


The reason for the error
This error is caused by using Tornado’s ioLoop.add_timeout() or IOLoop.add_callback() method. The value of the deadline parameter passed is not an integer or floating point number. Numeric type parameters should be used.
How to solve
The solution is to check the value of the deadline parameter passed to the IOLoop.add_timeout() or IOLoop.add_callback() method in the code to make sure it is an integer or floating point number.
For example, if you are passing a stringor other non-numeric type value, convert it to an integer or float.
If the error is due to other reasons, please provide more context and code snippets to help me give you a more detailed answer.
Usage example
Yes, here is an example:
import tornado.ioloop def my_callback(): print("callback called") # This will work deadline = tornado.ioloop.IOLoop.current().time() + 5.0 tornado.ioloop.IOLoop.current().add_timeout(deadline, my_callback) # This will raise "TypeError("Unsupported deadline %r" % deadline)" deadline = "5.0" tornado.ioloop.IOLoop.current().add_timeout(deadline, my_callback)
In the first example, we are passing a floating point number as the deadline, which is correct. In the second example, we are passing a string, which will cause an error. We should convert deadline to float type.
deadline = float("5.0") tornado.ioloop.IOLoop.current().add_timeout(deadline, my_callback)
This way you can avoid errors
If you want to run the callback function at some point in the future, you can use the IOLoop.add_timeout() method, which accepts a timestamp as the first parameter, and The callback function is run after this timestamp is reached. For example, if you want to run a callback function after 5 seconds, you can use the following code:
import tornado.ioloop def my_callback(): print("callback called") deadline = tornado.ioloop.IOLoop.current().time() + 5.0 tornado.ioloop.IOLoop.current().add_timeout(deadline, my_callback) # Start the IOLoop tornado.ioloop.IOLoop.current().start()
If you want to run the callback function in the next event loop, you can use the IOLoop.add_callback() method.
import tornado.ioloop def my_callback(): print("callback called") # This will call the callback on the next iteration of the event loop tornado.ioloop.IOLoop.current().add_callback(my_callback) # Start the IOLoop tornado.ioloop.IOLoop.current().start()
Another method is to use the IOLoop.call_later() method, which accepts a number of seconds as the first parameter and runs the callback function after the time has elapsed.
For example, if you want to run the callback function after 5 seconds, you can use the following code:
import tornado.ioloop def my_callback(): print("callback called") tornado.ioloop.IOLoop.current().call_later(5, my_callback) # Start the IOLoop tornado.ioloop.IOLoop.current().start()
If you want to use these methods in more advanced scenarios, you can find more information in the Tornado documentation.
The above is the detailed content of Solution to prompt TypeError(\'Unsupported deadline %r\' % deadline). For more information, please follow other related articles on the PHP Chinese website!

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

WebStorm Mac version
Useful JavaScript development tools

Notepad++7.3.1
Easy-to-use and free code editor

Atom editor mac version download
The most popular open source editor

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.