# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors
# License: GNU General Public License v3. See license.txt

from __future__ import unicode_literals
import frappe
from frappe import _


def get_monthly_results(goal_doctype, goal_field, date_col, filter_str, aggregation = 'sum'):
	'''Get monthly aggregation values for given field of doctype'''
	# TODO: move to ORM?
	if(frappe.db.db_type == 'postgres'):
		month_year_format_query = '''to_char("{}", 'MM-YYYY')'''.format(date_col)
	else:
		month_year_format_query = 'date_format(`{}`, "%m-%Y")'.format(date_col)

	conditions = ('where ' + filter_str) if filter_str else ''
	results = frappe.db.sql('''SELECT {aggregation}(`{goal_field}`) AS {goal_field},
		{month_year_format_query} AS month_year
		FROM `{table_name}` {conditions}
		GROUP BY month_year'''
		.format(
			aggregation=aggregation,
			goal_field=goal_field,
			month_year_format_query=month_year_format_query,
			table_name="tab" + goal_doctype,
			conditions=conditions
		), as_dict=True)

	month_to_value_dict = {}
	for d in results:
		month_to_value_dict[d['month_year']] = d[goal_field]

	return month_to_value_dict

@frappe.whitelist()
def get_monthly_goal_graph_data(title, doctype, docname, goal_value_field, goal_total_field, goal_history_field,
	goal_doctype, goal_doctype_link, goal_field, date_field, filter_str, aggregation="sum"):
	'''
		Get month-wise graph data for a doctype based on aggregation values of a field in the goal doctype

		:param title: Graph title
		:param doctype: doctype of graph doc
		:param docname: of the doc to set the graph in
		:param goal_value_field: goal field of doctype
		:param goal_total_field: current month value field of doctype
		:param goal_history_field: cached history field
		:param goal_doctype: doctype the goal is based on
		:param goal_doctype_link: doctype link field in goal_doctype
		:param goal_field: field from which the goal is calculated
		:param filter_str: where clause condition
		:param aggregation: a value like 'count', 'sum', 'avg'

		:return: dict of graph data
	'''

	from frappe.utils.formatters import format_value
	import json

	meta = frappe.get_meta(doctype)
	doc = frappe.get_doc(doctype, docname)

	goal = doc.get(goal_value_field)
	formatted_goal = format_value(goal, meta.get_field(goal_value_field), doc)

	current_month_value = doc.get(goal_total_field)
	formatted_value = format_value(current_month_value, meta.get_field(goal_total_field), doc)

	from frappe.utils import today, getdate, formatdate, add_months
	current_month_year = formatdate(today(), "MM-yyyy")

	history = doc.get(goal_history_field)
	try:
		month_to_value_dict = json.loads(history) if history and '{' in history else None
	except ValueError:
		month_to_value_dict = None

	if month_to_value_dict is None:
		doc_filter = (goal_doctype_link + " = " + frappe.db.escape(docname)) if doctype != goal_doctype else ''
		if filter_str:
			doc_filter += ' and ' + filter_str if doc_filter else filter_str
		month_to_value_dict = get_monthly_results(goal_doctype, goal_field, date_field, doc_filter, aggregation)
		frappe.db.set_value(doctype, docname, goal_history_field, json.dumps(month_to_value_dict))

	month_to_value_dict[current_month_year] = current_month_value

	months = []
	months_formatted = []
	values = []
	values_formatted = []
	for i in range(0, 12):
		date_value = add_months(today(), -i)
		month_value = formatdate(date_value, "MM-yyyy")
		month_word = getdate(date_value).strftime('%b %y')
		month_year = getdate(date_value).strftime('%B') + ', ' + getdate(date_value).strftime('%Y')
		months.insert(0, month_word)
		months_formatted.insert(0, month_year)
		if month_value in month_to_value_dict:
			val = month_to_value_dict[month_value]
		else:
			val = 0
		values.insert(0, val)
		values_formatted.insert(0, format_value(val, meta.get_field(goal_total_field), doc))

	y_markers = []
	summary_values = [
		{
			'title': _("This month"),
			'color': '#ffa00a',
			'value': formatted_value
		}
	]

	if float(goal) > 0:
		y_markers = [
			{
				'label': _("Goal"),
				'lineType': "dashed",
				'value': goal
			},
		]
		summary_values += [
			{
				'title': _("Goal"),
				'color': '#5e64ff',
				'value': formatted_goal
			},
			{
				'title': _("Completed"),
				'color': '#28a745',
				'value': str(int(round(float(current_month_value)/float(goal)*100))) + "%"
			}
		]

	data = {
		'title': title,
		# 'subtitle':

		'data': {
			'datasets': [
				{
					'values': values,
					'formatted': values_formatted
				}
			],
			'labels': months,
		},

		'summary': summary_values,
	}

	if y_markers:
		data["data"]["yMarkers"] = y_markers

	return data