使用Rest Assured 5.4.0验证JSON Schema时遇无JSON文本读取错误

针对你遇到的这个JSON Schema验证异常，以下是几个针对性的排查和解决方向：

1. 确认Schema文件的路径与存在性 #

你使用matchesJsonSchemaInClasspath方法加载Schema，需确保：

• 文件assortment/schema/postResponseSchema.json确实存在于项目的classpath目录中（比如Maven项目要放在src/test/resources/assortment/schema/下）
• 路径拼写完全正确，注意大小写（部分操作系统区分路径大小写）

可以先通过代码验证文件是否能被读取：

InputStream schemaStream = ClassLoader.getSystemResourceAsStream("assortment/schema/postResponseSchema.json");
if (schemaStream == null) {
    throw new RuntimeException("Schema文件未找到，请检查路径");
}

2. 排查Schema文件的内容格式问题 #

即便在线验证Schema有效，也可能存在本地文件的编码或隐形字符问题：

• 检查文件是否带有UTF-8 BOM头（Windows下保存的文件容易出现），可以用Notepad++等工具将文件转为UTF-8无BOM格式重新保存
• 手动读取Schema内容并输出，确认没有空行、不可见字符或格式损坏：

String schemaContent = new String(
    ClassLoader.getSystemResourceAsStream("assortment/schema/postResponseSchema.json").readAllBytes(),
    StandardCharsets.UTF_8
);
System.out.println("Schema内容: " + schemaContent);
// 改用直接传入内容的方式验证
.body(JsonSchemaValidator.matchesJsonSchema(schemaContent))

3. 检查接口响应体是否有效 #

异常提示"无JSON文本可读"，也可能是接口返回的响应体为空或非JSON格式：

• 查看.log().all()输出的响应内容，确认接口是否返回了预期的JSON数据，而非空内容、HTML错误页面（如500错误）或其他格式
• 先验证接口响应的状态码是否为2xx，再执行Schema验证：

.then().log().all()
.statusCode(200)
.assertThat()
.body(JsonSchemaValidator.matchesJsonSchemaInClasspath("assortment/schema/postResponseSchema.json"))

4. 简化你的Schema（可选） #

你的Schema中stocks数组的items字段使用了数组形式，但两个对象结构完全一致，这在JSON Schema中是冗余的。可以简化为：

{"$schema": "http://json-schema.org/draft-04/schema#","type": "object","properties": {"date": {"type": "string"},"stocks": {"type": "array","items": {"type": "object","properties": {"nnt": {"type": "string"},"sku": {"type": "string"},"qnt": {"type": "integer"},"supInn": {"type": "string"},"supId": {"type": "string"},"supDate": {"type": "string"},"nds": {"type": "integer"},"gnvls": {"type": "boolean"},"dp": {"type": "boolean"},"man": {"type": "string"},"exp": {"type": "string"},"prcMan": {"type": "number"},"prcOpt": {"type": "number"},"prcOptNds": {"type": "number"},"prcRet": {"type": "integer"},"prcReestr": {"type": "number"},"prcGnvlsMax": {"type": "number"},"sumOpt": {"type": "number"},"sumOptNds": {"type": "number"},"mrGnvls": {"type": "number"},"tag": {"type": "integer"},"nomenclatureId": {"type": "integer"}},"required": ["nnt","sku","qnt","supInn","supId","supDate","nds","gnvls","dp","man","exp","prcMan","prcOpt","prcOptNds","prcRet","prcReestr","prcGnvlsMax","sumOpt","sumOptNds","mrGnvls","tag","nomenclatureId"]}}},"required": ["date","stocks"]}

冗余的数组形式可能导致解析器误判，简化后能减少潜在的验证问题。

内容的提问来源于stack exchange，提问作者Sergey K