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QGIS Python Programming Cookbook
QGIS Python Programming Cookbook

QGIS Python Programming Cookbook: Over 140 recipes to help you turn QGIS from a desktop GIS tool into a powerful automated geospatial framework

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QGIS Python Programming Cookbook

Chapter 2. Querying Vector Data

In this chapter, we will cover the following recipes:

  • Loading a vector layer from a file
  • Loading a vector layer from a geodatabase
  • Examining vector layer features
  • Examining vector layer attributes
  • Filtering a layer by geometry
  • Filtering a layer by attributes
  • Buffering a feature
  • Measuring the distance between two points
  • Measuring the distance along a line
  • Calculating the area of a polygon
  • Creating a spatial index
  • Calculating the bearing of a line

Introduction

This chapter demonstrates how to work with vector data through Python in QGIS. We will first work through loading different sources of vector data. Next, we'll move on to examining the contents of the data. Then, we'll spend the remainder of the chapter performing spatial and database operations on vector data.

Loading a vector layer from a file sample

This recipe describes the most common type of data used in QGIS, a file. In most cases, you'll start a QGIS project by loading a shapefile.

Getting ready

For ease of following the examples in this book, it is recommended that you create a directory called qgis_data in your root or user directory, which provides a short pathname. This setup will help prevent the occurrence of any frustrating errors resulting from path-related issues on a given system. In this recipe and others, we'll use a point shapefile of New York City museums, which you can download from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip this file and place the shapfile's contents in a directory named nyc within your qgis_data directory.

How to do it...

Now, we'll walk through the steps of loading a shapefile and adding it to the map, as follows:

  1. Start QGIS.
  2. From the Plugins menu, select Python Console.
  3. In the Python console, create the layer:
    layer...

Loading a vector layer from a spatial database

The PostGIS geodatabase is based on the open source Postgres database. The geodatabase provides powerful geospatial data management and operations. PyQGIS fully supports PostGIS as a data source. In this recipe, we'll add a layer from a PostGIS database.

Getting ready

Installing and configuring PostGIS is beyond the scope of this book, so we'll use a sample geospatial database interface from the excellent service www.QGISCloud.com. www.QGISCloud.com has its own Python plugin called QGIS Cloud. You can sign up for free and create your own geodatabase online by following the site's instructions, or you can use the example used in the recipe.

How to do it...

Perform the following steps to load a PostGIS layer into a QGIS map:

  1. First, create a new DataSourceURI instance:
    uri = QgsDataSourceURI()
    
  2. Next, create the database connection string:
    uri.setConnection("spacialdb.com", "9999", "lzmjzm_hwpqlf", "lzmjzm_hwpqlf...

Examining vector layer features

Once a vector layer is loaded, you may want to investigate the data. In this recipe, we'll load a vector point layer from a shapefile and take a look at the x and y values of the first point.

Getting ready

We'll use the same New York City Museums layer from Loading a vector layer from a file recipe in this chapter. You can download the layer from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will load the layer, get the features, grab the first feature, obtain its geometry, and take a look at the values for the first point:

  1. First, load the layer:
    layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp", "New York City Museums", "ogr")
    
  2. Next, get an iterator of the layer's features:
    features = layer.getFeatures()
    
  3. Now...

Examining vector layer attributes

A true GIS layer contains both spatial geometry and database attributes. In this recipe, we'll access a vector point layer's attributes in PyQGIS. We'll use a file-based layer from a shapefile, but once a layer is loaded in QGIS, every vector layer works the same way.

Getting ready

Once again, we'll use the same New York City Museums layer from the Loading a vector layer from a file recipe in this chapter. You can download the layer from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll load the layer, access the features iterator, grab the first feature, and then view the attributes as a Python list:

  1. First, load the shapefile as a vector layer:
    layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp", "New York...

Filtering a layer by geometry

In this recipe, we'll perform a spatial operation to select a subset of a point layer based on the points contained in an overlapping polygon layer. We'll use shapefiles in both cases, with one being a point layer and the other a polygon. This kind of subset is one of the most common GIS operations.

Getting ready

We will need two new shapefiles that have not been used in previous recipes. You can download the point layer from https://geospatialpython.googlecode.com/files/MSCities_Geo_Pts.zip.

Similarly, you can download the geometry layer from https://geospatialpython.googlecode.com/files/GIS_CensusTract.zip.

Unzip these shapefiles and place them in a directory named ms within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will perform several steps to select features in the point layer that fall within the polygon layer, as follows:

  1. First, load the point layer:
    lyrPts = QgsVectorLayer("/qgis_data/ms...

Introduction


This chapter demonstrates how to work with vector data through Python in QGIS. We will first work through loading different sources of vector data. Next, we'll move on to examining the contents of the data. Then, we'll spend the remainder of the chapter performing spatial and database operations on vector data.

Loading a vector layer from a file sample


This recipe describes the most common type of data used in QGIS, a file. In most cases, you'll start a QGIS project by loading a shapefile.

Getting ready

For ease of following the examples in this book, it is recommended that you create a directory called qgis_data in your root or user directory, which provides a short pathname. This setup will help prevent the occurrence of any frustrating errors resulting from path-related issues on a given system. In this recipe and others, we'll use a point shapefile of New York City museums, which you can download from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip this file and place the shapfile's contents in a directory named nyc within your qgis_data directory.

How to do it...

Now, we'll walk through the steps of loading a shapefile and adding it to the map, as follows:

  1. Start QGIS.

  2. From the Plugins menu, select Python Console.

  3. In the Python console, create the layer:

    layer = QgsVectorLayer...

Loading a vector layer from a spatial database


The PostGIS geodatabase is based on the open source Postgres database. The geodatabase provides powerful geospatial data management and operations. PyQGIS fully supports PostGIS as a data source. In this recipe, we'll add a layer from a PostGIS database.

Getting ready

Installing and configuring PostGIS is beyond the scope of this book, so we'll use a sample geospatial database interface from the excellent service www.QGISCloud.com. www.QGISCloud.com has its own Python plugin called QGIS Cloud. You can sign up for free and create your own geodatabase online by following the site's instructions, or you can use the example used in the recipe.

How to do it...

Perform the following steps to load a PostGIS layer into a QGIS map:

  1. First, create a new DataSourceURI instance:

    uri = QgsDataSourceURI()
    
  2. Next, create the database connection string:

    uri.setConnection("spacialdb.com", "9999", "lzmjzm_hwpqlf", "lzmjzm_hwpqlf", "0e9fcc39")
    
  3. Now, describe the data source...

Examining vector layer features


Once a vector layer is loaded, you may want to investigate the data. In this recipe, we'll load a vector point layer from a shapefile and take a look at the x and y values of the first point.

Getting ready

We'll use the same New York City Museums layer from Loading a vector layer from a file recipe in this chapter. You can download the layer from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will load the layer, get the features, grab the first feature, obtain its geometry, and take a look at the values for the first point:

  1. First, load the layer:

    layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp", "New York City Museums", "ogr")
    
  2. Next, get an iterator of the layer's features:

    features = layer.getFeatures()
    
  3. Now, get the first feature from the iterator:

    f = features...

Examining vector layer attributes


A true GIS layer contains both spatial geometry and database attributes. In this recipe, we'll access a vector point layer's attributes in PyQGIS. We'll use a file-based layer from a shapefile, but once a layer is loaded in QGIS, every vector layer works the same way.

Getting ready

Once again, we'll use the same New York City Museums layer from the Loading a vector layer from a file recipe in this chapter. You can download the layer from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll load the layer, access the features iterator, grab the first feature, and then view the attributes as a Python list:

  1. First, load the shapefile as a vector layer:

    layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp", "New York City Museums", "ogr")
    
  2. Next, get the features...

Filtering a layer by geometry


In this recipe, we'll perform a spatial operation to select a subset of a point layer based on the points contained in an overlapping polygon layer. We'll use shapefiles in both cases, with one being a point layer and the other a polygon. This kind of subset is one of the most common GIS operations.

Getting ready

We will need two new shapefiles that have not been used in previous recipes. You can download the point layer from https://geospatialpython.googlecode.com/files/MSCities_Geo_Pts.zip.

Similarly, you can download the geometry layer from https://geospatialpython.googlecode.com/files/GIS_CensusTract.zip.

Unzip these shapefiles and place them in a directory named ms within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will perform several steps to select features in the point layer that fall within the polygon layer, as follows:

  1. First, load the point layer:

    lyrPts = QgsVectorLayer("/qgis_data/ms/MSCities_Geo_Pts...

Filtering a layer by attributes


In addition to the spatial queries outlined in the previous recipe, we can also subset a layer by its attributes. This type of query resembles a more traditional relational database query and in fact uses SQL statements. In this recipe, we will filter a point shapefile-based layer by an attribute.

Getting ready

We'll use the same New York City Museums layer used in the previous recipes in this chapter. You can download the layer from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we'll filter the layer by an attribute, select the filtered features, and zoom to them, as follows:

  1. First, we load the point layer:

    lyrPts = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp", "Museums", "ogr")
    
  2. Next, we add the layer to the map in order to visualize the points:

    QgsMapLayerRegistry...

Buffering a feature intermediate


Buffering a feature creates a polygon around a feature as a selection geometry or just a simple visualization. In this recipe, we'll buffer a point in a point feature and add the returned polygon geometry to the map.

Getting ready

Once again, we'll use the same New York City Museums layer. You can download the layer from https://geospatialpython.googlecode.com/svn/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

This recipe involves both a spatial operation and multiple visualizations. To do this, perform the following steps:

  1. First, load the layer:

    lyr = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp", "Museums", "ogr")
    
  2. Next, visualize the layer on the map:

    QgsMapLayerRegistry.instance().addMapLayers([lyr])
    
  3. Access the layer's features:

    fts = lyr.getFeatures()
    
  4. Grab the first feature:

    ft = fts.next()
    
  5. Select this feature:

    lyr.setSelectedFeatures...
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Description

If you are a geospatial analyst who wants to learn more about automating everyday GIS tasks or a programmer who is responsible for building GIS applications,this book is for you. The short, reusable recipes make concepts easy to understand. You can build larger applications that are easy to maintain when they are put together.

Who is this book for?

If you are a geospatial analyst who wants to learn more about automating everyday GIS tasks or a programmer who is responsible for building GIS applications,this book is for you. The short, reusable recipes make concepts easy to understand. You can build larger applications that are easy to maintain when they are put together.

What you will learn

  • Build a library of reusable scripts with ScriptRunner
  • Create, import, and edit geospatial data on disk or in memory
  • Get to know more about dynamic mapping
  • Create and add features to static maps
  • Create a mapbook
  • Reproject a vector layer
  • Geolocate photos on a map
  • Combine multiple rasters into one image

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Length: 340 pages
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Publication date : Mar 26, 2015
Length: 340 pages
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Table of Contents

10 Chapters
1. Automating QGIS Chevron down icon Chevron up icon
2. Querying Vector Data Chevron down icon Chevron up icon
3. Editing Vector Data Chevron down icon Chevron up icon
4. Using Raster Data Chevron down icon Chevron up icon
5. Creating Dynamic Maps Chevron down icon Chevron up icon
6. Composing Static Maps Chevron down icon Chevron up icon
7. Interacting with the User Chevron down icon Chevron up icon
8. QGIS Workflows Chevron down icon Chevron up icon
9. Other Tips and Tricks Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

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ainardi Sep 29, 2015
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this book makes me understand qgis, i am a engineer, working in c++,QTi recommanded it, from the basic qgis to advanced information this book is helpfull
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NG May 14, 2015
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The QGIS Python Programming Cookbook is the second great PyQGIS book published by Packt. The first one is Erik Westra’s Building Mapping Applications with QGIS. If you are new to PyQGIS and want to get started quickly I suggest you look into these two books, instead of the many convoluted, incomplete, and often outdated tutorials on the web or in other books. I personally started with Erik Westra’s book, which within in a few days, clarified a lot of thing to me. Then I looked into this book. Once you know the basics of PyQGIS and how it all works, this book is a great resource to boost your skills and learn many tricks. Because, let’s be honest, not everyone is capable of looking at the C++ QGIS documentation and translating it quickly into Python. Reading the documentation is not only a matter of translating C++ datatypes etc., which is actually the easy part, but it is more a matter of understanding how it all fits together. This is often not as clear as it is with other libraries, such as the much more intuitive ArcPy. This book fills in many of those gaps. The level of detail is very enjoyable, as many of the recipes describe each line of code in great detail, even sometimes when it seems unnecessary.After a general intro to PyQGIS and setting up environments and an IDE (Eclipse, using PyDev), Chapter 2 and 3 are all about vector data. From simply loading data, to querying data, to creating layers in memory, to adding and removing features, to joining attributes; it is all in there. If you work a lot with vector data these two chapters will either teach you how to accomplish many common tasks or they will inspire you to look into new things.Chapter 4 goes into raster data, and although that is not the focus of my work, it seems like if features some very useful recipes, such as swapping raster bands, reprojecting, building pyramids and classification. I know these are things that are commonly asked about in forums.Chapter 5 covers dynamic maps, which talks a lot about accessing and working with the canvas, most likely one of the most commonly used features when working with PyQGIS. It also goes into topics such as creating graduated symbol renderers (again, something that is asked on forums a lot), using charts, and building tools that directly use the canvas (such as a selection tool, or placing points on the map).Chapter 6 then talks about making static maps, so basically it is about doing in a programmatic way what you would manually do using the Print Composer. Again, this is not the focus of what I do but I can tell you that this is a fairly little talked about topic in other resources. I was not aware this was even possible until I looked into this book.Chapter 7 teaches you how to interact with users, that is, how to work with message bars and dialogs. But it also covers other very useful recipes, such as programming a progress bar or using radio buttons and checkboxes.Chapter 8 touches upon more advanced topics, such as NDVI, geocoding addresses, tracking a GPS device and performing nearest neighbor analysis or heat maps. Perhaps not the things you do on a daily basis, but nevertheless it is very convenient to have these recipes. Although not all are directly relevant to me I thought this was still an inspiring chapter as it showed me some possibilities of PyGIS that I had not thought about.The final chapter, Chapter 9, is a collection of random tips and tricks that do not directly fit any of the other chapters.All in all, I would say that this is most likely the most useful PyQGIS book out at this point, although if you are a complete beginner I highly suggest you look into Erik Westra’s book as well, which will teach you the necessary basics and many more advanced topics as well. If you own these two books you will not have to look into any other ones.The downsides? No serious downsides, but the only thing that might be missing is a chapter on PyQt. Although PyQt is used in a few recipes, I feel like that it is one of the most important parts if one works a lot with PyQGIS, especially once one is building plugins. Although not directly part of the QGIS API, I feel like a lot of readers would be incredibly thankful for an entire chapter on it.Another little piece of advice: this book should probably contain ’PyQGIS’ in the title, such as ‘PyQGIS Programming Cookbook’, because a lot of us actually browse the web for things like ‘PyQGIS book’, which usually returns some of the less useful resources.
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Rudy J. Stricklan Sep 01, 2017
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I found this book well worth the money and valuable for my QGIS coding purposes.Pluses:• Introduces and explains the setup of a simple yet powerful PyQGIS development environment using the QGIS Script Runner plugin and the PyDEV Python IDE• Has 170+ practical PyQGIS coding examples that are well-explained• Applicable to Linux, Windows and MacOS environmentsMinuses:• Assumes quite a bit of prior QGIS experience and terminology—it’s not a book for beginners• The section on the PyQGIS API assumes you have experience understanding the QGIS C++ API, which in my case I do not. I wish I could find a good text that provides an explanation of — and examples of using— the PyQGIS API from a Python programmer’s point of view.• Ditto with the section on building QGIS plugins—it’s pretty much a Reader’s Digest rehash of the QGIS document on the same topic, glossing over subjects like resource files and the like. Again, maybe ‘resources’ is standard terminology for C++ programmers (icons, bitmaps, etc.), but it wouldn’t insult Python programmers’ intelligences to devote a line or two of explanations or examples for them.Again, well worth the money for my specific purposes.
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Amazon Customer Nov 28, 2017
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Great book
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Josiah May 11, 2015
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I'm learning PyQGIS while working on a project, and have found this book to a good resource. It's pretty straightforward and well-organized. I like how it breaks down exercises into compact parts, a few paragraphs, with sciprts that dont rely upon variables or data referenced prior in the book. I also use the PyQGIS Developer Cookbook, which is also pretty great (and free!), but it does have a few typos here and there, and build scripts up with variables used much earlier. Perhaps because I'm a beginner to PyQGIS and Python, the Joel Lawhead books is more appealing. I especially like chapter 3's coverage of how to add a field to a vector layer, as well as chapt 8's workflow coverage, especially the part on collecting field data.With Open Source and technology, you'll still have to rely upon Stack Exchange and other online resources but it's nice to have a comprehensive book availabe too. Now, I just wish the amazing and wondeful QGIS development team would bring back the 'export as python script' option in Graphical Modeler. That way you could quickly see what your model looks like coded out, and reverse engineer your own code.I'm still working my way through this book, but it's proving to be useful, and probably worth checking out if you're working with PyQGIS.
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