What this book covers
Chapter 1, Package Installation and Management, explains how to install and manage the code libraries used in the book.
Chapter 2, Introduction to Geospatial Code Libraries, covers the major code libraries used to process and analyze geospatial data.
Chapter 3, Introduction to Geospatial Databases, introduces the geospatial databases used for data storage and analysis.
Chapter 4, Data Types, Storage, and Conversion, focuses on the many different data types (both vector and raster) that exist within GIS.
Chapter 5, Vector Data Analysis, covers Python libraries such as Shapely, OGR, and GeoPandas. which are used for analyzing and processing vector data.
Chapter 6, Raster Data Processing, explores using GDAL and Rasterio to process raster datasets in order to perform geospatial analysis.
Chapter 7, Geoprocessing with Geodatabases, shows the readers how to use Spatial SQL to perform geoprocessing with database tables containing a spatial column.
Chapter 8, Automating QGIS Analysis, teaches the readers how to use PyQGIS to automate analysis within the QGIS mapping suite.
Chapter 9, ArcGIS API for Python and ArcGIS Online, introduces the ArcGIS API for Python, which enables users to interact with Esri's cloud platform, ArcGIS Online, using Python 3.
Chapter 10, Geoprocessing with a GPU Database, covers using Python tools to interact with cloud-based data to search and process data.
Chapter 11, Flask and GeoAlchemy2, describes how to use the Flask Python web framework and the GeoAlchemy ORM to perform spatial data queries.
Chapter 12, GeoDjango, covers using the Django Python web framework and the GeoDjango ORM to perform spatial data queries.
Chapter 13, Geospatial REST API, teaches the readers how to create a REST API for geospatial data.
Chapter 14, Cloud Geodatabase Analysis and Visualization, introduces the readers to the CARTOframes Python package, enabling the integration of Carto maps, analysis, and data services into data science workflows.
Chapter 15, Automating Cloud Cartography, covers a new location data visualization library for Jupyter Notebooks.
Chapter 16, Python Geoprocessing with Hadoop, explains how to perform geospatial analysis using distributed servers.
python开发的一本新书。
Hello! Python is written for people who’d like to learn more about Python
and how to program. You might be completely new to programming, or
you might have some prior experience; either way, Hello! Python will take
you from your first steps through writing networked games and web
applications.
The style of this book is different from most programming books. Rather
than present a laundry list of every possible feature, I’ve chosen to show
you a more real-world picture. Starting with chapter 2, you’ll be follow-
ing along as we write real, useful programs—warts and all. All program-
ming language features have a purpose, and it’s hard to recognize that
purpose if you don’t see all the bugs, broken code, and badly written pro-
grams that the feature is supposed to help with.
This book is the result of teaching computer graphics for one and two semester,<br>year two/three undergraduate and postgraduate lecture courses in Computer Graphics.<br>Throughout the book, theory is followed by implementation using C/C++ and<br>complete programs are provided with suggestions for change to enhance student<br>understanding. During 30 years of university teaching the author has become aware<br>of the frustration that many students suffer, of code fragments that ‘never quite<br>work’ and programs that on a different system require system dependent additions!
Exploring the world of game development with a focus on C++, this book explans the basics of mathematics as it relates to game programming, covers the fundamentals of C++, and describes a number of algorithms commonly used in games
