Merge pull request #381 from tbarsballe/docker-jupyter-2025

Update Dockerfile to 2025 build of jupyter/minimal-notebook

Author: tbarsballe

README.md

@@ -1,17 +1,15 @@
-## Planet Interactive Guides
+# Planet Jupyter Notebook Guides
 
 In this repository, you'll find a collection of [Jupyter notebooks](http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_is_jupyter.html) from the software developers, data scientists, and developer advocates at [Planet](https://www.planet.com/). These interactive, open-source ([APLv2](LICENSE)) guides are designed to help you work with our APIs and tools, explore Planet data, and learn how to extract information from our massive archive of high-cadence satellite imagery. We hope these guides will inspire you to ask interesting questions of Planet data. Need help? Find a bug? Please [file an issue](https://github.com/planetlabs/notebooks/issues/new) and we'll get back to you.
 
-## Install and use these notebooks
+## Install and Use Planet Jupyter Notebooks
 
 ### System Prerequisites
-* [Docker](https://store.docker.com/search?type=edition&offering=community)
-* [Planet Account](https://www.planet.com/explorer/?signup=1)
+* [Docker](https://docs.docker.com/get-started/get-docker/)
+* [Planet Account](https://insights.planet.com/sign-up)
 * [Planet API Key](https://www.planet.com/account/)
 
-NOTE: After installing Docker, Windows users should install WSL2 Backend when prompted.
-
-### Clone or update repo:
+### Clone or Update Repo
 
 If you've never cloned the Planet notebooks repo, run the following:
 
@@ -29,7 +27,7 @@ git pull
 
 ## Authentication
 
-## Access your Planet API Key in Python
+## Access Your Planet API Key in Python
 
 Authentication with Planet's API Key can be achieved by using a valid Planet API Key.
 
@@ -53,7 +51,7 @@ PLANET_API_KEY = os.getenv('PL_API_KEY')
 
 Now, your Planet API Key is stored in the variable ```PLANET_API_KEY``` and is ready to use in your Python code.
 
-### Sentinel Hub Python SDK
+## Sentinel Hub Python SDK
 Some Notebooks in this repository use the [Sentinel Hub Python SDK](https://sentinelhub-py.readthedocs.io/en/latest/index.html).  Currently, this SDK uses a different method of authenticating than what is used with the Planet APIs and SDK for Python. 
 
 For the Sentinel Hub Python SDK, you must provide a ```client_id``` and a ```client_secret``` which can be obtained from the [Dashboard](https://apps.sentinel-hub.com/dashboard/) app. You can find full instructions on setting up the client credentials in this SDK from the [SDK documentation](https://sentinelhub-py.readthedocs.io/en/latest/configure.html).
@@ -75,140 +73,45 @@ else:
 ```
 
 ## Run Planet Notebooks in Docker
-Planet Notebooks rely on a complex stack of technologies that are not always easy to install and properly 
-configure. To ease this complexity we provide a docker container for running the notebook on docker compatible 
-systems. To install docker on your system please see docker's [documentation](https://docs.docker.com/engine/installation/)
-for your operating system.
+Planet Notebooks rely on a complex stack of technologies that are not always easy to install and properly configure. To ease this complexity we provide a Docker container for running the notebook on Docker compatible systems. To install Docker on your system please see [Docker documentation](https://docs.docker.com/get-started/get-docker/) for your operating system.
 
-### Download prebuilt Docker image (recommended)
-The Docker image for these notebooks is hosted in the [planetlabs/notebooks](https://hub.docker.com/r/planetlabs/notebooks) repo on DockerHub. To download and prepare the image for use, run:
+### Build the Docker image
 
-```bash
-cd notebooks
-docker pull planetlabs/notebooks
-docker tag planetlabs/notebooks planet-notebooks
-
-# If you get errors running the above, you might have to add sudo to the beginning:
-#sudo docker pull planetlabs/notebooks
-#sudo docker tag planetlabs/notebooks planet-notebooks
-```
-
-If you want to re-build the Docker image yourself, this is documented below in the "Appendix: Build the Docker image" section.
-
-### Run the container
-To run the container (after building or downloading it), add your Planet API key below and issue the following command from the git repository root directory:
+First you must build the docker image. After checking out the repository, you run:
 
 ```bash
-docker run -it --rm -p 8888:8888 -v $PWD:/home/jovyan/work -e PL_API_KEY='[YOUR-API-KEY]' planet-notebooks
-
-# If you get a permissions error running the above, you should add sudo to the front:
-# sudo docker run -it --rm -p 8888:8888 -v $PWD:/home/jovyan/work -e PL_API_KEY='[YOUR-API-KEY]' planet-notebooks
-# Windows users run: winpty docker run -it --rm -p 8888:8888 -v "/$PWD":/home/joyvan/work -e PL_API_KEY='[YOUR-API-KEY]' planet-notebooks
-
+docker build -t planet-notebooks planet-notebook-docker/
 ```
 
-This does several things:  
+This will build and install the Docker image on your system, making it available to run. This may take some time (from 10 minutes to an hour) depending on your network connection and how long Anaconda takes to configure its environment.
 
-1. Maps the docker container's ```8888``` port to your system's ```8888``` port.  This makes the 
-container available to your host systems web browser.
+> [!IMPORTANT]
+> You may need to rebuild the Docker image if this repository changes or if you need to use newer versions of the Planet SDK for Python.  
 
-1. Maps a host system path ```$PWD``` to the docker container's working directory.
-This ensures that the notebooks you create, edit, and save are available on your host system under the
-`jupyter-notebooks` sub-directory and are not *destroyed* when you exit the container.
-This also allows for running tests in the `tests` sub-directory.
+### Run the Container
+To run the container after building it, add your Planet API key to the command below and run it from the cloned `planetlabs/notebooks` repository root directory in Unix bash, Windows PowerShell, Git Bash, or WSL.
 
-1. Ensures that the directory in the Docker container named `/home/jovyan/work` that has the notebooks
-in them is accessible to the Jupyter notebook server.
+```bash
+docker run -it --rm -p 8888:8888 -v "$(pwd)/jupyter-notebooks:/home/jovyan/work" -e PL_API_KEY='your-key' planet-notebooks
+```
 
-1. Starts an interactive terminal that is accessible through http://localhost:8888.
+> [!TIP]
+> If you get permission errors: Add sudo to the front (Linux/Mac) or run PowerShell as Administrator (Windows).
 
-1. Sets an environment variable with your unique Planet API key for authenticating against the API.
+This does several things:  
 
-1. Includes the ```--rm``` option to clean up the notebook after you exit the process.
+1. **Maps port 8888** - Makes the container accessible at http://localhost:8888
+2. **Mounts your notebooks** - Maps `jupyter-notebooks/` folder to `/home/jovyan/work` so your work persists and notebooks are accessible to Jupyter
+3. **Sets your API key** - Replace `your-key` with your actual Planet API key for API authentication
+4. **Starts interactive terminal** - Accessible through the web browser
+5. **Auto-cleanup** - Removes container when you exit (`--rm`)
 
-### Open Jupyter notebooks
+### Open Jupyter Notebooks
 Once the Docker container is running, the CLI output will display a URL that you will use to access Jupyter notebooks
 with your browser.
 ```
 http://localhost:8888/?token=<UNIQUE-TOKEN>
 ```
 
-NOTE: This security token will change every time you start your Docker container.
-
-## Repository Organization
-
-### jupyter-notebooks
-
-#### exploring_planet_data: Working with our various image products, how to use the udm mask or deliver imagery to our GEE integration
-
-* [How to use the Data and Orders API to create analysis ready data](https://github.com/planetlabs/notebooks/tree/proserve_restructure/jupyter-notebooks/exploring_planet_data/analysis-ready-data)
-* [Converting Raster Results to Vector Features](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics-snippets/README.md)
-* [Introduction to Cloud Native Geospatial Tools](https://github.com/planetlabs/notebooks/tree/master/jupyter-notebooks/cloud-native-geospatial)
-* [Comparing Planet Scope with Landsat 8]()
-* [Deliver data to GEE](https://github.com/planetlabs/notebooks/tree/master/jupyter-notebooks/cloud-native-geospatial)
-* [Start working with satellite imagery in Python](https://github.com/planetlabs/notebooks/tree/master/jupyter-notebooks/cloud-native-geospatial)
-* [Create labels using Planet imagery](https://github.com/planetlabs/notebooks/tree/master/jupyter-notebooks/cloud-native-geospatial)
-* [Pixel-by-pixel comparison of PlanetScope and Landsat Scenes](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/landsat-ps-comparison/landsat-ps-comparison.ipynb)
-* [Visualize and convert a UDM to a binary mask](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/udm/udm.ipynb)
-* [Work with the Usable Data Mask (UDM2)](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/udm2)
-
-
-
-
-#### Search, activate, download with the Data API   
-* [Explore the Planet Data API with Python](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/data-api-tutorials/planet_data_api_introduction.ipynb)
-* [Search, activate, and download imagery with the Planet Python Client](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/data-api-tutorials/planet_python_client_introduction.ipynb)
-* [Search & Download Quickstart Guide](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/data-api-tutorials/search_and_download_quickstart.ipynb)
-* [Planet Data API reference](https://developers.planet.com/docs/apis/data/)
-
-#### Ordering, delivery, and tools with the Orders API
-* [Ordering and Delivery](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/orders_api_tutorials/ordering_and_delivery.ipynb)
-* [Tools and Toolchains](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/orders_api_tutorials/tools_and_toolchains.ipynb)
-* [Planet Orders API reference](https://developers.planet.com/docs/orders/)
-
-### Process Planet data
-* [Create a mosaic from multiple PlanetScope scenes](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/mosaicing/basic_compositing_demo.ipynb)
-* [Calculate a vegetation index from 4-band satellite imagery](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/ndvi/ndvi_planetscope.ipynb)
-* [Convert PlanetScope metadata from radiance to reflectance](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/toar/toar_planetscope.ipynb)
-
-
-### Analyze and visualize Planet data
-
-* Analytics quickstart:
-    1. [Summarizing Feeds and Subscriptions](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/quickstart/01_checking_available_feeds_and_subscriptions.ipynb)
-    2. [Getting Analytic Feed Results](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/quickstart/02_fetching_feed_results.ipynb)
-    3. [Visualizing Raster Results](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/quickstart/03_visualizing_raster_results.ipynb)
-* Analytics user guide:
-    1. [Getting Started with Planet Analytics API](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/user-guide/01_getting_started_with_the_planet_analytics_api.ipynb)
-    2. [Planet Analytic Feeds Results](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/user-guide/02_analytic_feeds_results.ipynb)
-    3. [Change Detection](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/user-guide/03_change_detection.ipynb)
-    4. [Summary Statistics - Buildings](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/user-guide/04_summary_statistics_buildings.ipynb)
-    5. [Summary Statistics - Ships and Clouds](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/user-guide/05_summary_statistics_ships_and_clouds.ipynb)
-* Other analytics notebooks:
-    * [Detect, count, and visualize ships in Planet imagery](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/ship-detector/01_ship_detector.ipynb)
-    * [Pixel-by-pixel comparison of PlanetScope and Landsat Scenes](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/landsat-ps-comparison/landsat-ps-comparison.ipynb)
-    * [Calculate Coverage for a Search Query](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/coverage/calculate_coverage.ipynb)
-    * [Segment and Classify Crops](https://github.com/planetlabs/notebooks/tree/master/jupyter-notebooks/crop-segmentation-and-classification)
-    * [Identify Forest Degradation](https://github.com/planetlabs/notebooks/tree/master/jupyter-notebooks/forest-monitoring)
-    * [Identify the Temporal Signature of Crops](https://github.com/planetlabs/notebooks/tree/master/jupyter-notebooks/temporal-analysis)
-
-    * [Creating a Heatmap of Vector Results](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/analytics/change_detection_heatmap.ipynb)
-
-
-Soon we hope to add notebooks from the researchers, technologists, geographers, and entrepreneurs who are already using Planet data to ask interesting and innovative questions about our changing Earth. If you're working with our imagery and have a notebook (or just an idea for a notebook) that you'd like to share, please [file an issue](https://github.com/planetlabs/notebooks/issues) and let us know.
-
-### Appendix: Build the Docker image
-
-This documents how to build the docker image yourself, rather than using the recommended step of downloading pre-built Docker images. This is useful if you are a developer adding dependencies or a new Jupyter notebook to this repo, for example.
-
-First you must build the docker image. Note, this only has to be done the first time you use it. After checking out the
-repository, you run:
-```bash
-cd planet-notebook-docker
-docker build --rm -t planet-notebooks .
-cd ..
-```
-
-This will build and install the Docker image on your system, making it available to run. This may take some 
-time (from 10 minutes to an hour) depending on your network connection and how long Anaconda takes to configure
-its environment.
+> [!NOTE]  
+> This security token will change every time you start your Docker container.

jupyter-notebooks/Analytics-API/user-guide/01_getting_started_with_the_planet_analytics_api.ipynb

@@ -1033,9 +1033,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "subscription_1"
@@ -1073,6 +1071,8 @@
    "outputs": [],
    "source": [
     "# Let's look at our multipolygon centroid in (Lat, Long)\n",
+    "import warnings\n",
+    "warnings.simplefilter('ignore')\n",
     "print(subscription_1['geometry'].centroid)\n",
     "\n",
     "# We need to input the center of our map in reverse order (Long, Lat) \n",
@@ -1139,9 +1139,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

jupyter-notebooks/use-cases/coastal-erosion-example/0_download_data.ipynb

@@ -34,9 +34,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

jupyter-notebooks/use-cases/coastal-erosion-example/1_rasterio_firstlook.ipynb

@@ -98,7 +98,8 @@
    "outputs": [],
    "source": [
     "# Let's import Rasterio\n",
-    "import rasterio"
+    "import rasterio\n",
+    "import os"
    ]
   },
   {
@@ -108,7 +109,7 @@
    "outputs": [],
    "source": [
     "# This notebook explores a single 3 band (blue, green, red) PlanetScope scene in a UTM projection.\n",
-    "image_file = \"/content/20170831_172754_101c_3b_Visual.tif\""
+    "image_file = f\"{os.getcwd()}/20170831_172754_101c_3b_Visual.tif\""
    ]
   },
   {
@@ -120,7 +121,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<open DatasetReader name='20170831_172754_101c_3b_Visual.tif' mode='r'>\n"
+      "<open DatasetReader name='/home/jovyan/work/jupyter-notebooks/use-cases/coastal-erosion-example/20170831_172754_101c_3b_Visual.tif' mode='r'>\n"
      ]
     }
    ],
@@ -141,7 +142,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "20170831_172754_101c_3b_Visual.tif\n",
+      "/home/jovyan/work/jupyter-notebooks/use-cases/coastal-erosion-example/20170831_172754_101c_3b_Visual.tif\n",
       "3\n"
      ]
     }
@@ -268,9 +269,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

jupyter-notebooks/use-cases/coastal-erosion-example/2_rasterbands.ipynb

@@ -83,6 +83,7 @@
    "outputs": [],
    "source": [
     "import rasterio\n",
+    "import os\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
    ]
@@ -100,7 +101,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "image_file = \"/content/20170831_172754_101c_3b_Visual.tif\""
+    "image_file = f\"{os.getcwd()}/20170831_172754_101c_3b_Visual.tif\""
    ]
   },
   {
@@ -112,7 +113,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<open DatasetReader name='20170831_172754_101c_3b_Visual.tif' mode='r'>\n"
+      "<open DatasetReader name='/home/jovyan/work/jupyter-notebooks/use-cases/coastal-erosion-example/20170831_172754_101c_3b_Visual.tif' mode='r'>\n"
      ]
     }
    ],
@@ -410,9 +411,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

jupyter-notebooks/use-cases/coastal-erosion-example/3_compute_NDWI.ipynb

@@ -82,6 +82,7 @@
    "outputs": [],
    "source": [
     "import rasterio\n",
+    "import os\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
    ]
@@ -99,7 +100,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "image_file = \"/content/20170831_172754_101c_3B_AnalyticMS.tif\"\n",
+    "image_file = f\"{os.getcwd()}/20170831_172754_101c_3B_AnalyticMS.tif\"\n",
     "satdat = rasterio.open(image_file)"
    ]
   },
@@ -286,9 +287,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }