158 lines
4.5 KiB
Python
158 lines
4.5 KiB
Python
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors
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# License: GNU General Public License v3. See license.txt
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from __future__ import unicode_literals
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import frappe
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from frappe import _
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def get_monthly_results(goal_doctype, goal_field, date_col, filter_str, aggregation = 'sum'):
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'''Get monthly aggregation values for given field of doctype'''
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# TODO: move to ORM?
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if(frappe.db.db_type == 'postgres'):
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month_year_format_query = '''to_char("{}", 'MM-YYYY')'''.format(date_col)
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else:
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month_year_format_query = 'date_format(`{}`, "%m-%Y")'.format(date_col)
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conditions = ('where ' + filter_str) if filter_str else ''
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results = frappe.db.sql('''SELECT {aggregation}(`{goal_field}`) AS {goal_field},
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{month_year_format_query} AS month_year
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FROM `{table_name}` {conditions}
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GROUP BY month_year'''
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.format(
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aggregation=aggregation,
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goal_field=goal_field,
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month_year_format_query=month_year_format_query,
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table_name="tab" + goal_doctype,
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conditions=conditions
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), as_dict=True)
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month_to_value_dict = {}
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for d in results:
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month_to_value_dict[d['month_year']] = d[goal_field]
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return month_to_value_dict
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@frappe.whitelist()
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def get_monthly_goal_graph_data(title, doctype, docname, goal_value_field, goal_total_field, goal_history_field,
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goal_doctype, goal_doctype_link, goal_field, date_field, filter_str, aggregation="sum"):
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'''
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Get month-wise graph data for a doctype based on aggregation values of a field in the goal doctype
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:param title: Graph title
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:param doctype: doctype of graph doc
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:param docname: of the doc to set the graph in
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:param goal_value_field: goal field of doctype
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:param goal_total_field: current month value field of doctype
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:param goal_history_field: cached history field
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:param goal_doctype: doctype the goal is based on
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:param goal_doctype_link: doctype link field in goal_doctype
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:param goal_field: field from which the goal is calculated
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:param filter_str: where clause condition
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:param aggregation: a value like 'count', 'sum', 'avg'
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:return: dict of graph data
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'''
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from frappe.utils.formatters import format_value
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import json
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# should have atleast read perm
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if not frappe.has_permission(goal_doctype):
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return None
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meta = frappe.get_meta(doctype)
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doc = frappe.get_doc(doctype, docname)
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goal = doc.get(goal_value_field)
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formatted_goal = format_value(goal, meta.get_field(goal_value_field), doc)
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current_month_value = doc.get(goal_total_field)
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formatted_value = format_value(current_month_value, meta.get_field(goal_total_field), doc)
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from frappe.utils import today, getdate, formatdate, add_months
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current_month_year = formatdate(today(), "MM-yyyy")
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history = doc.get(goal_history_field)
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try:
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month_to_value_dict = json.loads(history) if history and '{' in history else None
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except ValueError:
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month_to_value_dict = None
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if month_to_value_dict is None:
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doc_filter = (goal_doctype_link + " = " + frappe.db.escape(docname)) if doctype != goal_doctype else ''
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if filter_str:
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doc_filter += ' and ' + filter_str if doc_filter else filter_str
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month_to_value_dict = get_monthly_results(goal_doctype, goal_field, date_field, doc_filter, aggregation)
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month_to_value_dict[current_month_year] = current_month_value
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months = []
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months_formatted = []
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values = []
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values_formatted = []
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for i in range(0, 12):
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date_value = add_months(today(), -i)
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month_value = formatdate(date_value, "MM-yyyy")
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month_word = getdate(date_value).strftime('%b %y')
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month_year = getdate(date_value).strftime('%B') + ', ' + getdate(date_value).strftime('%Y')
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months.insert(0, month_word)
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months_formatted.insert(0, month_year)
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if month_value in month_to_value_dict:
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val = month_to_value_dict[month_value]
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else:
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val = 0
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values.insert(0, val)
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values_formatted.insert(0, format_value(val, meta.get_field(goal_total_field), doc))
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y_markers = []
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summary_values = [
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{
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'title': _("This month"),
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'color': '#ffa00a',
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'value': formatted_value
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}
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]
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if float(goal) > 0:
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y_markers = [
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{
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'label': _("Goal"),
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'lineType': "dashed",
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'value': goal
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},
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]
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summary_values += [
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{
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'title': _("Goal"),
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'color': '#5e64ff',
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'value': formatted_goal
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},
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{
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'title': _("Completed"),
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'color': '#28a745',
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'value': str(int(round(float(current_month_value)/float(goal)*100))) + "%"
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}
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]
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data = {
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'title': title,
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# 'subtitle':
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'data': {
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'datasets': [
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{
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'values': values,
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'formatted': values_formatted
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}
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],
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'labels': months,
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},
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'summary': summary_values,
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}
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if y_markers:
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data["data"]["yMarkers"] = y_markers
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return data
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