Query Builder

frappe.qb is a query builder written around PyPika to build a single interface for cross-db queries

While developing apps, you'll often need to retrieve some specific data from the database. One way to do this is to use frappe.db.sql and write raw SQL queries.

Maybe something like

result = frappe.db.sql(
    SELECT `path`,
            COUNT(*) as count,
            COUNT(CASE WHEN CAST(`is_unique` as Integer) = 1 THEN 1 END) as unique_count
    FROM `tabWeb Page View`
    WHERE `creation` BETWEEN {some_date} AND {some_later_date}

The query builder API makes this easier by providing a simple pythonic API to build SQL queries without limiting the flexibility of handwritten SQL.

The same query in the query builder would look something like

import frappe
from frappe.query_builder import DocType
from frappe.query_builder.functions import Count
from pypika.terms import Case

WebPageView = DocType("Web Page View") # you can also use frappe.qb.DocType to bypass an import

count_all = Count('*').as_("count")
case = Case().when(WebPageView.is_unique == "1", "1")
count_is_unique = Count(case).as_("unique_count")

result = (
        .select(WebPageView.path, count_all, count_is_unique)


Returns a Pypika query object which lets you build queries. Queries built using this object will be a type from pypika.dialects, sprinkled with some Frappe sugar. Some of its methods are:


lets you construct a from query to select data

Select query

query = frappe.qb.from_('Customer').select('id', 'fname', 'lname', 'phone')

The SQL query built is

SELECT `id`,`fname`,`lname`,`phone` FROM `tabCustomer`

A complex Select example

customers = frappe.qb.DocType('Customer')
q = (
        .select(customers.id, customers.fname,customers.lname, customers.phone)
        .where((customers.fname == 'Max') | (customers.id.like('RA%')) )
        .where(customers.lname == 'Mustermann')

The SQL query built is

SELECT `id`,`fname`,`lname`,`phone` FROM `tabCustomer` WHERE (`fname`='Max' OR `id` LIKE 'RA%') AND `lname`='Mustermann'

Some noteworthy things

  • We have created a customers variable to refer to the table in the query.
  • Select can take any number of arguments, selecting various Fields.
  • The '|' (pipe) or '&' (ampersand) operators can be used to refer to 'OR' or 'AND'.
  • Chaining the where() method appends 'AND' by default

You can read more about the other functions at the Pypika repo.


Returns a PyPika table object which can be used elsewhere. It will automatically add 'tab' if necessary.


Does the same thing as frappe.qb.DocType but will not append 'tab'. It's intended to be used with '__Auth' like tables.

Note: You should only use this if you know what you are doing.


Return a PyPika field object, this represents a column. They are usually used to compare columns with values.

One example would be

lname = frappe.qb.Field("lname")
q = frapppe.qb.from_("customers").select("*").where(lname == 'Mustermann')

Executing queries

Queries built using the frappe.qb namespace are PyPika objects. They will have to be converted to string objects so that your database management system can recognize them.

To check how your query object translates, you can type cast it with str or use the .get_sql method they come with.

query = frappe.qb.from_('Customer').select('id', 'fname', 'lname', 'phone')

# SELECT "id","fname","lname","phone" FROM "tabCustomer"

# SELECT "id","fname","lname","phone" FROM "tabCustomer"

str(query) == query.get_sql()
# True

Walk method

All queries built through frappe.qb are parameterized by default. All input fields, raw values, and functions are separated as Named parameters and sent to the database as a dictionary. Parameterization is done to sanitize queries which would prevent SQL injections.

You use the walk method to check out which parts are parameterized. It returns the parameterized query and the corresponding dictionary.

doctype = frappe.qb.DocType("DocType")

frappe.qb.from_(doctype).select('*').where(doctype.name == "somename").walk()
# ('SELECT * FROM `tabDocType` WHERE `name`=%(param1)s', {'param1': 'somename'})

Run method

This is the most preferred method to execute your queries. Every valid query has the run method which you may use to execute the query with.

frappe.qb.from_('Customer').select('id', 'fname', 'lname', 'phone').run()

The run method accepts kwargs which will be passed on while the query is being executed. You may pass whatever options are available in frappe.db.sql, through the run method.

To run debug on your query, or get the result in the form of List[Dict], you may use the following respectively:

In [7]: frappe.qb.from_('ToDo').select('name').run(debug=True)
SELECT "name" FROM "tabToDo"
Execution time: 0.0 sec
Out[7]: [('8d765f73a2',)]

In [8]: frappe.qb.from_('ToDo').select('name').run(as_dict=True)
Out[8]: [{'name': '8d765f73a2'}]

The run method internally calls the lower level frappe.db.sql API.


ou may choose to directly pass your query objects to frappe.db.sql too. This ignores permisions and paramaterisation of queries.

query = frappe.qb.from_('Customer').select('id', 'fname', 'lname', 'phone')


This module provides standard functions you might need while building queries, like Count() and Sum().

Joins and Sub-queries

You can check pypika documentation to join tables and add subqueries. Instead of Table, use frappe.qb.DocType


HasRole = frappe.qb.DocType('Has Role')
CustomRole = frappe.qb.DocType('Custom Role')

query = (frappe.qb.from_(HasRole)
    .on(CustomRole.name == HasRole.parent)
    .select(CustomRole.page, HasRole.parent, HasRole.role))

Simple functions

Say you want to count all the entries in a Notes table. You could do something like

from frappe.query_builder.functions import Count

Notes = frappe.qb.DocType("Notes")
count_pages = Count(Notes.content).as_("Pages")

result = frappe.qb.from_(Notes).select(count_pages).run(as_dict=True)

Custom Functions

frappe.query_builder.functions is a superset of pypika.functions, so it has all PyPika functions and some custom ones we made. You can make your custom functions by importing the CustomFunction class from PyPika

One implementation of the DateDiff function

from pypika import CustomFunction

customers = Tables('Customer')
DateDiff = CustomFunction('DATE_DIFF', ['interval', 'start_date', 'end_date'])

q = Query.from_(customers).select(
    DateDiff('day', customers.created_date, customers.updated_date)

If we print q, we would get

SELECT DATE_DIFF('day',"created_date","updated_date") FROM "Customer"

Notice how we specify arguments and the actual SQL text. The exact format might not work for more complex functions. The advanced section covers more complicated methods.

Constant Column

ConstantColumn is a class to define a pseudo column with a constant value.

from frappe.query_builder.custom import ConstantColumn

frappe.qb.from_("DocType").select("name", ConstantColumn("john").as_("user"))
# SELECT `name`,'john' `user` FROM `tabDocType`

Here we define a column user with the value "john."


Special functions

One such function is Match Against. It's different because it has a chained against argument. To implement something like this you need to inherit from PyPika's DistinctOptionFunction class.

The current MATCH class looks something like

from pypika.functions import DistinctOptionFunction
from pypika.utils import builder

class MATCH(DistinctOptionFunction):
    def __init__(self, column: str, *args:
        super(MATCH, self)._init_(" MATCH", column, *args)
        self._Against = False

    def get_function_sql(self, **kwargs):
        s = super(DistinctOptionFunction, self).get_function_sql(**kwargs)

        if self._Against:
            return f"{s} AGAINST (f'+{self._Against}*') IN BOOLEAN MODE)"
        return s

    def Against(self, text: str):
        self._Against = text
  • The __init__() method works similar to CustomFunction class above. You mention all the arguments and the SQL text.
  • The Against() method only stores a value that will be used in the get_function_sql()
  • It also has the @builder wrapper. In short, it lets these functions be chainable by making a copy of the object.
  • We have wrapped the get_function_sql() method, which allows us to append the required SQL text for Against.
  • this can further be extended to use any number other chains.

In use, the Match class looks like this

from frappe.query_builder.functions import Match

match = Match("Coloum name").Against("Some_text_match")
# MATCH('Coloum name') AGAINST ('+Some_text_match*' IN BOOLEAN MODE)



In the rare case where you have different functions for different SQL dialects, Which do the same thing, you can use the ImportMapper Utility. It maps functions based on the SQL dialect, so one query works across different SQL dialects.

It takes in a dict which maps functions to databases.

For example the the mapping for GroupConat looks like this

from frappe.query_builder.utils import ImportMapper, db_type_is
from frappe.query_builder.custom import GROUP_CONCAT, STRING_AGG

GroupConcat = ImportMapper(
        db_type_is.MARIADB: GROUP_CONCAT,
        db_type_is.POSTGRES: STRING_AGG

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