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正则表达式分词技巧

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正则表达式分词技巧 是 CoddyKit 上的免费 NLP Academy 课时。这是第 4 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 NLP Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 NLP Academy 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Tokenizing With Patterns

You can tokenize text by describing what a token looks like, then letting regex find every piece that fits your definition.

Match Words Directly

The pattern \w+ with findall grabs every run of word characters, giving you a clean list of words and ignoring the spaces between them.

re.findall("\w+", "Hello, world!")

Split Instead of Match

The re.split function breaks text wherever a pattern appears. Splitting on whitespace turns a sentence into a list of rough tokens fast.

re.split("\s+", "one  two three")

Split on Multiple Separators

With a character class, re.split can break on many separators at once, like spaces, commas, and semicolons in a single sweep.

re.split("[ ,;]+", "a, b;c d")

Keep Punctuation as Tokens

Sometimes punctuation matters. A pattern like \w+|[^\w\s] captures words and lone symbols separately, so nothing is silently dropped.

The Alternation Operator

The pipe means or. The pattern cat|dog matches either word, letting one regex describe several token shapes you care about.

re.findall("cat|dog", "a dog, a cat")

Match Numbers and Decimals

Numbers need their own rule. The pattern \d+\.?\d* matches whole numbers and decimals, so prices and amounts stay together as one token.

re.findall("\d+\.?\d*", "buy 3 for 4.50")

Handle Contractions

Naive splitting wrecks words like do not in its short form. A smarter token pattern can keep apostrophes inside a word where they belong.

Word Boundaries Help

The \b anchor marks a word boundary, the edge between a word and a non-word. It helps you grab whole words without grabbing neighbors.

Build a Token Pattern

A practical tokenizer often combines rules with alternation: match URLs, then numbers, then words, then symbols, in priority order.

Compile for Speed

If you reuse a pattern a lot, re.compile turns it into a reusable object. It reads cleaner and runs faster across many strings.

tok = re.compile("\w+")

Quick Check

You want to break a string anywhere one or more spaces appear. Which function fits best?

Recap: Regex Tokenizers

You used findall, split, alternation, and compile to turn raw text into exactly the tokens you want. Regex gives you full control. 🎯

常见问题解答

「正则表达式分词技巧」课时是免费的吗？

是的 — 「正则表达式分词技巧」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 NLP Academy 课程的其余内容，请升级到 CoddyKit PRO。 NLP Academy 课程共包含 4 节课。

「正则表达式分词技巧」这节课中我会学到什么？

按照您需要的方式精确切分文本你通过在浏览器中直接运行的动手代码来练习 NLP Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 NLP Academy 需要有经验吗？

无需任何先前经验。CoddyKit 上的 NLP Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 4 节课，共 4 节。

「正则表达式分词技巧」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 NLP Academy 课中编写并运行代码吗？

能。每节 NLP Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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