我已经做了一个你可以使用的小片段:

from django.conf import settings
from django.db import connection


def sql_echo(method, *args, **kwargs):
    settings.DEBUG = True
    result = method(*args, **kwargs)
    for query in connection.queries:
        print(query)
    return result


# HOW TO USE EXAMPLE:
# 
# result = sql_echo(my_method, 'whatever', show=True)

它以参数函数(包含sql查询)来检查和args, kwargs需要调用该函数。结果它返回函数返回的内容，并在控制台中打印SQL查询。

下面基于https://code.djangoproject.com/ticket/17741:返回有效的SQL查询

def str_query(qs):
    """
    qs.query returns something that isn't valid SQL, this returns the actual
    valid SQL that's executed: https://code.djangoproject.com/ticket/17741
    """
    cursor = connections[qs.db].cursor()
    query, params = qs.query.sql_with_params()
    cursor.execute('EXPLAIN ' + query, params)
    res = str(cursor.db.ops.last_executed_query(cursor, query, params))
    assert res.startswith('EXPLAIN ')
    return res[len('EXPLAIN '):]

我已经做了一个你可以使用的小片段:

from django.conf import settings
from django.db import connection


def sql_echo(method, *args, **kwargs):
    settings.DEBUG = True
    result = method(*args, **kwargs)
    for query in connection.queries:
        print(query)
    return result


# HOW TO USE EXAMPLE:
# 
# result = sql_echo(my_method, 'whatever', show=True)

它以参数函数(包含sql查询)来检查和args, kwargs需要调用该函数。结果它返回函数返回的内容，并在控制台中打印SQL查询。

为CREATE / UPDATE / DELETE /命令生成SQL，这在Django中是即时的

from django.db.models import sql

def generate_update_sql(queryset, update_kwargs):
    """Converts queryset with update_kwargs
    like : queryset.update(**update_kwargs) to UPDATE SQL"""

    query = queryset.query.clone(sql.UpdateQuery)
    query.add_update_values(update_kwargs)
    compiler = query.get_compiler(queryset.db)
    sql, params = compiler.as_sql()
    return sql % params

from django.db.models import sql

def generate_delete_sql(queryset):
    """Converts select queryset to DELETE SQL """
    query = queryset.query.chain(sql.DeleteQuery)
    compiler = query.get_compiler(queryset.db)
    sql, params = compiler.as_sql()
    return sql % params

from django.db.models import sql

def generate_create_sql(model, model_data):
    """Converts queryset with create_kwargs
    like if was: queryset.create(**create_kwargs) to SQL CREATE"""
    
    not_saved_instance = model(**model_data)
    not_saved_instance._for_write = True

    query = sql.InsertQuery(model)

    fields = [f for f in model._meta.local_concrete_fields if not isinstance(f, AutoField)]
    query.insert_values(fields, [not_saved_instance], raw=False)

    compiler = query.get_compiler(model.objects.db)
    sql, params = compiler.as_sql()[0]
    return sql % params

测试和使用

    def test_generate_update_sql_with_F(self):
        qs = Event.objects.all()
        update_kwargs = dict(description=F('slug'))
        result = generate_update_sql(qs, update_kwargs)
        sql = "UPDATE `api_event` SET `description` = `api_event`.`slug`"
        self.assertEqual(sql, result)

    def test_generate_create_sql(self):
        result = generate_create_sql(Event, dict(slug='a', app='b', model='c', action='e'))
        sql = "INSERT INTO `api_event` (`slug`, `app`, `model`, `action`, `action_type`, `description`) VALUES (a, b, c, e, , )"
        self.assertEqual(sql, result)

我相信这应该工作，如果你使用PostgreSQL:

from django.db import connections
from app_name import models
from django.utils import timezone

# Generate a queryset, use your favorite filter, QS objects, and whatnot.
qs=models.ThisDataModel.objects.filter(user='bob',date__lte=timezone.now())

# Get a cursor tied to the default database
cursor=connections['default'].cursor()

# Get the query SQL and parameters to be passed into psycopg2, then pass
# those into mogrify to get the query that would have been sent to the backend
# and print it out. Note F-strings require python 3.6 or later.
print(f'{cursor.mogrify(*qs.query.sql_with_params())}')

这里已经有几个很好的答案了。

还有一种方法。

在测试中，这样做:

with self.assertNumQueries(3):
    response = self.client.post(reverse('payments:pay_list'))
    # or whatever

如果查询数量错误，则测试失败，并在控制台中打印所有原始SQL查询。

此外，此类测试有助于控制SQL查询的数量不会随着代码的更改而增加，并且数据库负载不会过多。