More ruff formatting

Author: pgleeson

.github/workflows/ci.yml

@@ -18,10 +18,12 @@ jobs:
 
     steps:
     - uses: actions/checkout@v4
+
     - name: Set up Python  ${{ matrix.python-version }}
       uses: actions/setup-python@v5
       with:
         python-version:  ${{ matrix.python-version }}
+
     - name: Install OMV
       run: |
         pip install git+https://github.com/OpenSourceBrain/osb-model-validation
@@ -30,6 +32,7 @@ jobs:
     - name: Run OMV tests on engine ${{ matrix.engine }}
       run: |
         omv all -V --engine=${{ matrix.engine }}
+        
     - name: OMV final version info
       run: |
         omv list -V # list installed engines

.github/workflows/non_omv.yml

@@ -17,13 +17,17 @@ jobs:
 
     steps:
     - uses: actions/checkout@v4
+
     - name: Set up Python  ${{ matrix.python-version }}
       uses: actions/setup-python@v5
       with:
         python-version:  ${{ matrix.python-version }}
+
     - name: Install OpenCortex
       run: |
         pip install .
+        pip install ruff 
+
     - name: Run some examples
       run: |
         echo "Running non OMV tests..."

examples/neuromllite/SimpleNet.py

@@ -1,55 +1,76 @@
-from neuromllite import Network, Cell, InputSource, Population, Synapse, RectangularRegion, RandomLayout
+from neuromllite import (
+    Network,
+    Cell,
+    InputSource,
+    Population,
+    Synapse,
+    RectangularRegion,
+    RandomLayout,
+)
 from neuromllite import Projection, RandomConnectivity, Input, Simulation
 from neuromllite.NetworkGenerator import generate_and_run
 import sys
 
 ################################################################################
 ###   Build new network
 
-net = Network(id='SimpleNet')
-net.notes = 'Simple network with single population'
+net = Network(id="SimpleNet")
+net.notes = "Simple network with single population"
 net.temperature = 32.0
 
-cell = Cell(id='RS', neuroml2_source_file='../../NeuroML2/prototypes/izhikevich/RS.cell.nml')
+cell = Cell(
+    id="RS", neuroml2_source_file="../../NeuroML2/prototypes/izhikevich/RS.cell.nml"
+)
 net.cells.append(cell)
 
-syn = Synapse(id='ampa', neuroml2_source_file='../../NeuroML2/prototypes/synapses/ampa.synapse.nml')
+syn = Synapse(
+    id="ampa",
+    neuroml2_source_file="../../NeuroML2/prototypes/synapses/ampa.synapse.nml",
+)
 net.synapses.append(syn)
 
-input_source = InputSource(id='poissonFiringSyn',
-                           neuroml2_input='poissonFiringSynapse',
-                           parameters={'average_rate':"50Hz", 'synapse':syn.id, 'spike_target':"./ampa"})
+input_source = InputSource(
+    id="poissonFiringSyn",
+    neuroml2_input="poissonFiringSynapse",
+    parameters={"average_rate": "50Hz", "synapse": syn.id, "spike_target": "./ampa"},
+)
 net.input_sources.append(input_source)
 
-r1 = RectangularRegion(id='region1', x=0,y=0,z=0,width=100,height=100,depth=100)
+r1 = RectangularRegion(id="region1", x=0, y=0, z=0, width=100, height=100, depth=100)
 net.regions.append(r1)
 
-p0 = Population(id='RS_pop', size=3, component=cell.id, properties={'color':'0 .8 0'},random_layout = RandomLayout(region=r1.id))
+p0 = Population(
+    id="RS_pop",
+    size=3,
+    component=cell.id,
+    properties={"color": "0 .8 0"},
+    random_layout=RandomLayout(region=r1.id),
+)
 
 net.populations.append(p0)
 
-net.inputs.append(Input(id='Stim0',
-                        input_source=input_source.id,
-                        population=p0.id,
-                        percentage=100))
+net.inputs.append(
+    Input(id="Stim0", input_source=input_source.id, population=p0.id, percentage=100)
+)
 
 print(net.to_json())
-new_file = net.to_json_file('%s.json'%net.id)
+new_file = net.to_json_file("%s.json" % net.id)
 
 
 ################################################################################
 ###   Build Simulation object & save as JSON
 
-sim = Simulation(id='SimSimpleNet',
-                 network=new_file,
-                 duration='1000',
-                 dt='0.025',
-                 record_traces={'all':'*'})
+sim = Simulation(
+    id="SimSimpleNet",
+    network=new_file,
+    duration="1000",
+    dt="0.025",
+    record_traces={"all": "*"},
+)
 
 sim.to_json_file()
 
 
-
 ################################################################################
 ###   Run in some simulators