In 2024, you can finally use the python features with confidence

Mondo Technology Updated on 2024-03-07

Technology

Explore new features and upgrades in Python: a powerful tool to improve your programming efficiency.

Preface. In our day-to-day Python programming process, it is commonplace to worry about version compatibility and script calls. However, along with some important libraries such as numpy vs Python 39, we can finally get rid of these concerns and use a series of new features with confidence. This article will dive into these features and how they can improve our programming efficiency.

Print variables are really fragrant.

In the past, print was used

Functions output variable values need to be done by formatting strings or manually constructing output statements。However, python 38 new features introduced make it easy and enjoyable. By adding an equal sign to the end of the variable, we can print out the expression directly, and even support formatting semantics。This change gives us a much easier way to print, making debugging and exporting more intuitive.

In practical applications, this new printing method is not only for the output of variable values, but also for instant feedback on the best logic. For example, during debugging, we can pinpoint the problem more quickly by inserting this print statement at a key location and observing the value of the expression。This real-time interaction helps us debug and optimize more efficiently**.

Walrus operator.

The walrus operator may be a bit abstract in name, but it's very intuitive in practice. Its introduction allows us to define variables at the same time as conditional judgments, which is simple and straightforward. By analogy with the eyes and tusks of the walrus, :=

The operator becomes a shining star in **. Not only in conditionalism, walrus operators can be used in a variety of expression positions, such as while

Circulate. This is python 38 introduces a powerful and flexible feature that gives us more coding possibilities.

In actual coding, the flexibility of the walrus operator gives us more options. For example, when you need to judge conditions and evaluate expressions at the same time in a loop, the traditional way of writing may introduce additional variables, while using the walrus operator can accomplish both tasks in a single line, making it more concise. This simplicity not only improves readability, but also helps reduce potential errors.

Dictionary-derived calculation order.

In different versions of Python, there are some changes in the order in which dictionary derivations are calculated. In the past, it didn't calculate the key first, then the value. This change can have far-reaching implications for some complex use cases, especially when combined with walrus operators. Through the official example, we can see that this is a comprehensive application problem, although it may seem a bit tedious, but in some situations, the advantages of this method will be highlighted。Dictionary-derived computation order variations give us more flexibility in building dictionaries.

In actual programming, dictionary-derived computation order variations provide us with more options. For example, when we need to build a dictionary based on a certain condition, the new order of calculations allows us to make more flexible use of existing variables without being limited by order. This gives us more possibilities for combinations and variations, making ** more expressive.

Functools big upgrade.

functools

As a very useful built-in library in Python, it has always had many useful functions. In earlier versions of Python, cache functions needed to be called with or without arguments. This brings up some cumbersome questions, such as whether parentheses need to be added when calling. However, in the new version, specifically python 38. A new in-instance cache property decorator has been introduced. This change makes the use of cache functions more flexible, and each instantiated object has its own independent cache, which greatly improves the readability and maintainability of the cache.

In practical applications, functools

The big upgrade of the library gives us more advanced tools. For example, when dealing with functions that need to be cached, the new decorator makes it easier to control the granularity of the cache, regardless of whether the function has parameters or not. This flexibility not only improves performance, but also helps to better organize and manage.

Smart prompts are relevant.

Over time, Python's type system has matured and Python 38 also introduces a series of important type system updates. Among them, literal limit provides great convenience for developers who often need to customize general-purpose functions. By defining literal

We can get smarter hints that make the range of function parameters clearer. In addition, a new type system introduces typeddict

The key value of a dictionary can be specified, which may be a little cumbersome in some cases, but it provides more protection for type safety. Finally, the protocol class

The introduction of Python type gymnastics points the way to the future, which can specify that a type must have certain methods, and can be down to the name of the parameters, suitable for developers who need to write generic libraries。These updates and new features have made Python's type system more flexible and intelligent.

In real projects, these updates to the type system provide us with more powerful tools. For example, when writing functions that involve multiple data types, literal limits and typeddict

This allows us to identify potential bugs earlier and reduce debugging time. and protocol protocol

The use of this provides us with a more refined type specification, making it more rigorous and maintainable.

Epilogue. This article provides an in-depth look at Python 38 introduces a range of new features and library upgrades, from print variables to walrus operators to dictionary derivatives and functools

A big upgrade to the library, and finally a smart hint related update to the type system。These changes bring more convenience and flexibility to Python programming, which greatly improves development efficiency. In the ever-evolving world of programming, staying up-to-date with the latest syntax and tools is key to staying competitive, so I encourage everyone to try out these new features to experience the fun and productivity they bring. Don't forget to click three times in a row, your likes, favorites and followers are the biggest motivation for my creation. On the road of pursuing programming technology, let's move forward together, explore more unknown areas, and challenge more exciting programming tasks.

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