Frappe reports
Frappe Agent Skills gives AI coding assistants structured Frappe knowledge for DocTypes, APIs, Desk customization, frontend apps, reports, testing, and production patterns.
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Create reports in Frappe including Report Builder, Query Reports (SQL), and Script Reports (Python + JS). Use when building data analysis views, dashboards, or custom reporting features.
SKILL.md
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Frappe Reports
Build reports using Report Builder, Query Reports (SQL), or Script Reports (Python + JS).
When to use
- Creating data analysis or summary reports
- Building SQL-based query reports
- Implementing complex reports with Python logic and JS UI
- Adding custom filters, formatters, and charts to reports
- Creating printable report formats
Inputs required
- Report purpose and data requirements
- Source DocType(s) for the report
- Filter requirements
- Column definitions (fields, types, formatting)
- Whether report is standard (app-bundled) or custom (site-specific)
Procedure
0) Choose report type
| Type | Complexity | Code Required | Best For |
|---|---|---|---|
| Report Builder | Low | None | Simple field selection, grouping, sorting |
| Query Report | Medium | SQL only | Direct SQL queries, joins, aggregations |
| Script Report | High | Python + JS | Complex logic, computed fields, dynamic filters |
1) Report Builder
Create via UI with no code:
- Navigate to the Report list → New Report
- Select Reference DocType
- Choose Report Type = "Report Builder"
- Add columns, filters, sorting, and grouping via the builder UI
2) Query Report
Reports using raw SQL queries:
- Create Report → Type = "Query Report"
- Set Reference DocType (controls permissions)
- Write SQL query
SELECT
`tabSales Order`.name AS "Sales Order:Link/Sales Order:200",
`tabSales Order`.customer AS "Customer:Link/Customer:200",
`tabSales Order`.transaction_date AS "Date:Date:120",
`tabSales Order`.grand_total AS "Grand Total:Currency:150",
`tabSales Order`.status AS "Status:Data:100"
FROM `tabSales Order`
WHERE `tabSales Order`.docstatus = 1
{% if filters.company %}
AND `tabSales Order`.company = %(company)s
{% endif %}
{% if filters.from_date %}
AND `tabSales Order`.transaction_date >= %(from_date)s
{% endif %}
ORDER BY `tabSales Order`.transaction_date DESC
Column format in SELECT: "Label:Fieldtype/Options:Width"
| Fieldtype | Example |
|---|---|
| Link | "Customer:Link/Customer:200" |
| Currency | "Amount:Currency:150" |
| Date | "Date:Date:120" |
| Int | "Quantity:Int:100" |
| Data | "Status:Data:100" |
Filter variables: Use %(filter_name)s for parameterized queries.
3) Script Report (standard)
For app-bundled reports with full Python + JS control:
Create the report structure:
my_app/
└── my_module/
└── report/
└── sales_summary/
├── sales_summary.json # Report metadata
├── sales_summary.py # Python data logic
└── sales_summary.js # JS filters and UI
Python script (sales_summary.py):
import frappe
from frappe import _
def execute(filters=None):
columns = get_columns()
data = get_data(filters)
chart = get_chart(data)
return columns, data, None, chart
def get_columns():
return [
{
"label": _("Customer"),
"fieldname": "customer",
"fieldtype": "Link",
"options": "Customer",
"width": 200
},
{
"label": _("Total Orders"),
"fieldname": "total_orders",
"fieldtype": "Int",
"width": 120
},
{
"label": _("Total Amount"),
"fieldname": "total_amount",
"fieldtype": "Currency",
"width": 150
},
{
"label": _("Average Order"),
"fieldname": "avg_order",
"fieldtype": "Currency",
"width": 150
}
]
def get_data(filters):
conditions = get_conditions(filters)
data = frappe.db.sql("""
SELECT
customer,
COUNT(name) as total_orders,
SUM(grand_total) as total_amount,
AVG(grand_total) as avg_order
FROM `tabSales Order`
WHERE docstatus = 1 {conditions}
GROUP BY customer
ORDER BY total_amount DESC
""".format(conditions=conditions), filters, as_dict=True)
return data
def get_conditions(filters):
conditions = ""
if filters.get("company"):
conditions += " AND company = %(company)s"
if filters.get("from_date"):
conditions += " AND transaction_date >= %(from_date)s"
if filters.get("to_date"):
conditions += " AND transaction_date <= %(to_date)s"
return conditions
def get_chart(data):
if not data:
return None
return {
"data": {
"labels": [d.customer for d in data[:10]],
"datasets": [{
"name": _("Total Amount"),
"values": [d.total_amount for d in data[:10]]
}]
},
"type": "bar"
}
JavaScript script (sales_summary.js):
frappe.query_reports["Sales Summary"] = {
filters: [
{
fieldname: "company",
label: __("Company"),
fieldtype: "Link",
options: "Company",
default: frappe.defaults.get_user_default("Company"),
reqd: 1
},
{
fieldname: "from_date",
label: __("From Date"),
fieldtype: "Date",
default: frappe.datetime.add_months(frappe.datetime.get_today(), -1)
},
{
fieldname: "to_date",
label: __("To Date"),
fieldtype: "Date",
default: frappe.datetime.get_today()
}
],
onload(report) {
// Custom initialization
},
formatter(value, row, column, data, default_formatter) {
value = default_formatter(value, row, column, data);
// Highlight high-value customers
if (column.fieldname === "total_amount" && data.total_amount > 100000) {
value = `<span style="color: green; font-weight: bold">${value}</span>`;
}
return value;
}
};
Report JSON (sales_summary.json):
{
"name": "Sales Summary",
"doctype": "Report",
"report_type": "Script Report",
"ref_doctype": "Sales Order",
"module": "My Module",
"is_standard": "Yes",
"disabled": 0
}
4) Add report print format
Create sales_summary.html in the report folder for a custom print layout:
<h2>Sales Summary Report</h2>
<table class="table table-bordered">
<tr>
<th>Customer</th>
<th>Orders</th>
<th>Total</th>
</tr>
{% for row in data %}
<tr>
<td>{{ row.customer }}</td>
<td>{{ row.total_orders }}</td>
<td>{{ frappe.format(row.total_amount, {fieldtype: 'Currency'}) }}</td>
</tr>
{% endfor %}
</table>
5) Register report in hooks (optional)
Reports are auto-discovered if they follow the standard directory structure. No hooks.py entry is needed for standard reports.
Verification
- Report appears in Report list
- Filters work correctly and affect results
- Columns display with proper formatting
- Chart renders (if applicable)
- Permissions respected (only authorized users see data)
- Print format works
- Performance acceptable for expected data volume
Failure modes / debugging
- Report not found: Check module path and
is_standardsetting; runbench migrate - SQL syntax error: Test query in
bench --site <site> mariadbfirst - No data returned: Check
docstatusfilter; verify filters match data - Permission denied: Verify Reference DocType permissions for the user's role
- Slow query: Add indexes; use Query Builder; limit result set
Escalation
- For DocType schema →
frappe-doctype-development - For API endpoints (report data via API) →
frappe-api-development - For Desk UI customization →
frappe-desk-customization
References
- references/reports.md — Report types, creation, and examples
Guardrails
- Validate filters: Check filter values before building queries; handle empty/invalid input
- Handle empty results: Always handle case where query returns no data; show appropriate message
- Use
frappe.db.escape(): Escape user input in SQL queries to prevent injection - Limit result sets: Add LIMIT clause or pagination for large datasets
- Check permissions in execute: Verify user has permission to see the data
Common Mistakes
| Mistake | Why It Fails | Fix |
|---|---|---|
| SQL injection via filters | Security vulnerability | Use frappe.db.escape() or Query Builder with parameters |
| Missing permission checks | Unauthorized data access | Verify frappe.has_permission() or filter by allowed records |
| Unbounded queries | Timeouts, memory issues | Add LIMIT, use pagination, or filter by date range |
| Wrong column fieldtype | Formatting issues | Match column fieldtype to data (Currency, Date, etc.) |
| Not handling None in aggregations | Errors or wrong totals | Use COALESCE() or IFNULL() in SQL |
Hardcoded docstatus assumptions | Missing draft/cancelled records | Explicitly filter docstatus based on report needs |