"""
Functional Transformers

"""
from datetime import datetime, timedelta
import numpy as np
import pandas as pd



def rollfoward_snapshot_dates(df, from_date= datetime.now(), 
                                rollforward_days=7, 
                                column='SNAPSHOT_DATE'):
  """
  Updates snapshot year

  params:
    df (pd.DataFrame) - pandas dataframe
    from_date (date) - date to roll forward from
  """
  _df = df.copy()
  end_date = from_date + timedelta(days=rollforward_days - 1)
  rollout_dates = pd.date_range(start=from_date, end=end_date)
  _df[column] = rollout_dates
  return _df


def rollforward_snapshot_year(df, column='SNAPSHOT_YEAR'):
  """
  Updates snapshot year
  """
  _df = df.copy()
  _df[column]  = np.array([datetime.now().year for _ in range(len(df))])

  return _df


def rollforward_snapshot_isoweek(df, column='SNAPSHOT_ISOWEEK'):
  """ 
  Updates snapshot isoweek 
  
  """
  # roll forward snapshot date
  _df = df.copy()
  _df[column] = _df['SNAPSHOT_DATE'].apply(lambda date_x: date_x.isocalendar()[1])

  return _df


def rollforward_snapshot_month(df, column='SNAPSHOT_MONTH'):
  """ 
  Updates snapshot month 
  
  """
  # roll forward snapshot date
  _df = df.copy()
  _df[column] = _df['SNAPSHOT_DATE'].apply(lambda date_x: date_x.month)

  return _df

def rollforward_snapshot_day_of_year(df, 
                              column='SNAPSHOT_DAY_OF_YEAR'):
  """ 
  Updates snapshot day of year 
  
  """
  # roll forward snapshot date
  _df = df.copy()
  _df[column] = _df['SNAPSHOT_DATE'].apply(lambda date_x: date_x.timetuple().tm_yday)

  return _df


def rollforward_snapshot_day_of_week(df, 
                              column='SNAPSHOT_DAY_OF_WEEK'):
  """ 
  Updates snapshot day of week
  
  """
  # roll forward snapshot date
  _df = df.copy()
  _df[column] = _df['SNAPSHOT_DATE'].apply(lambda date_x: date_x.weekday())

  return _df


def rollforward_release_date(df, 
                              release_date:datetime,
                              column='RELEASE_DATE'):
  """ 
  Updates update release date
  """
  _df = df.copy()

  if isinstance(df, str):
    release_date = pd.to_datetime(release_date)

  _df[column] = release_date

  return _df

def rollforward_release_year(df, 
                              column='RELEASE_YEAR'):
  """ 
  Updates update release date
  """
  _df = df.copy()
  _df[column] = _df['RELEASE_DATE'].apply(lambda date_x: date_x.year)

  return _df

def rollforward_release_month(df, 
                              column='RELEASE_MONTH'):
  """ 
  Updates update release date
  """
  
  _df = df.copy()
  _df[column] = _df['RELEASE_DATE'].apply(lambda date_x: date_x.month)

  return _df


def rollforward_release_day_of_week(df,
                              column='RELEASE_DOW'):
  """ 
  Updates update release date
  """
  
  _df = df.copy()
  _df[column] = _df['RELEASE_DATE'].apply(lambda date_x: date_x.weekday())

  return _df

def rollforward_release_weekiso(df,
                              column='RELEASE_WEEKISO'):
  """ 
  Updates update release date
  """
  
  _df = df.copy()
  _df[column] = _df['RELEASE_DATE'].apply(lambda date_x: date_x.isocalendar()[1])

  return _df

def rollforward_release_age_days(df,
                              column='RELEASE_AGE_DAYS'):
  """ 
  Updates update release date
  """
  _df = df.copy()
  _df[column] = _df.apply(lambda row: (pd.to_datetime(row['SNAPSHOT_DATE']) - pd.to_datetime(row['RELEASE_DATE'])).days, axis=1)

  return _df

def rollforward_release_age_weeks(df,
                              column='RELEASE_AGE_WEEKS'):
  """ 
  Updates update release date
  """
  
  _df = df.copy()
  _df[column] = _df.apply(lambda row: (pd.to_datetime(row['SNAPSHOT_DATE']) - pd.to_datetime(row['RELEASE_DATE'])).days //7 , axis=1)

  return _df