Pymongo 是否内置了验证规则？答案

【问题标题】：Does Pymongo have validation rules built in?Pymongo 是否内置了验证规则？
【发布时间】：2018-03-16 02:34:04
【问题描述】：

我正在尝试根据架构验证插入的文档，并试图找到一种方法来验证插入的文档。

有像 MongoEngine 这样的库说他们可以完成这项工作，但是有没有办法直接通过 pymongo 进行文档验证？

【问题讨论】：

仅供参考：使用 pymongo 读取验证规则：db.get_collection('test').options().get('validator')

【解决方案1】：

MongoDB 支持引擎级别的文档验证，因此您可以通过 pymongo 获取它。您向引擎声明您的“模式”（实际上是规则）。这是一个很好的起点：https://docs.mongodb.com/manual/core/document-validation/

【讨论】：

你说对了一部分。 MongoDB 提供内置验证，但不幸的是，pymongo 的文档中没有说明验证
任何人都可以为此添加示例吗？我真的很挣扎！
是的，这就是我一直在寻找的，但我只是使用 mongo 引擎 ORM 解决了它

【解决方案2】：

python 驱动程序文档确实对如何使用db.command 有所了解。这是一个完整的工作示例：

    from pymongo import MongoClient
    from collections import OrderedDict
    import sys
    
    client = MongoClient()   # supply connection args as appropriate 
    db = client.testX
    
    db.myColl.drop()
    
    db.create_collection("myColl")  # Force create!
    
    #  $jsonSchema expression type is prefered.  New since v3.6 (2017):
    vexpr = {"$jsonSchema":
      {
             "bsonType": "object",
             "required": [ "name", "year", "major", "gpa" ],
             "properties": {
                "name": {
                   "bsonType": "string",
                   "description": "must be a string and is required"
                },
                "gender": {
                   "bsonType": "string",
                   "description": "must be a string and is not required"
                },
                "year": {
                   "bsonType": "int",
                   "minimum": 2017,
                   "maximum": 3017,
                   "exclusiveMaximum": False,
                   "description": "must be an integer in [ 2017, 3017 ] and is required"
                },
                "major": {
                   "enum": [ "Math", "English", "Computer Science", "History", None ],
                   "description": "can only be one of the enum values and is required"
                },
                "gpa": {
                   # In case you might want to allow doubles OR int, then add
                   # "int" to the bsonType array below:
                   "bsonType": [ "double" ],
                   "minimum": 0,
                   "description": "must be a double and is required"
                }
             }
      }
    }
    
    # Per the docs, args to command() require that the first kev/value pair
    # be the command string and its principal argument, followed by other
    # arguments.  There are two ways to do this:  Using an OrderDict:
    cmd = OrderedDict([('collMod', 'myColl'),
            ('validator', vexpr),
            ('validationLevel', 'moderate')]
    db.command(cmd)
    
    # Or, use the kwargs construct:
    # db.command('collMod','myColl', validator=vexpr, validationLevel='moderate')

    try:
        db.myColl.insert({"x":1})
        print "NOT good; the insert above should have failed."
    except:
        print "OK. Expected exception:", sys.exc_info()    
    
    try:
        okdoc = {"name":"buzz", "year":2019, "major":"Math", "gpa":3.8}
        db.myColl.insert(okdoc)
        print "All good."
    except:
        print "exc:", sys.exc_info()

【讨论】：

【解决方案3】：

您可以为您的文档验证架构创建一个单独的 JSON 文件，如下所示：

    {
      "collMod": "users",
      "validator": {
        "$jsonSchema": {
          "bsonType": "object",
          "required": ["email", "password","name"],
          "properties": {
            "email": {
              "bsonType": "string",
              "description": "Correo Electrónico"
            },
            "password": {
              "bsonType": "string",
              "description": "Una representación Hash de la contraseña"
            },
            "name": {
              "bsonType": "object",
              "required": ["first", "last"],
              "description": "Objeto que separa los nombres y apellidos",
              "properties":  {
                "first": {
                  "bsonType": "string",
                  "description": "Primer y segundo nombre"
                },
                "last": {
                  "bsonType": "string",
                  "description": "Primer y segundo apellido"
                }
              }
            },
          }
        }
      }
    }

然后就可以在python脚本中使用了，例如：

from pymongo import MongoClient
import json #parse JSON  file as dict
from collections import OrderedDict #preserve the order (key, value) in the gived insertions on the dict

client = MongoClient("your_mongo_uri")
db = client.your_db_name 

with open('your_schema_file.json', 'r') as j:
    d = json.loads(j.read())

d = OrderedDict(d)

db.command(d)

OrderedDict Info

collMod Info

Schema Validation Info

【讨论】：