chained sequential operation

简明释义

联锁顺序操作

英英释义

例句

1.In data processing, a chained sequential operation 链式顺序操作 allows multiple transformations to be applied in a single pipeline.

在数据处理过程中，链式顺序操作 chained sequential operation 允许在单一管道中应用多个转换。

2.By implementing a chained sequential operation 链式顺序操作, we can streamline our workflow significantly.

通过实施 链式顺序操作 chained sequential operation，我们可以显著简化工作流程。

3.The software uses a chained sequential operation 链式顺序操作 to ensure that each task is completed before the next one begins.

该软件使用 链式顺序操作 chained sequential operation 确保每个任务在下一个任务开始之前完成。

4.In programming, a chained sequential operation 链式顺序操作 can help reduce code redundancy and improve readability.

在编程中，链式顺序操作 chained sequential operation 可以帮助减少代码冗余并提高可读性。

5.The data analysis tool supports chained sequential operations 链式顺序操作 for performing complex calculations easily.

该数据分析工具支持 链式顺序操作 chained sequential operations，以便轻松执行复杂计算。

作文

In the realm of computer programming and data processing, the concept of chained sequential operation plays a significant role in enhancing the efficiency and clarity of code. This method involves linking multiple operations together in a sequence, where each operation is dependent on the result of the previous one. By employing this technique, programmers can create more streamlined and readable code, which ultimately leads to easier debugging and maintenance.Consider a simple example in a programming language like Python. Suppose we want to process a list of numbers by first filtering out the even numbers and then squaring the remaining odd numbers. Instead of writing separate functions for each step, we can utilize chained sequential operation to combine these tasks into a single line of code. For instance, we might write:pythonresult = [x**2 for x in filter(lambda y: y % 2 != 0, numbers)]In this example, the `filter` function is applied first to remove even numbers, and then the list comprehension squares each of the remaining numbers. The result is a new list that contains only the squares of the odd numbers. Here, the use of chained sequential operation allows us to efficiently perform multiple transformations in one go.The advantages of using chained sequential operation extend beyond just code brevity. It also improves the logical flow of operations, making it easier for others (or even ourselves at a later time) to understand what the code is doing. Each operation is clearly defined and connected, providing a clear path from input to output.Moreover, chained sequential operation can be particularly beneficial when working with large datasets. In data analysis, for example, one might need to clean, transform, and analyze data in a series of steps. By chaining these operations together, data scientists can create a more efficient workflow. Using libraries such as Pandas in Python, one can easily perform a series of operations on a DataFrame in a concise manner:pythondata_cleaned = (data.dropna() .filter(items=['column1', 'column2']) .assign(new_column=lambda x: x['column1'] + x['column2']))In this snippet, we first drop any rows with missing values, filter the necessary columns, and then create a new column based on the sum of two existing columns. This showcases how chained sequential operation can lead to cleaner and more understandable code.However, it is essential to use chained sequential operation judiciously. While it can enhance clarity and efficiency, overly complex chains can lead to confusion. If too many operations are chained together without proper separation or comments, it may become challenging to trace the flow of data. Therefore, striking a balance between conciseness and readability is crucial.In conclusion, chained sequential operation is a powerful tool in programming and data processing that allows for efficient and clear execution of multiple operations in sequence. By effectively linking operations, programmers can enhance their code's readability and maintainability while also improving performance. As with any technique, it is vital to use it wisely to ensure that the code remains accessible and understandable to all who may work with it in the future. Embracing chained sequential operation can undoubtedly lead to better programming practices and more effective data management.

在计算机编程和数据处理领域，链式顺序操作的概念在提高代码效率和清晰度方面发挥着重要作用。这种方法涉及将多个操作链接在一起，形成一个序列，其中每个操作都依赖于前一个操作的结果。通过采用这一技术，程序员可以创建更简洁、易读的代码，从而最终实现更容易的调试和维护。考虑一个简单的例子，在像Python这样的编程语言中。假设我们想处理一个数字列表，首先过滤掉偶数，然后对剩余的奇数进行平方处理。我们可以利用链式顺序操作将这些任务合并为一行代码，而不是为每个步骤编写单独的函数。例如，我们可能会这样写：pythonresult = [x**2 for x in filter(lambda y: y % 2 != 0, numbers)]在这个例子中，`filter`函数首先被应用以去除偶数，然后列表推导式对每个剩余的数字进行平方处理。结果是一个新列表，仅包含奇数的平方。在这里，使用链式顺序操作使我们能够高效地一次性执行多个转换。使用链式顺序操作的好处不仅限于代码的简洁性。它还改善了操作的逻辑流程，使其他人（甚至是我们自己在稍后的时间）更容易理解代码的功能。每个操作都被明确定义并连接，提供了从输入到输出的清晰路径。此外，当处理大型数据集时，链式顺序操作特别有利。在数据分析中，例如，一个人可能需要对数据进行清理、转换和分析，分步骤进行。通过将这些操作链接在一起，数据科学家可以创建更高效的工作流程。使用Python中的Pandas等库，可以轻松以简洁的方式对DataFrame执行一系列操作：pythondata_cleaned = (data.dropna() .filter(items=['column1', 'column2']) .assign(new_column=lambda x: x['column1'] + x['column2']))在这个代码片段中，我们首先删除任何缺失值的行，过滤所需的列，然后根据两列的和创建一个新列。这展示了如何利用链式顺序操作来实现更清晰、更易于理解的代码。然而，必须谨慎使用链式顺序操作。虽然它可以增强清晰度和效率，但过于复杂的链条可能导致混乱。如果将太多操作链接在一起而没有适当的分隔或注释，可能会很难追踪数据的流动。因此，在简洁性和可读性之间取得平衡至关重要。总之，链式顺序操作是在编程和数据处理中一种强大的工具，它允许以顺序高效且清晰地执行多个操作。通过有效地链接操作，程序员可以提高代码的可读性和可维护性，同时也改善性能。与任何技术一样，明智地使用它是确保代码对所有可能与其合作的人都保持可访问和可理解的关键。拥抱链式顺序操作无疑可以带来更好的编程实践和更有效的数据管理。