142 lines
4 KiB
Python
142 lines
4 KiB
Python
# Copyright (c) 2022, Frappe Technologies Pvt. Ltd. and Contributors
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# License: MIT. See LICENSE
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from contextlib import suppress
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import frappe
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from frappe import _
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from frappe.query_builder.functions import DateFormat, Function
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from frappe.query_builder.utils import DocType
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from frappe.utils.data import add_to_date, cstr, flt, now_datetime
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from frappe.utils.formatters import format_value
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def get_monthly_results(
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goal_doctype: str,
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goal_field: str,
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date_col: str,
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filters: dict,
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aggregation: str = "sum",
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) -> dict:
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"""Get monthly aggregation values for given field of doctype"""
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Table = DocType(goal_doctype)
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date_format = "%m-%Y" if frappe.db.db_type != "postgres" else "MM-YYYY"
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return dict(
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frappe.qb.get_query(
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table=goal_doctype,
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fields=[
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DateFormat(Table[date_col], date_format).as_("month_year"),
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Function(aggregation, goal_field),
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],
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filters=filters,
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validate_filters=True,
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)
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.groupby("month_year")
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.run()
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)
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@frappe.whitelist()
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def get_monthly_goal_graph_data(
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title: str,
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doctype: str,
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docname: str,
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goal_value_field: str,
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goal_total_field: str,
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goal_history_field: str,
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goal_doctype: str,
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goal_doctype_link: str,
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goal_field: str,
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date_field: str,
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aggregation: str = "sum",
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filters: str | dict | None = None,
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) -> dict:
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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 aggregation: a value like 'count', 'sum', 'avg'
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:param filters: optional filters
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:return: dict of graph data
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"""
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doc = frappe.get_doc(doctype, docname)
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doc.check_permission()
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meta = doc.meta
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goal = doc.get(goal_value_field)
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today_date = now_datetime().date()
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current_month_value = doc.get(goal_total_field)
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current_month_year = today_date.strftime("%m-%Y") # eg: "02-2022"
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formatted_value = format_value(current_month_value, meta.get_field(goal_total_field), doc)
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history = doc.get(goal_history_field)
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month_to_value_dict = None
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if history and "{" in cstr(history):
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with suppress(ValueError):
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month_to_value_dict = frappe.parse_json(history)
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if month_to_value_dict is None: # nosemgrep
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doc_filter = {}
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with suppress(ValueError):
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doc_filter = frappe.parse_json(filters or "{}")
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if doctype != goal_doctype:
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doc_filter[goal_doctype_link] = docname
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month_to_value_dict = get_monthly_results(
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goal_doctype, goal_field, date_field, doc_filter, aggregation
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)
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month_to_value_dict[current_month_year] = current_month_value
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month_labels = []
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dataset_values = []
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values_formatted = []
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y_markers = {}
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summary_values = [
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{"title": _("This month"), "color": "#ffa00a", "value": formatted_value},
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]
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if flt(goal) > 0:
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formatted_goal = format_value(goal, meta.get_field(goal_value_field), doc)
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summary_values += [
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{"title": _("Goal"), "color": "#5e64ff", "value": formatted_goal},
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{
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"title": _("Completed"),
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"color": "#28a745",
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"value": f"{round(flt(current_month_value) / flt(goal) * 100)}%",
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},
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]
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y_markers = {"yMarkers": [{"label": _("Goal"), "lineType": "dashed", "value": flt(goal)}]}
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for i in range(12):
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date_value = add_to_date(today_date, months=-i, as_datetime=True)
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month_word = date_value.strftime("%b %y") # eg: "Feb 22"
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month_labels.insert(0, month_word)
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month_value = date_value.strftime("%m-%Y") # eg: "02-2022"
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val = month_to_value_dict.get(month_value, 0)
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dataset_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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return {
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"title": title,
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"data": {
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"datasets": [{"values": dataset_values, "formatted": values_formatted}],
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"labels": month_labels,
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**y_markers,
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},
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"summary": summary_values,
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}
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