chore: cookbook example

src/components/SafeGlobalsTable.astro

@@ -24,7 +24,11 @@ const props: Props = Astro.props;
     <tbody>
       {Object.entries(props.globals).map(([name, value]) => (
         <tr>
-          <td>{name}</td>
+          <a href=""></a>
+          <td>
+            <a href={`#${name}`}></a>
+            {name}
+          </td>
           <td>{value.type}</td>
           <td>{value.docs}</td>
           <td>{value.parent}</td>

src/content/docs/cookbook/Reports/Script Reports/01.md

@@ -0,0 +1,176 @@
+---
+title: Child Table Data in Columns
+description: An example of a report that shows the child table values in a single row with the parent data. Also, columns can be dynamic.
+---
+
+## Introduction
+
+An example of a report that shows the child table values in a single row with the parent data. Also, columns can be dynamic.
+
+## Use Case
+
+Suppose we have a demo DocType named **Credit Card EMI** which has the following fields:
+
+1. Customer Name
+1. Total Amount
+1. Scheme: 3/6/12 Months
+1. EMIs: Child table with EMIs based on the scheme
+
+Here is a screenshot showing the form view:
+
+![Screenshot of Credit Card EMI Doctype form view](../../../../../assets/images/cookbook/reports/credit_card_emi_form_view.png)
+
+## The Report
+
+We want to create a report that has this EMIs in different columns, like shown below:
+
+![Credit Card EMI Summary Report](../../../../../assets/images/cookbook/reports/cc_report.png)
+
+## The Script
+
+```py
+
+import frappe
+
+# maximum number of EMIs for a Credit Card EMI
+# case when EMI is paid in 1 year
+NUM_MAX_EMI = 12
+
+
+def execute(filters=None):
+ columns = get_columns()
+ data = get_data(filters)
+
+ return columns, data
+
+
+def get_columns():
+ columns = [
+  {
+   "label": "Credit Card EMI",
+   "fieldname": "credit_card_emi",
+   "fieldtype": "Link",
+   "options": "Credit Card EMI",
+  },
+  {
+   "label": "Customer Name",
+   "fieldname": "customer_name",
+   "fieldtype": "Data",
+  },
+  {
+   "label": "Scheme",
+   "fieldname": "scheme",
+   "fieldtype": "Data",
+  },
+ ]
+
+ # 1 column for each EMI
+ for i in range(1, NUM_MAX_EMI + 1):
+  columns.append(
+   {
+    "label": "EMI {}".format(i),
+    "fieldname": "emi_{}".format(i),
+    "fieldtype": "Data",
+    "options": "EMI",
+   }
+  )
+
+ return columns
+
+
+def get_data(filters=None):
+ data = []
+
+ credit_card_emis = frappe.get_all(
+  "Credit Card EMI", fields=["name", "customer_name", "scheme"]
+ )
+
+ for credit_card_emi in credit_card_emis:
+  row = {
+   "credit_card_emi": credit_card_emi.name,
+   "customer_name": credit_card_emi.customer_name,
+   "scheme": credit_card_emi.scheme,
+  }
+
+  # get all EMIs (child items) for the Credit Card EMI
+  emis = frappe.get_all(
+   "EMI",
+   fields=["amount", "due_date", "paid", "idx"],
+   filters={"parent": credit_card_emi.name},
+  )
+
+  # e.g. emi_1 = 1000, emi_2 = 2000, emi_3 = 3000, etc.
+  for emi in emis:
+   row["emi_{}".format(emi.idx)] = format_currency(emi.amount)
+
+  # set rest of the EMI columns to "-"
+  for i in range(1, MAX_EMI + 1):
+   if "emi_{}".format(i) not in row:
+    row["emi_{}".format(i)] = "-"
+
+  data.append(row)
+
+ return data
+
+
+def format_currency(value, currency="INR"):
+ return frappe.format_value(value, df={"fieldtype": "Currency"}, currency=currency)
+```
+
+## Optimizing The Data Fetching
+
+If you observe the `get_data()` method, you will see we are calling the `frappe.get_all` method to get child items for each **Credit Card EMI** doc, which means 1 DB call per document (`O(n)` in computer *sciency* terms).
+
+We can use the Query Builder to reduce this to just one database call (line 141):
+
+```py {6-19}
+def get_data_with_qb(filters=None):
+ data = []
+ credit_card_emi = frappe.qb.DocType("Credit Card EMI")
+ emi = frappe.qb.DocType("EMI")
+
+ query = (
+  frappe.qb.from_(emi)
+  .join(credit_card_emi)
+  .on(emi.parent == credit_card_emi.name)
+  .select(
+   credit_card_emi.name.as_("credit_card_emi"),
+   credit_card_emi.customer_name,
+   credit_card_emi.scheme,
+   emi.amount,
+   emi.due_date,
+   emi.paid,
+   emi.idx,
+  )
+ )
+
+ emi_items = query.run(as_dict=True)
+
+ # group EMI items by Credit Card EMI
+ credit_card_emi_items = {}
+ for emi_item in emi_items:
+  credit_card_emi_items.setdefault(emi_item.credit_card_emi, []).append(emi_item)
+
+ # create a row for each Credit Card EMI
+ for credit_card_emi, emi_items in credit_card_emi_items.items():
+  row = {
+   "credit_card_emi": credit_card_emi,
+   "customer_name": emi_items[0].customer_name,
+   "scheme": emi_items[0].scheme,
+  }
+
+  # create a column for each EMI
+  for emi_item in emi_items:
+   row["emi_{}".format(emi_item.idx)] = format_currency(emi_item.amount)
+
+  # set rest of the EMI columns to "-"
+  for i in range(1, MAX_EMI + 1):
+   if "emi_{}".format(i) not in row:
+    row["emi_{}".format(i)] = "-"
+
+  data.append(row)
+
+ return data
+```
+
+We had to add more data processing on the Python side though.