CN114625441A - Rule configuration method and device, computer equipment and storage medium - Google Patents
Rule configuration method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of artificial intelligence, and provides a rule configuration method, a rule configuration device, computer equipment and a storage medium, wherein the method comprises the following steps: receiving a rule configuration request triggered by a user; analyzing user information from the rule configuration request; based on the user information, calling a preset classification tree model and a data table to carry out authority verification on the user; if the authority passes the verification, acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool; and analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data. The method and the device can assist the user to rapidly carry out rule configuration operation, effectively reduce the complexity of rule configuration processing, and improve the intelligence of rule configuration processing. The method and the device can also be applied to the field of block chains, and the data such as the rule data can be stored on the block chains.
Description
Technical Field
The application relates to the technical field of artificial intelligence, in particular to a rule configuration method, a rule configuration device, computer equipment and a storage medium.
Background
With the development of science and technology, the application range of rule configuration is increasingly wide. In the business processing process of a company, a rule configuration tool is generally required to configure the usage rule of business data.
At present, most of the existing rule configuration tools need to be set by adopting programming language hard coding, the grammar is complex, professional developers are mainly oriented, the business personnel are not easy to intervene, and decoupling and separation between business logic and codes cannot be achieved. Other similar software is too old in technology, does not carry out front-end and back-end separation, is bloated in codes, is not easy to maintain and expand, and cannot meet the requirements of quick iteration and high concurrency in the Internet age. Therefore, the existing rule configuration mode has the technical problems of complex processing and lack of intelligence.
Disclosure of Invention
The application mainly aims to provide a rule configuration method, a rule configuration device, computer equipment and a storage medium, and aims to solve the technical problems of complex processing and lack of intelligence in the existing rule configuration mode.
The application provides a rule configuration method, which comprises the following steps:
receiving a rule configuration request triggered by a user;
analyzing user information from the rule configuration request;
based on the user information, calling a preset classification tree model and a data table to carry out authority verification on the user;
if the authority passes the verification, acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool;
and analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data.
Optionally, the rule configuration request further carries rule configuration content, and the step of obtaining a rule configuration file from the rule configuration request based on a preset rule definition tool includes:
analyzing the rule configuration content from the rule configuration request;
invoking the rule definition tool;
and carrying out rule configuration processing based on the rule definition tool and the rule configuration content to obtain the rule configuration file.
Optionally, the data table includes a role authority score table and a service operation authority score table, and the step of invoking a preset classification tree model and the data table to perform authority verification on the user based on the user information includes:
calling the classification tree model, the role authority score table and the service operation authority score table;
inputting the user information into the classification tree model, and determining the role category corresponding to the user information through the classification tree model;
determining a target permission score corresponding to the role category based on the role permission score table;
acquiring a service operation permission score interval corresponding to a configuration rule based on the service operation permission score table;
judging whether the target authority score is in the authority score interval or not;
and if the authority score is within the authority score interval, judging that the authority verification is passed, otherwise, judging that the authority verification is not passed.
Optionally, after the step of analyzing the rule configuration file based on the preset rule engine to generate corresponding rule data, the method includes:
judging whether a rule test request is received or not; the rule test request carries system information and scene definition information;
if yes, extracting the system information and the scene definition information from the rule test request;
acquiring the system information and a corresponding target rule;
analyzing and executing the target rule through the rule engine based on the scene definition information to obtain a corresponding rule calculation result;
and generating a test result corresponding to the target rule based on the rule calculation result.
Optionally, the step of analyzing and executing the target rule by the rule engine based on the scene definition information to obtain a corresponding rule calculation result includes:
analyzing the target rule through the rule engine to acquire input parameter data and output parameter data corresponding to the scene definition information; and the number of the first and second groups,
extracting an operation rule corresponding to the scene definition information from the target rule;
based on the rule engine, calculating the input parameter data by using the operation rule to obtain a rule calculation result;
the step of generating a test result corresponding to the target rule based on the rule calculation result includes:
judging whether the rule calculation result is the same as the parameter data;
if the rule calculation result is the same as the parameter output data, generating a first test result that the target rule passes the test;
and if the rule calculation result is different from the parameter data, generating a second test result that the target rule fails to pass the test.
Optionally, after the step of invoking a preset classification tree model and a data table to perform permission verification on the user based on the user information, the method includes:
if the authority verification is not passed, limiting the response to the rule configuration request;
generating corresponding alarm information based on the user information;
acquiring preset communication login information and acquiring a target communication address corresponding to a target user;
logging in to a corresponding communication server based on the communication login information;
and sending the alarm information to the target communication address through the communication server.
Optionally, after the step of analyzing the rule configuration file based on the preset rule engine to generate corresponding rule data, the method includes:
acquiring an occupied memory value of the rule data, and acquiring a preset memory threshold value;
judging whether the occupied memory value is larger than the memory threshold value or not;
if the memory threshold value is larger than the memory threshold value, storing the rule data in a block chain;
and if the rule data is not greater than the memory threshold, storing the rule data in a local preset database.
The present application further provides a rule configuration apparatus, including:
the receiving module is used for receiving a rule configuration request triggered by a user;
the analysis module is used for analyzing the user information from the rule configuration request;
the verification module is used for calling a preset classification tree model and a data table to carry out authority verification on the user based on the user information;
the first acquisition module is used for acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool if the authority verification passes;
and the first generation module is used for analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data.
The present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method.
The rule configuration method, the rule configuration device, the computer equipment and the storage medium have the following beneficial effects:
according to the rule configuration method, the rule configuration device, the computer equipment and the storage medium, after a rule configuration request triggered by a user is received, user information is firstly analyzed from the rule configuration request, a preset classification tree model and a data table are called to carry out authority verification on the user based on the user information, if the authority verification is passed, a rule configuration file is obtained from the rule configuration request based on a preset rule definition tool, and finally a preset rule engine is called to carry out analysis processing on the rule configuration file so as to generate corresponding rule data. By utilizing the front-end and back-end separation technology, a simple and flexible configuration interface is provided for a user, so that a non-IT professional can perform business logic configuration, the processing complexity of rule configuration is reduced, and the use experience of the user is improved; meanwhile, the technical scheme of separating the front end from the back end is adopted, the technical development and maintenance difficulty is simplified, cross-platform deployment and calling of the system are facilitated, and the processing intelligence of rule configuration is improved.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a rule configuration method according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of a rule configuration device according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
Referring to fig. 1, a rule configuration method according to an embodiment of the present application includes:
s10: receiving a rule configuration request triggered by a user;
s20: analyzing user information from the rule configuration request;
s30: based on the user information, calling a preset classification tree model and a data table to carry out authority verification on the user;
s40: if the authority passes the verification, acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool;
s50: and analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data.
As described in the foregoing steps S10-S50, the main implementation of the present method embodiment is a rule configuration device, which may be simply referred to as a device. In practical applications, the rule configuration device may be implemented by a virtual device, such as a software code, or may be implemented by an entity device in which a relevant execution code is written or integrated, and may perform human-computer interaction with a user through a keyboard, a mouse, a remote controller, a touch panel, or a voice control device. The rule configuration device in the embodiment can reduce the processing complexity of rule configuration and improve the intelligence of rule configuration processing. Specifically, a user-triggered rule configuration request is first received. The rule configuration request is a request triggered by a user and used for rule configuration on a current interface. In addition, the rule configuration request may carry user information and rule configuration content. The user information may include user name, user id information, and the like. The rule configuration content at least comprises access system information, scene definition information, rule description content of an operation rule corresponding to the scene definition information, an access parameter mapping relation and the like. And then analyzing the user information from the rule configuration request.
And then, based on the user information, calling a preset classification tree model and a data table to carry out authority verification on the user. The data table comprises a role authority point table and a service operation authority point table. In addition, for the specific implementation process of performing the authority verification on the user by calling the preset classification tree model and the data table based on the user information, the present application will further describe details in the following specific embodiments, which are not set forth herein. And if the authority passes the verification, acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool. After triggering the rule configuration request, the user can define the rule through the rule definition tool, so as to obtain the rule configuration file. In addition, the rule definition tool may specifically be a visualization tool developed based on Vue, and a user may perform rule configuration by using a natural language-like language that can be operated by an operator in a general software system based on the visualization tool developed Vue. Specifically, a user can set a rule configuration request through a client, the client receives the rule configuration request sent by the user, the rule configuration request carries rule configuration content, and the rule is configured according to the rule configuration content and a visualization tool developed by Vue, so that a rule configuration file is obtained.
And finally, analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data. Wherein the device may download a dependency package, i.e., a rules engine JAR, corresponding to the rules engine. And calling parameters by using a calling method defined in a Util tool class preset in the dependency package, defining input and output parameters in a Map form, positioning corresponding rules such as calculation rules through scene definition information, and integrating the calculation rules in the device to complete the configuration of the calculation rules. A rules engine is a software program that uses human-understandable terms (short for natural language-like) to describe business logic (e.g., formulas, algorithms, policies, procedures, etc.) and to parse execution. For general data processing logic and judgment logic, the rule engine can directly adopt terms defined by business personnel to describe the business logic, so that the business logic can be independently configured and managed without a program, the coupling of code modules is reduced, and the flexible change and quick effect of a later business party are met. Some service logic processing in charge of the information system can be completely configured by the rule engine, so that the risk of the project is reduced, the project schedule is guaranteed, the control capability of the service department on the information system is enhanced, the participation degree of the service department is improved, the communication workload of the service department and the technical department is reduced, the working pressure of the technical department is reduced, the maintenance cost of the system is reduced, and the adaptability, flexibility and intellectualization of the project are enhanced. In addition, after the user configures the rules, the rules can be persisted by using a rule engine. And analyzing the rule into rule data in a preset format by using a rule engine, such as a JSON file, and saving the rule data by calling a background related API (application programming interface). The file format adopts a general JSON format, so that cross-platform and cross-language interaction is facilitated. The rule data may be in a first predetermined format. For example, the first predetermined format may be a format that is convenient for database storage, and is not limited herein. For example, after receiving the storage request, the background API parses the data in the JSON format into Java language objects, and stores the Java language objects in the database through the database persistence tool, so that the user can conveniently query, modify, and parse and execute the Java language objects.
In this embodiment, after receiving a rule configuration request triggered by a user, user information is parsed from the rule configuration request, and based on the user information, a preset classification tree model and a data table are called to perform authority verification on the user, if the authority verification passes, a rule configuration file is obtained from the rule configuration request based on a preset rule definition tool, and finally, a preset rule engine is called to parse the rule configuration file to generate corresponding rule data. By utilizing the front-end and back-end separation technology, the embodiment provides a simple and flexible configuration interface for the user, so that a non-IT professional can perform service logic configuration, the processing complexity of rule configuration is reduced, and the use experience of the user is improved; meanwhile, the technical scheme of separating the front end from the back end is adopted, the technical development and maintenance difficulty is simplified, cross-platform deployment and calling of the system are facilitated, and the processing intelligence of rule configuration is improved.
Further, in an embodiment of the present application, the rule configuration request further carries rule configuration content, and the step S40 includes:
s400: analyzing the rule configuration content from the rule configuration request;
s401: calling the rule definition tool;
s402: and carrying out rule configuration processing based on the rule definition tool and the rule configuration content to obtain the rule configuration file.
As described in the foregoing steps S400 to S402, the rule configuration request further carries rule configuration content, and the step of obtaining a rule configuration file from the rule configuration request based on a preset rule definition tool specifically includes: firstly, the rule configuration content is analyzed from the rule configuration request. The rule configuration content may at least include access system information, scene definition information, rule description content of an operation rule corresponding to the scene definition information, an access parameter mapping relationship, and the like. By carrying out rule configuration processing on the rule configuration content, a rule configuration file corresponding to the service system can be generated and exported. In addition, after the rule configuration file is obtained, a corresponding file generation record can be generated, and the file generation record is equivalent to an operation log record which can be used for rollback operation. Specifically, the access system information at least includes system information, information of a person in charge, whether access is effective, time, applicant information, application system random code (unique key for the docked service system), and credential information (unique key corresponding to the rule configuration file for distinguishing this maintenance). The scene definition information at least comprises a scene ID (a unique key value of a calculation rule for calling a corresponding scene by a service system), whether step calculation is carried out or not (whether a plurality of arithmetic rules are maintained and a result is obtained according to step execution or not, whether only one arithmetic rule exists or not), a function name (corresponding to a Bean name in a project), a corresponding system ID and the like. The rule description content at least comprises a rule id, a rule content, an execution sequence (a plurality of rules can be set in the same scene and are finally assembled into a function, so that the execution sequence exists), a rule type (comprising a calculation rule and a condition rule, wherein the condition rule refers to condition judgment in the case of multiple steps). And if the condition rule is a condition rule, the downstream rule id is transferred to the corresponding downstream rule according to the condition in the condition rule definition for further processing. The in-out-reference mapping relation refers to a field mapping relation of in-reference and out-reference of a corresponding scene, and mainly comprises definitions of an in-reference field and an out-reference field of a corresponding service system, field types, field lengths (String type length definition), field precision (numerical type precision definition) and the like. The rule definition tool is then invoked. Wherein the rule definition tool may be a visualization tool developed based on Vue. And subsequently, rule configuration processing is carried out based on the rule definition tool and the rule configuration content to obtain the rule configuration file. Wherein, the user can adopt a natural language-like language which can be operated by an operator in a general software system for rule configuration based on a visualization tool developed by Vue. Specifically, a user can set a rule configuration request through a client, the client receives the rule configuration request sent by the user, the rule configuration request carries rule configuration content, and the rule is configured according to the rule configuration content and a visualization tool developed by Vue, so that a corresponding rule configuration file is obtained. In this embodiment, the rule configuration content is analyzed from the rule configuration request, and then the rule configuration processing is performed based on a preset visualization rule tool and the rule configuration content to obtain the rule configuration file, which is beneficial to subsequently calling a preset rule engine to analyze the rule configuration file to obtain corresponding rule data, so as to complete intelligent configuration of the rule data, improve the processing efficiency of the rule configuration, and improve the use experience of a user.
Further, in an embodiment of the present application, the step S30 includes:
s300: calling the classification tree model, the role authority score table and the service operation authority score table;
s301: inputting the user information into the classification tree model, and determining the role category corresponding to the user information through the classification tree model;
s302: determining a target permission score corresponding to the role category based on the role permission score table;
s303: acquiring a service operation permission score interval corresponding to a configuration rule based on the service operation permission score table;
s304: judging whether the target authority score is within the authority score interval or not;
s305: and if the authority score is within the authority score interval, judging that the authority verification is passed, otherwise, judging that the authority verification is not passed.
As described in the foregoing steps S300 to S305, the data table includes a role authority score table and a service operation authority score table, and the step of invoking a preset classification tree model and the data table to perform authority verification on the user based on the user information may specifically include: firstly, calling the classification tree model, the role authority score table and the service operation authority score table. The classification tree model is a pre-established model, each node except leaf nodes in the classification tree model corresponds to one classification rule, and each classification rule classifies one type of data in the user information. In addition, a role authority score table is created in advance, authority scores corresponding to all role categories are recorded in the role authority score table, a service operation authority score table is created in advance, and authority score intervals corresponding to all service operations are recorded in the service operation authority score table. And then inputting the user information into the classification tree model, and determining the role category corresponding to the user information through the classification tree model. Specifically, the user information can be classified layer by layer through the classification tree model, and finally the user information is distributed to a leaf node, wherein the leaf node corresponds to a role category. And then, according to the corresponding relation between the preset leaf node and the authority score, determining a target authority score corresponding to the user information. For example, suppose the user information includes: "station level: 6, the service department: a, service task: and 8 ', if the root node of the classification tree model is classified through the ' post level ', the second level node is classified through the ' service department ', and the third level node is classified through the ' service task ', the user information can be distributed to a leaf node through three-layer classification, and then the role type corresponding to the user information is obtained. And then determining a target permission score corresponding to the role category based on the role permission score table. The target authority score corresponding to the role category of the user information can be inquired from the role authority score table according to the corresponding relation between the role category and the authority score in the role authority score table. And subsequently acquiring the authority score interval of the business operation corresponding to the configuration rule based on the business operation authority score table. The value of the permission score interval is not specifically limited, and can be set according to actual requirements. And finally, judging whether the target authority score is in the authority score interval. And if the authority score is within the authority score interval, judging that the authority verification is passed, otherwise, judging that the authority verification is not passed. In the embodiment, the classification tree model is used for rapidly acquiring the target permission score corresponding to the user information, and then the target permission score of the user and the permission score interval of the business operation corresponding to the configuration rule are compared in a numerical value mode to obtain a corresponding comparison result, so that whether the user passes permission verification or not can be accurately and rapidly judged according to the comparison result. Only when the user is judged to pass the authority verification, the corresponding rule configuration processing flow is executed on the rule configuration request triggered by the user subsequently, and the adverse effect caused by responding to the rule configuration request input by the unauthorized user is effectively avoided. In addition, the corresponding rule configuration function is only opened for the legal user with the rule configuration authority, so that the normalization and the safety of the rule generation process are ensured.
Further, in an embodiment of the present application, after the step S50, the method includes:
s500: judging whether a rule test request is received or not; the rule test request carries system information and scene definition information;
s501: if yes, extracting the system information and the scene definition information from the rule test request;
s502: acquiring the system information and a corresponding target rule;
s503: analyzing and executing the target rule through the rule engine based on the scene definition information to obtain a corresponding rule calculation result;
s504: and generating a test result corresponding to the target rule based on the rule calculation result.
As described in the above steps S500 to S504, after the step of performing parsing processing on the rule configuration file based on the preset rule engine to generate corresponding rule data is performed, a test process for a rule may be further included. Specifically, it is first determined whether a rule test request is received. Wherein the rule test request is a request for verifying whether a rule generated by configuration conforms to a configuration specification. The rule test request carries system information and scene definition information. And if a rule test request is received, extracting the system information and the scene definition information from the rule test request. And then acquiring the system information and a corresponding target rule. And subsequently analyzing and executing the target rule through the rule engine based on the scene definition information to obtain a corresponding rule calculation result. Different rules can be correspondingly set for different business systems, one rule can correspond to operation rules under a plurality of scenes, the operation rules and scene definition information have corresponding relations, and the target rules can be tested and processed based on input parameter data and output parameter data corresponding to the scene definition information in the target rules. In addition, for the specific implementation process of analyzing and executing the target rule through the rule engine based on the scene definition information to obtain the corresponding rule calculation result, the detailed description will be further described in the following specific embodiments, and will not be set forth herein too much. And finally generating a test result corresponding to the target rule based on the rule calculation result. The comparison processing of the numerical values can be performed by comparing the rule calculation result with the parameter data corresponding to the scene definition information in the target rule, and then the corresponding test result is generated according to the obtained comparison result. If the obtained rule calculation result is the same as the parameter data, a test result that the target rule passes the test is generated, and if the obtained rule calculation result is different from the parameter data, a test result that the target rule fails the test is generated. In this embodiment, after the configuration of the target rule is completed, the test validation process for the target rule corresponding to the rule test request may be quickly executed subsequently based on the received rule test request, that is, the target rule is independently tested and validated based on the rule engine, which may greatly reduce the test workload compared to the conventional test method, and further effectively improve the test efficiency for the rule.
Further, in an embodiment of the present application, the step S503 includes:
s5030: analyzing the target rule through the rule engine to acquire input parameter data and output parameter data corresponding to the scene definition information; and the number of the first and second groups,
s5031: extracting an operation rule corresponding to the scene definition information from the target rule;
s5032: based on the rule engine, calculating the input parameter data by using the operation rule to obtain a rule calculation result;
the step S504 includes:
s5040: judging whether the rule calculation result is the same as the parameter data;
s5041: if the rule calculation result is the same as the parameter output data, generating a first test result that the target rule passes the test;
s5042: and if the rule calculation result is different from the parameter data, generating a second test result that the target rule fails to pass the test.
As described in the foregoing steps S5030 to S5042, the step of analyzing and executing the target rule by the rule engine based on the scene definition information to obtain a corresponding rule calculation result may specifically include: firstly, the target rule is analyzed and processed through the rule engine, and input parameter data and output parameter data corresponding to the scene definition information are obtained. The entry and exit parameter data and the scene definition information have a corresponding relationship, and the corresponding entry and exit parameter data can be extracted based on the scene definition information in the target rule. And extracting an operation rule corresponding to the scene definition information from the target rule. The operation rule and the scene definition information have a corresponding relationship, and the corresponding operation rule can be extracted based on the scene definition information in the target rule. The operation rules include, but are not limited to, simple addition, subtraction, multiplication, and division of four arithmetic operations, functional operations, execution order, and the like. And then based on the rule engine, calculating the input parameter data by using the operation rule to obtain the rule calculation result. The input parameter data can be substituted into the calculation formula corresponding to the operation rule to perform calculation, and the obtained calculation result is the rule calculation result. Specifically, the rule calculation principle can be expressed as: an operation rule generally includes multiple rows of regular expressions, where a row of expressions corresponds to multiple lattices, and each lattice corresponds to a corresponding constant value or regular variable. When rule calculation is performed, a user needs to specify a rule name and a rule variable (namely, input parameter data), the rule engine finds out a row expression associated with each rule from the rule name and the rule variable, then finds out a lattice corresponding to each row through the row expression, matches each lattice with the rule variable transmitted by the user, and finally performs rule calculation and returns a result. In addition, the storage of the rule data can be performed through a database, and the database can include the following data tables: rule table: storing each rule definition information, wherein the rule definition information and the rule row table are in one-to-many relation; rule row table: storing each row of expression in each rule definition, wherein the expression and the lattice variable table are in one-to-many relation; grid variable table: storing each grid information in the rule row, wherein the grid information and the decision variable table are in one-to-many relation; decision variable table: and configuring decision variables used in the grid variable table.
Further, the step of generating a test result corresponding to the target rule based on the rule calculation result may specifically include: and judging whether the rule calculation result is the same as the parameter output data or not. And if the rule calculation result is the same as the parameter output data, generating a first test result that the target rule passes the test. And if the rule calculation result is different from the parameter output data, generating a second test result that the target rule fails to pass the test. In this embodiment, the rule engine is used to analyze the target rule to obtain the entry parameter data, the exit parameter data, and the operation rule corresponding to the scene definition information, and then the operation rule may be used to perform calculation processing on the entry parameter data to obtain the rule calculation result, so as to quickly and accurately generate the rule calculation result, which is beneficial to subsequently and accurately generating the test result corresponding to the target rule based on the obtained rule calculation result, so as to complete the test process for the target rule. The target rule is independently tested and verified through the rule engine, so that the test workload can be greatly reduced compared with the traditional test mode, and the test efficiency of the rule is effectively improved.
Further, in an embodiment of the present application, after the step S30, the method includes:
s310: if the authority verification is not passed, limiting the response to the rule configuration request;
s311: generating corresponding alarm information based on the user information;
s312: acquiring preset communication login information and acquiring a target communication address corresponding to a target user;
s313: logging in a corresponding communication server based on the communication login information;
s314: and sending the alarm information to the target communication address through the communication server.
As described in steps S310 to S314 above, after the step of performing the authorization verification on the user by calling the preset classification tree model and the data table based on the user information is completed, if the user fails the authorization verification, the early warning processing on the current rule configuration operation may be further performed. Specifically, if the authority verification fails, the response to the rule configuration request is restricted. After the rule configuration request is limited to be processed, alarm information requesting for processing abnormality can be further returned to the related users, so that the related users can timely know that the current user sending the rule configuration request is an illegal user without the service processing authority for performing rule configuration. Corresponding alarm information is then generated based on the user information. The user information may include a user name or a user id. After the user information is obtained, corresponding alarm information can be generated based on the user information and a preset alarm information template. The alarm information template is an information template generated in advance according to actual use requirements, and the content of the information template is not limited, and may include: "the following users who illegally perform rule configuration are now monitored: … are provided. "additionally, the corresponding alert information may be generated by populating the user information to the respective locations of the alert information template. And then acquiring preset communication login information and acquiring a target communication address corresponding to the target user. Wherein the target user may be a manager related to maintenance work of the rule configuration. In addition, if the target communication address can be a mail, the corresponding communication login information is mail login information, and the communication server is a mail server. And subsequently logging in a corresponding communication server based on the communication login information. And finally, sending the alarm information to the target communication address through the communication server. In this embodiment, after it is determined that the user fails the authority verification, alarm information corresponding to the user information of the user is intelligently generated, and the alarm information is sent to the target communication address corresponding to the target user, so that the target user can timely know that the current user who sends the rule configuration request is an illegal user who does not have the service processing authority for performing the rule configuration based on the alarm information, and thus, corresponding processing can be timely performed, and the management and use experience of the target user is improved.
Further, in an embodiment of the application, after the step S50, the method includes:
s510: acquiring an occupied memory value of the rule data, and acquiring a preset memory threshold value;
s511: judging whether the occupied memory value is larger than the memory threshold value or not;
s512: if the memory threshold value is larger than the memory threshold value, the rule data are stored in a block chain;
s513: and if the rule data is not greater than the memory threshold, storing the rule data in a local preset database.
As described in the above steps S510 to S513, after the step of parsing the rule configuration file based on the preset rule engine to generate corresponding rule data is performed, an intelligent storage process for the rule data may be further included. Specifically, first, an occupied memory value of the rule data is obtained, and a preset memory threshold value is obtained. And then judging whether the occupied memory value is larger than the memory threshold value. The value of the memory threshold is not specifically limited, and may be set according to actual requirements. If the occupied memory value of the rule data is larger than the memory threshold value, the rule data is considered to be stored locally to influence the normal operation of the device, and then the rule data is stored to the block chain, so that the storage intelligence and the storage safety of the rule data are improved. And if the memory threshold value is larger than the memory threshold value, storing the rule data in a block chain. And if the rule data is not greater than the memory threshold, storing the rule data in a local preset database. In this embodiment, after the rule data is generated and the number of occupied memories of the rule data is obtained, the rule data is intelligently stored in the local database or the block chain according to the comparison result between the occupied memory value of the rule data and the preset memory threshold value, and the rule data is stored in the corresponding storage position according to the occupied memory value, so that the subsequent management and obtaining of the rule data can be facilitated, and the storage intelligence of the rule data is effectively improved.
The rule configuration method in the embodiment of the present application can also be applied to the field of blockchains, for example, data such as the above rule data is stored in a blockchain. By storing and managing the rule data using a block chain, the security and the non-tamper property of the rule data can be effectively ensured.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The block chain underlying platform can comprise processing modules such as user management, basic service, intelligent contract and operation monitoring. The user management module is responsible for identity information management of all blockchain participants, and comprises public and private key generation maintenance (account management), key management, user real identity and blockchain address corresponding relation maintenance (authority management) and the like, and under the authorization condition, the user management module supervises and audits the transaction condition of certain real identities and provides rule configuration (wind control audit) of risk control; the basic service module is deployed on all block chain node equipment and used for verifying the validity of the service request, recording the service request to storage after consensus on the valid request is completed, for a new service request, the basic service firstly performs interface adaptation analysis and authentication processing (interface adaptation), then encrypts service information (consensus management) through a consensus algorithm, transmits the service information to a shared account (network communication) completely and consistently after encryption, and performs recording and storage; the intelligent contract module is responsible for registering and issuing contracts, triggering the contracts and executing the contracts, developers can define contract logics through a certain programming language, issue the contract logics to a block chain (contract registration), call keys or other event triggering and executing according to the logics of contract clauses, complete the contract logics and simultaneously provide the function of upgrading and canceling the contracts; the operation monitoring module is mainly responsible for deployment, configuration modification, contract setting, cloud adaptation in the product release process and visual output of real-time states in product operation, such as: alarm, monitoring network conditions, monitoring node equipment health status, and the like.
Referring to fig. 2, an embodiment of the present application further provides a rule configuration apparatus, including:
the system comprises a receiving module 1, a rule configuration module and a rule configuration module, wherein the receiving module is used for receiving a rule configuration request triggered by a user;
the analysis module 2 is used for analyzing the user information from the rule configuration request;
the verification module 3 is used for calling a preset classification tree model and a data table to verify the authority of the user based on the user information;
the first obtaining module 4 is configured to obtain a rule configuration file from the rule configuration request based on a preset rule definition tool if the permission verification passes;
and the first generation module 5 is configured to analyze the rule configuration file based on a preset rule engine to generate corresponding rule data.
In this embodiment, the operations executed by the modules or units respectively correspond to the steps of the rule configuration method in the foregoing embodiment one to one, and are not described herein again.
Further, in an embodiment of the present application, the rule configuration request further carries rule configuration content, and the first obtaining module 4 includes:
the analysis unit is used for analyzing the rule configuration content from the rule configuration request;
the first calling unit is used for calling the rule definition tool;
and the processing unit is used for carrying out rule configuration processing on the basis of the rule definition tool and the rule configuration content to obtain the rule configuration file.
In this embodiment, the operations executed by the modules or units respectively correspond to the steps of the rule configuration method in the foregoing embodiment one to one, and are not described herein again.
Further, in an embodiment of the present application, the verification module 3 includes:
the second calling unit is used for calling the classification tree model, the role authority score table and the service operation authority score table;
the first determining unit is used for inputting the user information into the classification tree model and determining the role category corresponding to the user information through the classification tree model;
a second determination unit configured to determine a target permission score corresponding to the role category based on the role permission score table;
the first acquisition unit is used for acquiring an authority score interval of the business operation corresponding to the configuration rule based on the business operation authority score table;
the first judgment unit is used for judging whether the target authority score is in the authority score interval or not;
and the judging unit is used for judging that the authority verification passes if the authority score interval is within the authority score interval, and otherwise, judging that the authority verification does not pass.
In this embodiment, the operations executed by the modules or units respectively correspond to the steps of the rule configuration method in the foregoing embodiment one to one, and are not described herein again.
Further, in an embodiment of the present application, the rule configuration apparatus includes:
the first judgment module is used for judging whether a rule test request is received or not; the rule test request carries system information and scene definition information;
the extraction module is used for extracting the system information and the scene definition information from the rule test request if the rule test request is positive;
the second acquisition module is used for acquiring the system information and a corresponding target rule;
the first processing module is used for analyzing and executing the target rule through the rule engine based on the scene definition information to obtain a corresponding rule calculation result;
and the second generation module is used for generating a test result corresponding to the target rule based on the rule calculation result.
In this embodiment, the operations executed by the modules or units respectively correspond to the steps of the rule configuration method in the foregoing embodiment one by one, and are not described herein again.
Further, in an embodiment of the present application, the first processing module includes:
the second acquisition unit is used for analyzing the target rule through the rule engine and acquiring the parameter input data and the parameter output data corresponding to the scene definition information; and the number of the first and second groups,
an extraction unit configured to extract an operation rule corresponding to the scene definition information from the target rule;
the calculation unit is used for calculating the input parameter data by using the operation rule based on the rule engine to obtain a rule calculation result;
the second generating module includes:
a second judging unit, configured to judge whether the rule calculation result is the same as the parameter output data;
the first generating unit is used for generating a first test result of the target rule passing the test if the rule calculation result is the same as the parameter output data;
and the second generating unit is used for generating a second test result that the target rule fails to pass the test if the rule calculation result is different from the parameter data.
In this embodiment, the operations executed by the modules or units respectively correspond to the steps of the rule configuration method in the foregoing embodiment one to one, and are not described herein again.
Further, in an embodiment of the present application, the rule configuration apparatus includes:
the second processing module is used for limiting the response to the rule configuration request if the authority verification fails;
the third generation module is used for generating corresponding alarm information based on the user information;
the third acquisition module is used for acquiring preset communication login information and acquiring a target communication address corresponding to a target user;
the login module is used for logging in a corresponding communication server based on the communication login information;
and the sending module is used for sending the alarm information to the target communication address through the communication server.
In this embodiment, the operations executed by the modules or units respectively correspond to the steps of the rule configuration method in the foregoing embodiment one to one, and are not described herein again.
Further, in an embodiment of the present application, the rule configuration apparatus includes:
a fourth obtaining module, configured to obtain an occupied memory value of the rule data, and obtain a preset memory threshold;
the second judgment module is used for judging whether the occupied memory value is larger than the memory threshold value or not;
the first storage module is used for storing the rule data in a block chain if the rule data is larger than the memory threshold;
and the second storage module is used for storing the rule data in a local preset database if the rule data is not greater than the memory threshold.
In this embodiment, the operations executed by the modules or units respectively correspond to the steps of the rule configuration method in the foregoing embodiment one by one, and are not described herein again.
Referring to fig. 3, a computer device, which may be a server and whose internal structure may be as shown in fig. 3, is also provided in the embodiment of the present application. The computer device comprises a processor, a memory, a network interface, a display screen, an input device and a database which are connected through a system bus. Wherein the processor of the computer device is designed to provide computing and control capabilities. The memory of the computer device comprises a storage medium and an internal memory. The storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and computer programs in the storage medium to run. The database of the computer device is used for storing user information, classification tree models, data tables, rule configuration files and rule data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The display screen of the computer equipment is an indispensable image-text output equipment in the computer, and is used for converting digital signals into optical signals so that characters and figures are displayed on the screen of the display screen. The input device of the computer equipment is the main device for information exchange between the computer and the user or other equipment, and is used for transmitting data, instructions, some mark information and the like to the computer. The computer program is executed by a processor to implement a rule configuration method.
The processor executes the steps of the rule configuration method:
receiving a rule configuration request triggered by a user;
analyzing user information from the rule configuration request;
based on the user information, calling a preset classification tree model and a data table to carry out authority verification on the user;
if the authority passes the verification, acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool;
and analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data.
Those skilled in the art will appreciate that the structure shown in fig. 3 is only a block diagram of a part of the structure related to the present application, and does not constitute a limitation to the apparatus and the computer device to which the present application is applied.
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where when the computer program is executed by a processor, the computer program implements a rule configuration method, and specifically:
receiving a rule configuration request triggered by a user;
analyzing user information from the rule configuration request;
based on the user information, calling a preset classification tree model and a data table to carry out authority verification on the user;
if the authority passes the verification, acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool;
and analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data.
To sum up, after receiving a rule configuration request triggered by a user, the rule configuration method, the rule configuration device, the computer device, and the storage medium provided in the embodiments of the present application may analyze user information from the rule configuration request, call a preset classification tree model and a data table to perform authority verification on the user based on the user information, obtain a rule configuration file from the rule configuration request based on a preset rule definition tool if the authority verification passes, and finally call a preset rule engine to perform analysis processing on the rule configuration file to generate corresponding rule data. The embodiment of the application provides a simple and flexible configuration interface for the user by utilizing the front-end and back-end separation technology, so that a non-IT professional can perform business logic configuration, the processing complexity of rule configuration is reduced, and the use experience of the user is improved; meanwhile, the technical scheme of separating the front end from the back end is adopted, the technical development and maintenance difficulty is simplified, cross-platform deployment and calling of the system are facilitated, and the processing intelligence of rule configuration is improved.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, and the computer program may be stored in a computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium provided herein and used in the examples may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (10)
1. A method for rule configuration, comprising:
receiving a rule configuration request triggered by a user;
analyzing user information from the rule configuration request;
based on the user information, calling a preset classification tree model and a data table to carry out authority verification on the user;
if the authority passes the verification, acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool;
and analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data.
2. The rule configuration method according to claim 1, wherein the rule configuration request further carries rule configuration content, and the step of obtaining a rule configuration file from the rule configuration request based on a preset rule definition tool includes:
analyzing the rule configuration content from the rule configuration request;
calling the rule definition tool;
and carrying out rule configuration processing based on the rule definition tool and the rule configuration content to obtain the rule configuration file.
3. The rule configuration method according to claim 1, wherein the data table includes a role authority score table and a service operation authority score table, and the step of invoking a preset classification tree model and the data table to perform the authority verification on the user based on the user information includes:
calling the classification tree model, the role authority score table and the service operation authority score table;
inputting the user information into the classification tree model, and determining the role category corresponding to the user information through the classification tree model;
determining a target permission score corresponding to the role category based on the role permission score table;
acquiring a service operation permission score interval corresponding to a configuration rule based on the service operation permission score table;
judging whether the target authority score is within the authority score interval or not;
and if the authority score is within the authority score interval, judging that the authority verification is passed, otherwise, judging that the authority verification is not passed.
4. The method according to claim 1, wherein after the step of parsing the rule configuration file based on a preset rule engine to generate corresponding rule data, the method comprises:
judging whether a rule test request is received or not; the rule test request carries system information and scene definition information;
if yes, extracting the system information and the scene definition information from the rule test request;
acquiring the system information and a corresponding target rule;
analyzing and executing the target rule through the rule engine based on the scene definition information to obtain a corresponding rule calculation result;
and generating a test result corresponding to the target rule based on the rule calculation result.
5. The method of claim 4, wherein the step of analyzing and executing the target rule by the rule engine based on the scene definition information to obtain a corresponding rule calculation result includes:
analyzing the target rule through the rule engine to acquire input parameter data and output parameter data corresponding to the scene definition information; and the number of the first and second groups,
extracting an operation rule corresponding to the scene definition information from the target rule;
based on the rule engine, the input parameter data is calculated by using the operation rule, and a rule calculation result is obtained;
the step of generating a test result corresponding to the target rule based on the rule calculation result includes:
judging whether the rule calculation result is the same as the parameter data;
if the rule calculation result is the same as the parameter output data, generating a first test result that the target rule passes the test;
and if the rule calculation result is different from the parameter data, generating a second test result that the target rule fails to pass the test.
6. The rule configuration method according to claim 1, wherein the step of invoking a preset classification tree model and a data table to verify the user's right based on the user information comprises:
if the authority verification is not passed, limiting the response to the rule configuration request;
generating corresponding alarm information based on the user information;
acquiring preset communication login information and acquiring a target communication address corresponding to a target user;
logging in to a corresponding communication server based on the communication login information;
and sending the alarm information to the target communication address through the communication server.
7. The method for configuring rules according to claim 1, wherein after the step of parsing the rule configuration file based on a preset rule engine to generate corresponding rule data, the method comprises:
acquiring an occupied memory value of the rule data, and acquiring a preset memory threshold value;
judging whether the occupied memory value is larger than the memory threshold value or not;
if the memory threshold value is larger than the memory threshold value, the rule data are stored in a block chain;
and if the rule data is not greater than the memory threshold, storing the rule data in a local preset database.
8. A rule configuration apparatus, comprising:
the receiving module is used for receiving a rule configuration request triggered by a user;
the analysis module is used for analyzing the user information from the rule configuration request;
the verification module is used for calling a preset classification tree model and a data table to carry out authority verification on the user based on the user information;
the first acquisition module is used for acquiring a rule configuration file from the rule configuration request based on a preset rule definition tool if the authority verification passes;
and the first generation module is used for analyzing the rule configuration file based on a preset rule engine to generate corresponding rule data.
9. A computer device comprising a memory and a processor, the memory having stored therein a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method 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 of any one of claims 1 to 7.
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