Recently, we were required to implement a custom “New Project Wizard” for use in a client’s internal QGIS installation. The goal here was that users would be required to fill out certain metadata fields whenever they created a new QGIS project.

Fortunately, the PyQGIS (and underlying Qt) libraries makes this possibly, and relatively straightforward to do. Qt has a powerful API for creating multi-page “wizard” type dialogs, via the QWizard and QWizardPage classes. Let’s have a quick look at writing a custom wizard using these classes, and finally we’ll hook it into the QGIS interface using some PyQGIS magic.

We’ll start super simple, creating a single page wizard with no settings. To do this we first create a Page1 subclass of QWizardPage, a ProjectWizard subclass of QWizard, and a simple runNewProjectWizard function which launches the wizard. (The code below is designed for QGIS 3.0, but will run with only small modifications on QGIS 2.x):

class Page1(QWizardPage):

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setTitle('General Properties')
        self.setSubTitle('Enter general properties for this project.')


class ProjectWizard(QWizard):
    
    def __init__(self, parent=None):
        super().__init__(parent)
        
        self.addPage(Page1(self))
        self.setWindowTitle("New Project")


def runNewProjectWizard():
    d=ProjectWizard()
    d.exec()

If this code is executed in the QGIS Python console, you’ll see something like this:

Not too fancy (or functional) yet, but still not bad for 20 lines of code! We can instantly make this a bit nicer by inserting a custom logo into the widget. This is done by calling setPixmap inside the ProjectWizard constructor.

class ProjectWizard(QWizard):
    
    def __init__(self, parent=None):
        super().__init__(parent)
        
        self.addPage(Page1(self))
        self.setWindowTitle("New Project")

        logo_image = QImage('path_to_logo.png')
        self.setPixmap(QWizard.LogoPixmap, QPixmap.fromImage(logo_image))

That’s a bit nicer. QWizard has HEAPS of options for tweaking the wizards — best to read about those over at the Qt documentation. Our next step is to start adding some settings to this wizard. We’ll keep things easy for now and just insert a number of text input boxes (QLineEdits) into Page1:

class Page1(QWizardPage):

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setTitle('General Properties')
        self.setSubTitle('Enter general properties for this project.')

        # create some widgets
        self.project_number_line_edit = QLineEdit()
        self.project_title_line_edit = QLineEdit()
        self.author_line_edit = QLineEdit()        
        
        # set the page layout
        layout = QGridLayout()
        layout.addWidget(QLabel('Project Number'),0,0)
        layout.addWidget(self.project_number_line_edit,0,1)
        layout.addWidget(QLabel('Title'),1,0)
        layout.addWidget(self.project_title_line_edit,1,1)
        layout.addWidget(QLabel('Author'),2,0)
        layout.addWidget(self.author_line_edit,2,1)
        self.setLayout(layout)

There’s nothing particularly new here, especially if you’ve used Qt widgets before. We make a number of QLineEdit widgets, and then create a grid layout containing these widgets and accompanying labels (QLabels). Here’s the result if we run our wizard now:

So now there’s the option to enter a project number, title and author. The next step is to force users to populate these fields before they can complete the wizard. Fortunately, QWizardPage has us covered here and we can use the registerField() function to do this. By calling registerField, we make the wizard aware of the settings we’ve added on this page, allowing us to retrieve their values when the wizard completes. We can also use registerField to automatically force their population by appending a * to the end of the field names. Just like this…

class Page1(QWizardPage):
    def __init__(self, parent=None):
        super().__init__(parent)
        ...
        self.registerField('number*',self.project_number_line_edit)
        self.registerField('title*',self.project_title_line_edit)
        self.registerField('author*',self.author_line_edit)

If we ran the wizard now, we’d be forced to enter something for project number, title and author before the Finish button becomes enabled. Neat! By registering the fields, we’ve also allowed their values to be retrieved after the wizard completes. Let’s alter runNewProjectWizard to retrieve these values and do something with them:

def runNewProjectWizard():
   d=ProjectWizard()
   d.exec()

   # Set the project title
   title=d.field('title')
   QgsProject.instance().setTitle(d.field('title'))

   # Create expression variables for the author and project number
   number=d.field('number')
   QgsExpressionContextUtils.setProjectVariable(QgsProject.instance(),'project_number', number)
   author=d.field('author')
   QgsExpressionContextUtils.setProjectVariable(QgsProject.instance(),'project_author', author)
 

Here, we set the project title directly and create expression variables for the project number and author. This allows their use within QGIS expressions via the @project_number and @project_author variables. Accordingly, they can be embedded into print layout templates so that layout elements are automatically populated with the corresponding author and project number. Nifty!

Ok, let’s beef up our wizard by adding a second page, asking the user to select a sensible projection (coordinate reference system) for their project. Thanks to improvements in QGIS 3.0, it’s super-easy to embed a powerful pre-made projection selector widget into your scripts, which even includes a handy preview of the area of the world that the projection is valid for.

class Page2(QWizardPage):

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setTitle('Project Coordinate System')
        self.setSubTitle('Choosing an appropriate projection is important to ensure accurate distance and area measurements.')
        
        self.proj_selector = QgsProjectionSelectionTreeWidget()
        layout = QVBoxLayout()
        layout.addWidget(self.proj_selector)
        self.setLayout(layout)
        
        self.registerField('crs',self.proj_selector)
        self.proj_selector.crsSelected.connect(self.crs_selected)
        
    def crs_selected(self):
        self.setField('crs',self.proj_selector.crs())
        self.completeChanged.emit()
        
    def isComplete(self):
        return self.proj_selector.crs().isValid()

There’s a lot happening here. First, we subclass QWizardPage to create a second page in our widget. Then, just like before, we add some widgets to this page and set the page’s layout. In this case we are using the standard QgsProjectionSelectionTreeWidget to give users a projection choice. Again, we let the wizard know about our new setting by a call to registerField. However, since QWizard has no knowledge about how to handle a QgsProjectionSelectionTreeWidget, there’s a bit more to do here. So we make a connection to the projection selector’s crsSelected signal, hooking it up to a function which sets the wizard’s “crs” field value to the widget’s selected CRS. Here, we also emit the completeChanged signal, which indicates that the wizard page should re-validate the current settings. Lastly, we override QWizardPage’s isComplete method, checking that there’s a valid CRS selection in the selector widget. If we run the wizard now we’ll be forced to choose a valid CRS from the widget before the wizard allows us to proceed:

Lastly, we need to adapt runNewProjectWizard to also handle the projection setting:

def runNewProjectWizard():
    d=ProjectWizard()
    d.exec()

    # Set the project crs
    crs=d.field('crs')
    QgsProject.instance().setCrs(crs)

    # Set the project title
    title=d.field('title')
    ...

Great! A fully functional New Project wizard. The final piece of the puzzle is triggering this wizard when a user creates a new project within QGIS. To do this, we hook into the iface.newProjectCreated signal. By connecting to this signal, our code will be called whenever the user creates a new project (after all the logic for saving and closing the current project has been performed). It’s as simple as this:

iface.newProjectCreated.connect(runNewProjectWizard)

Now, whenever a new project is made, our wizard is triggered – forcing users to populate the required fields and setting up the project accordingly!

There’s one last little bit to do – we also need to prevent users cancelling or closing the wizard before completing it. That’s done by changing a couple of settings in the ProjectWizard constructor, and by overriding the default reject method (which prevents closing the dialog by pressing escape).

class ProjectWizard(QWizard):
    
    def __init__(self, parent=None):
        super().__init__(parent)
        ...
        self.setOption(QWizard.NoCancelButton, True)
        self.setWindowFlags(self.windowFlags() | QtCore.Qt.CustomizeWindowHint)
        self.setWindowFlags(self.windowFlags() & ~QtCore.Qt.WindowCloseButtonHint)

    def reject(self):
        pass

Here’s the full version of our code, ready for copying and pasting into the QGIS Python console:

icon_path = '/home/nyall/nr_logo.png'

class ProjectWizard(QWizard):
    
    def __init__(self, parent=None):
        super().__init__(parent)
        
        self.addPage(Page1(self))
        self.addPage(Page2(self))
        self.setWindowTitle("New Project")
        
        logo_image=QImage('path_to_logo.png')
        self.setPixmap(QWizard.LogoPixmap, QPixmap.fromImage(logo_image))
        
        self.setOption(QWizard.NoCancelButton, True)
        self.setWindowFlags(self.windowFlags() | QtCore.Qt.CustomizeWindowHint)
        self.setWindowFlags(self.windowFlags() & ~QtCore.Qt.WindowCloseButtonHint)
    def reject(self):
        pass
class Page1(QWizardPage):
    
    def __init__(self, parent=None):
        super().__init__(parent)
        self.setTitle('General Properties')
        self.setSubTitle('Enter general properties for this project.')

        # create some widgets
        self.project_number_line_edit = QLineEdit()
        self.project_title_line_edit = QLineEdit()
        self.author_line_edit = QLineEdit()        
        
        # set the page layout
        layout = QGridLayout()
        layout.addWidget(QLabel('Project Number'),0,0)
        layout.addWidget(self.project_number_line_edit,0,1)
        layout.addWidget(QLabel('Title'),1,0)
        layout.addWidget(self.project_title_line_edit,1,1)
        layout.addWidget(QLabel('Author'),2,0)
        layout.addWidget(self.author_line_edit,2,1)
        self.setLayout(layout)
        
        self.registerField('number*',self.project_number_line_edit)
        self.registerField('title*',self.project_title_line_edit)
        self.registerField('author*',self.author_line_edit)
 
 
class Page2(QWizardPage):
    
    def __init__(self, parent=None):
        super().__init__(parent)
        self.setTitle('Project Coordinate System')
        self.setSubTitle('Choosing an appropriate projection is important to ensure accurate distance and area measurements.')
        
        self.proj_selector = QgsProjectionSelectionTreeWidget()
        layout = QVBoxLayout()
        layout.addWidget(self.proj_selector)
        self.setLayout(layout)
        
        self.registerField('crs',self.proj_selector)
        self.proj_selector.crsSelected.connect(self.crs_selected)
        
    def crs_selected(self):
        self.setField('crs',self.proj_selector.crs())
        self.completeChanged.emit()
        
    def isComplete(self):
        return self.proj_selector.crs().isValid()
 
        
def runNewProjectWizard():
    d=ProjectWizard()
    d.exec()
    
    # Set the project crs
    crs=d.field('crs')
    QgsProject.instance().setCrs(crs)
    
    # Set the project title
    title=d.field('title')
    QgsProject.instance().setTitle(d.field('title'))

    # Create expression variables for the author and project number
    number=d.field('number')
    QgsExpressionContextUtils.setProjectVariable(QgsProject.instance(),'project_number', number)
    author=d.field('author')
    QgsExpressionContextUtils.setProjectVariable(QgsProject.instance(),'project_author', author)
    
    
iface.newProjectCreated.connect(runNewProjectWizard)

Following our recent successful QGIS Layout and Reporting Engine crowdfunding campaign, we’ve been hard at working ripping up the internals of the QGIS 2.x print composer and rebuilding a brand new, shiny QGIS layouts engine. This is exciting work – it’s very satisfying to be able to cleanup a lot of the old composer code in QGIS and take opportunities along the way to fix long standing bugs and add new features.

While it’s not ready for daily use yet, there’s already been a lot of interesting changes which have landed in the layouts work as a result of this campaign. Let’s take a look at what’s been implemented so far…

• We’ve added support for different measurements units all throughout layouts. While this means it’s now possible to set page sizes using centimeters, inches, pixels, points, etc, it goes much deeper than just that. In layouts, everything which has a size or position can take advantage of this unit support. So you can have page sizes in centimeters, but a map item with a size set in points, and positioned in millimeters! Having pixels as a unit type makes creation of screen-based layouts much easier – even right down to pixel perfect positioning and sizing of items…
• Page handling has been totally reworked. Instead of the single “number of pages” control available in QGIS 2.x, layouts have complete flexibility in page setup. It’s now possible to have a layout with mixed page sizes and orientations (including data defined page size for different pages in the layout!). 
• A revised status bar, with improved layout interaction widgets. We’ve also taken the opportunity to add some new features like a zoom level slider and option to zoom to layout width:
• Layout interaction tools (such as pan/zoom/insert item/etc) have been reworked. There’s now a much more flexible framework for creation of layout tools (based off the main QGIS map canvas approach), which even allows for plugins to implement their own layout interaction tools! As part of this we’ve addressed a long standing annoyance which meant that creating new items always drew the “preview” shape of the new item as a rectangle – even for non-rectangular items. Now you get a real shape showing exactly how the created item will be sized and positioned:
  
• On the topic of plugins – the layout branch has full support for plugin-provided item types. This means that QGIS plugins can create new classes of items which can be added to a layout. This opens the door for plugins allowing charts and visualisations which take advantage of all the mature Python and JS charting libraries! This is a really exciting change – in 2.x there was no way for plugins to extend or interact with composer, so we’re really keen to see where the community takes this when 3.0 is released.
• We’ve ported another feature commonly found in illustration/DTP applications. Now, when you’re creating a new item and just click in your layout (instead of click-and-drag), you get a handy dialog allowing you to specify the exact position and dimensions for the created item. You can again see in this dialog how layouts have full support for units for both the position and size:
• Another oft-requested feature which we’ve finally been able to add (thanks to the refactored and cleaned code) is a context menu for layouts! It’s currently quite empty, but will be expanded as this work progresses…
• Snapping to guides and grids has been reworked. We’ve added a new snapping marker to show exactly were items will be snapped to:
• Snapping to guides now occurs when creating new layout items (this didn’t happen in Composer in 2.x – only snapping to grids occurred when drawing new items).
• The snapped cursor position is shown in status bar whenever a snapped point will be used, instead of the unsnapped position.
• Unlike in Composers in QGIS 2.x, Layouts in 3.0 adopt the standard UX of dragging out rulers to create guide lines (instead of clicking on a ruler position to create a new guide). Creation of a horizontal guide is now done by grabbing the top ruler and dragging it down, and a vertical guide is created by grabbing the left ruler and dragging it out to the layout.
• Better feedback is given in the ruler when a guide can be dragged. We now show guide positions in the rulers, and give an indication (via mouse cursor change) when these guides can be repositioned by click-and-drag.
• Another very exciting change is the addition of a new “Guide Manager”. The guide manager allows numeric modification of existing guides and creation of new guides. Finally it’s possible to position guides at exact locations! Again, you can see the full support for layout units in place here – guides can be positioned using any available unit.
  
• There’s also a handy new shortcut in the Guide Manager to allow applying the guides from the current page to all other pages in your layout.
• We’ve refined the snapping logic. In Composer in QGIS 2.x,  grids would always take precedence whenever both a grid and guide were within tolerance of a point. Now, guides will always take precedence – since they have been manually set by users we make the assumption that they have been explicitly placed at highly desirable snapping locations, and should be selected over the general background grid. Additionally, grid snapping was previously only done if BOTH the x and y of the point could be snapped to the grid. We now snap to the nearest grid line for x/y separately. This means if a point is close to a vertical grid line but not a horizontal one it will still snap to that nearby vertical grid line.
• Lastly, we’ve added a handy context menu to the rulers:

This is just a taster of the great new functionality coming in QGIS 3.0. This is all a direct result of the forward-thinking investments and generosity of the backers in our QGIS Layout and Reporting Engine crowdfunding campaign. Without their contributions, none of this would be possible – so our thanks go out to those organisations and individuals once again!

Stay tuned for more updates as the work continues…

Thanks to the tireless efforts and incredible generosity of the QGIS user community, our crowdfunded QGIS Layout and Reporting Engine campaign was a tremendous success! We’ve reached the funding goal for this project, and as a result QGIS 3.0 will include a more powerful print composer with a reworked code base. You can read more about what we have planned at the campaign page.

We’d like to take this opportunity to extend our heartfelt thanks to all the backers who have pledged to support this project:

• The Swiss QGIS User group (funded preliminary work in refactoring how compositions are handled and stored within projects)
• The QGIS Grant Program (2016) (funded preliminary work allowing for a flexible property framework which will be used within the project)
• Land Vorarlberg, Austria
• Tudor Bărăscu
• Oester Messtechnik GmbH, Thun, Switzerland
• Ferdinando Urbano, Italy
• Alta ehf, Reykjavik, Iceland
• Trage Wegen, Belgium
• QGIS Denmark User Group, Denmark
• Debuco Techniek B.V., Netherlands
• The QWAT Project
• QGIS Sweden User Group, Sweden
• Andreas Neumann
• Kristianstads kommun, Sweden
• City of Vevey, Switzerland
• Kanton Thurgau, Switzerland
• Ricardo Pinho, Portugal
• Portugese QGIS User Group, Portugal
• Waymotion, Portugal
• Lloyd Analytics LLC, USA
• Canton of Neuchâtel, Switzerland
• Hartmut Dickel, Switzerland

We’ve also received numerous anonymous contributions in addition to these – please know that the QGIS community extends their gratitude for your contributions too! This campaign was also successful thanks to The Agency for Data Supply and Efficiency, Denmark, who stepped up and have funded an initial component of this project directly.

We’d also like to thank every member of the QGIS community who assisted with promoting this campaign and bringing it to the attention of these backers. Without your efforts we would not have been able to reach these backers and the campaign would not have been successful.

We’ll be posting more updates as this work progresses. Stay tuned…

If you’ve been following our recent blog posts, you’ll be aware that we are currently running a crowd funding campaign to extend the capabilities of QGIS’ print composer. You can read full details about this over at the campaign page.

The good news is that we’ve just hit the mid way point of the funds! Many generous backers have stepped up with contributions and we’re well on the way to reaching the funding goal. However, we still need your help make this work a reality.

Right now, what we need most is interested users and community members who will reach out to their local QGIS users and seek more backing for the campaign. We need to publicise the campaign beyond the regular online QGIS community, to the thousands of enterprises and organisations which rely on QGIS for their daily mapping operations. We need community members who can get in contact with these organisations and help convince them that investing back into the open source software they utilise is beneficial (and often will even SAVE them money in the long run, due to the increased productivity that changes like our composer improvements will bring!).

So, while social media reshares have been vital to reaching the current stage, we now need more “hands on” helpers who will take this on. If you know of any organisations which depend on QGIS for their mapping outputs, now’s the time to get in contact with them directly and advise them of this campaign!

Last week we kicked off the first (of hopefully many) Australian QGIS hackfests Developers Meetings. It was attended by 3 of the core QGIS development team: Nathan Woodrow, Martin Dobias and myself (Nyall Dawson), along with various family members. While there’s been QGIS hackfests in Europe for over 10 years, and others scattered throughout various countries (I think there was a Japanese one recently… but Twitter’s translate tool leaves me with little confidence about this!), there’s been no events like this in the Southern hemisphere yet. I’ve been to a couple in Europe and found them to be a great way to build involvement in the project, for both developers and non-developers alike.

In truth the Australian hackfest plans began mostly an excuse for Nathan and I to catch up with Martin Dobias before he heads back out of this hemisphere and returns to Europe. That said, Nathan and I have long spoken about ways we can build up the QGIS community in Australia, so in many ways this was a trial run for future events. It was based it in Noosa, QLD (and yes, we did manage to tear ourselves away from our screens long enough to visit the beach!).

Nathan Woodrow (@NathanW2), myself (@nyalldawson), and Martin Dobias (@wonder-sk)

Here’s a short summary of what we worked on during the hackfest:

• Martin implemented a new iterator style accessor for vertices within geometries. The current approach to accessing vertices in QGIS is far from optimal. You either have the choice of an inefficient methods (eg QgsGeometry.asPolyline(), asPolygon(), etc) which requires translations of all vertices to a different data structure (losing any z/m dimensional values in the process), or an equally inefficient QgsAbstractGeometry.coordinateSequence() method, which at least keeps z/m values but still requires expensive copies of every vertex in the geometry. For QGIS 3.0 we’ve made a huge focus on optimising geometry operations and vertex access is one of the largest performance killers remaining in the QGIS code. Martin’s work adds a proper iterator for the vertices within a geometry object, both avoiding all these expensive copies and also simplifying the API for plugins. When this work lands traversing the vertices will become as simple as

for v in geom.vertices():
   ... do something with the vertex!

• Martin is also planning on extending this work to allow simple iteration over the parts and rings within geometries too. When this lands in QGIS we can expect to see much faster geometry operations.
• Nathan fixed a long standing hassle with running standalone PyQGIS scripts outside of the QGIS application on Windows. In earlier versions there’s a LOT of batch file mangling and environment variable juggling required before you can safely import the qgis libraries within Python. Thanks to Nathan’s work, in QGIS 3.0 this will be as simple as just making sure that the QGIS python libraries are included in your Python path, and then importing qgis.core/gui etc will work without any need to create environment variables for OSGEO/GDAL/PLUGINS/etc. Anyone who has fought with this in the past will definitely appreciate this change, and users of Python IDEs will also appreciate how simple it is now to make the PyQGIS libraries available in these environments.
• Nathan also worked on “profiles” support for QGIS 3.0. This work will add isolated user profiles within QGIS, similar to how Chrome handles this. Each profile has it’s own separate set of settings, plugins, etc. This work is designed to benefit both plugin developers and QGIS users within enterprise environments. You can read more about what Nathan has planned for this here.
• I continued the ongoing work of moving long running interface “blocking” operations to background tasks. In QGIS 3.0 many of these tasks churn away in the background, allowing you to continue work while the operation completes. It’s been implemented so far for vector and raster layer saving, map exports to images/PDF (not composers unfortunately), and obtaining feature counts within legends. During the hackfest I moved the layer import which occurs when you drag and drop a layer to a destination in the browser to a background task.
• On the same topic, I took some inspiration from a commit in Sourcepole’s QGIS fork and reworked how composer maps are cached. One of my biggest gripes with QGIS’ composer is how slow it is to work with when you’ve got a complex map included. This change pushes the map redrawing into a background thread, so that these redraws no longer “lock up” the UI. It makes a HUGE difference in how usable composer is. This improvement also allowed me to remove those confusing map item “modes” (Cache/Render/Rectangle) – now everything is redrawn silently in the background whenever required.
• Lastly, I spent a lot of time on a fun feature I’ve long wanted in QGIS – a unified search “locator” bar. This feature is heavily inspired by Qt Creator’s locator bar. It sits away down in the status bar, and entering any text here fires up a bunch of background search tasks. Inbuilt searches include searching the layers within the current project (am I the only one who loses layers in the tree in complex projects!?), print layouts in the project, processing algorithms, and menu/toolbar actions. The intention here is that plugins will “take over” and add additional search functionality, such as OSM place names searching, data catalog searches, etc. I’m sure when QGIS 3.0 is released this will quickly become indispensable!

The upcoming QGIS 3.0 locator bar

Big thanks go out to Nathan’s wife, Stacey, who organized most of the event and without whom it probably would never have happened, and to Lutra Consulting who sponsored an awesome dinner for the attendees.

We’d love this to be the first of many. The mature European hackfests are attended by a huge swath of the community, including translators, documentation writers, and plugin developers (amongst others). If you’ve ever been interested in finding out how you can get more involved in the project it’s a great way to dive in and start contributing. There’s many QGIS users in this part of the world and we really want to encourage a community of contributors who “give back” to the project. So let Nathan or myself know if you’d be interested in attending other events like this, or helping to organize them locally yourself…

A lot of cartographers have a love/hate relationship with label halos. On one hand they can be an essential technique for improving label readability, especially against complex background layers. On the other hand they tend to dominate maps and draw unwanted attention to the map labels.

In this post I’m going to share my preferred techniques for using label halos. I personally find this technique is a good approach which minimises the negative effects of halos, while still providing a good boost to label readability. (I’m also going to share some related QGIS 3.0 news at the end of this post!)

Let’s start with some simple white labels over an aerial image:

These labels aren’t very effective. The complex background makes them hard to read, especially the “Winton Shire” label at the bottom of the image. A quick and nasty way to improve readability is to add a black halo around the labels:

Sure, it’s easy to read the labels now, but they stand out way too much and it’s difficult to see anything here except the labels!

We can improve this somewhat through a better choice of halo colour:

This is much better. We’ve got readable labels which aren’t too domineering. Unfortunately the halo effect is still very prominent, especially where the background image varies a lot. In this case it works well for the labels toward the middle of the map, but not so well for the labels at the top and bottom.

A good way to improve this is to take advantage of blending (or “composition”) modes (which QGIS has native support for). The white labels will be most readable when there’s a good contrast with the background map, i.e. when the background map is dark. That’s why we choose a halo colour which is darker than the text colour (or vice versa if you’ve got dark coloured labels). Unfortunately, by choosing the mid-toned brown colour to make the halos blend in more, we are actually lightening up parts of this background layer and both reducing the contrast with the label and also making the halo more visible. By using the “darken” blend mode, the brown halo will only be drawn for pixels were the brown is darker then the existing background. It will darken light areas of the image, but avoid lightening pixels which are already dark and providing good contrast. Here’s what this looks like:

The most noticeable differences are the labels shown above darker areas – the “Winton Shire” label at the bottom and the “Etheridge Shire” at the top. For both these labels the halo is almost imperceptible whilst still subtly doing it’s part to make the label readable. (If you had dark label text with a lighter halo color, you can use the “lighten” blend mode for the same result).

The only issue with this map is that the halo is still very obvious around “Shire” in “Richmond Shire” and “McKinlay” on the left of the map. This can be reduced by applying a light blur to the halo:

There’s almost no loss of readability by applying this blur, but it’s made those last prominent halos disappear into the map. At first glance you probably wouldn’t even notice that there’s any halos being used here. But if we compare back against the original map (which used no halos) we can see the huge difference in readability:

Compare especially the Winton Shire label at the bottom, and the Richmond Shire label in the middle. These are much clearer on our tweaked map versus the above image.

Now for the good news… when QGIS 3.0 is released you’ll no longer have to rely on an external illustration/editing application to get this effect with your maps. In fact, QGIS 3.0 is bringing native support for applying many types of live layer effects to label buffers and background shapes, including blur. This means it will be possible to reproduce this technique directly inside your GIS, no external editing or tweaking required!

At North Road we believe that crowdfunding is a sustainable way to maintain and enhance open source software, like the QGIS open source GIS package. We’ve run a number of successful crowdfunding campaigns in the past, including support in QGIS for live layer effects, a point cluster renderer, and a unique value renderer for raster layers.

Now, we’re proud to announce our latest crowd funding endeavour, and our biggest to date, the QGIS Layout and Reporting Engine Campaign.

This campaign covers stage 1 of a large, ongoing project to modernise and expand on QGIS’ print composer and layout facilities. Over time QGIS’ composer functionality has grown extensively and now is capable of creating flexible, high quality cartographic outputs. However, we’ve now hit a limit where the current code architecture is prohibiting further improvements and important fixes. In order to add a reporting framework to QGIS, it is necessary for us to refactor and improve large sections of the composer code.

If this campaign is successful, we’ll be adding flexible report generation features to QGIS and cleaning up all the existing composer code. As part of these clean up, we’ll be taking the opportunity to tackle a number of current limitations which cannot be addressed in the current composition code:

• Layouts will become unit aware, allowing for item placement and properties using millimetres, inches, pixels, centimetres, points, etc.
• Layouts will have the ability to include mixed page sizes and orientations.
• Plugins will be able to create custom composer item types (eg allow utilisation of 3rd party graphing and visualisation libraries!).
• Individual layout items can be rasterised without affecting the rest of the layout. For instance, a map which requires rasterisation due to its use of blend modes will not require all other layout items (such as headings, legends, etc) to be rasterised. This will greatly benefit PDF outputs for complex map layouts.
• The code refresh will allow more extensive use of data defined layout item properties.
• A render caching system will be implemented for items, speeding up use of the layout designer and also paving the way for use of live paint effects on layout items (eg dynamic drop shadows).

Full details on what we have planned are available here: QGIS Layout and Reporting Engine Campaign.

To make it possible we need 30,000€ pledged before 31 May 2017. You can help make this a reality by supporting the campaign or by sharing the campaign page and increasing exposure to the campaign. Updates to follow!

I’ve recently spent some time optimising the performance of various QGIS plugins and algorithms, and I’ve noticed that there’s a few common performance traps which developers fall into when fetching features from a vector layer. In this post I’m going to explore these traps, what makes them slow, and how to avoid them.

As a bit of background, features are fetched from a vector layer in QGIS using a QgsFeatureRequest object. Common use is something like this:

request = QgsFeatureRequest()
for feature in vector_layer.getFeatures(request):
    # do something

This code would iterate over all the features in layer. Filtering the features is done by tweaking the QgsFeatureRequest, such as:

request = QgsFeatureRequest().setFilterFid(1001)
feature_1001 = next(vector_layer.getFeatures(request))

In this case calling getFeatures(request) just returns the single feature with an ID of 1001 (which is why we shortcut and use next(…) here instead of iterating over the results).

Now, here’s the trap: calling getFeatures is expensive. If you call it on a vector layer, QGIS will be required to setup an new connection to the data store (the layer provider), create some query to return data, and parse each result as it is returned from the provider. This can be slow, especially if you’re working with some type of remote layer, such as a PostGIS table over a VPN connection. This brings us to our first trap:

Trap #1: Minimise the calls to getFeatures()

A common task in PyQGIS code is to take a list of feature IDs and then request those features from the layer. A see a lot of older code which does this using something like:

for id in some_list_of_feature_ids:
    request = QgsFeatureRequest().setFilterFid(id)
    feature = next(vector_layer.getFeatures(request))
    # do something with the feature

Why is this a bad idea? Well, remember that every time you call getFeatures() QGIS needs to do a whole bunch of things before it can start giving you the matching features. In this case, the code is calling getFeatures() once for every feature ID in the list. So if the list had 100 features, that means QGIS is having to create a connection to the data source, set up and prepare a query to match a single feature, wait for the provider to process that, and then finally parse the single feature result. That’s a lot of wasted processing!

If the code is rewritten to take the call to getFeatures() outside of the loop, then the result is:

request = QgsFeatureRequest().setFilterFids(some_list_of_feature_ids)
for feature in vector_layer.getFeatures(request):
    # do something with the feature

Now there’s just a single call to getFeatures() here. QGIS optimises this request by using a single connection to the data source, preparing the query just once, and fetching the results in appropriately sized batches. The difference is huge, especially if you’re dealing with a large number of features.

Trap #2: Use QgsFeatureRequest filters appropriately

Here’s another common mistake I see in PyQGIS code. I often see this one when an author is trying to do something with all the selected features in a layer:

for feature in vector_layer.getFeatures():
    if not feature.id() in vector_layer.selectedFeaturesIds():
        continue

    # do something with the feature

What’s happening here is that the code is iterating over all the features in the layer, and then skipping over any which aren’t in the list of selected features. See the problem here? This code iterates over EVERY feature in the layer. If you’re layer has 10 million features, we are fetching every one of these from the data source, going through all the work of parsing it into a QGIS feature, and then promptly discarding it if it’s not in our list of selected features. It’s very inefficient, especially if fetching features is slow (such as when connecting to a remote database source).

Instead, this code should use the setFilterFids() method for QgsFeatureRequest:

request = QgsFeatureRequest().setFilterFids(vector_layer.selectedFeaturesIds())
for feature in vector_layer.getFeatures(request):
    # do something with the feature

Now, QGIS will only fetch features from the provider with matching feature IDs from the list. Instead of fetching and processing every feature in the layer, only the actual selected features will be fetched. It’s not uncommon to see operations which previously took many minutes (or hours!) drop down to a few seconds after applying this fix.

Another variant of this trap uses expressions to test the returned features:

filter_expression = QgsExpression('my_field > 20')
for feature in vector_layer.getFeatures():
    if not filter_expression.evaluate(feature):
        continue

    # do something with the feature

Again, this code is fetching every single feature from the layer and then discarding it if it doesn’t match the “my_field > 20” filter expression. By rewriting this to:

request = QgsFeatureRequest().setFilterExpression('my_field > 20')
for feature in vector_layer.getFeatures(request):
    # do something with the feature

we hand over the bulk of the filtering to the data source itself. Recent QGIS versions intelligently translate the filter into a format which can be applied directly at the provider, meaning that any relevant indexes and other optimisations can be applied by the provider itself. In this case the rewritten code means that ONLY the features matching the ‘my_field > 20’ criteria are fetched from the provider – there’s no time wasted messing around with features we don’t need.

Trap #3: Only request values you need

The last trap I often see is that more values are requested from the layer then are actually required. Let’s take the code:

my_sum = 0
for feature in vector_layer.getFeatures(request):
    my_sum += feature['value']

In this case there’s no way we can optimise the filters applied, since we need to process every feature in the layer. But – this code is still inefficient. By default QGIS will fetch all the details for a feature from the provider. This includes all attribute values and the feature’s geometry. That’s a lot of processing – QGIS needs to transform the values from their original format into a format usable by QGIS, and the feature’s geometry needs to be parsed from it’s original type and rebuilt as a QgsGeometry object. In our sample code above we aren’t doing anything with the geometry, and we are only using a single attribute from the layer. By calling setFlags( QgsFeatureRequest.NoGeometry ) and setSubsetOfAttributes() we can tell QGIS that we don’t need the geometry, and we only require a single attribute’s value:

my_sum = 0
request = QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry).setSubsetOfAttributes(['value'], vector_layer.fields() )
for feature in vector_layer.getFeatures(request):
    my_sum += feature['value']

None of the unnecessary geometry parsing will occur, and only the ‘value’ attribute will be fetched and populated in the features. This cuts down both on the processing required AND the amount of data transfer between the layer’s provider and QGIS. It’s a significant improvement if you’re dealing with larger layers.

Conclusion

Optimising your feature requests is one of the easiest ways to speed up your PyQGIS script! It’s worth spending some time looking over all your uses of getFeatures() to see whether you can cut down on what you’re requesting – the results can often be mind blowing!

Great news! Thanks in part to some generous last minute pledges, our QGIS Point Cluster Renderer campaign has successfully reached its target. This means that QGIS 3.0 will now include a full feature and flexible cluster renderer.

In the meantime, we’d like to extend our warmest thanks to the following generous contributors, whose pledges have made this work possible:

• Andreas Neumann
• Qtibia Engineering (Tudor Barascu)
• Karl-Magnus Jönsson
• Geonesia (Nicolas Ponzo)

Plus numerous additional anonymous backers whose generous contributions are also highly valued. If you run into any of these funders at a QGIS user group or conference, make sure you treat them like the GIS rock-stars they are!

Keep an eye out on our social media accounts as we’ll be posting more video demonstrations of this work as it lands in the QGIS codebase.

Last week I posted regarding some thoughts I’ve had recently concerning what I perceive as a general confusion about how QGIS is developed and how users can successfully get things to change in the project. The post certainly started a lot of conversation! However, based on feedback received I realise some parts of the posts were being misinterpreted and some clarification is needed. So here we go…

1. Please keep filing bug reports/feature requests

I don’t think I was very clear about this – but my original post wasn’t meant to be a discouragement from filing bug reports or feature requests. The truth is that there is a LOT of value in these reports, and if you don’t file a report then the QGIS team will never be aware of the bug or your feature idea. Here’s some reasons why you SHOULD file a report:

• QGIS developers are a conscientious mob, and generally take responsibility for any regressions they’ve caused by changes they’ve made. In other words, there’s very much an attitude of “I-broke-it, I’ll-fix-it” in the project. So, if a new feature is buggy or has broken something else then filing bugs ASAP is the best way to make the developer aware of these issues. In my experience they’ll usually be addressed rapidly.
• As mentioned in the original post – there’s always a pre-release bug fix sprint, so filing a bug (especially if it’s a critical one) may mean that it’s addressed during this sprint.
• Filing feature requests can gain traction if your idea is innovative, novel, or interesting enough to grab a developer’s attention!

Speaking for myself, I regularly check new incoming tickets (at least once a day), and I know I’m not the only one. So filing a report WILL bring your issue to developer’s attention. Which leads to…

2. Frustration is understandable!

I can honestly understand why people get frustrated and resort to an aggressive “why hasn’t this been fixed yet?!” style reply. I believe that these complaints are caused because people have the misunderstanding that filing a bug report is the ONLY thing they can do to get an issue fixed. If filing a report IS the only avenue you have to get something fixed/implemented, then it’s totally understandable to be annoyed when your ticket gets no results. This is a failing on behalf of the project though – we need to be clearly communicating that filing a report is the LEAST you can do. It’s a good first step, but on its own it’s just the beginning and needs to be followed up by one of the methods I described in the initial post.

3. It applies to more than just code

When I wrote the original piece I focused on just the code aspect of the QGIS project. That’s only because I’m a developer and it’s the area I know best. But it applies equally across the whole project, including documentation, translations, infrastructure, websites, packaging QGIS releases, etc. In fact, some of these non-code areas are the best entry points into the project as they don’t require a development background, and eg the documentation and translation teams have done a great job making it easy to submit contributions. Find something missing in the QGIS documentation? Add it yourself! Missing a translation of the website which prevents QGIS adoption within your community? Why not sponsor a translator to tackle this task?!

4. It applies to more than just QGIS!

Again, I wrote the original piece focusing on QGIS because that’s the project I’m most familiar with. You could just as easily substitute GDAL, GEOS, OpenLayers, PostGIS, Geoserver, R, D3, etc… in and it would be equally valid!

Hopefully that helps clarify some of the points raised by the earlier article. Let’s keep the discussion flowing – I’d love to hear if you have any other suggestions or questions raised by this topic.

In part 3 of my exploration of variables in QGIS 2.12, I’m going to dig into how variables are scoped in QGIS and what layer level variables are available (you can read parts 1 and 2 for a general introduction to variables).

Some background

Before we get to the good stuff, a bit of background in how variables work behind-the-scenes is important. Whenever an expression is evaluated in QGIS the context of the expression is considered. The context is built up from a set of scopes, which are all stacked on top of each other in order from least-specific to most-specific. It’s easier to explain with an example. Let’s take an expression used to set the source of a picture in a map composer. When this expression is evaluated, the context will consist of:

1. The global scope, consisting of variables set in the QGIS options dialog, and other installation-wide properties
2. The project scope, which includes variables set in the Project Properties dialog and the auto-generated project variables like @project_path, @project_title (you can read more about this in part 2)
3. A composer scope, with any variables set for the current composer, plus variables for @layout_pagewidth, @layout_pageheight, @layout_numpages, etc.
4. A composer item scope for the picture, with item-specific variables including @item_id

The more specific scopes will override any existing clashing variables from less specific scopes. So a global @my_var variable will be overridden by an @my_var variable set for the composer:

Another example. Let’s consider now an expression set for a data-defined label size. When this expression is evaluated the context will depend on where the map is being rendered. If it’s in the main map canvas then the context will be:

1. The global scope
2. The project scope
3. A map settings scope, with variables relating to how the map is being rendered. Eg @map_rotation, @map_scale, etc
4. A layer scope. More on this later, but the layer scope includes layer-level variables plus preset variables for @layer_name and @layer_id

If instead the map is being rendered inside a map item in a map composer, the context will be:

1. The global scope
2. The project scope
3. The composer scope
4. An atlas scope, if atlas is enabled. This contains variables like @atlas_pagename, @atlas_feature, @atlas_totalfeatures.
5. A composer item scope for the map item
6. A map settings scope (with scale and rotation determined by the map item’s settings)
7. The layer scope

Using layer level variables

Ok, enough with the details. The reason I’ve explained all this is to help explain when layer level variables come into play. Basically, they’ll be available whenever an expression is evaluated inside of a particular layer. This includes data defined symbology and labeling, field calculator, and diagrams. You can’t use a layer-level variable inside a composer label, because there’s no layer scope used when evaluating this. Make sense? Great! To set a layer level variable, you use the Variables section in the Layer Properties dialog:

Any layer level variables you set will be saved inside your current project, i.e. layer variables are per-layer and per-project. You can also see in the above screenshot that as well as the layer level variables QGIS also lists the existing variables from the Project and Global scopes. This helps show exactly what variables are accessible by the layer and whether they’ve been overridden by any scopes. You can also see that there’s two automatic variables, @layer_id and @layer_name, which contain the unique layer ID and user-set layer name too.

Potential use cases for layer-level variables

In the screenshot above I’ve set two variables, @class1_threshold and @class2_threshold. I’m going to use these to sync up some manual class breaks between rule based symbology and rule based labeling. Here’s how I’ve set up the rule-based symbols for the layer:

In a similar way, I’ve also created matching rule-based labeling (another new feature in QGIS 2.12):

Here’s what my map looks like now, with label and symbol colors matched:

If I’d hard-coded the manual class breaks, it would be a pain to keep the labeling and symbology in sync. I’d have to make sure that the breaks are updated everywhere I’ve used them in both the symbology and labeling settings. Aside from being boring, tedious work, this would also prevent immediate before/after comparisons. Using variables instead means that I can update the break value in a single place (the variables panel) and have all my labeling and symbols immediately reflect this change when I hit apply!

Another recent use case I had was teaming layer-level variables along with Time Manager. I wanted my points to falloff in both transparency and size with age, and this involved data defined symbol settings scattered all throughout my layer symbology. By storing the decay fall-off rate in a variable, I could again tweak this falloff by changing the value in a single place and immediately see the result. It also helps with readability of the data defined expressions. Instead of trying to decipher a random, hard-coded value, it’s instead immediately obvious that this value relates to a decay fall-off rate. Much nicer!

I’m sure there’s going to be hundreds of novel uses of layer-level variables which I never planned for when adding this feature. I’d love to hear about them though – leave a comment if you’d like to share your ideas!

One last thing – the new “layer_property” function

This isn’t strictly related to variables, but another new feature which was introduced in QGIS 2.12 was a new “layer_property” expression function. This function allows you to retrieve any one of a bunch of properties relating to a specific map layer, including the layer CRS, metadata, source path, etc.

This function can be used anywhere in QGIS. For instance, it allows you to insert dynamic metadata about layers into a print composer layout. In the screenshot below I’ve used expressions like layer_property(‘patron’,’crs’) and layer_property(‘patron’,’source’) to insert the CRS and source path of the “patron” layer into the label. If either the CRS or the file path ever changes, this label will be automatically updated to reflect the new values.

So there you go – layer level variables and the layer_property function – here in QGIS 2.12 and making your workflow in QGIS easier. In the final part of this series, we’ll explore the magical @value variable. Trust me, I’ve saved the best for last!

TimeManager is a fantastic plugin for QGIS which allows you to create animated maps from your data. You can read all about it here and here, and there’s a really nice demonstration of it here.

I’ve been playing with TimeManager a fair bit over the last month, and thought I’d share a quick tip on improving the appearance of TimeManager’s time stamp. TimeManager includes some basic functionality for placing a time stamp in the corner of your outputs, but it’s fairly limited. There’s only some basic appearance options, and no way to control the date or time formats displayed.

But, there’s a trick we can use to get around this: use a temporary point layer for the time stamp label. Let me elaborate:

1. Create a throwaway point layer. It doesn’t matter what fields or format this layer has.
2. Add a single point feature to this layer at the place you’d like the improved time stamp to appear at.

   

3. We don’t want to see the marker, so hide the symbol for this layer by setting it to use a transparent fill and outline.

   

4. Then, enable labels for this layer. Here’s the trick – set the label expression for the label to use “animation_datetime()” (or for QGIS 2.8, “$animation_datetime”). This is a custom function provided by the TimeManager plugin which evaluates to the current frame’s date and time.

   

5. Now, you can use all the built-in options within QGIS for styling this label. Buffers, drop shadows, background shapes… anything!

   

6. Apply and check. Much nicer!

   

7. To tweak the formatting of the time stamp’s date and time, you can modify the label expression using the built-in ‘format_date’, ‘year’, ‘month’, etc functions. Let’s try “format_date(animation_datetime(),’ddd dd MMM yyyy’)”:

   

Now, our final formatted time stamp looks like this:

…and there we go. Using this simple trick allows you to take advantage of all the possibilities which the QGIS labelling and expression engines allow!

*Bonus points for the first person to use this technique along with data defined controls for animating the label colour/size!

I’m pleased to announce that the crowdfunded work on layer effects for QGIS is now complete and available in the current development snapshots! Let’s dive in and explore how these effects work, and check out some of the results possible using them.

I’ll start with a simple polygon layer, with some nice plain styling:

If I open the properties for this layer and switch to the Style tab, there’s a new checkbox for “Draw effects“. Let’s enable that, and then click the little customise effects button to its right:

A new “Effects Properties” dialog opens:

You can see that currently the only effect listed is a “Source” effect. Source effects aren’t particularly exciting – all they do is draw the original layer unchanged. I’m going to change this to a “Blur” effect by clicking the “Effect type” combo box and selecting “Blur“:

If I apply the settings now, you’ll see that the polygon layer is now blurry. Now we’re getting somewhere!

Ok, so back to the Effects Properties dialog. Let’s try something a bit more advanced. Instead of just a single effect, it’s possible to chain multiple effects together to create different results. Let’s make a traditional drop shadow by adding a “Drop shadow” effect under the “Source” effect:

Effects are drawn top-down, so the drop shadow will appear below the source polygons:

Of course, if you really wanted, you could rearrange the effects so that the drop shadow effect is drawn above the source!..

You can stack as many effects as you like. Here’s a purple inner glow over a source effect, with a drop shadow below everything:

Now it’s time to get a bit more creative… Let’s explore the “transform” effect. This effect allows you to apply all kinds of transformations to your layer, including scaling, shearing, rotation and translation:

Here’s what the layer looks like if I add a horizontally shearing transform effect above an outer glow effect:

Transforms can get really freaky. Here’s what happens if we apply a 180° rotation to a continents layer (with a subtle nod to xkcd):

Remember that all these effects are applied when the layers are rendered, so no modifications are made to the underlying data.

Now, there’s one last concept regarding effects which really blasts open what’s possible with them, and that’s “Draw modes“. You’ll notice that this combo box contains a number of choices, including “Render“, “Modify” and “Render and Modify“:

These draw modes control how effects are chained together. It’s easiest to demonstrate how draw modes work with an example, so this time I’ll start with a Transform effect over a Colorise effect. The transform effect is set to a 45° rotation, and the colorise effect set to convert to grayscale. To begin, I’ll set the transform effect to a draw mode of Render only:

In this mode, the results of the effect will be drawn but won’t be used to modify the underlying effects:

So what we have here is that the polygon is drawn rotated by 45° by the transform effect, and then underneath that there’s a grayscale copy of the original polygon drawn by the colorise effect. The results of the transform effect have been rendered, but they haven’t affected the underlying colorise effect.

If I instead set the Transform effect’s draw mode to “Modifier only” the results are quite different:

Now, the transform effect is rotating the polygon by 45° but the result is not rendered. Instead, it is passed on to the subsequent colorise effect, so that now the colorise effect draws a grayscale copy of the rotated polygon. Make sense? We could potentially chain a whole stack of modifier effects together to get some great results. Here’s a transform, blur, colorise, and drop shadow effect all chained together using modifier only draw modes:

The final draw mode, “Render and modify” both renders the effect and applies its result to underlying effects. It’s a combination of the two other modes. Using draw modes to customise the way effects chain is really powerful. Here’s a combination of effects which turn an otherwise flat star marker into something quite different:

The last thing I’d like to point out is that effects can be either applied to an entire layer, or to the individual symbol layers for features within a layer. Basically, the possibilities are almost endless! Python plugins can also extend this further by implementing additional effects.

All this work was funded through the 71 generous contributors who donated to the crowdfunding campaign. A big thank you goes out to you all whole made this work possible! I honestly believe that this feature takes QGIS’ cartographic possibilities to whole new levels, and I’m really excited to see the maps which come from it.

Lastly, there’s two other crowdfunding campaigns which are currently in progress. Lutra consulting is crowdfunding for a built in auto trace feature, and Radim’s campaign to extend the functionality of the QGIS GRASS plugin. Please check these out and contribute if you’re interested in their work and would like to see these changes land in QGIS.

I’ve been working on QGIS for a number of years now and, contrary to what I thought when I started, my wishlist seems to grow longer with every feature I add to QGIS! Unfortunately, almost all of my QGIS development work is done on a volunteer basis and it’s sometimes hard to justify the time required to tackle items on this list. So here’s your chance to help me fix this!

Here’s a quick list of things which I’d love to add to QGIS (or improve), but would need someone to step up and help sponsor their development:

• Raster marker symbol type: Currently QGIS supports a number of marker symbol types (simple markers, font markers, SVG markers) but there’s no option to just use a raster image file for a symbol. A few versions back I added support for a raster image fill type, and now I’d love to do the same for markers. Options could include overriding the image size, rotation and opacity. And of course, all of these properties would be data-definable.
  
• Paint effects for diagrams: The successful Kickstarter campaign meant that QGIS 2.10 includes a powerful framework for applying live effects to layers, including drop shadows, outer glows, blurs, and colour effects (plus lots of others!). I’d like to take this framework and allow effects to be applied to diagrams on a layer. Drop shadows and outer glows would really help aid the readability of diagrams by allowing them to sit on a different visual layer to the rest of the map. The effects framework was designed to allow reuse across all of QGIS, and diagrams would be the next logical step in this.

  

• Additional diagram types/options: While we’re on the topic of diagrams, there’s lots more that we could do with QGIS’ diagram support. We’ve currently got support for pie charts, text diagrams and histograms, but there’s a lot of really nice diagram styles which we don’t yet support. Everybody loves infographics with nicely designed diagrams… so I’d love the chance to extend what’s possible using QGIS diagram engine. Some ideas include icon arrays, circle packing.
• Adding a geometry widget in the attribute table: This feature has been on my mind a lot lately. What I’d like to add is a new “geometry widget” as the last column in a layer’s attribute table. This widget would allow you to do all sorts of modifications to the geometry attached to a feature. Possible options include clearing the geometry (resetting it to null), copying the geometry as WKT or GeoJSON, or pasting geometry into the feature from a WKT string (making it super easy to copy the geometry between features). This could also be extended in future to start incorporating the editing capabilities current possible through the Plain Geometry Editor plugin.

  

• Options for non square/straight line legend patches: QGIS’ legend currently has no options for customising the shape of legend patches. Polygon layers in the legend are rectangles, line layers are straight lines — that’s it. There’s lots of room for improvement here. I’d like to add options for shapes such as circles, rounded rectangles, jagged lines, and possibly even custom shapes (via a WKT string or something similar).

  

• Improving the heatmap plugin: The current heatmap plugin needs some love. The code and UI could do with a big refresh. I’d love a chance to totally revamp this plugin and move it into QGIS core code, and allow it to be used from within processing models. I’d also like to add additional hotspot techniques, such as Getis Ord Gi* hotspotting, to the plugin.
• Extending the raster calculator: QGIS’ raster calculator was given a bunch of needed fixes and improvements in 2.10, but there’s more we could do. The major limitation with the calculator is that it currently only supports functions with at most two parameters. This needs to be fixed so that we can add a bunch of much desired functions to the calculator – eg min, max, avg, coalesce, if, etc… Lack of support for multi-parameter functions is really holding back what’s possible in the calculator.

Of course, this list is just a start. I’m always keen to chat about any other features you’d like to see added to QGIS (or even tackle specific pet-hate bugs or frustrations!). Just drop me an email at [email protected] to discuss.

Oh, one last thing – I’m in the process of preparing for my next crowd funded feature for QGIS – and this one is big! More on that shortly.

As we discussed in QGIS 3 is under way, the QGIS project is working toward the next major version of the application and these developments have major impact on any custom scripts or plugins you’ve developed for QGIS.

We’re now just over a week into this work, and already there’s been tons of API breaking changes landing the code base. In this post we’ll explore some of these changes, what’s motivated them, and what they mean for your scripts.

The best source for keeping track of these breaking changes is to watch the API break documentation on GitHub. This file is updated whenever a change lands which potentially breaks plugins/scripts, and will eventually become a low-level guide to porting plugins to QGIS 3.0.

API clean-ups

So far, lots of the changes which have landed have related to cleaning up the existing API. These include:

Removal of deprecated API calls

The API has been frozen since QGIS 2.0 was released in 2013, and in the years since then many things have changed. As a result, different parts of the API were deprecated along the way as newer, better ways of doing things were introduced. The deprecated code was left intact so that QGIS 2.x plugins would still all function correctly. By removing these older, deprecated code paths it enables the QGIS developers to streamline the code, remove hacky workarounds, untested methods, and just generally “clean things up”. As an example, the older labelling system which pre-dates QGIS 2.0 (it had no collision detection, no curved labels, no fancy data defined properties or rule based labelling!) was still floating around just in case someone tried to open a QGIS 1.8 project. That’s all gone now, culling over 5000 lines of outdated, unmaintained code. Chances are this won’t affect your plugins in the slightest. Other removals, like the removal of QgsMapRenderer (the renderer used before multi-threaded rendering was introduced) likely have a much larger impact, as many scripts and plugins were still using QgsMapRenderer classes and calls. These all need to be migrated to the new QgsMapRendererJob and QgsMapSettings classes.

Renaming things for consistency

Consistent naming helps keep the API predictable and more user friendly. Lots of changes have landed so far to make the naming of classes and methods more consistent. These include things like:

• Making sure names use consistent capitalization. Eg, there was previously methods named “writeXML” and “writeXml”. These have all been renamed to consistently use camel case, including for acronyms. (In case you’re wondering – this convention is used to follow the Qt library conventions).
• Consistent use of terms. The API previously used a mix of “CRS” and “SRS” for similar purposes – it now consistently uses “CRS” for a coordinate reference system.
• Removal of abbreviations. Lots of abbreviated words have been removed from the names, eg “destCrs” has become “destinationCrs”. The API wasn’t consistently using the same abbreviations (ie “dest”/”dst”/”destination”), so it was decided to remove all use of abbreviated words and replace them with the full word. This helps keep things predictable, and is also a bit friendlier for non-native English speakers.

The naming changes all need to be addressed to make existing scripts and plugins compatible with QGIS 3.0. It’s potentially quite a lot of work for plugin developers, but in the long term it will make the API easier to use.

Changes to return and argument types

There’s also been lots of changes relating to the types of objects returned by functions, or the types of objects used as function arguments. Most of these involve changing the c++ types from pointers to references, or from references to copies. These changes are being made to strengthen the API and avoid potential crashes. In most cases they don’t have any affect on PyQGIS code, with some exceptions:

• Don’t pass Python “None” objects as QgsCoordinateReferenceSystems or as QgsCoordinateTransforms. In QGIS 3.0 you must pass invalid QgsCoordinateReferenceSystem objects (“QgsCoordinateReferenceSystem()”) or invalid QgsCoordinateTransform (“QgsCoordinateTransform()”) objects instead.

Transparent caching of CRS creation

The existing QgsCRSCache class has been removed. This class was used to cache the expensive results of initializing a QgsCoordinateReferenceSystem object, so that creating the same CRS could be done instantly and avoid slow databases lookups. In QGIS 3.0 this caching is now handled transparently, so there is no longer a need for the separate QgsCRSCache and it has been removed. If you were using QgsCRSCache in your PyQGIS code, it will need to be removed and replaced with the standard QgsCoordinateReferenceSystem constructors.

This change has the benefit that many existing plugins which were not explicitly using QgsCRSCache will now gain the benefits of the faster caching mechanism – potentially this could dramatically speed up existing plugin algorithms.

In summary

The QGIS developers have been busy fixing, improving and cleaning up the PyQGIS API. We recognise that these changes result in significant work for plugin and script developers, so we’re committed to providing quality documentation for how to adapt your code for these changes, and we will also investigate the use of automated tools to help ease your code transition to QGIS 3.0. We aren’t making changes lightly, but instead are carefully refining the API to make it more predictable, streamlined and stable.

If you’d like assistance with (or to outsource) the transition of your existing QGIS scripts and plugins to QGIS 3.0, just contact us at North Road to discuss. Every day we’re directly involved in the changes moving to QGIS 3.0, so we’re ideally placed to make this transition painless for you!

With the imminent release of QGIS 2.16, the development attention has now shifted to the next scheduled release – QGIS 3.0! If you haven’t been following the discussion surrounding this I’m going to try and summarise what exactly 3.0 means and how it will impact any scripts or plugins you’ve developed for QGIS.

QGIS 3.0 is the first major QGIS release since 2.0 was released way back in September 2013. Since that release so much has changed in QGIS… a quick glance over the release notes for 2.14 shows that even for this single point release there’s been hundreds of changes. Despite this, for all 2.x releases the PyQGIS API has remained stable, and a plugin or script which was developed for use in QGIS 2.0 will still work in QGIS 2.16.

Version 3.0 will introduce the first PyQGIS API break since 2013. An API break like this is required to move QGIS to newer libraries such as Qt 5 and Python 3, and allows the development team the flexibility to tackle long-standing issues and limitations which cannot be fixed using the 2.x API. Unfortunately, the side effect of this API break is that the scripts and plugins which you use in QGIS 2.x will no longer work when QGIS 3.0 is released!

Numerous API breaking changes have already started to flow into QGIS, and 2.16 isn’t even yet publicly available. The best way to track these changes is to keep an eye on the “API changes” documentation.  This document describes all the changes which are flowing in which affect PyQGIS code, and describe how best they should be addressed by plugin and script maintainers. Some changes are quite trivial and easy to update code for, others are more extreme (such as changes surrounding moving to PyQt5 and Python 3) and may require significant time to adapt for.

I’d encourage all plugin and script developers to keep watching the API break documentation, and subscribe to the developers list for additional information about required changes as they are introduced.

If you’re looking for assistance or to outsource adaptation of your plugins and scripts to QGIS 3.0 – the team at North Road are ideally placed to assist! Our team includes some of the most experienced QGIS developers who are directly involved with the development of QGIS 3.0, so you can be confident knowing that your code is in good hands. Just contact us to discuss your QGIS development requirements.

You can read more about QGIS 3.0 API changes in The road to QGIS 3.0 – part 1.

Following on from part 1 in which I introduced how variables can be used in map composers, I’d like to now explore how using variables can make it easier to manage your QGIS projects. As a quick refresher, variables are a new feature in QGIS 2.12 which allow you to create preset values for use anywhere you can use an expression in QGIS.

Let’s imagine a typical map project. You load up QGIS, throw a bunch of layers on your map, and then get stuck into styling and labelling them ‘just right’. Over time the project gets more and more complex, with a stack of layers all styled using different rendering and labelling rules. You keep tweaking settings until you’re almost happy with the result, but eventually realise that you made the wrong choice of font for the labelling and now need to go through all your layers and labelling rules and update each in turn to the new typeface. Ouch.

Variables to the rescue! As you may recall from part 1, you can reuse variables anywhere in QGIS where you can enter an expression. This includes using them for data defined overrides in symbology and labelling. So, lets imagine that way back at the beginning of our project we created a project level variable called @main_label_font:

Now, we can re-use that variable in a data defined override for the label font setting. In fact, QGIS makes this even easier for you by showing a “variables” sub-menu allowing easy access to all the currently defined variables accessible to the layer:

When we hit Apply all our labels will be updated to use the font face defined by the @main_label_font variable, so in this case ‘Courier New’:

In a similar way we can bind all the other layer’s label fonts to the same variable, so @main_label_font will be reused by all the layers in the project. Then, when we later realise that Courier New was a horrible choice for labelling the map, it’s just a matter of opening up the Project Properties dialog and updating the value of the @main_label_font variable:

And now when we hit Apply the font for all our labelled layers will be updated all at once:

It’s not only a huge time saver, it also makes changes like this easier because you can try out different font faces by updating the variable and hitting apply and seeing the effect that the changes have all at once. Updating multiple layers manually tends to have the consequence that you forget what the map looked like before you started making the change, making direct comparisons harder.

Of course, you could have multiple variables for other fonts used by your project too, eg @secondary_label_font and @highlighted_feature_font. Plus, this approach isn’t limited to just setting the label font. You could utilise project level variables for consolidating font sizes, symbol line thickness, marker rotation, in fact, ANYTHING that has one of those handy little data defined override buttons next to it:

One last thing before I wrap up part 2 of this series. The same underlying changes which introduced variables to QGIS also allows us to begin introducing a whole stack of new, useful functions to the expression engine. One of these which also helps with project management is the new project_color function. Just like how we can use project level variables throughout a project, project_color lets you reuse a color throughout your project. First, you need to create a named colour in the Default Styles group under the Project Properties dialog:

Then, you can set a data defined override for a symbol or label colour to the expression “project_color(‘red alert!’)“:

When you go back and change the corresponding colour in the Project Properties dialog, every symbol bound to this colour will also be updated!

So, there you have it. With a little bit of forward planning and by taking advantage of the power of expression variables in QGIS 2.12 you can help make your mapping projects much easier to manage and update!

That’s all for now, but we’re still only just getting started with variables. Part 3, coming soon!.. (Update: Part 3 is available now)

If you’re not like me and don’t keep a constant eye over at QGIS development change log (be careful – it’s addictive!), then you’re probably not aware of a bunch of labelling improvements which recently landed in QGIS master version. I’ve been working recently on a large project which involves a lot (>300) of atlas map outputs, and due to the size of this project it’s not feasible to manually tweak placements of labels. So, I’ve been totally at the mercy of QGIS’ labelling engine for automatic label placements. Generally it’s quite good but there were a few things missing which would help this project. Fortunately, due to the open-source nature of QGIS, I’ve been able to dig in and enhance the label engine to handle these requirements (insert rhetoric about beauty of open source here!). Let’s take a look at them one-by-one:

Data defined quadrant in “Around Point” placement mode

First up, it’s now possible to specify a data defined quadrant when a point label is set to the Around Point placement mode. In the past, you had a choice of either Around Point mode, in which QGIS automatically places labels around point features in order to maximise the number of labels shown, or the Offset from Point mode, in which all labels are placed at a specified position relative to the points (eg top-left). In Offset from Point mode you could use data defined properties to force labels for a feature to be placed at a specific relative position by binding the quadrant to a field in your data. This allowed you to manually tweak the placement for individual labels, but at the cost of every other label being forced to the same relative position. Now, you’ve also got the option to data define the relative position when in Around Point mode, so that the rest of the labels will fall back to being automatically placed. Here’s a quick example – I’ll start with a layer with labels in Around Point mode:

You can see that some labels are sitting to the top right of the points, others to the bottom right, and some in the top middle, in order to fit all the labels for these points. With this new option, I can setup a data defined quadrant for the labels, and then force the ‘Tottenham’ label (top left of the map) to display below and to the left of the point:

Here’s what the result looks like:

The majority of the labels are still auto-placed, but Tottenham is now force to the lower left corner.

Data defined label priority

Another often-requested feature which landed recently is the ability to set the priority for individual labels. QGIS has long had the ability to set the priority for an entire labelling layer, but you couldn’t control the priority of features within a layer. That would lead to situations like that shown below, where the most important central station (the green point) hasn’t been labelled:

By setting a data defined priority for labels, I can set the priority either via values manually entered in a field or by taking advantage of an existing “number of passengers” field present in my data. End result is that this central station is now prioritised over any others:

Obstacle only layers

The third new labelling feature is the option for “Obstacle only” layers. What this option does is allow a non-labelled layer to act as an obstacle for the labels in other layers, so they will be discouraged from drawing labels over the features in the obstacle layer. Again, it’s best demonstrated with an example. Here’s my stations layer with labels placed automatically – you can see that some labels are placed right over the features in the rail lines layer:

Now, let’s set the rail lines layer to act as an obstacle for other labels:

The result is that labels will be placed so that they don’t cover the rail lines anymore! (Unless there’s no other choice). Much nicer.

Control over how polygons act as obstacles for labels

This change is something I’m really pleased about. It’s only applicable for certain situations, but when it works the improvements are dramatic.

Let’s start with my labelled stations map, this time with an administrative boundary layer in the background:

Notice anything wrong with this map? If you’re like me, you won’t be able to look past those labels which cross over the admin borders. Yuck. What’s happening here is that although my administrative regions layer is set to discourage labels being placed over features, there’s actually nowhere that labels can possibly be placed which will avoid this. The admin layer covers the entire map, so regardless of where the labels are placed they will always cover an administrative polygon feature. This is where the new option to control how polygon layers act as obstacles comes to the rescue:

Now, I can set the administrative layer to only avoid placing labels over feature’s boundaries! I don’t care that they’ll still be placed inside the features (since we have no choice!), but I don’t want them sitting on top of these boundaries. The result is a big improvement:

Now, QGIS has avoided placing labels over the boundaries between regions. Better auto-placement of labels like this means much less time required manually tweaking their positioning, and that’s always a good thing!

Draw only labels which fit inside a polygon

The last change is fairly self explanatory, so no nice screenshots here. QGIS now has the ability to prevent drawing labels which are too large to fit inside their corresponding polygon features. Again, in certain circumstances this can make a huge cartographic improvement to your map.

So there you go. Lots of new labelling goodies to look forward to when QGIS 2.12 rolls around.

It’s been quite some time since I last had a chance to blog and a lot has happened since then. Not least of which is that QGIS 2.12 has now been released with a ton of new features that I’ve neglected to write about! To try and get things moving along here again I’m planning on writing a short series exploring how variables work in QGIS 2.12 and the exciting possibilities they unlock. First, let’s look into how variables can be used with QGIS map composer…

So, let’s get started! A new concept introduced in QGIS 2.12 is the ability to set custom variables for use in QGIS’ expression engine. The easiest way to do this is through the “Project Properties” dialog, under the “Variables” section:

You’ll see in the screenshot above that a blank project includes a number of read-only preset variables, such as @project_path and @project_title. (All variables in QGIS are prefixed with an @ character to differentiate them from fields or functions). You can add your own variables to this list by clicking the + button, as shown below:

Here I’ve added some new variables, @project_version and @author. Now, any of these variables can be used anywhere that you can use expressions in QGIS, including the field calculator, data defined symbology, labelling, map composer text, etc. So, you could make a map composer template with a label that includes the @author, @project_version and @project_path variables:

Sure, you *could* also manually enter all these details directly into the label for the same result. But what happens when you have multiple composers in your project, and need to update the version number in all of them? Or you move your project to a new folder and need to make sure the path is updated accordingly? Manually updating multiple composers is a pain – make QGIS do the work for you and instead use variables! This would especially be helpful if you’re saving map composer templates for use across multiple projects or users. Using variables will ensure that the template is automatically updated with the right details for the current project.

Another neat thing about QGIS variables is that they can be inherited and overridden, just like CSS rules. Opening the options dialog will also show a Variables group for setting “Global” variables. These variables are always available for your QGIS installation, regardless of what project you’re working on at the time. If your workplace tends to reorganise a lot and constantly shuffle your department around, you could add a global variable for @work_department, so that changing the global variable value in one place will automatically filter through to any existing and future projects you have.

And like I mentioned earlier, these variables are inherited through various “contexts” within QGIS. If I reopen the Project Properties dialog, you’ll see that a project has access to all the global variables plus the variables set within that specific project. In addition, by adding a variable with the same name to the Project variables the value of the Global variable will be overridden:

There’s also a variable editor within each individual composer’s properties tab, so variables can also be set and overridden on a composer-by-composer basis within a project. It’s a really flexible and powerful approach which both simplifies workflows and also opens up lots of new possibilities.

Stay tuned for more on this topic – this topic has only just scratched the surface of how expression variables have changed QGIS! (You can also read part 2 and part 3)

In part 3 of my exploration of variables in QGIS 2.12, I’m going to dig into how variables are scoped in QGIS and what layer level variables are available (you can read parts 1 and 2 for a general introduction to variables).

Some background

Before we get to the good stuff, a bit of background in how variables work behind-the-scenes is important. Whenever an expression is evaluated in QGIS the context of the expression is considered. The context is built up from a set of scopes, which are all stacked on top of each other in order from least-specific to most-specific. It’s easier to explain with an example. Let’s take an expression used to set the source of a picture in a map composer. When this expression is evaluated, the context will consist of:

1. The global scope, consisting of variables set in the QGIS options dialog, and other installation-wide properties
2. The project scope, which includes variables set in the Project Properties dialog and the auto-generated project variables like @project_path, @project_title (you can read more about this in part 2)
3. A composer scope, with any variables set for the current composer, plus variables for @layout_pagewidth, @layout_pageheight, @layout_numpages, etc.
4. A composer item scope for the picture, with item-specific variables including @item_id

The more specific scopes will override any existing clashing variables from less specific scopes. So a global @my_var variable will be overridden by an @my_var variable set for the composer:

Another example. Let’s consider now an expression set for a data-defined label size. When this expression is evaluated the context will depend on where the map is being rendered. If it’s in the main map canvas then the context will be:

1. The global scope
2. The project scope
3. A map settings scope, with variables relating to how the map is being rendered. Eg @map_rotation, @map_scale, etc
4. A layer scope. More on this later, but the layer scope includes layer-level variables plus preset variables for @layer_name and @layer_id

If instead the map is being rendered inside a map item in a map composer, the context will be:

1. The global scope
2. The project scope
3. The composer scope
4. An atlas scope, if atlas is enabled. This contains variables like @atlas_pagename, @atlas_feature, @atlas_totalfeatures.
5. A composer item scope for the map item
6. A map settings scope (with scale and rotation determined by the map item’s settings)
7. The layer scope

Using layer level variables

Ok, enough with the details. The reason I’ve explained all this is to help explain when layer level variables come into play. Basically, they’ll be available whenever an expression is evaluated inside of a particular layer. This includes data defined symbology and labeling, field calculator, and diagrams. You can’t use a layer-level variable inside a composer label, because there’s no layer scope used when evaluating this. Make sense? Great! To set a layer level variable, you use the Variables section in the Layer Properties dialog:

Setting a layer variable

Any layer level variables you set will be saved inside your current project, i.e. layer variables are per-layer and per-project. You can also see in the above screenshot that as well as the layer level variables QGIS also lists the existing variables from the Project and Global scopes. This helps show exactly what variables are accessible by the layer and whether they’ve been overridden by any scopes. You can also see that there’s two automatic variables, @layer_id and @layer_name, which contain the unique layer ID and user-set layer name too.

Potential use cases for layer-level variables

In the screenshot above I’ve set two variables, @class1_threshold and @class2_threshold. I’m going to use these to sync up some manual class breaks between rule based symbology and rule based labeling. Here’s how I’ve set up the rule-based symbols for the layer:

Rule based symbology using layer level variables

In a similar way, I’ve also created matching rule-based labeling (another new feature in QGIS 2.12):

Matching rule-based labels

Here’s what my map looks like now, with label and symbol colors matched:

*Map for illustrative purposes only… not for cartographic/visual design excellence!

If I’d hard-coded the manual class breaks, it would be a pain to keep the labeling and symbology in sync. I’d have to make sure that the breaks are updated everywhere I’ve used them in both the symbology and labeling settings. Aside from being boring, tedious work, this would also prevent immediate before/after comparisons. Using variables instead means that I can update the break value in a single place (the variables panel) and have all my labeling and symbols immediately reflect this change when I hit apply!

Another recent use case I had was teaming layer-level variables along with Time Manager. I wanted my points to falloff in both transparency and size with age, and this involved data defined symbol settings scattered all throughout my layer symbology. By storing the decay fall-off rate in a variable, I could again tweak this falloff by changing the value in a single place and immediately see the result. It also helps with readability of the data defined expressions. Instead of trying to decipher a random, hard-coded value, it’s instead immediately obvious that this value relates to a decay fall-off rate. Much nicer!

I’m sure there’s going to be hundreds of novel uses of layer-level variables which I never planned for when adding this feature. I’d love to hear about them though – leave a comment if you’d like to share your ideas!

One last thing – the new “layer_property” function

This isn’t strictly related to variables, but another new feature which was introduced in QGIS 2.12 was a new “layer_property” expression function. This function allows you to retrieve any one of a bunch of properties relating to a specific map layer, including the layer CRS, metadata, source path, etc.

This function can be used anywhere in QGIS. For instance, it allows you to insert dynamic metadata about layers into a print composer layout. In the screenshot below I’ve used expressions like layer_property(‘patron’,’crs’) and layer_property(‘patron’,’source’) to insert the CRS and source path of the “patron” layer into the label. If either the CRS or the file path ever changes, this label will be automatically updated to reflect the new values.

Inserting dynamic layer properties into a composer label

So there you go – layer level variables and the layer_property function – here in QGIS 2.12 and making your workflow in QGIS easier. In the final part of this series, we’ll explore the magical @value variable. Trust me, I’ve saved the best for last!