Tests with cov

.coveragerc

@@ -1 +1,2 @@
-
+[coverage:run]
+source = mobility

.github/workflows/install-and-test.yml

@@ -59,4 +59,4 @@ jobs:
       shell: bash -el {0}
 
     - name: Upload coverage reports to Codecov
-      uses: codecov/codecov-action@v4
+      uses: codecov/codecov-action@v5

pyproject.toml

@@ -48,6 +48,7 @@ classifiers = [
 
 [project.optional-dependencies]
 dev = [
+    "coverage",
     "flake8",
     "pytest",
     "pytest-cov",
@@ -78,4 +79,4 @@ mobility = [
 [tool.setuptools.packages.find]
 where = ["."]
 include = ["mobility*"]
-exclude = ["certs", "certs.*"]
+exclude = ["certs", "certs.*"]

tests/back/integration/test_901_ensure_quickstart_works.py

@@ -0,0 +1,34 @@
+import os
+import dotenv
+
+import mobility
+
+dotenv.load_dotenv()
+
+# Using Foix (a small town) and a limited radius for quick results
+transport_zones = mobility.TransportZones("fr-09122", radius = 10)
+
+# Using EMP, the latest national mobility survey for France
+emp = mobility.EMPMobilitySurvey()
+
+# Creating a synthetic population of 1000 for the area
+pop = mobility.Population(transport_zones, sample_size = 1000)
+
+# Simulating the trips for this population for three modes : car, walk and bicyle, and only home and work motives (OtherMotive is mandatory)
+pop_trips = mobility.PopulationTrips(
+    pop,
+    [mobility.CarMode(transport_zones), mobility.WalkMode(transport_zones), mobility.BicycleMode(transport_zones)],
+    [mobility.HomeMotive(), mobility.WorkMotive(), mobility.OtherMotive(population=pop)],
+    [emp],
+    n_iterations=1
+    )
+
+# You can get the weekday trips to inspect them
+weekday_flows = pop_trips.get()["weekday_flows"].collect()
+
+# You can can also get global metrics that will be compared to the theoetical values for this population 
+global_metrics = pop_trips.evaluate("global_metrics")
+
+# You can also plot the flows, with labels for the cities that are bigger than their neighbours
+labels = pop_trips.get_prominent_cities()
+pop_trips.plot_od_flows(labels=labels)