如何从架构数据库XML创建嵌套字典（JSON）？

huangapple
go评论117阅读模式
英文:

How to make a nested dict (json) from a schema database xml?

问题

以下是您提供的XML代码的翻译：

  1. <?xml version="1.0" encoding="UTF-8" ?>
  2. <project name="so_project" id="Project-9999">
  3.     <schema name="database1">
  4.         <table name="table1">
  5.             <column name="foo" type="int"/>
  6.             <column name="bar" type="string"/>
  7.             <column name="details_resolution" type="array[object]">
  8.                 <column name="timestamp" type="timestamp"/>
  9.                 <column name="user_id" type="string"/>
  10.                 <column name="user_name" type="string"/>
  11.             </column>
  12.             <column name="details_closure" type="array[object]">
  13.                 <column name="timestamp" type="timestamp"/>
  14.                 <column name="auto_closure" type="bool"/>
  15.             </column>
  16.         </table>
  17.     </schema>
  18.     <schema name="database2">
  19.         <table name="table1">
  20.             <column name="foo" type="int"/>
  21.             <column name="bar" type="string"/>
  22.             <column name="details" type="array[object]">
  23.                 <column name="timestamp" type="timestamp"/>
  24.                 <column name="value" type="float"/>
  25.             </column>
  26.         </table>
  27.     </schema>
  28. </project>

请注意，这只是XML代码的翻译，没有任何其他内容。

英文:

Here is my input file.xml :

  1. &lt;?xml version=&quot;1.0&quot; encoding=&quot;UTF-8&quot; ?&gt;
  2. &lt;project name=&quot;so_project&quot; id=&quot;Project-9999&quot;&gt;
  3.     &lt;schema name=&quot;database1&quot;&gt;
  4.         &lt;table name=&quot;table1&quot;&gt;
  5.             &lt;column name=&quot;foo&quot; type=&quot;int&quot;/&gt;
  6.             &lt;column name=&quot;bar&quot; type=&quot;string&quot;/&gt;
  7.             &lt;column name=&quot;details_resolution&quot; type=&quot;array[object]&quot;&gt;
  8.                 &lt;column name=&quot;timestamp&quot; type=&quot;timestamp&quot;/&gt;
  9.                 &lt;column name=&quot;user_id&quot; type=&quot;string&quot;/&gt;
  10.                 &lt;column name=&quot;user_name&quot; type=&quot;string&quot;/&gt;
  11.             &lt;/column&gt;
  12.             &lt;column name=&quot;details_closure&quot; type=&quot;array[object]&quot;&gt;
  13.                 &lt;column name=&quot;timestamp&quot; type=&quot;timestamp&quot;/&gt;
  14.                 &lt;column name=&quot;auto_closure&quot; type=&quot;bool&quot;/&gt;
  15.             &lt;/column&gt;
  16.         &lt;/table&gt;
  17.     &lt;/schema&gt;
  18.     &lt;schema name=&quot;database2&quot;&gt;
  19.         &lt;table name=&quot;table1&quot;&gt;
  20.             &lt;column name=&quot;foo&quot; type=&quot;int&quot;/&gt;
  21.             &lt;column name=&quot;bar&quot; type=&quot;string&quot;/&gt;
  22.             &lt;column name=&quot;details&quot; type=&quot;array[object]&quot;&gt;
  23.                 &lt;column name=&quot;timestamp&quot; type=&quot;timestamp&quot;/&gt;
  24.                 &lt;column name=&quot;value&quot; type=&quot;float&quot;/&gt;
  25.             &lt;/column&gt;
  26.         &lt;/table&gt;
  27.     &lt;/schema&gt;
  28. &lt;/project&gt;

.. and I'm trying to make this classical nested dict :

  1. {
  2.     &quot;database1&quot;: {
  3.         &quot;table1&quot;: {
  4.             &quot;foo&quot;: &quot;int&quot;,
  5.             &quot;bar&quot;: &quot;string&quot;,
  6.             &quot;details_resolution&quot;: {
  7.                 &quot;timestamp&quot;: &quot;timestamp&quot;,
  8.                 &quot;user_id&quot;: &quot;string&quot;,
  9.                 &quot;user_name&quot;: &quot;string&quot;
  10.             },
  11.             &quot;details_closure&quot;: {
  12.                 &quot;timestamp&quot;: &quot;timestamp&quot;,
  13.                 &quot;auto_closure&quot;: &quot;bool&quot;
  14.             }
  15.         }
  16.     },
  17.     &quot;database2&quot;: {
  18.         &quot;table1&quot;: {
  19.             &quot;foo&quot;: &quot;int&quot;,
  20.             &quot;bar&quot;: &quot;string&quot;,
  21.             &quot;details&quot;: {
  22.                 &quot;timestamp&quot;: &quot;timestamp&quot;,
  23.                 &quot;value&quot;: &quot;float&quot;
  24.             }
  25.         }
  26.     }
  27. }

PS : Each database can eventually have more than one table.

I tried some AI codes but none of them gave me the expected result..
I'm sorry guys to not being able to show my attempts !

SO, any help would be greately appreciated.

答案1

得分: 1

您可以使用 xml.etree.ElementTree 模块。

  1. import xml.etree.ElementTree as ET
  3. def parse_column(column_elem):
  4.     column_data = {}
  5.     column_data['name'] = column_elem.get('name')
  6.     column_data['type'] = column_elem.get('type')
  7.     return column_data
  9. def parse_table(table_elem):
  10.     table_data = {}
  11.     table_name = table_elem.get('name')
  12.     for column_elem in table_elem.findall('column'):
  13.         column_data = parse_column(column_elem)
  14.         table_data[column_data['name']] = column_data['type']
  15.     return {table_name: table_data}
  17. def parse_schema(schema_elem):
  18.     schema_data = {}
  19.     schema_name = schema_elem.get('name')
  20.     for table_elem in schema_elem.findall('table'):
  21.         table_data = parse_table(table_elem)
  22.         schema_data.update(table_data)
  23.     return {schema_name: schema_data}
  25. def parse_xml(xml_content):
  26.     root = ET.fromstring(xml_content)
  27.     project_data = {}
  28.     for schema_elem in root.findall('schema'):
  29.         schema_data = parse_schema(schema_elem)
  30.         project_data.update(schema_data)
  31.     return project_data
  33. # 读取 XML 文件
  34. with open('file.xml', 'r') as f:
  35.     xml_content = f.read()
  37. # 解析 XML 并生成嵌套字典
  38. nested_dict = parse_xml(xml_content)
  39. print(nested_dict)

这是您提供的代码的翻译部分。

英文:

You can use xml.etree.ElementTree

  1. import xml.etree.ElementTree as ET
  3. def parse_column(column_elem):
  4.     column_data = {}
  5.     column_data[&#39;name&#39;] = column_elem.get(&#39;name&#39;)
  6.     column_data[&#39;type&#39;] = column_elem.get(&#39;type&#39;)
  7.     return column_data
  9. def parse_table(table_elem):
  10.     table_data = {}
  11.     table_name = table_elem.get(&#39;name&#39;)
  12.     for column_elem in table_elem.findall(&#39;column&#39;):
  13.         column_data = parse_column(column_elem)
  14.         table_data[column_data[&#39;name&#39;]] = column_data[&#39;type&#39;]
  15.     return {table_name: table_data}
  17. def parse_schema(schema_elem):
  18.     schema_data = {}
  19.     schema_name = schema_elem.get(&#39;name&#39;)
  20.     for table_elem in schema_elem.findall(&#39;table&#39;):
  21.         table_data = parse_table(table_elem)
  22.         schema_data.update(table_data)
  23.     return {schema_name: schema_data}
  25. def parse_xml(xml_content):
  26.     root = ET.fromstring(xml_content)
  27.     project_data = {}
  28.     for schema_elem in root.findall(&#39;schema&#39;):
  29.         schema_data = parse_schema(schema_elem)
  30.         project_data.update(schema_data)
  31.     return project_data
  33. # Read XML file
  34. with open(&#39;file.xml&#39;, &#39;r&#39;) as f:
  35.     xml_content = f.read()
  37. # Parse XML and generate nested dictionary
  38. nested_dict = parse_xml(xml_content)
  39. print(nested_dict)

答案2

得分: 0

使用[标签：beautifulsoup]的解决方案：

  1. from bs4 import BeautifulSoup
  3. with open("your_file.xml", "r") as f_in:
  4.     soup = BeautifulSoup(f_in.read(), "xml")
  7. def parse_columns(t):
  8.     out = {}
  9.     for c in t.find_all("column", recursive=False):
  10.         if c.find("column"):
  11.             out[c["name"]] = parse_columns(c)
  12.         else:
  13.             out[c["name"]] = c["type"]
  14.     return out
  17. def parse_schema(sch):
  18.     out = {}
  19.     for t in sch.select("table"):
  20.         out[t["name"]] = parse_columns(t)
  21.     return out
  24. out = {}
  25. for sch in soup.select("schema"):
  26.     out[sch["name"]] = parse_schema(sch)
  28. print(out)

打印输出：

  1. {
  2.     "database1": {
  3.         "table1": {
  4.             "foo": "int",
  5.             "bar": "string",
  6.             "details_resolution": {
  7.                 "timestamp": "timestamp",
  8.                 "user_id": "string",
  9.                 "user_name": "string",
  10.             },
  11.             "details_closure": {"timestamp": "timestamp", "auto_closure": "bool"},
  12.         }
  13.     },
  14.     "database2": {
  15.         "table1": {
  16.             "foo": "int",
  17.             "bar": "string",
  18.             "details": {"timestamp": "timestamp", "value": "float"},
  19.         }
  20.     },
  21. }
英文:

Solution using [tag:beautifulsoup]:

  1. from bs4 import BeautifulSoup
  3. with open(&quot;your_file.xml&quot;, &quot;r&quot;) as f_in:
  4.     soup = BeautifulSoup(f_in.read(), &quot;xml&quot;)
  7. def parse_columns(t):
  8.     out = {}
  9.     for c in t.find_all(&quot;column&quot;, recursive=False):
  10.         if c.find(&quot;column&quot;):
  11.             out[c[&quot;name&quot;]] = parse_columns(c)
  12.         else:
  13.             out[c[&quot;name&quot;]] = c[&quot;type&quot;]
  14.     return out
  17. def parse_schema(sch):
  18.     out = {}
  19.     for t in sch.select(&quot;table&quot;):
  20.         out[t[&quot;name&quot;]] = parse_columns(t)
  21.     return out
  24. out = {}
  25. for sch in soup.select(&quot;schema&quot;):
  26.     out[sch[&quot;name&quot;]] = parse_schema(sch)
  28. print(out)

Prints:

  1. {
  2.     &quot;database1&quot;: {
  3.         &quot;table1&quot;: {
  4.             &quot;foo&quot;: &quot;int&quot;,
  5.             &quot;bar&quot;: &quot;string&quot;,
  6.             &quot;details_resolution&quot;: {
  7.                 &quot;timestamp&quot;: &quot;timestamp&quot;,
  8.                 &quot;user_id&quot;: &quot;string&quot;,
  9.                 &quot;user_name&quot;: &quot;string&quot;,
  10.             },
  11.             &quot;details_closure&quot;: {&quot;timestamp&quot;: &quot;timestamp&quot;, &quot;auto_closure&quot;: &quot;bool&quot;},
  12.         }
  13.     },
  14.     &quot;database2&quot;: {
  15.         &quot;table1&quot;: {
  16.             &quot;foo&quot;: &quot;int&quot;,
  17.             &quot;bar&quot;: &quot;string&quot;,
  18.             &quot;details&quot;: {&quot;timestamp&quot;: &quot;timestamp&quot;, &quot;value&quot;: &quot;float&quot;},
  19.         }
  20.     },
  21. }

答案3

得分: 0

在XSLT 3.0中：

  1. <xsl:output method="json" indent="yes" />
  2. <xsl:template match="/">
  3.   <xsl:map>
  4.     <xsl:apply-templates select="*/schema"/>
  5.   </xsl:map>
  6. </xsl:template>
  8. <xsl:template match="*[*]">
  9.   <xsl:map-entry key="string(@name)">
  10.     <xsl:map>
  11.       <xsl:apply-templates select="*"/>
  12.     </xsl:map>
  13.   </xsl:map-entry>
  14. </xsl:template>
  16. <xsl:template match="*">
  17.   <xsl:map-entry key="string(@name)" select="string(@type)"/>
  18. </xsl:template>

解释：

  • 第一个模板规则匹配文档，创建最外层的地图，并处理schema元素，跳过project级别。

  • 第二个模板规则匹配具有一个或多个子元素的元素；它为容器元素创建一个具有@name属性作为键的地图条目，并通过递归应用模板规则生成另一个地图作为内容。

  • 第三个模板规则匹配没有子元素的元素；它为容器元素创建一个地图条目，其中@name作为键，@type作为相应的值。

英文:

In XSLT 3.0:

  1.   &lt;xsl:output method=&quot;json&quot; indent=&quot;yes&quot; /&gt;
  2.   
  3.   &lt;xsl:template match=&quot;/&quot;&gt;
  4.     &lt;xsl:map&gt;
  5.       &lt;xsl:apply-templates select=&quot;*/schema&quot;/&gt;
  6.     &lt;/xsl:map&gt;
  7.   &lt;/xsl:template&gt;
  9.   &lt;xsl:template match=&quot;*[*]&quot;&gt;
  10.      &lt;xsl:map-entry key=&quot;string(@name)&quot;&gt;
  11.         &lt;xsl:map&gt;
  12.           &lt;xsl:apply-templates select=&quot;*&quot;/&gt;
  13.         &lt;/xsl:map&gt;
  14.      &lt;/xsl:map-entry&gt;
  15.   &lt;/xsl:template&gt;
  16.   
  17.   &lt;xsl:template match=&quot;*&quot;&gt;
  18.     &lt;xsl:map-entry key=&quot;string(@name)&quot; select=&quot;string(@type)&quot;/&gt;
  19.   &lt;/xsl:template&gt;

See https://xsltfiddle.liberty-development.net/bdvWh3 for the full stylesheet including boilerplate.

Explanation:

  • The first template rule matches the document, creates the outermost map, and processes the schema element, skipping the project level.

  • The second template rule matches elements that have one or more children; it creates a map entry for the container element with the @name attribute as the key, and generates another map as the content, by applying template rules to the children recursively.

  • The third template rule matches elements with no children; it creates a map entry for the container element, with @name as the key and @type as the corresponding value.

huangapple
  • 本文由 发表于 2023年7月18日 07:01:46
  • 转载请务必保留本文链接：https://go.coder-hub.com/76708573.html
  • json
  • python
  • xml
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