with open("metadatified.pdf", "wb") as f: writer.write(f) Here are three typical contracts that require a deep understanding of the PyQGIS 3 PDF workflow: 1. Batch PDF Generation from a Template Scenario: A city planning department has 50 district maps. Each PDF must show the same legend, title block, and scale bar, but with a different map extent and a district-specific label.
writer.add_metadata(metadata)
from pypdf import PdfMerger merger = PdfMerger() for i in range(10): merger.append(f"C:/GIS/atlas_page_i.pdf") merger.write("C:/GIS/final_mapbook.pdf") merger.close() Modern PDF workflows require embedded metadata (author, title, keywords). While QgsLayoutExporter does not directly set PDF metadata, you can post-process the PDF: pyqgis programmer 39s guide 3 pdf work
district_layer = QgsProject.instance().mapLayersByName("districts")[0] for feature in district_layer.getFeatures(): # Set map extent to feature geometry map_item.zoomToExtent(feature.geometry().boundingBox()) # Update a text label with district name title_label.setText(f"District feature['name']") # Refresh layout layout.refresh() exporter.exportToPdf(f"feature['name'].pdf", settings) Scenario: You need a PDF where clicking a feature on a legend or table opens a bookmarked page. with open("metadatified
result = exporter.exportToPdf("C:/GIS/output.pdf", settings) if result == QgsLayoutExporter.Success: print("PDF exported successfully") else: print(f"Export failed: result") One of the most powerful uses of PyQGIS PDF workflows is creating atlas-style map books without the QGIS GUI. The QgsLayoutExporter can iterate over features. writer
Introduction Quantum GIS (QGIS) has evolved from a simple open-source desktop application into a full-fledged geospatial ecosystem. At its heart lies PyQGIS —the Python binding that allows you to automate, extend, and customize every aspect of the software. For developers and GIS analysts, the transition from QGIS 2.x to 3.x brought a seismic shift in API design, performance, and capability.