feat(python): Repaired python bindings

Python bindings have now been brought back up to feature pairity with
C++. Further, stubs have been added for all python features so that code
completion will work

validation/pynucastro/GridFireEquiv/GridFireEvolve.py

@@ -0,0 +1,95 @@
+from fourdst.composition import Composition
+from gridfire.type import NetIn
+from gridfire.policy import MainSequencePolicy
+from gridfire.solver import CVODESolverStrategy
+from enum import Enum
+from typing import Dict, Union, SupportsFloat
+import json
+import dicttoxml
+
+def init_composition() -> Composition:
+    Y = [7.0262E-01, 9.7479E-06, 6.8955E-02, 2.5000E-04, 7.8554E-05, 6.0144E-04, 8.1031E-05, 2.1513E-05]
+    S = ["H-1", "He-3", "He-4", "C-12", "N-14", "O-16", "Ne-20", "Mg-24"]
+    return Composition(S, Y)
+
+def init_netIn(temp: float, rho: float, time: float, comp: Composition) -> NetIn:
+    netIn = NetIn()
+    netIn.temperature = temp
+    netIn.density = rho
+    netIn.tMax = time
+    netIn.dt0 = 1e-12
+    netIn.composition = comp
+    return netIn
+
+class StepData(Enum):
+    TIME = 0
+    DT = 1
+    COMP = 2
+    CONTRIB = 3
+
+
+class StepLogger:
+    def __init__(self):
+        self.num_steps: int = 0
+        self.step_data: Dict[int, Dict[StepData, Union[SupportsFloat, Dict[str, SupportsFloat]]]] = {}
+
+    def log_step(self, context):
+        engine = context.engine
+        self.step_data[self.num_steps] = {}
+        self.step_data[self.num_steps][StepData.TIME] = context.t
+        self.step_data[self.num_steps][StepData.DT] = context.dt
+        comp_data: Dict[str, SupportsFloat] = {}
+        for species in engine.getNetworkSpecies():
+            sid = engine.getSpeciesIndex(species)
+            comp_data[species.name()] = context.state[sid]
+        self.step_data[self.num_steps][StepData.COMP] = comp_data
+        self.num_steps += 1
+
+    def to_json (self, filename: str):
+        serializable_data = {
+            stepNum: {
+                StepData.TIME.name: step[StepData.TIME],
+                StepData.DT.name: step[StepData.DT],
+                StepData.COMP.name: step[StepData.COMP],
+            }
+            for stepNum, step in self.step_data.items()
+        }
+        with open(filename, 'w') as f:
+            json.dump(serializable_data, f, indent=4)
+
+    def to_xml(self, filename: str):
+        serializable_data = {
+            stepNum: {
+                StepData.TIME.name: step[StepData.TIME],
+                StepData.DT.name: step[StepData.DT],
+                StepData.COMP.name: step[StepData.COMP],
+            }
+            for stepNum, step in self.step_data.items()
+        }
+        xml_data = dicttoxml.dicttoxml(serializable_data, custom_root='StepLog', attr_type=False)
+        with open(filename, 'wb') as f:
+            f.write(xml_data)
+
+def main(temp: float, rho: float, time: float):
+    comp = init_composition()
+    netIn = init_netIn(temp, rho, time, comp)
+
+    policy = MainSequencePolicy(comp)
+    engine = policy.construct()
+
+    solver = CVODESolverStrategy(engine)
+
+    step_logger = StepLogger()
+    solver.set_callback(lambda context: step_logger.log_step(context))
+
+    solver.evaluate(netIn, False)
+    step_logger.to_xml("log_data.xml")
+
+if __name__ == "__main__":
+    import argparse
+    parser = argparse.ArgumentParser(description="Simple python example of GridFire usage")
+    parser.add_argument("-t", "--temp", type=float, help="Temperature in K", default=1.5e7)
+    parser.add_argument("-r", "--rho", type=float, help="Density in g/cm^3", default=1.5e2)
+    parser.add_argument("--tMax", type=float, help="Time in s", default=3.1536 * 1e17)
+    args = parser.parse_args()
+    main(args.temp, args.rho, args.tMax)