Low-code charging method and system based on declarative component

Abstract

The invention discloses a low-code charging method and system based on a declarative component, and relates to the technical field of data processing, and the method comprises the steps: building a multi-dimensional analysis feature; performing parameter import on the corresponding charging service component in the declarative component according to the analysis characteristics of the time domain, the charging gradient and the fee adjustment strategy, and establishing each function model; according to the multi-dimensional analysis features, processing logic analysis of the analysis features is carried out, processing logic conditions are constructed, and the processing logic conditions are utilized to configure a logic execution module; and adjusting and generating a charging page through a page rendering module according to the configuration parameters of each functional component and the logic execution module, and performing charging processing through a charging adjustment page. The technical problems of complex charging rule configuration and poor system flexibility in the prior art are solved, and the technical effects of simplifying the charging rule configuration and improving the charging adjustment flexibility are achieved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a low-code billing method and system based on declarative components. Background Art

[0002] Traditional billing systems require complex rule configuration and extensive code writing to set and adjust billing rules, making modification and optimization of billing rules cumbersome and time-consuming. Especially with constantly changing business needs, traditional billing systems lack flexibility and struggle to quickly adapt to new billing rules and scenarios. Furthermore, adjusting billing rules often requires lengthy development cycles, and these systems often lack sufficient scalability, failing to promptly reflect changes in the market and business environment. Summary of the Invention

[0003] This application provides a low-code billing method and system based on declarative components, which is used to solve the technical problems of complex billing rule configuration and poor system flexibility in the existing technology.

[0004] In view of the above problems, this application provides a low-code billing method and system based on declarative components.

[0005] In a first aspect, the present application provides a low-code billing method based on declarative components, the method comprising:

[0006] The billing rules are analyzed based on the time domain, billing gradient, and fee adjustment strategy to establish multi-dimensional analysis features. According to the analysis features of the time domain, billing gradient, and fee adjustment strategy, the parameters of the corresponding billing business components in the declarative components are imported to establish various functional models. According to the multi-dimensional analysis features, the processing logic of each analysis feature is analyzed, the processing logic conditions are constructed, and the logic execution module is configured using the processing logic conditions. According to the configuration parameters of each functional component and the logic execution module, the billing page is adjusted and generated through the page rendering module, and the billing processing is performed through the billing adjustment page.

[0007] A second aspect of the present application provides a low-code billing system based on declarative components, the system comprising:

[0008] The parsing module is used to parse the billing rules based on the time domain, billing gradient, and fee adjustment strategy, and establish multi-dimensional parsing features; the parameter import module is used to import parameters of the corresponding billing business components in the declarative components according to the parsing features of the time domain, billing gradient, and fee adjustment strategy, and establish various functional models; the processing logic parsing module is used to perform processing logic analysis of each parsing feature according to the multi-dimensional parsing features, construct processing logic conditions, and configure the logic execution module using the processing logic conditions; the billing processing module is used to adjust and generate the billing page through the page rendering module according to the configuration parameters of each functional component and the logic execution module, and perform billing processing through the billing adjustment page.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application analyzes the time domain, billing gradient, and fee adjustment strategy of the billing rules to establish multi-dimensional analysis features; according to the analysis features of the time domain, billing gradient, and fee adjustment strategy, the corresponding billing business components in the declarative component are parameterized and various functional models are established; according to the multi-dimensional analysis features, each analysis feature processing logic is analyzed, processing logic conditions are constructed, and the logic execution module is configured using the processing logic conditions; according to the configuration parameters of each functional component and the logic execution module, the billing page adjustment is generated through the page rendering module, and billing processing is performed through the billing adjustment page. The present invention solves the technical problems of the existing technology such as complex billing rule configuration and poor system flexibility, and achieves the technical effect of simplifying the billing rule configuration and improving the flexibility of billing adjustment through the multi-dimensional analysis of the time domain, billing gradient, and fee adjustment strategy and the low-code configuration method of the declarative component. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A flowchart of a low-code billing method based on declarative components provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of a low-code billing system based on declarative components is provided in an embodiment of the present application.

[0014] Description of the accompanying drawings: parsing module 11, parameter importing module 12, processing logic parsing module 13, billing processing module 14. DETAILED DESCRIPTION

[0015] This application provides a low-code billing method and system based on declarative components to solve the technical problems of complex billing rule configuration and poor system flexibility in the existing technology. Through multi-dimensional analysis of time domain, billing gradient and adjustment strategy and low-code configuration of declarative components, the technical effect of simplifying billing rule configuration and improving billing adjustment flexibility is achieved.

[0016] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0017] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0018] Example 1, as Figure 1 As shown, the present application provides a low-code billing method based on declarative components, the method comprising:

[0019] Step S100: Analyze the charging rules in terms of time domain, charging gradient, and charging adjustment strategy to establish multi-dimensional analysis features.

[0020] In an embodiment of the present application, the preset billing rules are first parsed in terms of time domain, billing gradient and fee adjustment strategy, so as to establish a multi-dimensional parsing feature. Specifically, the time domain in the billing rules is first parsed. The time domain refers to the time range in which the billing takes effect, including different date types and time period types. Classification is performed according to the date type in the billing rules, such as natural days, working days and non-working days, and time periods are further divided according to these date types, such as the time period on working days is 07:30 to 21:30, and the time period on non-working days is 10:00 to 21:30. This process determines which billing rules to use within different date and time ranges. Next, a time domain parsing feature is generated based on each date category and time period category.

[0021] Next, the billing gradient in the billing rules is parsed. The billing gradient is reflected in the charging ladder or segmented billing model. For example, in some scenarios, the parking fee increases based on the length of parking. According to the ladder or segmented model set in the billing rules, the different charging standards of the billing unit are parsed. For example, the portion of parking that exceeds 1 hour but does not exceed 3 hours is charged at a certain rate, while the portion that exceeds 3 hours is charged at a higher rate. By parsing these ladder or segmented rules, parsing features are generated for the billing gradient to ensure that the corresponding charging standards are correctly applied in different time periods and durations.

[0022] During the fee adjustment policy analysis process, the preferential policies set in the billing rules are analyzed. The fee adjustment policy involves rules that provide preferential treatment to specific vehicles or users, such as free parking time, discounts, and other special offers. The preferential conditions defined in the billing rules are analyzed, including which vehicles or users can enjoy the preferential treatment, the prerequisites for the preferential treatment (such as parking time exceeding a certain time limit), and the specific preferential treatment coefficients (such as discount rates or exemption amounts). The fee adjustment analysis features are generated by analyzing these fee adjustment policies.

[0023] Finally, the time domain analysis features, billing gradient analysis features and fee adjustment strategy analysis features are combined to construct a multi-dimensional analysis feature.

[0024] Furthermore, in the method provided in the embodiment of the application, parameters of corresponding functional components in the declarative component are imported according to the analytical characteristics of the time domain, billing gradient, and price adjustment strategy, and the method also includes:

[0025] Build a declarative component framework, including a billing business component library, a logic execution module, and a page rendering module; wherein, the billing business component library includes a time domain component, a billing component, and a fee adjustment component, and the logic execution module includes an execution logic device, and the execution logic device contains the billing business logic.

[0026] In an embodiment of the present application, a declarative component framework is built. The first step in building a declarative component framework is to build a billing business component library, which includes a time domain component, a billing component, and a fee adjustment component. The time domain component defines and manages the time range of billing by parsing the date type and time period type in the billing rules. The date type can be a natural day, a working day, a non-working day, etc., and the time period type includes peak time, non-peak time, etc. The billing component is responsible for calculating the fees according to specific billing standards. The billing standards include different methods such as time-based, per-time, and tiered billing. For example, in the tiered billing mode, different fee standards are set for different time periods according to the parking duration, ensuring that appropriate billing methods can be applied in various parking duration situations. The fee adjustment component is used to process preferential policies in the billing rules. This component adjusts the final fee by parsing preferential conditions (such as free parking time, discounts, etc.). In actual applications, the fee adjustment component dynamically adjusts the fee based on conditions such as parking duration and vehicle type. For example, according to the set preferential rules, parking fees within a specific period of time can be automatically reduced or exempted, or different discounts can be provided according to different types of vehicles (such as new energy vehicles).

[0027] Next, we build the logic execution module. The execution logic assembler within the logic execution module is the core component, responsible for executing specific billing business logic based on the component configurations in the billing business component library. The execution logic assembler receives parsed features extracted from the billing business component library, such as the time domain, billing gradient, and rate adjustment policy, and processes them according to the predefined business logic. By analyzing and processing the input rules, the execution logic assembler can gradually execute billing calculations according to the pre-set sequence and conditions. For example, it can automatically calculate fees based on the billing rules for a specific time period and adjust the final fee based on preferential policies.

[0028] All components in the architecture are built on the Spring Boot software framework and utilize RESTful API technology to facilitate business communication and data exchange between functional modules. This RESTful API enables efficient data transmission and information exchange between billing business components and logic execution modules, ensuring flexible expansion and maintenance.

[0029] The page rendering module enables user-friendly display and adjustment of billing rules. Users can dynamically generate billing pages using drag-and-drop operations, allowing them to quickly modify billing rules and display content. The page rendering module automatically updates page content based on the configuration and execution logic in the billing business component library, ensuring real-time display and adjustment of billing information and rules.

[0030] Furthermore, in the method provided in the embodiment of the application, establishing multi-dimensional analytical features also includes:

[0031] Perform date-based classification according to different billing types in the billing rules to obtain date categories; based on the date categories, classify the time ranges in each date category to obtain time period categories; use the date categories and time period categories as time domain analysis features and add them to the multi-dimensional analysis features.

[0032] In this embodiment of the present application, when processing billing rules, dates are first classified based on the different billing types defined in the billing rules to obtain date categories. Billing types include natural days, working days, and non-working days. By parsing the date types specified in the billing rules, dates are divided into multiple categories, such as working days and non-working days. In this way, corresponding billing standards are set for each date category based on the different date types.

[0033] Next, based on the obtained date categories, the time range within each date category is further classified to obtain time period categories. Time period categories refer to the specific time periods further divided within each date category. For example, within the weekday category, different time periods are divided, such as peak hours (e.g., 07:30 to 09:30) and off-peak hours (e.g., 09:30 to 17:30).

[0034] The date and time period categories are then combined to generate time-domain analytical features. These features are key elements in billing rules, reflecting their applicability under different date and time period categories. Finally, these features are incorporated into the multi-dimensional analytical features.

[0035] Furthermore, in the method provided in the embodiment of the application, establishing multi-dimensional analytical features also includes:

[0036] According to the charging calculation unit in the billing rule, the billing unit characteristics are classified to obtain the billing unit type, which includes time and number of times; based on the step-by-step or time-period billing rules of the billing unit type, the relationship between the billing unit and the unit fee and the gradient billing is established to obtain the charging calculation characteristics; the billing unit type and its charging calculation characteristics are added as billing analysis characteristics to the multi-dimensional analysis characteristics.

[0037] In this embodiment of the present application, the billing unit characteristics are first classified according to the charging calculation units defined in the billing rules to obtain the billing unit type. The charging calculation units include "time" and "number of times," which help determine the basic unit of fee calculation. "Time" in the billing unit type indicates that the fee is charged according to the time period, such as by the hour or by the minute; while "number of times" indicates that the fee is charged according to the number of parking times, such as charging by the time.

[0038] Then, based on the obtained billing unit type, i.e., time and number of times, the relationship between the billing unit and the unit fee and gradient billing is further analyzed and constructed. If the billing rule adopts tiered billing or time-of-day billing, establish corresponding billing standards and fee structures for each billing unit type. In tiered billing, the fee increases gradually as the billing unit increases. For example, the part of parking that exceeds 1 hour but does not exceed 3 hours is charged according to a certain fee standard, while the part that exceeds 3 hours is charged according to a higher standard. Time-of-day billing sets different fees for different time periods, such as the charging standard for peak hours is higher than that for non-peak hours. Through this process, the charging calculation characteristics are established according to the billing unit type.

[0039] The billing unit type is then combined with its corresponding charge calculation features to generate the billing parsing features. These are key features related to charge calculation within the billing rules, including the billing unit type (such as time or number of times) and its associated fee scale and gradient billing rules. Finally, the billing parsing features are added to the multi-dimensional parsing features as part of the billing rules.

[0040] Furthermore, in the method provided in the embodiment of the application, establishing multi-dimensional analytical features also includes:

[0041] Obtain the preferential policy in the billing rule; analyze the preferential target characteristics, preferential execution conditions, and exemption coefficients according to the preferential policy to obtain the fee adjustment analysis characteristics; and add the fee adjustment analysis characteristics to the multi-dimensional analysis characteristics.

[0042] In this embodiment of the present application, preferential policies within pre-set billing rules are first obtained. The preferential policies are then parsed by a rule parsing engine, extracting relevant preferential content from the billing rules. For example, some billing rules provide free parking for new energy vehicles or offer parking fee reductions during specific time periods. These preferential policies are extracted by parsing the text within the rules using regular expressions or structured configuration rules.

[0043] Next, based on the extracted discount policies, the discount target features, discount execution conditions, and discount coefficients are analyzed. Analysis of the discount target features first identifies specific types of users or vehicles eligible for the discount. For example, based on features such as vehicle type (e.g., new energy vehicles) and user identity (e.g., membership), the discount conditions are determined. The discount execution conditions define the circumstances under which the discount policy takes effect. For example, a discount only applies if parking exceeds a certain time period, or only during a specific time period. Parsing these execution conditions ensures that the discount is applied only when the specific requirements are met. Furthermore, the discount coefficient is analyzed. The discount coefficient refers to the fee reduction percentage or amount specified in the discount policy. For example, some rules may stipulate a 30% discount on parking fees, or free parking for periods not exceeding a certain time period. During parsing, these discount information is extracted from the rules to obtain the corresponding discount coefficient, which is then applied to the actual fee calculation. The above parsing steps ultimately generate the fee adjustment parsing features, which contain the specific implementation of the discount policy, including applicable user types, applicable conditions, and the specific discount percentage.

[0044] Finally, the fee adjustment analysis features are added to the multi-dimensional analysis features.

[0045] Step S200: Import parameters of corresponding billing service components in the declarative component according to the analytical features of the time domain, billing gradient, and price adjustment strategy, and establish various functional models.

[0046] In an embodiment of the present application, when processing billing rules, firstly, parameters of the billing service component in the declarative component are imported according to the analytical characteristics of the time domain, billing gradient and fee adjustment policy.

[0047] Specifically, the applicable time domain rules are first determined based on time domain parsing features by analyzing different date categories and time periods (such as weekdays, non-weekdays, peak hours, and off-peak hours). Time domain parsing features include classification results for date types and time period types, which determine which billing rules apply to which time periods and dates. Based on these time domain features, the corresponding parameters are imported into the time domain component to ensure that the correct billing logic is executed within specific dates and time periods. In this way, the time domain component can automatically select the appropriate billing mode based on different time domain features and adjust the fee calculation rules during the billing process.

[0048] Next, based on the billing gradient parsing feature, the parameters of the corresponding billing business components are imported. The billing gradient parsing feature involves tiered billing or segmented billing rules, which are segmented or tiered pricing based on billing units (such as parking duration). According to these gradient rules, the corresponding fee calculation parameters are imported into the billing component. For example, when the parking duration reaches a certain threshold, the fee standard is adjusted according to the set tiered billing rules. By mapping these gradient features to the billing component, parking fees can be flexibly calculated and ensured to change dynamically with the increase in duration.

[0049] Finally, based on the fee adjustment strategy analysis features, the relevant parameters are imported into the fee adjustment component. The fee adjustment strategy involves reducing or discounting fees under specific conditions, such as preferential policies, free parking time, etc. The fee adjustment analysis features include preferential target features (such as which vehicle types or user groups can enjoy the discount), preferential execution conditions (such as parking time reaching a certain threshold), reduction coefficients (such as discount ratio), etc. By analyzing these features, the relevant parameters are imported into the fee adjustment component to ensure that discounts or reductions can be correctly applied when specific conditions are met.

[0050] By importing time domain analysis features, billing gradient analysis features and fee adjustment strategy analysis features into corresponding business components, the billing model can be automatically adjusted according to these analysis features, thereby generating functional models suitable for specific business needs and completing the establishment of various functional models.

[0051] Step S300: performing logic analysis on each analysis feature processing according to the multi-dimensional analysis feature, constructing a processing logic condition, and configuring a logic execution module using the processing logic condition.

[0052] In an embodiment of the present application, the cross-relationships of the features of each dimension are first identified based on the multi-dimensional analytical features to reveal the interactions between the time domain, billing gradient and fee adjustment strategy. By identifying these cross-relationships, the mutual influence of different features in the actual billing scenario is clarified, and a clear causal chain is formed. Based on these cross-relationships, causal relationship analysis is performed in the logical order of the time domain, billing gradient and fee adjustment strategy to ensure that the execution order of each billing rule is correct. For example, first determine whether it has entered the peak period based on the time domain, then analyze whether the parking time exceeds a certain period based on the billing gradient, and finally apply the fee adjustment strategy to calculate exemptions or discounts. Next, identify the time reset nodes in the billing processing logic. The time reset node refers to a specific time point in the billing process. At these nodes, the relevant billing data or rules are reset, such as resetting the billing cycle every 24 hours, or recalculating the fee after parking. After identifying the cross-relationships and time reset nodes, specific processing logic conditions are constructed based on this information.

[0053] Finally, use the processing logic conditions to configure the logic execution module. The logic execution module is the core of the billing process and executes specific billing operations based on the configured processing logic conditions. By configuring conditions such as time domain, billing gradient, rate adjustment policy, and time reset node in the logic execution module, the corresponding billing logic is automatically adjusted and executed according to different billing scenarios.

[0054] Furthermore, in the method provided in the embodiment of the application, performing a processing logic analysis of each analytical feature according to the multi-dimensional analytical feature and constructing a processing logic condition also includes:

[0055] According to the multi-dimensional analytical features, the cross-relationships of the features of each dimension are identified to obtain the cross-relationships; based on the cross-relationships, a causal relationship analysis is performed in the logical order of time domain-billing gradient-fee adjustment strategy to obtain each billing processing logic; the time reset node in the billing processing logic is identified; and according to the each billing processing logic and the time reset node, the processing logic conditions are constructed.

[0056] In an embodiment of the present application, the multi-dimensional parsing features include time domain parsing features, billing gradient parsing features, and fee adjustment strategy parsing features. Cross-relationship identification is performed based on these parsing features. Specifically, the time domain parsing features (such as working days, non-working days, peak hours, and non-peak hours) are first classified and combined with the billing gradient parsing features (such as step billing, pay-per-use, and time-based billing). This process checks how each billing feature interacts in different time domains, for example, different step charging rules or segmented charging rules are used during peak hours. By comparing the time periods and billing types in the billing rules one by one, the cross-influences between different billing methods are analyzed, and finally the cross-relationships are identified.

[0057] Next, based on the identified cross-relationships, a causal analysis is performed in the logical order of time domain-billing gradient-fee adjustment strategy. During this process, the time domain analysis characteristics are used to determine whether it belongs to the peak period or the off-peak period. Then, the billing gradient analysis characteristics are used to determine whether to use tiered billing, pay-per-use billing, or other methods. Finally, the fee adjustment strategy analysis characteristics are used to determine whether discounts or other preferential treatments should be applied. Through causal analysis, the logic of each billing process is obtained, that is, it is clear how different billing rules should be applied under specific conditions. For example, if the current period is the peak period on a weekday, the peak period billing rules are applied first, followed by the corresponding tiered billing mode. If the conditions are met, the discount policy is applied. Causal analysis ensures the correct execution order of each billing rule and enables the billing process logic to be adjusted according to business needs.

[0058] After causal analysis is complete, identify time reset nodes in the billing processing logic. Time reset nodes are defined as specific times at which fees need to be recalculated or adjusted. For example, the billing cycle might need to be reset every 24 hours, or fees might need to be recalculated at the end of a parking session. By periodically checking time data, these reset nodes can be identified, ensuring that the billing logic can make appropriate adjustments or recalculations when the reset point is reached.

[0059] Finally, based on the causal analysis and the identification of the time reset node, the processing logic conditions are constructed. The processing logic conditions define how to apply the billing rules, how to adjust the fees, and when to reset the billing rules in different billing scenarios. These conditions are set through the rule engine or conditional logic. For example, tiered billing is only enabled when the parking duration exceeds a certain threshold; or discounts are applied during a specific period (such as nighttime or holidays). When the time reset node is triggered, the billing conditions are re-evaluated and the fees are recalculated according to the new billing rules. These processing logic conditions ensure that the billing process can be flexibly adjusted and accurately executed in different scenarios.

[0060] Step S400: Based on the configuration parameters of each functional component and the logic execution module, a billing page is adjusted and generated through the page rendering module, and billing processing is performed through the billing adjustment page.

[0061] In an embodiment of the present application, first, a billing page is generated by a page rendering module based on the configuration parameters of each functional component and the logic execution module. At this time, the page rendering module dynamically generates a billing page based on the set parameters in each functional component (such as the time domain component, the billing component, the fee adjustment component) and the logic execution module. These pages display the current billing rules, standards, and policies, so that the specific parameters of the billing (such as time period, billing method, preferential policy, etc.) can be clearly presented, ensuring that each billing step and rule can be clearly displayed.

[0062] The relationship between the parameters on the billing page and the functional component configuration parameters is then parsed and identified. Billing page parameters include time domain characteristics (e.g., peak hours, off-peak hours), billing gradient characteristics (e.g., tiered billing, hourly billing), and fee adjustment policy characteristics (e.g., discounts, free time). By entering these parameters into the billing adjustment page, a search is performed on the time domain, billing gradient, fee adjustment policy, and processing logic conditions. These rules are then matched and calculated, and the final cost calculation result is derived based on the rules.

[0063] Through this process, the billing adjustment page performs corresponding fee calculations based on the input parameters and ultimately outputs the billing results.

[0064] Furthermore, in the method provided in the embodiment of the application, the billing process is performed through the billing adjustment page, further comprising:

[0065] According to the billing adjustment page, the billing page parameters are obtained, and the billing page parameters correspond to the configuration parameters of each functional component and the logic execution module; parameter identification is performed according to the billing page parameters, and the identified page parameters are input into the billing adjustment page to search the time domain, billing gradient, adjustment strategy and processing logic conditions, and the fee is calculated according to the search rules, and the billing results are output.

[0066] In an embodiment of the present application, the billing page parameters are first obtained from the billing adjustment page. These parameters include various settings related to billing rules, such as time domain characteristics (such as working days, non-working days, peak hours, non-peak hours, etc.), billing gradient characteristics (such as step billing, hourly billing, pay-per-use billing, etc.), and fee adjustment strategy characteristics (such as discounts, free time, etc.). These parameters are extracted from the system configuration through the page rendering module and correspond one-to-one to the configuration parameters of each functional component (time domain component, billing component, fee adjustment component, etc.) and the logic execution module.

[0067] Next, parameter identification is performed based on these billing page parameters. This identification process refers to parsing the extracted page parameters to determine the billing rule characteristics corresponding to each parameter. Through identification, the role of each parameter in billing is clarified and mapped to the corresponding functional components and logic execution modules. For example, the identification of time domain characteristics may mean applying different billing rules according to different time periods (such as peak hours and non-peak hours), the identification of billing gradient characteristics determines whether to calculate the fees according to tiered billing or time-based billing, and the identification of fee adjustment strategy characteristics may trigger preferential policies such as discounts or exemptions.

[0068] Once parameter identification is complete, these identified parameters are entered into the billing adjustment page, and a search is performed for time domain, billing gradient, adjustment strategy, and processing logic conditions. This process involves finding the logical conditions and rules related to the billing rules, and determining the final fee calculation method based on these conditions. For example, based on the time domain characteristics, determine whether it is a peak period. If it is a peak period, a higher rate will be used for tiered billing; if it is a low-peak period, the standard fee will be used or a discount will be applied. Based on the search for processing logic conditions, the fee calculation is performed according to the set rules, and the final billing result is determined.

[0069] Finally, the fee calculation is performed according to the search rules and the final billing result is output.

[0070] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0071] This application analyzes the time domain, billing gradient, and fee adjustment strategy of the billing rules to establish multi-dimensional analysis features; according to the analysis features of the time domain, billing gradient, and fee adjustment strategy, the corresponding billing business components in the declarative component are parameterized and various functional models are established; according to the multi-dimensional analysis features, each analysis feature processing logic is analyzed, processing logic conditions are constructed, and the logic execution module is configured using the processing logic conditions; according to the configuration parameters of each functional component and the logic execution module, the billing page adjustment is generated through the page rendering module, and billing processing is performed through the billing adjustment page. The present invention solves the technical problems of the existing technology such as complex billing rule configuration and poor system flexibility, and achieves the technical effect of simplifying the billing rule configuration and improving the flexibility of billing adjustment through the multi-dimensional analysis of the time domain, billing gradient, and fee adjustment strategy and the low-code configuration method of the declarative component.

[0072] Example 2 is based on the same inventive concept as the low-code billing method based on declarative components in the previous embodiment. Figure 2 As shown, this application provides a low-code billing system based on declarative components. The system and method embodiments in the embodiments of this application are based on the same inventive concept. The system includes:

[0073] The parsing module 11 is used to parse the billing rules based on the time domain, billing gradient, and fee adjustment strategy, and establish multi-dimensional parsing features; the parameter import module 12 is used to import parameters of the corresponding billing business components in the declarative components according to the parsing features of the time domain, billing gradient, and fee adjustment strategy, and establish various functional models; the processing logic parsing module 13 is used to perform processing logic analysis of each parsing feature according to the multi-dimensional parsing features, construct processing logic conditions, and configure the logic execution module using the processing logic conditions; the billing processing module 14 is used to adjust and generate the billing page through the page rendering module according to the configuration parameters of each functional component and the logic execution module, and perform billing processing through the billing adjustment page.

[0074] Furthermore, the system is also used to implement the following functions:

[0075] Build a declarative component framework, including a billing business component library, a logic execution module, and a page rendering module; wherein, the billing business component library includes a time domain component, a billing component, and a fee adjustment component, and the logic execution module includes an execution logic device, and the execution logic device contains the billing business logic.

[0076] Furthermore, the system is also used to implement the following functions:

[0077] Perform date-based classification according to different billing types in the billing rules to obtain date categories; based on the date categories, classify the time ranges in each date category to obtain time period categories; use the date categories and time period categories as time domain analysis features and add them to the multi-dimensional analysis features.

[0078] Furthermore, the system is also used to implement the following functions:

[0079] According to the charging calculation unit in the billing rule, the billing unit characteristics are classified to obtain the billing unit type, which includes time and number of times; based on the step-by-step or time-period billing rules of the billing unit type, the relationship between the billing unit and the unit fee and the gradient billing is established to obtain the charging calculation characteristics; the billing unit type and its charging calculation characteristics are added as billing analysis characteristics to the multi-dimensional analysis characteristics.

[0080] Furthermore, the system is also used to implement the following functions:

[0081] Obtain the preferential policy in the billing rule; analyze the preferential target characteristics, preferential execution conditions, and exemption coefficients according to the preferential policy to obtain the fee adjustment analysis characteristics; and add the fee adjustment analysis characteristics to the multi-dimensional analysis characteristics.

[0082] Furthermore, the system is also used to implement the following functions:

[0083] According to the multi-dimensional analytical features, the cross-relationships of the features of each dimension are identified to obtain the cross-relationships; based on the cross-relationships, a causal relationship analysis is performed in the logical order of time domain-billing gradient-fee adjustment strategy to obtain each billing processing logic; the time reset node in the billing processing logic is identified; and according to the each billing processing logic and the time reset node, the processing logic conditions are constructed.

[0084] Furthermore, the system is also used to implement the following functions:

[0085] According to the billing adjustment page, the billing page parameters are obtained, and the billing page parameters correspond to the configuration parameters of each functional component and the logic execution module; parameter identification is performed according to the billing page parameters, and the identified page parameters are input into the billing adjustment page to search the time domain, billing gradient, adjustment strategy and processing logic conditions, and the fee is calculated according to the search rules, and the billing results are output.

[0086] To better explain the technical content of this application, an example of low-code billing using declarative components is shown in Table 1:

[0087] Table 1: Charging rules for temporary parking spaces on a certain road in Guangzhou

[0088]

[0089] During the charging period of each billing cycle, new energy vehicles charging at a dedicated charging space for the first time can enjoy free parking for up to one hour (inclusive). However, if the aforementioned vehicle parks for more than one hour, it must pay the urban road temporary parking space usage fee for the entire parking time in accordance with this charging standard.

[0090] 1. Drag the Time Domain component - Date Classification to the Rules page to define working and non-working days. The Date Classification allows you to select a date type and write general specifications and exceptions for the date type's name and scope of use.

[0091] 2. Drag the Time Domain component - Time Period Classification to the Rules page to divide paid and free time periods. Time Period Classification is subordinate to Date Classification. Writing standards: All (multiple) time periods under a date classification cannot overlap, and the cumulative total of all time periods must equal 24 hours.

[0092] 3. Drag and drop the billing component - periodic billing to implement tiered billing. Based on demand, the bill remains unchanged for a certain period of time. After a certain period of time has accumulated, the fee will be increased in fixed time units. This component is placed within the charging period.

[0093] 4. Drag and drop the billing component - Maximum Limit to achieve the maximum daily charge. This means that after the parking fee reaches the limit, the maximum limit will be charged and no parking fees will be accumulated. Place it within the charging period as needed to achieve the maximum limit within the billing period.

[0094] 5. Drag and drop the fee adjustment component - Free Parking Time. This allows you to park for free for up to a specified time. Set the parking duration to avoid paying parking fees within the specified time. Also, configure its execution logic, i.e., write preconditions, to implement different free policies for different vehicles.

[0095] 6. The logic execution module configures a reset point to ensure that only one free parking time is enjoyed for the first time within a billing cycle. For example, "During the charging period of each billing cycle, new energy vehicles can enjoy free parking for no more than one hour (inclusive) when charging at a dedicated charging parking space for the first time."

[0096] 7 Based on the drag and drop of components 1-6 and the logical configuration, the billing terminal page is rendered.

[0097] The business system can request billing through the billing engine billing API interface. The request method is POST, and the parameters are shown in Table 2 below:

[0098] Table 2

[0099]

[0100] Through the low-code billing method and system based on declarative components provided in this application, there is no need to develop new software for the adjustment of billing rules. Declarative components are used to execute different logic according to different business logic to achieve differentiated deployment of billing results. This can not only significantly improve billing efficiency and reduce operating costs, but also support business innovation and expansion, which is of great significance for reducing R&D costs and improving the operating efficiency of parking lots.

[0101] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0103] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A low-code billing method based on declarative components, characterized in that: include: Analyze billing rules by time domain, billing gradient, and adjustment strategy, and establish multi-dimensional analytical features; Based on the analytical characteristics of the time domain, billing gradient, and fee adjustment strategy, parameters of the corresponding billing business components in the declarative components are imported to establish various functional models; Performing logic analysis on each analytical feature processing according to the multi-dimensional analytical features, constructing processing logic conditions, and configuring a logic execution module using the processing logic conditions; According to the configuration parameters of each functional component and the logic execution module, the billing page is adjusted and generated through the page rendering module, and the billing processing is performed through the billing adjustment page.

2. The low-code billing method based on declarative components according to claim 1 is characterized in that Import parameters for the corresponding functional components in the declarative components based on the parsing characteristics of the time domain, billing gradient, and price adjustment policy. This previously included: Build a declarative component framework, including a billing business component library, a logic execution module, and a page rendering module; The billing service component library includes a time domain component, a billing component, and a fee adjustment component. The logic execution module includes an execution logic device, and the execution logic device includes billing service logic.

3. The low-code billing method based on declarative components according to claim 2 is characterized in that Establish multi-dimensional analytical features, including: Classify dates based on different billing types in the billing rules to obtain date categories; Based on the date categories, classify the time ranges in each date category to obtain time period categories; The date category and the time period category are used as time domain analysis features and added to the multi-dimensional analysis features.

4. The low-code billing method based on declarative components according to claim 3 is characterized in that Establishing multi-dimensional analytical features also includes: Classify the charging unit characteristics according to the charging calculation unit in the charging rule to obtain the charging unit type, wherein the charging unit type includes time and number of times; Based on the tiered or time-based billing rules of the billing unit type, establish the relationship between the billing unit and the unit fee, and the gradient billing, and obtain the charge calculation characteristics; The billing unit type and the charge calculation feature thereof are added as billing analysis features to the multi-dimensional analysis features.

5. The low-code billing method based on declarative components according to claim 4 is characterized in that Establishing multi-dimensional analytical features also includes: Obtain the preferential policy in the billing rules; Analyze the preferential target characteristics, preferential execution conditions, and reduction / exemption coefficients according to the preferential policy to obtain fee adjustment analysis characteristics; The fee adjustment analysis feature is added to the multi-dimensional analysis feature.

6. The low-code billing method based on declarative components according to claim 1 is characterized in that Performing logic analysis on each analytical feature processing according to the multi-dimensional analytical features and constructing processing logic conditions includes: Identify the cross-relationship between features in each dimension based on the multi-dimensional analytical features to obtain the cross-relationship; Based on the cross-relationship, a causal relationship analysis is performed in the logical order of time domain-billing gradient-price adjustment strategy to obtain the billing processing logic; Identify time reset nodes in billing processing logic; The processing logic conditions are constructed according to the various billing processing logics and time reset nodes.

7. The low-code billing method based on declarative components according to claim 6 is characterized in that Use the Billing Adjustment page to process billing, including: Obtaining billing page parameters according to the billing adjustment page, wherein the billing page parameters correspond to configuration parameters of each functional component and the logic execution module; Parameter identification is performed based on the billing page parameters, and the identified page parameters are input into the billing adjustment page to search for time domain, billing gradient, adjustment strategy and processing logic conditions, and the fee is calculated according to the search rules to output the billing results.

8. A low-code billing system based on declarative components, characterized by: The system comprises: The parsing module is used to analyze billing rules by time domain, billing gradient, and fee adjustment strategy, and establish multi-dimensional parsing features; The parameter import module is used to import parameters of the corresponding billing business components in the declarative components based on the analytical characteristics of the time domain, billing gradient, and fee adjustment policy, and establish various functional models; A processing logic analysis module, configured to perform processing logic analysis of each analysis feature according to the multi-dimensional analysis feature, construct processing logic conditions, and configure a logic execution module using the processing logic conditions; The billing processing module is used to adjust and generate the billing page through the page rendering module according to the configuration parameters of each functional component and the logic execution module, and perform billing processing through the billing adjustment page.

Images