Import RenewMap project data to a QGIS project.
Check the API docs
https://renewmap.readme.io/reference/get-a-list-of-network-infra
You will need an API key to get started.
Check the Getting Started page for instructions.
In QGIS, you can run a Python script to fetch RenewMap API data into your project.
- Select Plugins > Python Console and then select 📝 Show editor
- Create a new blank script using the ➕ icon.
- Paste the code below into the blank script, replacing
'YOUR_API_KEY'
with your actual API key. - Run the script with the ▶️ icon.
- The latest RenewMap data will appear in your project:
- A LineString layer called Network with operating network infrastructure data.
- A MultiPolygon layer called Network - Development with network infrastructure in development.
Note: the layer is stored in memory and will be lost when you close the project. Re-run the script whenever you want to get the latest data.
If you want to persist the layer to your next session, right click the layer in the Layers pane and select Make permanent. However, this permanent layer will not update with new data.
import pandas as pd
import requests
from qgis.core import QgsVectorLayer, QgsField, QgsFeature, QgsGeometry, QgsProject
from PyQt5.QtCore import QVariant
from shapely.geometry import shape
from dataclasses import dataclass
from typing import List, Dict
API_KEY = "YOUR_API_KEY" # Replace with your actual API key
BASE_URL = "https://api.renewmap.com.au/api/v1/network"
DATA_KEY = "network"
@dataclass
class APIConfig:
"""Configuration class for API parameters.
Attributes:
base_url: Base URL for the API endpoint
limit: Number of records per request
headers: HTTP headers for API requests
"""
base_url: str = BASE_URL
limit: int = 1000
headers: Dict = None
def __post_init__(self):
"""Initialize default headers if none provided"""
if self.headers is None:
self.headers = {
"accept": "application/json",
"Authorization": f"Bearer {API_KEY}"
}
def fetch_data(config: APIConfig) -> pd.DataFrame:
"""Fetch data from API using pagination.
Args:
config: APIConfig object containing API configuration
Returns:
DataFrame containing all fetched data
"""
dfs = []
offset=0
# Fetch data in chunks using pagination
while True:
url = f"{config.base_url}?limit={config.limit}&offset={offset}"
response = requests.get(url, headers=config.headers)
response.raise_for_status()
data_dict = response.json()
df = pd.DataFrame(data_dict[DATA_KEY])
if df.empty:
break # No more data available
dfs.append(df)
offset += config.limit # Increment offset for next request
return pd.concat(dfs, ignore_index=True)
def create_qgis_fields(df: pd.DataFrame) -> List[QgsField]:
"""Create QGIS fields based on GeoDataFrame columns.
Args:
df: Input GeoDataFrame with project data
Returns:
List of QgsField objects
"""
# Loop through columns to dynamically create QgsField objects
fields = []
for column in df.columns:
field_type = QVariant.String # Adjust the type based on your data
fields.append(QgsField(column, field_type))
return fields
def create_feature(row: pd.Series) -> QgsFeature:
"""Create QGIS feature from GeoDataFrame row.
Args:
row: Series containing single project data row with geometry
Returns:
QgsFeature object with geometry and attributes
"""
feature = QgsFeature()
# Convert shapely geometry to QgsGeometry
shapely_geom = shape(row['geometry'])
qgs_geometry = QgsGeometry.fromWkt(shapely_geom.wkt)
# Set geometry
feature.setGeometry(qgs_geometry)
# Set attributes for all columns except geometry
attributes = [str(row[column]) for column in row.index if column != 'geometry']
feature.setAttributes(attributes)
return feature
def create_multilinestring_layer(df: pd.DataFrame) -> QgsVectorLayer:
"""Create QGIS vector layer from DataFrame.
Args:
df: DataFrame containing project data
Returns:
QgsVectorLayer object with all features
"""
# Create a memory layer for MultiLineStrings
layer = QgsVectorLayer("LineString?crs=epsg:4326", "Network", "memory")
# Add fields to the layer
fields = create_qgis_fields(df)
layer.dataProvider().addAttributes(fields)
layer.updateFields()
# Add features to the multilinestring layer
multiline_data = df[df['geometry'].apply(lambda x: shape(x).geom_type == 'MultiLineString')]
for _, row in multiline_data.iterrows():
feature = create_feature(row)
if not feature.geometry().isNull():
layer.dataProvider().addFeature(feature)
layer.updateExtents()
return layer
def create_multipolygon_layer(df: pd.DataFrame) -> QgsVectorLayer:
# Create a memory layer for MultiPolygons
layer = QgsVectorLayer("Polygon?crs=epsg:4326", "Network - Development", "memory")
# Add fields to the layer
fields = create_qgis_fields(df)
layer.dataProvider().addAttributes(fields)
layer.updateFields()
# Add features to the multipolygon layer
polygon_data = df[df['geometry'].apply(lambda x: shape(x).geom_type == 'MultiPolygon')]
for _, row in polygon_data.iterrows():
feature = create_feature(row)
if not feature.geometry().isNull():
layer.dataProvider().addFeature(feature)
layer.updateExtents()
return layer
config = APIConfig()
df = fetch_data(config)
multilinestring_layer = create_multilinestring_layer(df)
multipolygon_layer = create_multipolygon_layer(df)
QgsProject.instance().addMapLayer(multilinestring_layer)
QgsProject.instance().addMapLayer(multipolygon_layer)