{ "cells": [ { "cell_type": "markdown", "id": "0", "metadata": {}, "source": [ "\"Open\n", "\n", "Uncomment the following line to install [geemap](https://geemap.org) if needed." ] }, { "cell_type": "code", "execution_count": null, "id": "1", "metadata": {}, "outputs": [], "source": [ "# !pip install geemap" ] }, { "cell_type": "markdown", "id": "2", "metadata": {}, "source": [ "## Automatic conversion from Earth Engine JavaScripts to Python scripts\n", "\n", "### Install Earth Engine API and geemap\n", "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://github.com/gee-community/geemap). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n", "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/gee-community/geemap#dependencies), including earthengine-api, folium, and ipyleaflet.\n", "\n", "**Important note**: A key difference between folium and ipyleaflet is that ipyleaflet is built upon ipywidgets and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input, while folium is meant for displaying static data only ([source](https://blog.jupyter.org/interactive-gis-in-jupyter-with-ipyleaflet-52f9657fa7a)). Note that [Google Colab](https://colab.research.google.com/) currently does not support ipyleaflet ([source](https://github.com/googlecolab/colabtools/issues/60#issuecomment-596225619)). Therefore, if you are using geemap with Google Colab, you should use [`import geemap.foliumap`](https://github.com/gee-community/geemap/blob/master/geemap/foliumap.py). If you are using geemap with [binder](https://mybinder.org/) or a local Jupyter notebook server, you can use [`import geemap`](https://github.com/gee-community/geemap/blob/master/geemap/geemap.py), which provides more functionalities for capturing user input (e.g., mouse-clicking and moving)." ] }, { "cell_type": "code", "execution_count": null, "id": "3", "metadata": {}, "outputs": [], "source": [ "import geemap" ] }, { "cell_type": "code", "execution_count": null, "id": "4", "metadata": {}, "outputs": [], "source": [ "geemap.show_youtube(\"RpIaalFk4H8\")" ] }, { "cell_type": "markdown", "id": "5", "metadata": {}, "source": [ "### Convert Earth Engine JavaScripts to Python scripts" ] }, { "cell_type": "code", "execution_count": null, "id": "6", "metadata": {}, "outputs": [], "source": [ "import os\n", "from geemap.conversion import *\n", "\n", "# Create a temporary working directory\n", "work_dir = os.path.join(os.path.expanduser(\"~\"), \"geemap\")\n", "# Get Earth Engine JavaScript examples. There are five examples in the geemap package folder.\n", "# Change js_dir to your own folder containing your Earth Engine JavaScripts,\n", "# such as js_dir = '/path/to/your/js/folder'\n", "js_dir = get_js_examples(out_dir=work_dir)\n", "\n", "# Convert all Earth Engine JavaScripts in a folder recursively to Python scripts.\n", "js_to_python_dir(in_dir=js_dir, out_dir=js_dir, use_qgis=True)\n", "print(\"Python scripts saved at: {}\".format(js_dir))" ] }, { "cell_type": "markdown", "id": "7", "metadata": {}, "source": [ "### Convert Earth Engine Python scripts to Jupyter Notebooks" ] }, { "cell_type": "code", "execution_count": null, "id": "8", "metadata": {}, "outputs": [], "source": [ "# Convert all Earth Engine Python scripts in a folder recursively to Jupyter notebooks.\n", "nb_template = get_nb_template() # Get the notebook template from the package folder.\n", "py_to_ipynb_dir(js_dir, nb_template)\n", "\n", "# Execute all Jupyter notebooks in a folder recursively and save the output cells.\n", "# execute_notebook_dir(in_dir=js_dir)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" } }, "nbformat": 4, "nbformat_minor": 5 }