,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.13.2"
   },
   "toc": {
    "base_numbering": 1,

guide/06-imagery-and-raster-analysis/using-raster-analysis.ipynb

@@ -8,7 +8,9 @@
     "\n",
     "Raster Analysis can be used to create and execute spatial analysis models and image processing chains which leverage distributed storage and analysis. This powerful capability is available with ArcGIS Enterprise, and enables scalable raster analysis including terrain analysis, suitability analysis, vegetation analysis as well as persistent imagery product generation.\n",
     "\n",
-    "The `arcgis.raster.analytics` module provides the raster analysis functionality. This module contains functions that enable you to call raster analysis tools in your GIS."
+    "The [`arcgis.raster.analytics`](/python/latest/api-reference/arcgis.raster.analytics.html) submodule provides the raster analysis functionality. This module contains functions that enable you to call raster analysis tools in your GIS.\n",
+    "\n",
+    "> _**Note:**_ When leveraging Esri hosted content, organizations should review the [ArcGIS Online terms of use](https://doc.arcgis.com/en/arcgis-online/reference/terms-of-use.htm), as well as the terms of use for the data layer to ensure they are in compliance with extracting data and/or making it available in other systems."
    ]
   },
   {
@@ -414,7 +416,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.13.2"
   },
   "toc": {
    "base_numbering": 1,

guide/13-managing-arcgis-applications/itemgraph_and_remap_data.ipynb

@@ -314,7 +314,7 @@
    ],
    "source": [
     "# conversely, we can grab a dependent item and see what items immediately contain it and need it to exist\n",
-    "result_flayer = graph.get_item(\"41dd3cca32914cc7ae8fd3a727f44e17\")\n",
+    "result_flayer = graph.get_node(\"41dd3cca32914cc7ae8fd3a727f44e17\")\n",
     "result_flayer.item"
    ]
   },
@@ -887,7 +887,7 @@
    "source": [
     "# so we can see that one of them is from our root item, and one is from a dependent item\n",
     "# let's see what that sub item is\n",
-    "sub_node = graph2.get_item(\"7099b3c2e979415e975d00e58afed77e\")\n",
+    "sub_node = graph2.get_node(\"7099b3c2e979415e975d00e58afed77e\")\n",
     "webmap = sub_node.item\n",
     "webmap"
    ]
@@ -991,7 +991,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.11"
+   "version": "3.13.2"
   }
  },
  "nbformat": 4,

samples/03_org_administrators/clone_a_group.ipynb

@@ -328,7 +328,7 @@
     "        target_item_properties = ItemProperties(title=item.title,\n",
     "                              tags=item.tags,\n",
     "                              text=item.get_data(try_json=True),\n",
-    "                              item_type=item.type,\n",
+    "                              type=item.type,\n",
     "                              snippet=item.snippet,\n",
     "                              description=item.description,\n",
     "                              thumbnail=thumbnail_file)        \n",

samples/03_org_administrators/validate_user_profiles.ipynb

@@ -283,7 +283,7 @@
    "source": [
     "item_props = ItemProperties(\n",
     "    title = out_file,\n",
-    "    item_type = ItemTypeEnum.CSV,\n",
+    "    type = ItemTypeEnum.CSV,\n",
     "    tags = \"user_profile_report\",\n",
     "    snippet = \"Report on user profile data from Python API\"\n",
     ")\n",