pymongo的聚合操作

其他 2020-02-29 20:34:11 阅读次数: 0

pymongo的聚合操作

数据类型样式

/* 1 */
{
    "_id" : ObjectId("5e5a32fe2a89d7c2fc05b9fc"),
    "user_id" : "1",
    "amount" : 500,
    "status" : "A"
}

/* 2 */
{
    "_id" : ObjectId("5e5a33092a89d7c2fc05ba07"),
    "user_id" : "1",
    "amount" : 250,
    "status" : "A"
}

/* 3 */
{
    "_id" : ObjectId("5e5a33152a89d7c2fc05ba13"),
    "user_id" : "2",
    "amount" : 200,
    "status" : "A"
}

/* 4 */
{
    "_id" : ObjectId("5e5a33262a89d7c2fc05ba1c"),
    "user_id" : "1",
    "amount" : 300,
    "status" : "B"
}

$match：过滤数据，返回符合条件的数据 

    def aggregate(self):
        match_dict = {"$match":{"status":"A"}}
        result = self.db["test_info"].aggregate([match_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)



<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FF1648>
{'_id': ObjectId('5e5a32fe2a89d7c2fc05b9fc'), 'user_id': '1', 'amount': 500, 'status': 'A'}
{'_id': ObjectId('5e5a33092a89d7c2fc05ba07'), 'user_id': '1', 'amount': 250, 'status': 'A'}
{'_id': ObjectId('5e5a33152a89d7c2fc05ba13'), 'user_id': '2', 'amount': 200, 'status': 'A'}

$group：将过滤后的数据进行分组 

    def aggregate_match_group(self):
        match_dict = {"$match": {"status": "A"}}
        group_dict = {"$group":{"_id":"$user_id"}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FEF708>
{'_id': '2'}
{'_id': '1'}

# 注意： {"$group":{"_id":"$user_id"}}  分组的名称必须是_id才行换成其他key或者自己重新命名key报错：pymongo.errors.OperationFailure: The field 'user_id' must be an accumulator object

分组后，我们要求，每组的amount的总和是多少？

    def aggregate_match_group(self):
        match_dict = {"$match": {"status": "A"}}
        group_dict = {"$group":{"_id":"$user_id","amount_total":{"$sum":"$amount"}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)



<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FECD48>
{'_id': '2', 'amount_total': 200}
{'_id': '1', 'amount_total': 750}

# 注意：虽然分了两组，但是其实第二组，包含了两个内容

怎么才能显示，每个里面成员的数量呢？

    def aggregate_match_group(self):
        match_dict = {"$match": {"status": "A"}}
        group_dict = {"$group":{"_id":"$user_id","part_quantity":{"$sum":1}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FF0E08>
{'_id': '2', 'part_quantity': 1}
{'_id': '1', 'part_quantity': 2}

# 注意： {"$sum":1} 表示组内有一个，按照1递增， {"$sum":2}  就变成了 {'_id': '1', 'part_quantity': 4} 也就是按照2递增！

如果我们想知道整个文档里面符合$match过滤条件的文档有多少个呢？

    def aggregate_match_group(self):
        match_dict = {"$match": {"status": "A"}}
        group_dict = {"$group":{"_id":None,"part_quantity":{"$sum":1}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)

<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FEBFC8>
{'_id': None, 'part_quantity': 3}

如果想知道整个collection里面有多少个文档呢？

    def aggregate_match_group(self):
        match_dict = {"$match": {}}
        group_dict = {"$group":{"_id":None,"part_quantity":{"$sum":1}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FF1D48>
{'_id': None, 'part_quantity': 4}

将$match过滤条件设置为{ }，就可以作用于整个collection，$group分组条件"_id"：None，表示文档不分组，也就是整个文档是一组！

/* 1 */
{
    "_id" : ObjectId("5e5a41b22a89d7c2fc05c1c5"),
    "user_id" : "1",
    "name" : "科比",
    "hometown" : "费城",
    "age" : "100",
    "gender" : "男"
}

/* 2 */
{
    "_id" : ObjectId("5e5a41db2a89d7c2fc05c1dc"),
    "user_id" : "2",
    "name" : "纳什",
    "hometown" : "加拿大",
    "age" : "100",
    "gender" : "男"
}

/* 3 */
{
    "_id" : ObjectId("5e5a42022a89d7c2fc05c1f1"),
    "user_id" : "3",
    "name" : "蔡徐坤",
    "hometown" : "不详",
    "age" : "100",
    "gender" : "女"
}

/* 4 */
{
    "_id" : ObjectId("5e5a42252a89d7c2fc05c204"),
    "user_id" : "4",
    "name" : "gigi",
    "hometown" : "洛杉矶",
    "age" : "100",
    "gender" : "女"
}

怎么获取不同性别的人的所有user_id呢？

    def aggregate_match_group(self):
        match_dict = {"$match": {}}
        group_dict = {"$group":{"_id":"$gender","user_id":{"$push":"$user_id"}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


{'_id': '女', 'user_id': ['3', '4']}
{'_id': '男', 'user_id': ['1', '2']}

# 注意：$push：将结果追加到列表中

 def aggregate_match_group(self):
        match_dict = {"$match": {}}
        group_dict = {"$group":{"_id":"$gender","user_id":{"$push":"$$ROOT"}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FF0DC8>
{'_id': '女', 'user_id': [{'_id': ObjectId('5e5a42022a89d7c2fc05c1f1'), 'user_id': '3', 'name': '蔡徐坤', 'hometown': '不详', 'age': '100', 'gender': '女'}, {'_id': ObjectId('5e5a42252a89d7c2fc05c204'), 'user_id': '4', 'name': 'gigi', 'hometown': '洛杉矶', 'age': '100', 'gender': '女'}]}
{'_id': '男', 'user_id': [{'_id': ObjectId('5e5a41b22a89d7c2fc05c1c5'), 'user_id': '1', 'name': '科比', 'hometown': '费城', 'age': '100', 'gender': '男'}, {'_id': ObjectId('5e5a41db2a89d7c2fc05c1dc'), 'user_id': '2', 'name': '纳什', 'hometown': '加拿大', 'age': '100', 'gender': '男'}]}

# $$sort将整个文档放入列表中

$gorup分组条件的 "_id" 多条件分组

    def aggregate_match_group(self):
        match_dict = {"$match": {}}
        group_dict = {"$group":{"_id":{"user_id":"$user_id","name":"$name","hometown":"$hometown","age":"$age","gender":"$gender"}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


{'_id': {'user_id': '4', 'name': 'gigi', 'hometown': '洛杉矶', 'age': '100', 'gender': '女'}}
{'_id': {'user_id': '3', 'name': '蔡徐坤', 'hometown': '不详', 'age': '100', 'gender': '女'}}
{'_id': {'user_id': '2', 'name': '纳什', 'hometown': '加拿大', 'age': '100', 'gender': '男'}}
{'_id': {'user_id': '1', 'name': '科比', 'hometown': '费城', 'age': '100', 'gender': '男'}}
   def aggregate_match_group(self):
        match_dict = {"$match": {}}
        group_dict = {"$group":{"_id":{"name":"$name","age":"$age","gender":"$gender"}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)



<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002D4EE48>
{'_id': {'name': 'gigi', 'age': '100', 'gender': '女'}}
{'_id': {'name': '蔡徐坤', 'age': '100', 'gender': '女'}}
{'_id': {'name': '纳什', 'age': '100', 'gender': '男'}}
{'_id': {'name': '科比', 'age': '100', 'gender': '男'}}

多条件分组，并统计数量

    def aggregate_match_group(self):
        match_dict = {"$match": {}}
        group_dict = {"$group":{"_id":{"年龄":"$age","性别":"$gender"},"人数":{"$sum":1}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FECD88>
{'_id': {'年龄': '100', '性别': '女'}, '人数': 2}
{'_id': {'年龄': '100', '性别': '男'}, '人数': 2}

对查询数据进行修改

/* 1 */
{
    "_id" : ObjectId("5e5a41b22a89d7c2fc05c1c5"),
    "user_id" : "1",
    "name" : "科比",
    "hometown" : "费城",
    "age" : "42",
    "gender" : "男"
}

/* 2 */
{
    "_id" : ObjectId("5e5a41db2a89d7c2fc05c1dc"),
    "user_id" : "2",
    "name" : "纳什",
    "hometown" : "加拿大",
    "age" : "40",
    "gender" : "男"
}

/* 3 */
{
    "_id" : ObjectId("5e5a42022a89d7c2fc05c1f1"),
    "user_id" : "3",
    "name" : "蔡徐坤",
    "hometown" : "不详",
    "age" : "3",
    "gender" : "女"
}

/* 4 */
{
    "_id" : ObjectId("5e5a42252a89d7c2fc05c204"),
    "user_id" : "4",
    "name" : "gigi",
    "hometown" : "洛杉矶",
    "age" : "14",
    "gender" : "女"
}

获取年龄年龄大于3岁，小于42岁的人的信息

$match

    def aggregate_match_group(self):
        match_dict = {"$match":{"age":{"$gt":"3"}}}
        result = self.db["test_info"].aggregate([match_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)

<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FF1C48>
{'_id': ObjectId('5e5a41b22a89d7c2fc05c1c5'), 'user_id': '1', 'name': '科比', 'hometown': '费城', 'age': '42', 'gender': '男'}
{'_id': ObjectId('5e5a41db2a89d7c2fc05c1dc'), 'user_id': '2', 'name': '纳什', 'hometown': '加拿大', 'age': '40', 'gender': '男'}

# 查询错误：gigi的年龄也是大于3，不显示，我们将数据里面的年龄类型从str换成int类型，继续查看

    def aggregate_match_group(self):
        match_dict = {"$match":{"age":{"$gt":3}}}
        result = self.db["test_info"].aggregate([match_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FF1C88>
{'_id': ObjectId('5e5a41b22a89d7c2fc05c1c5'), 'user_id': '1', 'name': '科比', 'hometown': '费城', 'age': 42, 'gender': '男'}
{'_id': ObjectId('5e5a41db2a89d7c2fc05c1dc'), 'user_id': '2', 'name': '纳什', 'hometown': '加拿大', 'age': 40, 'gender': '男'}
{'_id': ObjectId('5e5a42252a89d7c2fc05c204'), 'user_id': '4', 'name': 'gigi', 'hometown': '洛杉矶', 'age': 14, 'gender': '女'}

# 查询正确：因此当进行比较值的操作，注意字段类型必须是int类型

获取年龄大于3岁，不同性别的人数

 def aggregate_match_group(self):
        match_dict = {"$match":{"age":{"$gt":3}}}
        group_dict = {"$group":{"_id":"$gender","数量":{"$sum":1}}}
        result = self.db["test_info"].aggregate([match_dict,group_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FF1C88>
{'_id': '女', '数量': 1}
{'_id': '男', '数量': 2}

$preject类型与find里面的limit，需要显示的设置为1，不显示的设置为0

    def aggregate_project(self):
        project_dict = {"$project":{"_id":0,"name":1,"hometown":1}}
        result = self.db["test_info"].aggregate([project_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FE9F88>
{'name': '科比', 'hometown': '费城'}
{'name': '纳什', 'hometown': '加拿大'}
{'name': '蔡徐坤', 'hometown': '不详'}
{'name': 'gigi', 'hometown': '洛杉矶'}

# 注意：其他字段没有赋值1就不显示，但是_id字段除外，不设置，默认显示

    def aggregate_project(self):
        group_dict = {"$group":{"_id":"$gender","quantity":{"$sum":1}}}
        project_dict = {"$project":{"_id":1,"quantity":1}}
        result = self.db["test_info"].aggregate([group_dict,project_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


{'_id': '女', 'quantity': 2}
{'_id': '男', 'quantity': 2}

$sort：排序命令

年龄从小到大返回排序好的数据

  def aggregate_sort(self):
        sort_dict = {"$sort":{"age":1}}
        result = self.db["test_info"].aggregate([sort_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000003012148>
{'_id': ObjectId('5e5a42022a89d7c2fc05c1f1'), 'user_id': '3', 'name': '蔡徐坤', 'hometown': '不详', 'age': 3, 'gender': '女'}
{'_id': ObjectId('5e5a42252a89d7c2fc05c204'), 'user_id': '4', 'name': 'gigi', 'hometown': '洛杉矶', 'age': 14, 'gender': '女'}
{'_id': ObjectId('5e5a41db2a89d7c2fc05c1dc'), 'user_id': '2', 'name': '纳什', 'hometown': '加拿大', 'age': 40, 'gender': '男'}
{'_id': ObjectId('5e5a41b22a89d7c2fc05c1c5'), 'user_id': '1', 'name': '科比', 'hometown': '费城', 'age': 42, 'gender': '男'}

年龄从大到小返回排序好的数据

    def aggregate_sort(self):
        sort_dict = {"$sort":{"age":-1}}
        result = self.db["test_info"].aggregate([sort_dict])
        print(type(result))
        print(result)
        for i in result:
            print(i)


<class 'pymongo.command_cursor.CommandCursor'>
<pymongo.command_cursor.CommandCursor object at 0x0000000002FE5F88>
{'_id': ObjectId('5e5a41b22a89d7c2fc05c1c5'), 'user_id': '1', 'name': '科比', 'hometown': '费城', 'age': 42, 'gender': '男'}
{'_id': ObjectId('5e5a41db2a89d7c2fc05c1dc'), 'user_id': '2', 'name': '纳什', 'hometown': '加拿大', 'age': 40, 'gender': '男'}
{'_id': ObjectId('5e5a42252a89d7c2fc05c204'), 'user_id': '4', 'name': 'gigi', 'hometown': '洛杉矶', 'age': 14, 'gender': '女'}
{'_id': ObjectId('5e5a42022a89d7c2fc05c1f1'), 'user_id': '3', 'name': '蔡徐坤', 'hometown': '不详', 'age': 3, 'gender': '女'}

数据类型

/* 10 */
{
    "_id" : ObjectId("5e58c4102a89d7c2fc051ba4"),
    "vaccine_name" : "破伤风",
    "vaccine_id" : "2",
    "user_id" : "110",
    "farm_id" : "110",
    "fold_id" : "110",
    "farm_name" : "110牧场",
    "fold_name" : "110圈舍",
    "animal_number" : "133",
    "equipment_number" : "133",
    "type" : "goat",
    "inject_quantity" : "100",
    "vaccine_time" : ISODate("2020-06-15T15:45:22.000Z"),
    "is_delete" : "0"
}

/* 11 */
{
    "_id" : ObjectId("5e5a510d2a89d7c2fc05cac7"),
    "vaccine_name" : "破伤风",
    "vaccine_id" : "2",
    "user_id" : "110",
    "farm_id" : "110",
    "fold_id" : "110",
    "farm_name" : "110牧场",
    "fold_name" : "110圈舍",
    "animal_number" : "133",
    "equipment_number" : "133",
    "type" : "goat",
    "inject_quantity" : "100",
    "vaccine_time" : ISODate("2020-07-15T15:45:22.000Z"),
    "is_delete" : "0"
}

/* 12 */
{
    "_id" : ObjectId("5e5a511b2a89d7c2fc05cad2"),
    "vaccine_name" : "破伤风",
    "vaccine_id" : "2",
    "user_id" : "110",
    "farm_id" : "110",
    "fold_id" : "110",
    "farm_name" : "110牧场",
    "fold_name" : "110圈舍",
    "animal_number" : "133",
    "equipment_number" : "133",
    "type" : "goat",
    "inject_quantity" : "100",
    "vaccine_time" : ISODate("2020-08-15T15:45:22.000Z"),
    "is_delete" : "0"
}

/* 13 */
{
    "_id" : ObjectId("5e5a51282a89d7c2fc05cada"),
    "vaccine_name" : "破伤风",
    "vaccine_id" : "2",
    "user_id" : "110",
    "farm_id" : "110",
    "fold_id" : "110",
    "farm_name" : "110牧场",
    "fold_name" : "110圈舍",
    "animal_number" : "133",
    "equipment_number" : "133",
    "type" : "goat",
    "inject_quantity" : "100",
    "vaccine_time" : ISODate("2020-10-15T15:45:22.000Z"),
    "is_delete" : "0"
}

/* 14 */
{
    "_id" : ObjectId("5e5a51422a89d7c2fc05caec"),
    "vaccine_name" : "破伤风",
    "vaccine_id" : "2",
    "user_id" : "110",
    "farm_id" : "110",
    "fold_id" : "110",
    "farm_name" : "110牧场",
    "fold_name" : "110圈舍",
    "animal_number" : "133",
    "equipment_number" : "133",
    "type" : "goat",
    "inject_quantity" : "100",
    "vaccine_time" : ISODate("2020-11-15T15:45:22.000Z"),
    "is_delete" : "0"
}

/* 15 */
{
    "_id" : ObjectId("5e5a514d2a89d7c2fc05caf5"),
    "vaccine_name" : "破伤风",
    "vaccine_id" : "2",
    "user_id" : "110",
    "farm_id" : "110",
    "fold_id" : "110",
    "farm_name" : "110牧场",
    "fold_name" : "110圈舍",
    "animal_number" : "133",
    "equipment_number" : "133",
    "type" : "goat",
    "inject_quantity" : "100",
    "vaccine_time" : ISODate("2020-12-15T15:45:22.000Z"),
    "is_delete" : "0"
}

需求：获取equipment_number=13，vaccine_time按照时间倒叙排列，返回数据

    def get_all_by_time_object(self,collection):
        """按照时间类型排序 vaccine_time的类型是 ISODate("2020-12-15T15:45:22.000Z")类型"""
        if self.connect_result:
            match_dict = {"$match":{"equipment_number":"133","type":"goat"}}
            sort_dict = {"$sort":{"vaccine_time":-1}}
            result = self.db[collection].aggregate([match_dict,sort_dict])
            for i in result:
                print(i)

{'_id': ObjectId('5e5a514d2a89d7c2fc05caf5'), 'vaccine_name': '破伤风', 'vaccine_id': '2', 'user_id': '110', 'farm_id': '110', 'fold_id': '110', 'farm_name': '110牧场', 'fold_name': '110圈舍', 'animal_number': '133', 'equipment_number': '133', 'type': 'goat', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 12, 15, 15, 45, 22), 'is_delete': '0'}
{'_id': ObjectId('5e5a51422a89d7c2fc05caec'), 'vaccine_name': '破伤风', 'vaccine_id': '2', 'user_id': '110', 'farm_id': '110', 'fold_id': '110', 'farm_name': '110牧场', 'fold_name': '110圈舍', 'animal_number': '133', 'equipment_number': '133', 'type': 'goat', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 11, 15, 15, 45, 22), 'is_delete': '0'}
{'_id': ObjectId('5e5a51282a89d7c2fc05cada'), 'vaccine_name': '破伤风', 'vaccine_id': '2', 'user_id': '110', 'farm_id': '110', 'fold_id': '110', 'farm_name': '110牧场', 'fold_name': '110圈舍', 'animal_number': '133', 'equipment_number': '133', 'type': 'goat', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 10, 15, 15, 45, 22), 'is_delete': '0'}
{'_id': ObjectId('5e5a511b2a89d7c2fc05cad2'), 'vaccine_name': '破伤风', 'vaccine_id': '2', 'user_id': '110', 'farm_id': '110', 'fold_id': '110', 'farm_name': '110牧场', 'fold_name': '110圈舍', 'animal_number': '133', 'equipment_number': '133', 'type': 'goat', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 8, 15, 15, 45, 22), 'is_delete': '0'}
{'_id': ObjectId('5e5a510d2a89d7c2fc05cac7'), 'vaccine_name': '破伤风', 'vaccine_id': '2', 'user_id': '110', 'farm_id': '110', 'fold_id': '110', 'farm_name': '110牧场', 'fold_name': '110圈舍', 'animal_number': '133', 'equipment_number': '133', 'type': 'goat', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 7, 15, 15, 45, 22), 'is_delete': '0'}
{'_id': ObjectId('5e58c4102a89d7c2fc051ba4'), 'vaccine_name': '破伤风', 'vaccine_id': '2', 'user_id': '110', 'farm_id': '110', 'fold_id': '110', 'farm_name': '110牧场', 'fold_name': '110圈舍', 'animal_number': '133', 'equipment_number': '133', 'type': 'goat', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 6, 15, 15, 45, 22), 'is_delete': '0'}

过滤掉一些字段，选择性显示需要的字段

    def get_all_by_time_object(self,collection):
        """按照时间类型排序 vaccine_time的类型是 ISODate("2020-12-15T15:45:22.000Z")类型"""
        if self.connect_result:
            match_dict = {"$match":{"equipment_number":"133","type":"goat"}}
            sort_dict = {"$sort":{"vaccine_time":-1}}
            project_dict = {"$project":{"_id":0,"animal_number":1,"inject_quantity":1,"vaccine_time":1,"vaccine_name":1}}
            result = self.db[collection].aggregate([match_dict,sort_dict,project_dict])
            for i in result:
                print(i)

{'vaccine_name': '破伤风', 'animal_number': '133', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 12, 15, 15, 45, 22)}
{'vaccine_name': '破伤风', 'animal_number': '133', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 11, 15, 15, 45, 22)}
{'vaccine_name': '破伤风', 'animal_number': '133', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 10, 15, 15, 45, 22)}
{'vaccine_name': '破伤风', 'animal_number': '133', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 8, 15, 15, 45, 22)}
{'vaccine_name': '破伤风', 'animal_number': '133', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 7, 15, 15, 45, 22)}
{'vaccine_name': '破伤风', 'animal_number': '133', 'inject_quantity': '100', 'vaccine_time': datetime.datetime(2020, 6, 15, 15, 45, 22)}

# TODO 待续

#

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