import pandas as pd
import json
from datetime import datetime
import numpy as np
import math


def jsonify(obj):
    if isinstance(obj, dict):
        return {jsonify(k):jsonify(v) for k,v in obj.items()}
    elif isinstance(obj, list):
        return [jsonify(v) for v in obj]
    elif isinstance(obj, float) and math.isnan(obj):
        return None
    # elif isinstance(obj, int) and obj > 10:
    #     return datetime.fromtimestamp(obj)
    elif isinstance(obj, datetime):
        return str(obj)
    return obj

root_dir = "/home/tonydero/projects/weather-pydash/"

sensors_dict = pd.read_pickle(root_dir+"output/saved_sensors_dict.pkl")
json_dict = jsonify(sensors_dict)
# print(datetime.fromtimestamp(list(none_dict.keys())[0]))
# print(type(datetime.fromtimestamp(list(none_dict.keys())[0])) == datetime)
# print(type(list(none_dict.keys())[-1]) == datetime)
# print(list(none_dict.keys())[-1].strftime("%s"))
# none_df = pd.DataFrame(none_dict)

with open(root_dir+'output/json_dict.json', 'w', encoding='utf-8') as f:
    json.dump(json_dict, f, ensure_ascii=False, indent=4)
with open(root_dir+"output/json_dict.json", "r") as jf:
    json_read_dict = json.load(jf)

int_timestamps = {int(k):v for k,v in json_read_dict.items()}

print(json_dict == int_timestamps)

# sensors_df = pd.DataFrame(sensors_dict)

# sensors_df.T.to_csv("sensors_df.csv")
# print(datetime.now().strftime("%s"))
# none_df.T.to_csv(root_dir+"output/none_df.csv")

# none_read_df = pd.read_csv(root_dir+"output/none_df.csv")
# print(none_read_df)
# concat_df = pd.concat([none_read_df, none_read_df], ignore_index=True)
# print(concat_df.tail())