在Django的模型中执行原始SQL查询的方法
有时候你会发现Django数据库API带给你的也只有这么多，那你可以为你的数据库写一些自定义SQL查询。 你可以通过导入django.db.connection对像来轻松实现，它代表当前数据库连接。 要使用它，需要通过connection.cursor()得到一个游标对像。 然后，使用cursor.execute(sql, [params])来执行SQL语句，使用cursor.fetchone()或者cursor.fetchall()来返回记录集。 例如:
>>> from django.db import connection
>>> cursor = connection.cursor()
>>> cursor.execute("""
... SELECT DISTINCT first_name
... FROM people_person
... WHERE last_name = %s""", ['Lennon'])
>>> row = cursor.fetchone()
>>> print row
['John']
connection和cursor几乎实现了标准Python DB-API，你可以访问` http://www.python.org/peps/pep-0249.html
不要把你的视图代码和django.db.connection语句混杂在一起，把它们放在自定义模型或者自定义manager方法中是个不错的主意。 比如，上面的例子可以被整合成一个自定义manager方法，就像这样：
from django.db import connection, models
class PersonManager(models.Manager):
def first_names(self, last_name):
cursor = connection.cursor()
cursor.execute("""
SELECT DISTINCT first_name
FROM people_person
WHERE last_name = %s""", [last_name])
return [row[0] for row in cursor.fetchone()]
class Person(models.Model):
first_name = models.CharField(max_length=50)
last_name = models.CharField(max_length=50)
objects = PersonManager()
然后这样使用:
>>> Person.objects.first_names('Lennon')
['John', 'Cynthia']
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1389
52
What is the difference between HQL and SQL in Hibernate framework?
Apr 17, 2024 pm 02:57 PM
HQL and SQL are compared in the Hibernate framework: HQL (1. Object-oriented syntax, 2. Database-independent queries, 3. Type safety), while SQL directly operates the database (1. Database-independent standards, 2. Complex executable queries and data manipulation).
The world's most powerful open source MoE model is here, with Chinese capabilities comparable to GPT-4, and the price is only nearly one percent of GPT-4-Turbo
May 07, 2024 pm 04:13 PM
Imagine an artificial intelligence model that not only has the ability to surpass traditional computing, but also achieves more efficient performance at a lower cost. This is not science fiction, DeepSeek-V2[1], the world’s most powerful open source MoE model is here. DeepSeek-V2 is a powerful mixture of experts (MoE) language model with the characteristics of economical training and efficient inference. It consists of 236B parameters, 21B of which are used to activate each marker. Compared with DeepSeek67B, DeepSeek-V2 has stronger performance, while saving 42.5% of training costs, reducing KV cache by 93.3%, and increasing the maximum generation throughput to 5.76 times. DeepSeek is a company exploring general artificial intelligence
Hello, electric Atlas! Boston Dynamics robot comes back to life, 180-degree weird moves scare Musk
Apr 18, 2024 pm 07:58 PM
Boston Dynamics Atlas officially enters the era of electric robots! Yesterday, the hydraulic Atlas just "tearfully" withdrew from the stage of history. Today, Boston Dynamics announced that the electric Atlas is on the job. It seems that in the field of commercial humanoid robots, Boston Dynamics is determined to compete with Tesla. After the new video was released, it had already been viewed by more than one million people in just ten hours. The old people leave and new roles appear. This is a historical necessity. There is no doubt that this year is the explosive year of humanoid robots. Netizens commented: The advancement of robots has made this year's opening ceremony look like a human, and the degree of freedom is far greater than that of humans. But is this really not a horror movie? At the beginning of the video, Atlas is lying calmly on the ground, seemingly on his back. What follows is jaw-dropping
KAN, which replaces MLP, has been extended to convolution by open source projects
Jun 01, 2024 pm 10:03 PM
Earlier this month, researchers from MIT and other institutions proposed a very promising alternative to MLP - KAN. KAN outperforms MLP in terms of accuracy and interpretability. And it can outperform MLP running with a larger number of parameters with a very small number of parameters. For example, the authors stated that they used KAN to reproduce DeepMind's results with a smaller network and a higher degree of automation. Specifically, DeepMind's MLP has about 300,000 parameters, while KAN only has about 200 parameters. KAN has a strong mathematical foundation like MLP. MLP is based on the universal approximation theorem, while KAN is based on the Kolmogorov-Arnold representation theorem. As shown in the figure below, KAN has
FisheyeDetNet: the first target detection algorithm based on fisheye camera
Apr 26, 2024 am 11:37 AM
Target detection is a relatively mature problem in autonomous driving systems, among which pedestrian detection is one of the earliest algorithms to be deployed. Very comprehensive research has been carried out in most papers. However, distance perception using fisheye cameras for surround view is relatively less studied. Due to large radial distortion, standard bounding box representation is difficult to implement in fisheye cameras. To alleviate the above description, we explore extended bounding box, ellipse, and general polygon designs into polar/angular representations and define an instance segmentation mIOU metric to analyze these representations. The proposed model fisheyeDetNet with polygonal shape outperforms other models and simultaneously achieves 49.5% mAP on the Valeo fisheye camera dataset for autonomous driving
Tesla robots work in factories, Musk: The degree of freedom of hands will reach 22 this year!
May 06, 2024 pm 04:13 PM
The latest video of Tesla's robot Optimus is released, and it can already work in the factory. At normal speed, it sorts batteries (Tesla's 4680 batteries) like this: The official also released what it looks like at 20x speed - on a small "workstation", picking and picking and picking: This time it is released One of the highlights of the video is that Optimus completes this work in the factory, completely autonomously, without human intervention throughout the process. And from the perspective of Optimus, it can also pick up and place the crooked battery, focusing on automatic error correction: Regarding Optimus's hand, NVIDIA scientist Jim Fan gave a high evaluation: Optimus's hand is the world's five-fingered robot. One of the most dexterous. Its hands are not only tactile
The latest from Oxford University! Mickey: 2D image matching in 3D SOTA! (CVPR\'24)
Apr 23, 2024 pm 01:20 PM
Project link written in front: https://nianticlabs.github.io/mickey/ Given two pictures, the camera pose between them can be estimated by establishing the correspondence between the pictures. Typically, these correspondences are 2D to 2D, and our estimated poses are scale-indeterminate. Some applications, such as instant augmented reality anytime, anywhere, require pose estimation of scale metrics, so they rely on external depth estimators to recover scale. This paper proposes MicKey, a keypoint matching process capable of predicting metric correspondences in 3D camera space. By learning 3D coordinate matching across images, we are able to infer metric relative
Single card running Llama 70B is faster than dual card, Microsoft forced FP6 into A100 | Open source
Apr 29, 2024 pm 04:55 PM
FP8 and lower floating point quantification precision are no longer the "patent" of H100! Lao Huang wanted everyone to use INT8/INT4, and the Microsoft DeepSpeed team started running FP6 on A100 without official support from NVIDIA. Test results show that the new method TC-FPx's FP6 quantization on A100 is close to or occasionally faster than INT4, and has higher accuracy than the latter. On top of this, there is also end-to-end large model support, which has been open sourced and integrated into deep learning inference frameworks such as DeepSpeed. This result also has an immediate effect on accelerating large models - under this framework, using a single card to run Llama, the throughput is 2.65 times higher than that of dual cards. one
