阅读说明：本技术 非关系型数据库的表单校验规则生成方法和系统 (Form verification rule generation method and system for non-relational database ) 是由 郭鑫程 陈和国 于 2021-09-06 设计创作，主要内容包括：本申请涉及一非关系型数据库的表单校验规则生成方法和系统,其中,该非关系型数据库的表单校验规则生成方法,包括：确定表名称,依据所述表名称从非关系型数据库中确定与所述表名称对应的对象集合；遍历所述对象集合,依次获取所述对象集合中的字段名称集合和每个字段名称所对应的数据集合；将所述每个字段名称所对应的数据集合中的数据与预设规则库里的预设规则进行匹配,依据匹配结果生成所述字段的校验规则。通过本申请,解决了相关技术中存在的现有的表单验证规则生成技术不支持非关系型数据库的问题,实现了支持非关系型数据库的表单验证方法的技术效果,提高了非关系型数据库的表单验证效率。(The application relates to a method and a system for generating form verification rules of a non-relational database, wherein the method for generating the form verification rules of the non-relational database comprises the following steps: determining a table name, and determining an object set corresponding to the table name from a non-relational database according to the table name; traversing the object set, and sequentially acquiring a field name set in the object set and a data set corresponding to each field name; and matching the data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating the verification rule of the field according to the matching result. By the method and the device, the problem that the existing form verification rule generation technology in the related technology does not support the non-relational database is solved, the technical effect of the form verification method supporting the non-relational database is achieved, and the form verification efficiency of the non-relational database is improved.)

1. A method for generating form verification rules of a non-relational database is characterized by comprising the following steps:

determining a table name, and determining an object set corresponding to the table name from a non-relational database according to the table name;

traversing the object set, and sequentially acquiring a field name set in the object set and a data set corresponding to each field name;

and matching the data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating the verification rule of the field according to the matching result.

2. The method of claim 1, wherein the matching the data in the data set corresponding to each field name with a preset rule in a preset rule base and generating the field check rule according to the matching result comprises:

determining the attribute of the data in the data set corresponding to the field name;

determining the attribute of a preset rule in the preset rule base;

determining the corresponding relation between the data and the preset rule according to the attribute of the data and the attribute of the preset rule, matching the data with the preset rule according to the corresponding relation, and generating the check rule of the field according to the matching result.

3. The method of claim 1, wherein the matching the data in the data set corresponding to each field name with a preset rule in a preset rule base and generating the field check rule according to the matching result comprises:

determining data in a data set corresponding to the field name;

determining a preset rule in the preset rule base;

and matching the data with the rules one by one, and generating the check rules of the fields according to the matching results.

4. The method of claim 1, wherein before traversing the object set and obtaining a field name set and a data set corresponding to each field name in the object set, the method further comprises:

the object formats in the object collection are converted to formats supported by the programming language.

5. The method as claimed in claim 1, wherein the data in the data set corresponding to each field name is matched with a preset rule in a preset rule base, and after the field check rule is generated according to the matching result, the method further comprises:

acquiring data in a data set corresponding to each field name;

judging whether the data is matched with a preset rule in the preset rule base or not, generating a check rule of the field according to a matching result when the data is matched with the rule, and marking the field corresponding to the data when the data is not matched with the rule.

6. The method of claim 5, wherein when the data does not match the rule, marking a field corresponding to the data, the method further comprises:

and compiling a check rule for the field corresponding to the data.

7. The method of claim 1, wherein traversing the object set and sequentially obtaining a field name set and a data set corresponding to each field name in the object set comprises:

traversing all the obtained fields of the objects in the non-relational database, and obtaining a field name set in the object set according to a traversal result;

and traversing the data corresponding to the field name sets in the object set, and acquiring the data sets corresponding to the names of all the fields according to the traversal result.

8. A system for generating form verification rules for a non-relational database, comprising: a terminal device and a server device; the terminal equipment is connected with the server equipment;

the terminal equipment is used for sending a request instruction of a user;

the server device is used for executing the form verification rule generation method of the non-relational database in any one of claims 1 to 7.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to perform the method for generating form verification rules for non-relational databases according to any one of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for generating form verification rules for non-relational databases according to any one of claims 1 to 7.

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method and a system for generating form verification rules for a non-relational database.

Background

In production and life, the demand of data collection through an electronic form is increasing day by day, for example, marketing questionnaires, business data collection by daily operation of enterprises and public institutions, body temperature data collection by communities during epidemic situations and the like are presented as a whole: the requirements are fast to generate, the iteration of the form content is fast, the data volume of the form is increased sharply, and the like. Whereas a software engineer might make a questionnaire form a day in the past to meet business needs, a business today might need to create tens of forms per day to collect a wide variety of data.

In order to better collect the data filled by the user, various input experience optimization, foolproof design and other works are needed to be done during filling, and the content input by the user is checked, judged, and error prompted, so that the input experience of the user is improved, and the cost for cleaning mass data in the future is reduced. For example, when it is desired to collect date and time data generated at a certain time, it is generally desirable to collect date and time data with a uniform format, and if not limited, various expressions of the five-door may be collected, which often requires a large amount of cost for data cleaning in the future, and increases the cost of enterprises unnecessarily. In addition, when data with magnitude more than thousands of times of the past is faced, the traditional relational database cannot meet the requirement on performance. For example, conventional relational databases exhibit a significant drop in read and write speed when the number of individual table rows exceeds one hundred million or even more. Many systems have introduced non-relational databases to speed up applications.

The relational database has a data table structure, and the data table is composed of three parts of a table name, fields in the table and records of the table. Designing a data table structure is to define the file name of the data table, determine which fields the data table contains, the field name, the field type, and the width of each field, and input these data into the computer. However, the non-relational database lacks a table structure description characteristic, and usually requires an engineer to manually write a form verification rule, which consumes a large amount of labor cost.

The existing form verification rule generation technology is usually only applicable to relational databases, only analyzes table structures and does not analyze data contents, and the existing form verification rule generation technology cannot be applied to MongoDB or other non-relational databases at all.

Aiming at the problem that the existing form verification rule generation technology in the related technology does not support a non-relational database, no effective solution is provided at present.

Disclosure of Invention

The embodiment provides a method and a system for generating a form verification rule of a non-relational database, so as to solve the problem that the existing form verification rule generation technology in the related art does not support the non-relational database.

In a first aspect, in this embodiment, a method for generating form verification rules of a non-relational database is provided, including: determining a table name, and determining an object set corresponding to the table name from a non-relational database according to the table name; traversing the object set, and sequentially acquiring a field name set in the object set and a data set corresponding to each field name; and matching the data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating the verification rule of the field according to the matching result.

In some embodiments, matching data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating a check rule of the field according to a matching result includes: determining the attribute of the data in the data set corresponding to the field name; determining the attribute of a preset rule in the preset rule base; determining the corresponding relation between the data and the preset rule according to the attribute of the data and the attribute of the preset rule, matching the data with the preset rule according to the corresponding relation, and generating the check rule of the field according to the matching result.

In some embodiments, matching data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating a check rule of the field according to a matching result includes: determining data in a data set corresponding to the field name; determining a preset rule in the preset rule base; and matching the data with the rules one by one, and generating the check rules of the fields according to the matching results.

In some embodiments, before traversing the object set and acquiring a field name set and a data set corresponding to each field name in the object set, the method further includes:

the object formats in the object collection are converted to formats supported by the programming language.

In some embodiments, after matching the data in the data set corresponding to each field name with a preset rule in a preset rule base and generating a check rule of the field according to a matching result, the method further includes:

acquiring data in a data set corresponding to each field name; judging whether the data is matched with a preset rule in the preset rule base or not, generating a check rule of the field according to a matching result when the data is matched with the rule, and marking the field corresponding to the data when the data is not matched with the rule.

In some embodiments, when the data does not match the rule, marking a field corresponding to the data, the method further comprises:

and compiling a check rule for the field corresponding to the data.

In some embodiments, traversing the object set, and sequentially obtaining a field name set and a data set corresponding to each field name in the object set includes: traversing all the obtained fields of the objects in the non-relational database, and obtaining a field name set in the object set according to a traversal result; and traversing the data corresponding to the field name sets in the object set, and acquiring the data sets corresponding to the names of all the fields according to the traversal result.

In a second aspect, in this embodiment, a system for generating form verification rules of a non-relational database is provided, including: a terminal device and a server device; the terminal equipment is connected with the server equipment;

the terminal equipment is used for sending a request instruction of a user; the server device is used in the method for generating the form verification rule of the non-relational database according to the first aspect.

In a third aspect, in this embodiment, there is provided an electronic apparatus, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the processor implements the method for generating form verification rules of the non-relational database according to the first aspect.

In a fourth aspect, in the present embodiment, there is provided a storage medium, on which a computer program is stored, which when executed by a processor, implements the form verification rule generation method for the non-relational database according to the first aspect.

Compared with the related art, in the form verification rule generation method for the non-relational database provided in this embodiment, by determining the table name, an object set corresponding to the table name is determined from the non-relational database according to the table name; traversing the object set, and sequentially acquiring a field name set in the object set and a data set corresponding to each field name; and matching the data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating the verification rule of the field according to the matching result. The method solves the problem that the existing form verification rule generation technology in the related technology does not support the non-relational database, realizes the technical effect of the form verification method supporting the non-relational database, and improves the form verification efficiency of the non-relational database.

The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below to provide a more thorough understanding of the application.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

FIG. 1 is a flowchart of a method for generating form verification rules of a non-relational database according to this embodiment;

FIG. 2 is a flowchart of a method for generating form verification rules for non-relational databases according to the preferred embodiment;

fig. 3 is a block diagram showing the configuration of a form verification rule generating apparatus for a non-relational database according to the present embodiment.

Detailed Description

For a clearer understanding of the objects, aspects and advantages of the present application, reference is made to the following description and accompanying drawings.

Unless defined otherwise, technical or scientific terms used herein shall have the same general meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The use of the terms "a" and "an" and "the" and similar referents in the context of this application do not denote a limitation of quantity, either in the singular or the plural. The terms "comprises," "comprising," "has," "having," and any variations thereof, as referred to in this application, are intended to cover non-exclusive inclusions; for example, a process, method, and system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or modules, but may include other steps or modules (elements) not listed or inherent to such process, method, article, or apparatus. Reference throughout this application to "connected," "coupled," and the like is not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. Reference to "a plurality" in this application means two or more. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. In general, the character "/" indicates a relationship in which the objects associated before and after are an "or". The terms "first," "second," "third," and the like in this application are used for distinguishing between similar items and not necessarily for describing a particular sequential or chronological order.

The non-relational database in the present application takes the MongoDB as an example, and the MongoDB is a database based on distributed file storage. Written in the C + + language. It is intended to provide an extensible high performance data storage solution for WEB applications. MongoDB is a product between relational databases and non-relational databases, and among the non-relational databases, the MongoDB has the most abundant functions and is most similar to the relational databases. The data structure supported by the method is very loose and is in a json-like bson format, so that more complex data types can be stored. The biggest characteristic of Mongo is that the query language supported by Mongo is very strong, the syntax of Mongo is similar to the object-oriented query language, most functions of single-table query of similar relational databases can be almost realized, and index establishment of data is also supported.

Fig. 1 is a flowchart of a method for generating a form verification rule of a non-relational database according to this embodiment, and as shown in fig. 1, the method includes the following steps:

step S101, determining a table name, and determining an object set corresponding to the table name from a non-relational database according to the table name.

Since the data in the MongoDB database is stored in the form of distributed objects, it does not have the form of a line of relational databases, unlike a relational database. For example, the table name in the MongoDB database is X, and one of the objects in Q of table X includes table name X, field a, field B, and field C, and the values a1, B1, and C1 corresponding to the fields; another object of the table X comprises a table name X, a field A, a field D and a field E, and values a2, D2 and E2 corresponding to the fields. It can be seen that even if the objects of the same data table are used, the specific fields and the number of fields may be different.

After the table name X is determined, all objects corresponding to the table name X are searched from the montodb database, for example: field a, field B, and field C, and field a, field D, and field E.

Step S102, traversing the object set, and sequentially acquiring the field name set in the object set and the data set corresponding to each field name.

Firstly, traversing all inquired objects, such as traversing field A, field B and field C, field A, field D and field E and the like, and acquiring names of all objects according to a traversal result, wherein the name of the field A is a class sequence number, and the name of the field B is a name; the name of field C is an identification number and the name of field D is a telephone number. All values corresponding to field a are: one year and one shift, the values corresponding to field B are: three, lie four, etc., the value corresponding to field C is 123456789123456789 and the value corresponding to field D is 13000000000 or 13200000000.

Step S103, matching the data in the data set corresponding to each field name with the preset rules in the preset rule base, and generating the verification rules of the fields according to the matching results.

In this embodiment, one of the preset rules is an arabic numeral with 18 digits, or the digits are 18 digits, the first 17 digits are all arabic numerals, and the 18 th digit can be a letter. And if the preset rule is matched with the value corresponding to the identity card number, taking the preset rule as a check rule of the field C.

And the other preset rule is an Arabic number with 11 digits, and the preset rule is matched with a value corresponding to the telephone number and is used as a verification rule of the field D.

Through the steps, compared with the related technology, the method adopts a path completely different from the related technology, starts from the value corresponding to the object in the database, and finally generates the check rule for checking the non-relational database through a series of preset rules and matching the value corresponding to the object with the preset rules. The method solves the problem that the existing form verification rule generation technology in the related technology does not support the non-relational database, realizes the technical effect of the form verification method supporting the non-relational database, improves the form verification efficiency of the non-relational database, and greatly reduces the labor cost.

In some embodiments, matching the data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating a check rule of the field according to a matching result includes: determining the attribute of the data in the data set corresponding to the field name; determining the attribute of a preset rule in a preset rule base; determining the corresponding relation between the data and the preset rule according to the attribute of the data and the attribute of the preset rule, matching the data with the preset rule according to the corresponding relation, and generating the verification rule of the field according to the matching result.

Specifically, taking a body temperature registration form of a certain unit as an example, during an epidemic situation, the unit needs to measure the body temperature of employees and record data for later reference, and the body temperature registration form comprises three fields of a job number, a name and the body temperature. The body temperature of each employee was measured daily and registered.

When traversing the values corresponding to the fields, the attribute of the values corresponding to the fields is determined, in this embodiment, for example, it is determined whether the values corresponding to the fields are all the attributes of the chinese characters, if the values corresponding to the fields are all the chinese characters, the attribute of the values corresponding to the fields is determined to be the chinese characters, the attribute of the preset rule in the preset rule base is determined, then the attributes of the preset rule are screened from the preset rule base and are all the preset rules of the chinese characters, after the attributes of the preset rule are screened out and are all the preset rules of the chinese characters, the fields whose attributes are all the chinese characters are matched with the attributes, and if the values corresponding to the fields are successfully matched with the preset rules, the check rule corresponding to the fields is the preset rule.

Through the steps, the matching speed can be improved, the matching with all the preset rules in the preset rule base is not needed, only the rules containing the Chinese character attributes in the preset rule base are needed to be matched, and a large amount of time can be saved.

In some embodiments, matching the data in the data set corresponding to each field name with a preset rule in a preset rule base, and generating a check rule of the field according to a matching result includes:

determining data in a data set corresponding to the field name;

determining a preset rule in a preset rule base;

and matching the data with the rules one by one, and generating the verification rules of the fields according to the matching results.

In this embodiment, taking the unit body temperature registry as an example, first determining a value corresponding to a field, then determining preset rules in a preset rule base, and matching the value corresponding to the field with the preset rules in the preset rule base one by one, for example, the field is a value of body temperature, the values are all 10-ary arabic numbers with 1 decimal, any value in the value set is matched with any rule in the preset rule base until the preset rule is matched with the rule that the preset rule is also 10-ary arabic numbers with 1 decimal, and the preset rule is used as a check rule.

In some embodiments, before traversing the object set and acquiring the field name set in the object set and the data set corresponding to each field name, the method for generating the form verification rule of the non-relational database further includes: the object formats in the object collection are converted to formats supported by the programming language.

In the MongoDB database, data is stored in a BSON (Binary verified Document Format), which is a computer data exchange Format mainly used as a data storage and network transmission Format in the MongoDB database. It is a binary representation that can be used to represent simple data structures, associative arrays (called "objects" or "documents" in MongoDB), and various data types in MongoDB. BSON is named as JSON, meaning Binary JSON (Binary JSON). Since most programming languages have no native support for BSON, the data format in the mongodb database must be converted once to be able to access the data in the mongodb database in the program code.

In this embodiment, since the data in the BSON format is the source data, the source data cannot be directly accessed, and the data in the BSON format is converted into the data in the Map format. The converted data can directly traverse the keys, and the keys can also be used for accessing the data with the data format Map.

In some embodiments, after matching the data in the data set corresponding to each field name with the preset rule in the preset rule base and generating the check rule of the field according to the matching result, the method further includes: acquiring data in a data set corresponding to each field name; and judging whether the data is matched with a preset rule in a preset rule base, generating a verification rule of the field according to a matching result when the data is matched with the rule, and marking the field corresponding to the data when the data is not matched with the rule.

In this embodiment, taking the unit body temperature registry as an example, the numerical value corresponding to the field is determined, the field name is taken as an example, the numerical value corresponding to the field name is matched with the preset rules in the preset rule base one by one, and when the numerical value corresponding to the field name is matched with the corresponding preset rules, the preset rules are taken as the verification rules. For example, the preset rule is: the numerical values corresponding to the field are all Chinese characters, and the number of the Chinese characters is one of 2, 3 or 4. And taking the preset rule as a check rule.

And when the numerical value corresponding to the field cannot be matched with all preset rules in the preset rule base, marking the field name corresponding to the data, and reminding a programmer that the preset rule is not found in the field.

For example, the job number of the company is a serial number with 6 digits, such as 000001, 000002 … …

999999. When the number of the employees reaches 999999, if the newly-entered employees enter the job, no job number is allocated to the new employees. The company determines whether the number of digits of the work number of the new employee is 6 digits unchanged, the first digit of the work number is a letter, for example, a00001, a00002, D90003, E37777 and the like, and when the numerical value corresponding to the field is matched with the preset rule, the preset rule corresponding to the numerical value with the number of digits of 6 is not matched. And marking the data corresponding to the field, and reminding a programmer that the preset rule is not found in the field and the verification rule cannot be generated for the field.

In some embodiments, when the data does not match the rule, a field corresponding to the data is marked, and the method for generating the form verification rule of the non-relational database further includes: and compiling a check rule for the field corresponding to the data.

When the data corresponding to the field cannot be matched with the corresponding preset rule, the field is marked to remind a programmer that the preset rule is not found in the field and a verification rule cannot be generated for the field, the programmer needs to compile the verification rule for the field according to the characteristics of the field, add the verification rule into a preset rule base and preset the preset rule in the rule base.

In this embodiment, for example, a check rule is compiled for the numerical value corresponding to the job number, where the check rule is a rule that the number of digits is 6, the first digit is a letter or a number, and the remaining five digits are numbers.

And adding the check rule into a preset rule base, and updating the preset rule in the preset rule base.

In some embodiments, traversing the object set, and sequentially obtaining the field name set and the data set corresponding to each field name in the object set includes: traversing all the obtained fields of the objects in the non-relational database, and obtaining a field name set in the object set according to a traversal result; and traversing the data corresponding to the field name sets in the object set, and acquiring the data sets corresponding to the names of all the fields according to the traversal result.

The present embodiment is described and illustrated below by means of preferred embodiments.

Fig. 2 is a flowchart of a method for generating form verification rules of a non-relational database according to the preferred embodiment, and as shown in fig. 2, the flowchart includes the following steps:

s201: and determining a table name, and determining an object set corresponding to the table name from the non-relational database according to the table name.

S202: traversing all the acquired fields of the objects in the non-relational database, and acquiring a field name set in the object set according to a traversal result.

S203: and traversing the data corresponding to the field name sets in the object set, and acquiring the data sets corresponding to the names of all the fields according to the traversal result.

S204: and matching the data in the data set corresponding to each field name with the preset rules in the preset rule base, and generating the verification rules of the fields according to the matching results.

In this embodiment, for example, during the initial period of a epidemic situation, the unit a performs daily temperature survey of employees, the form has 3 fields such as job number, name, and body temperature, and when data is recorded for the first time, no verification rule is set for the table in the database, so that it is necessary to manually clean data afterwards, for example, whether there is a Chinese period misused as a decimal point, and all Chinese characters corresponding to Arabic numerals in the table are converted into Arabic numerals.

After the epidemic scale is reduced, the collection of the form is stopped, and the original data is stored after being cleaned. Later, due to repeated epidemic situations, the unit A restarts to collect the body temperature data of the staff every day, and the verification rules of the extracted form can be summarized and extracted quickly according to the information of the form. For example, it can be derived from historical data that the name field must be chinese characters and the body temperature field must be 10 arabic numerals with 1 decimal for subsequent submission verification, eliminating or reducing the workload of manually cleaning the data.

The present application is directed to using real data to summarize a rule and using the rule for guiding subsequent runs. If the method does not pass through the method, only a software engineer can be relied on to manually arrange or summarize the form verification rules of various fields in the database.

The embodiment further provides a device for generating a form verification rule of a non-relational database, where the device is used to implement the foregoing embodiment and the preferred embodiments, and the description already made is omitted here for brevity. The terms "module," "unit," "subunit," and the like as used below may implement a combination of software and/or hardware for a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Fig. 3 is a block diagram of a structure of a form verification rule generating device of a non-relational database according to this embodiment, and as shown in fig. 3, the device includes: the device comprises a determining module, an obtaining module and a generating module;

the determining module is used for determining an object set corresponding to the table name from the non-relational database according to the table name;

the acquisition module is used for sequentially acquiring a field name set and a data set corresponding to each field name in the object set by traversing the object set;

a generation module; and the system is used for matching the data in the data set corresponding to each field name with the preset rules in the preset rule base and generating the verification rules of the fields according to the matching results.

The above modules may be functional modules or program modules, and may be implemented by software or hardware. For a module implemented by hardware, the modules may be located in the same processor; or the modules can be respectively positioned in different processors in any combination.

In this embodiment, a system for generating form verification rules of a non-relational database is further provided, including: a terminal device and a server device; the terminal equipment is connected with the server equipment; the terminal equipment is used for sending a request instruction of a user; the server device is configured to perform the steps in any of the above method embodiments.

There is also provided in this embodiment an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.

Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.

Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:

s1, determining the table name, and determining the object set corresponding to the table name from the non-relational database according to the table name.

And S2, traversing the object set, and sequentially acquiring the field name set in the object set and the data set corresponding to each field name.

And S3, matching the data in the data set corresponding to each field name with the preset rules in the preset rule base, and generating the verification rules of the fields according to the matching results.

It should be noted that, for specific examples in this embodiment, reference may be made to the examples described in the foregoing embodiments and optional implementations, and details are not described again in this embodiment.

In addition, in combination with the method for generating the form verification rule of the non-relational database provided in the foregoing embodiment, a storage medium may also be provided in this embodiment to implement the method. The storage medium having stored thereon a computer program; the computer program, when executed by a processor, implements the method for generating form verification rules for a non-relational database according to any one of the above embodiments.

It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to be limiting. All other embodiments, which can be derived by a person skilled in the art from the examples provided herein without any inventive step, shall fall within the scope of protection of the present application.

It is obvious that the drawings are only examples or embodiments of the present application, and it is obvious to those skilled in the art that the present application can be applied to other similar cases according to the drawings without creative efforts. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.

The term "embodiment" is used herein to mean that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly or implicitly understood by one of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the patent protection. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.