> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-docs-zh.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 分割 JSON 数据 - 文本分割器集成

> 使用 LangChain Python 集成 Split JSON 数据文本分割器。

这个 JSON 分割器 [splits](https://langchain-docs-zh.mintlify.site/langchain/oss/integrations/splitters.md) JSON 数据，同时允许控制块大小。它会深度遍历 JSON 数据并构建更小的 JSON 块。它尝试保持嵌套的 JSON 对象完整，但如果需要，会将其分割，以保持块大小在 min\_chunk\_size 和 max\_chunk\_size 之间。

如果值不是嵌套的 JSON，而是一个非常大的字符串，则不会分割该字符串。如果您需要块大小的硬性上限，请考虑将这些块与递归文本分割器组合使用。有一个可选的预处理步骤来分割列表，方法是首先将它们转换为 JSON（字典），然后按此方式分割。

1. 文本如何分割：JSON 值。
2. 块大小如何测量：按字符数。

```python theme={null}
pip install -qU langchain-text-splitters
```

首先我们加载一些 JSON 数据：

```python theme={null}
import json

import requests

# This is a large nested json object and will be loaded as a python dict
json_data = requests.get("https://api.smith.langchain.com/openapi.json").json()
```

## 基本用法

指定 `max_chunk_size` 来约束块大小：

```python theme={null}
from langchain_text_splitters import RecursiveJsonSplitter

splitter = RecursiveJsonSplitter(max_chunk_size=300)
```

要获取 JSON 块，使用 `.split_json` 方法：

```python theme={null}
# Recursively split json data - If you need to access/manipulate the smaller json chunks
json_chunks = splitter.split_json(json_data=json_data)

for chunk in json_chunks[:3]:
    print(chunk)
```

```python theme={null}
{'openapi': '3.1.0', 'info': {'title': 'LangSmith', 'version': '0.1.0'}, 'servers': [{'url': 'https://api.smith.langchain.com', 'description': 'LangSmith API endpoint.'}]}
{'paths': {'/api/v1/sessions/{session_id}': {'get': {'tags': ['tracer-sessions'], 'summary': 'Read Tracer Session', 'description': 'Get a specific session.', 'operationId': 'read_tracer_session_api_v1_sessions__session_id__get'}}}}
{'paths': {'/api/v1/sessions/{session_id}': {'get': {'security': [{'API Key': []}, {'Tenant ID': []}, {'Bearer Auth': []}]}}}}
```

要获取 LangChain [Document](https://reference.langchain.com/python/langchain-core/documents/base/Document) 对象，使用 `.create_documents` 方法：

```python theme={null}
# The splitter can also output documents
docs = splitter.create_documents(texts=[json_data])

for doc in docs[:3]:
    print(doc)
```

```python theme={null}
page_content='{"openapi": "3.1.0", "info": {"title": "LangSmith", "version": "0.1.0"}, "servers": [{"url": "https://api.smith.langchain.com", "description": "LangSmith API endpoint."}]}'
page_content='{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": ["tracer-sessions"], "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}'
page_content='{"paths": {"/api/v1/sessions/{session_id}": {"get": {"security": [{"API Key": []}, {"Tenant ID": []}, {"Bearer Auth": []}]}}}}'
```

或者使用 `.split_text` 直接获取字符串内容：

```python theme={null}
texts = splitter.split_text(json_data=json_data)

print(texts[0])
print(texts[1])
```

```json theme={null}
{"openapi": "3.1.0", "info": {"title": "LangSmith", "version": "0.1.0"}, "servers": [{"url": "https://api.smith.langchain.com", "description": "LangSmith API endpoint."}]}
{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": ["tracer-sessions"], "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}
```

## 如何从列表内容管理块大小

请注意，此示例中的一个块大于指定的 `max_chunk_size` 300。查看其中一个更大的块，我们看到那里有一个列表对象：

```python theme={null}
print([len(text) for text in texts][:10])
print()
print(texts[3])
```

```json theme={null}
[171, 231, 126, 469, 210, 213, 237, 271, 191, 232]

{"paths": {"/api/v1/sessions/{session_id}": {"get": {"parameters": [{"name": "session_id", "in": "path", "required": true, "schema": {"type": "string", "format": "uuid", "title": "Session Id"}}, {"name": "include_stats", "in": "query", "required": false, "schema": {"type": "boolean", "default": false, "title": "Include Stats"}}, {"name": "accept", "in": "header", "required": false, "schema": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Accept"}}]}}}}
```

默认情况下，JSON 分割器不会分割列表。

指定 `convert_lists=True` 来预处理 JSON，将列表内容转换为带有 `index:item` 作为 `key:val` 对的字典：

```python theme={null}
texts = splitter.split_text(json_data=json_data, convert_lists=True)
```

让我们看看块的大小。现在它们都在最大值以下

```python theme={null}
print([len(text) for text in texts][:10])
```

```text theme={null}
[176, 236, 141, 203, 212, 221, 210, 213, 242, 291]
```

列表已被转换为字典，即使分割成多个块，也保留了所有需要的上下文信息：

```python theme={null}
print(texts[1])
```

```json theme={null}
{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": {"0": "tracer-sessions"}, "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}
```

```python theme={null}
# We can also look at the documents
docs[1]
```

```python theme={null}
Document(page_content='{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": ["tracer-sessions"], "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}')
```

***

> 官方原文：[src/oss/python/integrations/splitters/recursive\_json\_splitter.mdx](https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/splitters/recursive_json_splitter.mdx) · 非官方翻译，译文由 AI 生成，以英文原文为准。


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