#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 13 15:14:51 2018
"""

import sys
import json
import datetime
import numpy as np
import pandas as pd
import os
import glob
import shutil
from copy import deepcopy
from pandas.io.json.normalize import nested_to_record
import ast

if sys.version_info[0] >= 3:
    py3 = True
else:
    py3 = False


#https://stackoverflow.com/questions/10756427/loop-through-all-nested-dictionary-values
#def print_nested(d):
#    if isinstance(d, dict):
#        for k, v in d.items():
#            print_nested(v)
#    elif hasattr(d, '__iter__') and not isinstance(d, str):
#        for item in d:
#            print_nested(item)
#    elif isinstance(d, str):
#        print(d)
#
#    else:
#        print(d)
toolPath = os.path.dirname(os.path.abspath(__file__))
table_lib = os.path.join(toolPath,'lib')
templates_path = os.path.join(table_lib,'templates','code_tables')

def templates():
    tables = glob.glob(os.path.join(templates_path,'*.json'))
    return [ os.path.basename(x).split(".")[0] for x in tables ]

def copy_template(table, out_dir = None,out_path = None):
    tables = templates()
    if table in tables:
        table_path = os.path.join(templates_path,table + '.json')
        table_out = out_path if out_path else os.path.join(out_dir,table + '.json')
        shutil.copyfile(table_path,  table_out)
        if os.path.isfile( table_out):
            print('Schema template {0} copied to {1}'.format(table, table_out))
            return
        else:
            print('copy_template ERROR:')
            print('\tError copying table template {0} copied to {1}'.format(table, table_out))
            return
    else:
        print('copy_template ERROR:')
        print('\tRequested template {} must be a valid name.'.format(table))
        print('\tValid names are: {}'.format(", ".join(tables)))
        return

def expand_integer_range_key(d):
    # Looping based on print_nested above
    if isinstance(d, dict):
        for k,v in list(d.items()):
            if 'range_key' in k[0:9]:
                range_params = k[10:-1].split(",")
                try:
                    lower = int(range_params[0])
                except Exception as e:
                    print("Lower bound parsing error in range key: ",k)
                    print("Error is:")
                    print(e)
                    return
                try:
                    upper = int(range_params[1])
                except Exception as e:
                    if range_params[1] == 'yyyy':
                        upper = datetime.date.today().year
                    else:
                        print("Upper bound parsing error in range key: ",k)
                        print("Error is:")
                        print(e)
                        return
                if len(range_params) > 2:
                    try:
                        step = int(range_params[2])
                    except Exception as e:
                        print("Range step parsing error in range key: ",k)
                        print("Error is:")
                        print(e)
                        return
                else:
                    step = 1
                for i_range in range(lower,upper + 1,step):
                    deep_copy_value = deepcopy(d[k]) # Otherwiserepetitions are linked and act as one!
                    d.update({str(i_range):deep_copy_value})
                d.pop(k, None)
            else:
                for k, v in d.items():
                    expand_integer_range_key(v)


def eval_dict_items(item):
    try:
        return ast.literal_eval(item)
    except:
        return item

def read_table(table_path):
    with open(table_path) as fileObj:
        table = json.load(fileObj)
    keys_path = ".".join([".".join(table_path.split('.')[:-1]),'keys'])
    if os.path.isfile(keys_path):
        with open(keys_path) as fileObj:
            table_keys = json.load(fileObj)
            table['_keys'] = {}
            for x,y in table_keys.items():
                key = eval_dict_items(x)
                values = [ eval_dict_items(k) for k in y ]
                table['_keys'][key] = values
    expand_integer_range_key(table)
    return table

def table_keys(table):
    separator = '∿' # something hopefully not in keys...
    if table.get('_keys'):
        _table = deepcopy(table)
        _table.pop('_keys')
        keys = list(nested_to_record(_table,sep = separator).keys())

        return [ x.split(separator) for x in keys ]
    else:
        return list(table.keys())


def get_nested(table,*args):
    # HERE HAVE TO ADD WHICH ITEM TO GET FROM THE KEY: WE HAVE TO ADD VALUE, LOWER, ETC...TO THE CODE TABLES!!!
    # CAN BE AND OPTIONAL PARAMETER, LIKE: similarly, would have to add tbis to table_value_from_keys
#    def get_nested(table,param = None,*args):
#       nested_get_str = 'table'
#       z = np.array([*args])
#       for i,x in enumerate(z):
#           nested_get_str += '.get(z[' + str(i) + '])'
#       if param:
#           nested_get_str += '.get(' + param + ')'
#       try:
#           return eval(nested_get_str)
#       except:
#           return None
    nested_get_str = 'table'
    z = np.array([*args])
    for i,x in enumerate(z):
        nested_get_str += '.get(z[' + str(i) + '])'
    try:
        return eval(nested_get_str)
    except:
        return None

def table_value_from_keys(table,df):
    # df is pd.DataFrame or Series
    v_nested_get = np.vectorize(get_nested) # Because cannot directly vectorize a nested get, we build it in a function, and then vectorize it
    calling_str = 'v_nested_get(table'
    if isinstance(df, pd.DataFrame):
        #return v_nested_get(table,[ df[x]  for x in df]) # This won't work
        for i,x in enumerate(df.columns):
            calling_str += ',df[' + str(x) + '].astype(str)' # have to do likewise in not DataFrame!!!
        calling_str += ')'
        return eval(calling_str)
    else:
        return v_nested_get(table,df)