Book Image

ArcPy and ArcGIS - Second Edition

By : Silas Toms, Dara OBeirne
Book Image

ArcPy and ArcGIS - Second Edition

By: Silas Toms, Dara OBeirne

Overview of this book

ArcGIS allows for complex analyses of geographic information. The ArcPy module is used to script these ArcGIS analyses, providing a productive way to perform geo-analyses and automate map production. The second edition of the book focuses on new Python tools, such as the ArcGIS API for Python. Using Python, this book will guide you from basic Python scripting to advanced ArcPy script tools. This book starts off with setting up your Python environment for ArcGIS automation. Then you will learn how to output maps using ArcPy in MXD and update feature class in a geodatabase using arcpy and ArcGIS Online. Next, you will be introduced to ArcREST library followed by examples on querying, updating and manipulating ArcGIS Online feature services. Further, you will be enabling your scripts in the browser and directly interacting with ArcGIS Online using Jupyter notebook. Finally, you can learn ways to use of ArcPy to control ArcGIS Enterprise and explore topics on deployments, data quality assurances, data updates, version control, and editing safeguards. By the end of the book, you will be equipped with the knowledge required to create automated analysis with administration reducing the time-consuming nature of GIS.
Table of Contents (13 chapters)
Introduction to ArcGIS Online

Introduction to the ArcGIS API for Python

The ArcGIS API for Python is the interface in which you can program your on-premise and cloud GIS web services using Python. In December 2016, ESRI officially released the 1.0 version of the API. It is considered a Pythonic implementation of an API, which means it conforms to the best practices in its design and uses the standard data structures any professional Python programmer would be familiar with. It begins to implement some of the long-held best practices that are used by traditional programmers for the GIS professional. To get started with the API, we will need to configure our machines and begin to learn a new environment for Python programming using Anaconda and Jupyter.

Installing and configuring Anaconda with Jupyter