import json

def transform_value(key, value):
    if isinstance(value, dict):
        if 'Value' in value and 'Unit' in value:
            value_type = "str" if isinstance(value['Value'], str) else "float"
            return {
                "key": key,
                "type": "dict",
                "value": [
                    {"key": "Value", "type": value_type, "value": value['Value']},
                    {"key": "Unit", "type": "str", "value": value['Unit']}
                ]
            }
        else:
            return {
                "key": key,
                "type": "dict",
                "value": [transform_value(k, v) for k, v in value.items()]
            }
    elif isinstance(value, list):
        return {
            "key": key,
            "type": "list",
            "value": [transform_value("", item) for item in value]
        }
    elif isinstance(value, str):
        return {
            "key": key,
            "type": "str",
            "value": value
        }
    else:
        raise ValueError(f"Unsupported value type: {type(value)}")

def my_json_to_kadi(data):
    return [transform_value(key, value) for key, value in data.items()]



# Print the output JSON in a formatted way

# Example JSON input
input_json = {
    "Material": {
        "Name": "LLTO",
        "Composition": "(Li,La)TiO-type",
        "Type": "Perovskite-type",
        "Properties": {
            "Ionic Conductivity": {"Value": "10^-3", "Unit": "S cm^-1"},
            "Chemical Stability": "",
            "Dendrite Formation Risk": "",
            "Operating Voltage": "",
            "Flexibility": "",
            "Processing": ""
        }
    },
    "Performance": {
        "Specific Capacity": {"Value": "", "Unit": ""},
        "Energy Density": {"Value": "", "Unit": ""},
        "Capacity Retention": "",
        "Operating Temperature": {"Value": "Room temperature", "Unit": ""}
    },
    "Usage": {
        "Battery Type": "",
        "Benefits": []
    }
}

# input_json = {
#     "Doctor_Patient_Discussion": {
#         "Initial_Observation": {
#             "Symptoms": [
#                 "pale",
#                 "sore throat",
#                 "running a temperature"
#             ],
#             "Initial_Assessment": "You\u2019ve moderate fever."
#         },
#         "Medical_Examination": {
#             "Temperature": "99.8",
#             "Blood_Pressure": "fine",
#             "Doctor_Assessment": "few symptoms of malaria",
#             "Diagnosis": "few symptoms of malaria"
#         },
#         "Treatment_Plan": {
#             "Prescription": [
#                 "three medicines",
#                 "a syrup"
#             ]
#         }
#     }
# }

# input_json = {
#     "Doctor_Patient_Discussion": {
#         "Initial_Observation": {
#             "Symptoms": [
#                 "pale",
#                 "sore throat",
#                 "running a temperature"
#             ],
#             "Initial_Assessment": "You\u2019ve moderate fever."
#         },
#         "Medical_Examination": {
#             "Temperature": "99.8",
#             "Blood_Pressure": "fine",
#             "Doctor_Assessment": "few symptoms of malaria",
#             "Diagnosis": "few symptoms of malaria"
#         },
#         "Treatment_Plan": {
#             "Prescription": [
#                 "three medicines",
#                 "a syrup"
#             ]
#         }
#     }
# }

input_json = {
  "Experiment": {
    "Material": "LATP powders",
    "SynthesisRoute": "modified sol-gel synthesis route described by (Bucharsky et al., 2015)",
    "Precursors": [
      {
        "Name": "lithium acetate Li(C2H3O2) ⋅2H2O",
        "Purity": "purity ≥ 99 %",
        "Supplier": "Alfa Aesar GmbH & Co KG",
        "Location": "Germany"
      },
      {
        "Name": "aluminum nitrate Al(NO3)3 ⋅9H2O",
        "Purity": "purity ≥ 98.5 %",
        "Supplier": "Merck KGaA",
        "Location": "Germany"
      },
      {
        "Name": "titanium-isopropoxide Ti[OCH(CH3)2]4",
        "Purity": "purity ≥ 98 %",
        "Supplier": "Merck KGaA",
        "Location": "Germany"
      }
    ],
    "Procedure": [
      {
        "Step": "Dissolve lithium acetate and aluminum nitrate in distilled water under constant stirring."
      },
      {
        "Step": "Add titanium-isopropoxide dropwise to the solution."
      },
      {
        "Step": "Add phosphoric acid slowly through a drip funnel to form a gel."
      },
      {
        "Step": "Dry the gel at room temperature for 24 h."
      }
    ],
    "HeatTreatment": [
      {
        "Step": "First, heat treat samples at 400°C for 6 h to achieve precursor formation and eliminate reaction gases."
      },
      {
        "Step": "Second, process samples at 900°C for 8 h to complete the reaction to crystalline LATP."
      }
    ],
    "BatchVariations": [
      {
        "Description": "Prepare one batch with all precursors in stoichiometric quantities (marked as 0.0 wt%)."
      },
      {
        "Description": "Explore different batches with either an excess up to +7.5 wt% or a deficiency up to -15.0 wt% of phosphoric acid compared to the stoichiometric composition."
      }
    ],
    "Processing": [
      {
        "Step": "Process the obtained powders in a planetary ball mill."
      },
      {
        "Step": "Form pellets by uniaxial pressing and then further densify by cold isostatic pressing at 400 MPa."
      },
      {
        "Step": "All pressed samples have a green density of approximately 62% relative density."
      }
    ],
    "Sintering": {
      "TemperatureRange": "850 to 1,050°C",
      "IsothermalSinteringTime": "30 to 540 min",
      "Cooling": "Cool down to room temperature in furnace",
      "DensityDetermination": "Determine densities by Archimedes’ method"
    },
    "IonicConductivityMeasurements": {
      "Method": "Impedance analysis",
      "Conditions": "At room temperature over the frequency range from 0.1 Hz to 1 MHz with an AC amplitude of 50 mV in the frequency response analyzer (AMTEK GmbH, VersaSTAT 4, Pennsylvania, United States)",
      "Reference": "For further details of the experimental part please refer to our previous work (Schiffmann et al., 2021)"
    }
  }
}


if __name__ == "__main__":
  # Transform the input JSON
  # output_json = transform_json2kadi(input_json)
  from kadi_apy.lib.conversion import json_to_kadi
  output_json = json_to_kadi(input_json)

  # Print the output JSON
  print(json.dumps(output_json, indent=2))