Archydro For Arcgis 10.5
Xena Donovan
Use simple and efficient tools powered by Web GIS, for sophisticated vector and raster analysis, geocoding, map making, routing and directions. Administer, organize and manage users, groups and information items in your GIS.
This library enables access to ready-to-use maps and curated geographic data from Esri and other authoritative sources, and works with your own data as well. It integrates well with the scientific Python ecosystem and includes rich support for Pandas and Jupyter notebook.
There are multiple ways in which you can experience the ArcGIS API for Python. The ArcGIS API for Python is distributed as a conda package named arcgis. Conda is a popular Python package and environment manager application that helps you install and update packages such as the ArcGIS API for Python and their dependencies.
Python has a rich collection of packages that can be used in ArcGIS Pro. To simplify the use of Python packages, ArcGIS Pro includes a package management system called conda. Conda takes the guesswork and hassle out of installing and updating packages and their dependencies.
To further extend the versatility and utility of Python packages, multiple installations of Python can coexist on a single workstation, independent of one another. Each of these installations is referred to as a Python environment. Each Python environment can have its own set of packages, allowing you to switch between sets of Python functionality without uninstalling and reinstalling packages each time.
Starting from version 2.5, ArcGIS Pro releases ship with conda and the arcgis package pre-installed. The functionality of conda is integrated into ArcGIS Pro through the Python Package Manager. The Python Package Manager removes many of the hurdles faced when writing Python code. It supports installing open-source and third-party libraries that are associated with an individual project, rather than the base Python installation. This simplifies the process of successfully sharing complex Python tools across multiple computers.
Note: By default, the Python Command Prompt opens in the ArcGIS Pro default arcgispro-py3 environment directory, usually C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\, with this defaultconda environment active. You cannot modify the packages in this environment. In order to add more packages, you need to create a clone of the default arcgispro-py3 environment. Follow the steps in the create environment technical article to clone an environment. You can then change the default environment that future ArcGIS Pro and Python Command Prompt sessions use to this cloned environment using the command: proswap . See Access conda from a command prompt for additional information.
Open a terminal application, navigate to the directory you want to work in, and activate the conda environment you want to use with the ArcGIS API for Python. Install the API with the following command:
Pipenv is the official packaging tool for managing environments and installing packages from the Python Package Index (PyPI). To install the ArcGIS API for Python from PyPI in a new environment, create a new folder named your-folder. Then, open a terminal, and run cd /path/to/your-folder to change directories into your-folder. Next, enter the following command to simultaneously create a new environment and install the API in it:
Both conda install -c esri arcgis and pip install arcgis will install all of the dependencies outlined in the system requirements section. However, the API can function in a 'stripped down' state with only a few dependencies. This allows developers to deploy the API with minimal footprint in space constrained environments. For this to work, you need to manually manage the dependencies in your environment based on the applications you need to solve and if you don't want to use every feature of the API. As of v2.1.0 of the Python API, the minimum dependencies needed include:
The above set of dependencies should allow you to establish a connection with your web GIS and perform a number of administrative and other tasks which involve processing on your GIS rather than in your Python kernel. Depending on your OS, this set up with minimal dependencies should take up about 50 mb in space. As your needs expand, you can then manually choose which dependencies to add to your Python environment. For instance, you can install pandas if you require to work with spatially enabled DataFrames and jupyter, if you need the notebook IDE.
Docker is a popular containerization technology. Docker containers bundle software in a complete file system with everything that is needed to run it. Docker containers run the same regardless of your operating system. To learn more about docker, refer to the official documentation.
The ArcGIS API for Python is shipped as a Docker image which you can download and power up whenever you want to use the API. These images when spun up into containers, run in an isolated environment without making any changes to your local file system.
Google Colab is a Google-hosted Jupyter notebook service that allows a user to access their notebooks from anywhere by storing them in Google Drive. It requires no setup beyond creating a Google account, and provides free computing resources, including cloud-based GPUs. To learn more, refer to the FAQ or tutorial. Colab is a very convenient platform for ArcGIS administration and management, as it allows a user to run scripts from wherever they have access to a Google account.
Google Colab runs in a cloud virtual machine that uses Ubuntu, meaning that it can process bash commands in addition to Python logic. Any command with a ! in front of it will be treated as if it were entered on the command line. This means that the ArcGIS API for Python can be installed with pip.
Currently, Google Colab is not readily compatible with the ArcGIS mapping widget, but may work with some functions that return iFrames, such as the WebExperience.preview() method. To enable these widgets (or any 3rd-party widget) in Colab, run from google.colab import output followed by output.enable_custom_widget_manager().
Note: At the time of writing this, this installation process works for the default version of Python that comes with Colab, 3.10.12. This means that only ArcGIS 2.2.0 and higher can be installed, as prior versions are not compatible with Python 3.10+. Downgrading the Python version in Colab is possible, but may interfere with other dependencies needed to run ArcGIS.
Install Anaconda from your install location. Once installed, you can use the Anaconda Navigator GUI application or the Anaconda Prompt command line console to operate the software. The procedure below outlines using the Anaconda Prompt and the conda utility on Windows:
At this point, all modules, classes and functions are available in the API for use in your Python scripts or Jupyter notebooks except the Map Widget. You can verify your install by making a connection to your GIS and printing properties:
NOTE: You may need to configure the map widget to use the Javascript API shipped with the portal you're connecting to in the disconnected environment. If gis.map() does not return a map, run the following code to configure the map widget with the Javascript API shipped with the portal:
If you already have an environment with the arcgis package installed, you can further install its deep learning dependencies to take advantage of the arcgis.learn module. Some of the deep learning samples available here can be referenced to understand the workflow.
Deep Learning Libraries Installer for ArcGIS is now available at -learning-frameworks. This installer includes a broad collection of components, such as PyTorch, TensorFlow, Fast.ai and scikit-learn, for performing deep learning and machine learning tasks. Note that this will install the deep learning frameworks into your currently active Pro Python environment; if you wish to install in an environment aside from the default arcgispro-py3 environment, switch to that environment before running the MSI using either ArcGIS Pro's Python manager UI or on the command line with proswap. Any subsequent clones of that environment will also include this full collection of packages.
Alternatively,
for a cloned environment of ArcGIS Pro's default environment, deep-learning-essentials metapackage can be used to install the required dependencies which can be done using the following command, in the Python Command Prompt (included with ArcGIS Pro):
This overview describes how to use ArcGIS API for Python to write Python code, incorporating capabilities such as mapping, query, analysis, geocoding, routing, portal administration, and more. Browse the sample notebooks to get started. You may choose to experience these sample notebooks in a live environment as they are available as ArcGIS Notebooks.
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