Processing method, device, electronic device and storage medium

Abstract

The present application relates to a processing method, device, electronic device and storage medium. The processing method provided by the present application can determine the target interaction form with the bound API under the target application for an unpublished application on a low compilation platform, that is, a target application in the construction stage, and then obtain the business indicators of the first API bound to the target interaction form, and determine the response performance of the target interaction form under the first API based at least on the business indicators of the first API. Therefore, the present invention can support the rapid evaluation of the response performance of the form solution selected by the user during the application construction stage, so that the user can flexibly adjust and optimize the form solution.

Description

Technical Field

[0001] The present application relates to the field of software technology, and more specifically, to a processing method, device, electronic device and storage medium. Background Art

[0002] At present, users can quickly build interactive form applications on low-compilation platforms and bind remote service APIs (Application Program Interface) to achieve dynamic data interaction capabilities of interactive form applications. In this process, when users build dynamic data form applications, there are multiple form components and API solutions to choose from, but different construction solutions will produce different performance differences, thus affecting the user experience.

[0003] In this regard, how to enable users who build interactive forms to quickly obtain API solutions that meet their requirements has become an urgent problem that needs to be solved at this stage. Summary of the invention

[0004] In view of this, the present application provides a processing method, device, electronic device and storage medium, and the technical solution is as follows:

[0005] On the one hand, the present application provides a processing method, the method comprising:

[0006] Determine a target interaction form bound to an application program interface API under a target application, wherein the target application is an unpublished application of a low-compilation platform;

[0007] A business indicator of a first API to which the target interactive form is bound is obtained, and a response performance of the target interactive form under the first API is determined based at least on the business indicator of the first API.

[0008] Preferably, obtaining the business indicator of the first API bound to the target interactive form includes:

[0009] Calling an API business indicator library, wherein the business indicator of each API in the business indicator library is determined by clustering and statistically analyzing the call logs of each API by the published applications of the low-compilation platform;

[0010] Determine the business indicator of the first API in the API business indicator library.

[0011] Preferably, the business indicator at least includes request return time, and determining the response performance of the target interactive form under the first API at least based on the business indicator of the first API includes:

[0012] Obtaining a calling status of the target interactive form to the first API;

[0013] If the calling state is a continuous calling, the accumulated sum of the request return durations of the first API is used as the form response duration of the target interactive form under the first API;

[0014] If the calling state is a discontinuous calling, a calculation is performed on the request return duration of the first API, and the corresponding calculation result is used as the form response duration of the target interactive form under the first API.

[0015] Preferably, the method further comprises:

[0016] Determining a second API having similarity to the first API;

[0017] Obtaining a business indicator of the second API, and determining a response performance of the target interactive form under the second API at least based on the business indicator of the second API;

[0018] By comparing the response performance of the target interactive form under the first API and the second API, a target API with the best response performance is selected from the first API and the second API.

[0019] Preferably, the determining of the second API having similarity to the first API comprises:

[0020] Calling an API similarity library, wherein the similarity between two APIs in the API similarity library is determined by analyzing request and return data in a call log of the two APIs by a published application of the low-compilation platform;

[0021] An API whose similarity with the first API meets a corresponding threshold is determined in the API similarity library as the second API.

[0022] Preferably, the method further comprises:

[0023] When the target API is the first API, output corresponding prompt information based on the first API; or

[0024] When the target API is the second API, corresponding recommendation information is output based on the second API.

[0025] Another aspect of the present application provides a processing device, the device comprising:

[0026] A form determination module, used to determine a target interactive form bound to an application program interface API under a target application, wherein the target application is an unpublished application of a low-compilation platform;

[0027] The performance determination module is used to obtain the business indicator of the first API bound to the target interactive form, and determine the response performance of the target interactive form under the first API at least based on the business indicator of the first API.

[0028] Preferably, the performance determination module obtains the business indicator of the first API bound to the target interaction form, including:

[0029] Calling an API business indicator library, wherein the business indicator of each API in the business indicator library is determined by clustering and statistically analyzing the call logs of each API by the published applications of the low-compilation platform; determining the business indicator of the first API in the API business indicator library.

[0030] Another aspect of the present application provides an electronic device, the electronic device comprising:

[0031] A memory, used to store applications and data generated by the operation of the applications;

[0032] A processor is used to execute the application to achieve the following functions: determining a target interaction form bound to an application program interface API under a target application, wherein the target application is an unpublished application of a low-compilation platform; obtaining business indicators of a first API to which the target interaction form is bound, and determining the response performance of the target interaction form under the first API at least based on the business indicators of the first API.

[0033] On the other hand, the present application provides a storage medium, wherein the storage medium stores computer program code, and when the computer program code is executed, any one of the processing methods described above is implemented.

[0034] Through the above technical solutions, it can be known that the processing method provided by the present application can determine the target interactive form bound to the API under the target application for the unpublished application of the low compilation platform, that is, the target application in the construction stage, and then obtain the business indicators of the first API bound to the target interactive form, and determine the response performance of the target interactive form under the first API at least based on the business indicators of the first API. Therefore, the present invention can support the rapid evaluation of the response performance of the form solution selected by the user during the application construction stage, so that the user can flexibly adjust and optimize the form solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0036] Figure 1 A hardware structure block diagram of an electronic device provided in an embodiment of the present application;

[0037] Figure 2 A method flow chart of the processing method provided in the embodiment of the present application;

[0038] Figure 3 A method flow chart of another processing method provided in an embodiment of the present application;

[0039] Figure 4 A method flow chart of another processing method provided in an embodiment of the present application;

[0040] Figure 5 A method flow chart of another processing method provided in an embodiment of the present application;

[0041] Figure 6 A method flow chart of another processing method provided in an embodiment of the present application;

[0042] Figure 7 A schematic diagram of a processing scenario provided in an embodiment of the present application;

[0043] Figure 8 A schematic diagram of the structure of a processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0046] To facilitate understanding of this application, the following first describes the background of building an interactive form application on a low-compilation platform and binding the remote service API:

[0047] The application development stage usually involves front-end development and back-end development. In the process of front-end development, the art design involves the application product prototype, such as the picture of the interactive form in the front-end page. The developer converts the picture of the interactive form into a certain format by writing code, such as a web page in HTML format that can be recognized by the browser. In this process, the web page developed by the front-end does not have the ability to interact with dynamic data, so back-end development is required. In the back-end development process, the developer develops the back-end program by writing code. The back-end program is used to perform business logic operations, such as adding, deleting, modifying and checking data in a specific database.

[0048] In order to achieve the connection between the front-end and the back-end, the back-end developers need to expose the back-end program as an API, and then the front-end developers bind the interactive form in the form of a web page to the API. As a result, the entire development process of the application is cumbersome, inefficient, and costly. It should be noted that the interactive form bound to the API is a dynamic data form, and the interactive data in the dynamic data form comes from the API. The interactive form in the embodiment of the present invention is a dynamic data form.

[0049] To solve this problem and simplify application development, the low-compilation platform can develop and encapsulate a large number of form components, which can be reused to achieve application development by dragging form components. Form components can include basic components such as input boxes, drop-down boxes, long text edit boxes, and complex components composed of multiple basic components. Taking the front-end design of interactive forms as an example, there is no need to convert through design drawings and development programs. Front-end developers can complete the design of interactive forms by dragging form components related to the interactive form with a certain logical relationship or a certain design layout. This can reduce the development time of interactive forms from the usual one week to just a few hours.

[0050] When front-end developers build dynamic data form applications on low-compilation platforms, they can choose from a variety of API solutions for interactive form components, but different construction solutions will produce different performance differences. The existing solutions can be summarized as follows:

[0051] 1) Preliminary evaluation of the form interaction performance is performed through application build preview. This method of performance evaluation has large errors. The remote service API used in the preview is generally based on artificial simulation data, which is difficult to reflect the actual interaction performance.

[0052] 2) After the dynamic data form application is released, the application performance is optimized during use. This method has poor flexibility and the cost of optimizing application performance during runtime is high. For example, if the application needs to be restarted, the impact on the existing business needs to be considered.

[0053] In order to solve the drawbacks of the above existing solutions, this application provides a processing method. Since the performance of the dynamic data form is mainly determined by the response performance of the remote service API, the response performance of the dynamic data form can be estimated by obtaining the API business indicators (i.e., performance indicators) bound to the dynamic data form, so that the performance of the API solution selected by the user can be evaluated during the user's interactive form construction.

[0054] The processing method provided in this application can be applied to electronic devices, see Figure 1 The hardware structure block diagram of the electronic device shown in the figure may include: a processor 11, a communication interface 12, a memory 13 and a communication bus 14;

[0055] In the embodiment of the present application, the number of the processor 11 , the communication interface 12 , the memory 13 , and the communication bus 14 is at least one, and the processor 11 , the communication interface 12 , and the memory 13 communicate with each other through the communication bus 14 .

[0056] The processor 11 may be a central processing unit (CPU), a graphics processing unit (GPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0057] The memory 13 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), etc., for example, at least one disk memory.

[0058] The memory 13 stores the application and the data generated by the application, and the processor 11 executes the application to realize the following functions:

[0059] Determine a target interaction form bound to an application program interface API under a target application, where the target application is an unpublished application on a low compilation platform; obtain business indicators of a first API to which the target interaction form is bound, and determine the response performance of the target interaction form under the first API at least based on the business indicators of the first API.

[0060] It should be noted that the refinement and expansion of the functions implemented by the processor executing the application program can be found in the description below.

[0061] This application embodiment provides a processing method, see Figure 2 The method flow chart shown in the figure comprises the following steps:

[0062] S101, determining a target interaction form bound to an application program interface API under a target application, where the target application is an unpublished application of a low-compilation platform.

[0063] In the embodiment of the present application, the front-end developer can build an interactive form application through the low-compilation platform, generate an interactive form under the application by dragging the form component, and bind the API to the interactive form to obtain dynamic data interaction capabilities. Therefore, for an application that is in the construction stage but not released on the low-compilation platform (i.e., the target application), the present application can analyze the interactive form (i.e., the target interactive form) selected by the user under the target application and bound to the API.

[0064] When front-end developers build interactive form applications on a low-compilation platform, when they generate an interactive form under the application by dragging a form component, they can bind a suitable API to the form component according to the business function implemented by the form component. A form component can be bound to one or more APIs.

[0065] For ease of understanding, let's take an example to illustrate that a front-end developer builds an interactive form application A on a low-compilation platform, and generates at least one interactive form under the application A by dragging form components, such as two interactive forms A_1 and A_2. Assuming that interactive form A_1 is an interactive form bound to an API selected by the front-end developer, after determining that the front-end developer has completed the operation of binding an API to a form component of interactive form A_1, the API bound to the form component can be analyzed.

[0066] S102: Obtain a business indicator of a first API to which the target interactive form is bound, and determine a response performance of the target interactive form under the first API at least based on the business indicator of the first API.

[0067] In an embodiment of the present application, for a target interactive form, a business analysis can be performed on the API to which it is bound (i.e., the first API) to obtain the business indicators of the first API, which can be determined by analyzing the business performance of the first API in a published interactive form application on a low-compilation platform, and can be specifically achieved by designing an automatic collection task to monitor and analyze the call status of the first API in the operating environment. The business indicators of the first API can include business indicators under the time dimension, such as request duration, to reflect the reaction speed of the response performance, and can include business indicators under the content dimension, such as the accuracy (or failure rate) of the request return data, to reflect the stability of the response performance.

[0068] Furthermore, since the dynamic data interaction performance of the interactive form mainly depends on the business performance of the bound API, the response performance of the interactive form under the first API can be estimated according to the API business indicators.

[0069] For ease of understanding, the following describes the dynamic data interaction process of the API in the published application:

[0070] Through the interactive form application publishing, installation and deployment of the application, the application can be started in the formal environment, and the user can use the application. In the process of using the published application, the user can enter information for the data item corresponding to a form component in the front-end interactive form, and then trigger the interactive form to call the API bound to the form component, send a corresponding set of parameters to the API, and the background program corresponding to the API will perform business logic operations, and the API will return the operation results to the front-end, which will display them in the defined form. In this way, the dynamic data interaction of the API in a published application is completed.

[0071] In actual business, an API can be bound to one or more interactive forms of published applications. For example, API1 can be bound to the interactive forms of published form application B and form application C at the same time. In addition, API1 can also be bound to multiple interactive forms under application B or application C at the same time.

[0072] For ease of understanding, the target application is application A and the target interactive form is interactive form A_1. After the front-end developer has finished binding API1 to a form component of interactive form A_1, the business performance of API1 in the published application can be analyzed to obtain the business indicators of API1.

[0073] Assuming that API1 is bound to both the interactive form B_1 and the interactive form B_2 of application B, and the interactive form C_1 of application C, the business indicators of API1 can be determined by analyzing the business performance of API1 in application B and application C. By designing automatic collection tasks to automatically monitor and analyze the call status of API1 by application B and application C in the running environment, the business indicators of API1 are calculated using cluster statistical analysis.

[0074] Continue to assume that the business indicator includes request duration, API1 is called m times by application B, and the m request return durations are a1, a2, ..., am respectively, and API1 is called n times by application C, and the n request return durations are b1, b2, ..., bn respectively. Then, the request duration of API1 can be determined by clustering analysis and statistics of m+n request return durations (including a1~am, and b1~bn), specifically, the shortest return duration, the longest return duration, the average return duration, the 95% request return duration, etc. among a1~am and b1~bn, and the embodiments of the present application do not limit this. It should be noted that the 95% request return duration is a normal distribution sorting of m+n request return durations in order from small to large request return durations, starting from the smallest request return duration. The average duration of 95% of m+n. The larger the request duration of the API, the slower the response speed of the response performance of API1.

[0075] When estimating the response performance of interactive form A_1 under API1 based on the request duration of API1, the request duration of API1 can be evaluated. The longer the request duration of API1 is, the worse its response performance is. Specifically, multiple response levels can be set, and each response level corresponds to a request duration range. Thus, the response level of API1 can be determined based on the request duration range in which the request duration of API1 is located. Of course, the longer the request duration of API1 is, the lower its response level is, and the worse the corresponding response performance is.

[0076] Assuming that the business indicator includes the accuracy of the request return data, since the API request return data generally includes a status code, which is used to indicate the success (for example, the status code is 1) / failure (for example, the status code is 0) of the remote service API, the success / failure of this call can be determined by parsing the status code in the request return data. API1 is called m times by application B, and among the m request return data, there are c times with a status code of 0 and d times with a status code of 1 (c+d=m), and API1 is called n times by application C, and among the n request return data, there are e times with a status code of 0 and f times with a status code of 1 (e+f=n). Then, the accuracy of the request return data of API1 can be d+f / m+n. The higher the accuracy, the more stable the response performance of API1. Of course, if the business indicator includes the failure rate of the request return data, then the failure rate of the request return data of API1 is c+e / m+n. The higher the failure rate, the more unstable the response performance of API1.

[0077] When estimating the response performance of interactive form A_1 under API1 based on the accuracy of the request return data of API1, the accuracy of the request return data of API1 can be evaluated. The greater the accuracy of the request return data of API1, the better its response performance. Specifically, multiple response levels can be set, and each response level corresponds to an accuracy range. Thus, the response level can be determined according to the accuracy range of the accuracy of the request return data of API1. Of course, the greater the accuracy of the request return data of API1, the higher its response level and the better the corresponding response performance.

[0078] It should be noted that if the business indicators include both request duration and the accuracy of request return data, the response level of API1's request duration (hereinafter referred to as the first response level) and the response level of API1's request return data accuracy (hereinafter referred to as the second response level) can be determined according to the above scheme. The priority of both request duration and request return data accuracy can be determined considering the specific business scenario, so as to make corresponding processing for the first response level and the second response level, such as weighted average, to determine the final response level. The higher the final response level, the better the response performance of the interactive form A_1 under API1.

[0079] Based on this, the response performance of the interactive form A_1 under API1 can be output, so that the front-end developers can quickly obtain the response performance of the interactive form A_1 under API1, and then make a reference for them to choose whether to continue to bind API1 or choose to bind other APIs.

[0080] The processing method provided in the embodiment of the present application can determine the target interactive form bound to the API under the target application for the low-compilation platform in the construction stage, and then obtain the business indicators of the first API bound to the target interactive form, and determine the response performance of the target interactive form under the first API at least based on the business indicators of the first API. Therefore, the present invention can support the rapid evaluation of the response performance of the form solution selected by the user during the application construction stage, so that the user can flexibly adjust and optimize the form solution.

[0081] As an implementation method for obtaining the business indicator of the first API bound to the target interactive form, the present application embodiment provides another processing method, see Figure 3 The method flow chart shown in the figure comprises the following steps:

[0082] S201, determining a target interaction form bound to an application program interface API under a target application, where the target application is an unpublished application of a low-compilation platform.

[0083] S202, calling an API business indicator library, where the business indicator of each API in the business indicator library is determined by clustering and statistically analyzing the call logs of each API by the published applications of the low-compilation platform.

[0084] In an embodiment of the present application, an automatic collection task can be designed to monitor and analyze the call status of each API in the operating environment, so as to build an API business indicator library, which contains business indicators of different APIs.

[0085] For the published interactive form application on the low compilation platform, the application can monitor the call status of each API bound to its interactive form in its operating environment, write the call status to the call log, and report the call log in real time. In the embodiment of the present application, the call logs of each API reported by each application can be combined, and then the business indicators of each API can be calculated by cluster statistical analysis, and the obtained business indicators of each API can be entered into the API business indicator library in real time.

[0086] For ease of understanding, let's take the published applications running in a certain period of time, including application B, application C, and application D, as an example. Application B, application C, and application D monitor the APIs called by their interactive forms in their respective running environments, and then write the API call status, such as request sending time, request response time, request return time, request data, return data, whether it is a continuous call (i.e., whether the call to the API is triggered by other APIs, or whether it triggers the call of other APIs), etc., to the call log and report it in real time.

[0087] Continuing to assume that the call log reported by application B contains the call status of API2 and API3, the call log reported by application C contains the call status of API3 and API4, and the call log reported by application D contains the call status of API2 and API4, then the business indicators of API2 can be calculated by clustering and statistically analyzing the call status of API2 reported by application B and application D, the business indicators of API3 can be calculated by clustering and statistically analyzing the call status of API3 reported by application B and application C, and the business indicators of API4 can be calculated by clustering and statistically analyzing the call status of API4 reported by application C and application D. The clustering analysis process of the API call status can refer to the clustering and statistical analysis process of the business indicators of API1 in the above embodiment, which will not be repeated here. The business indicators can include the request duration and the accuracy of the request return data.

[0088] S203: Determine the business indicator of the first API in the API business indicator library.

[0089] In an embodiment of the present application, after the first API is determined, the business indicator of the first API can be obtained by performing API matching in an API business indicator library.

[0090] S204: Determine the response performance of the target interactive form under the first API based at least on the business indicator of the first API.

[0091] The processing method provided in the embodiment of the present application can obtain the business indicators of the first API bound to the target interaction form in a pre-built API business indicator library for the target application in the construction stage of the low-compilation platform after determining the target interaction form with the API bound to the target application. This can quickly obtain the business indicators of the first API, and then quickly estimate the response performance of the target interaction form under the first API, so as to promptly remind the user to flexibly optimize the form solution.

[0092] As an implementation manner of determining the response performance of the target interactive form under the first API based at least on the business indicator of the first API, an embodiment of the present application provides another processing method, including the following steps:

[0093] S301, determining a target interaction form bound to an application program interface API under a target application, where the target application is an unpublished application of a low-compilation platform.

[0094] S302: Obtain business indicators of the first API bound to the target interactive form, where the business indicators at least include request return time.

[0095] S303: Obtain the calling status of the target interactive form to the first API.

[0096] In an embodiment of the present application, as described in the above embodiment, the call status of the API may include information such as the request sending time, request response time, request return time, request data, request return data, whether the call is continuous, etc.

[0097] Therefore, for a certain API bound to the target interactive form, if it is a continuous call, it means that the call of the API is triggered by other APIs. Therefore, for the first API, it is composed of multiple APIs, that is, there are multiple APIs bound to the dragged form component of the target interactive form. Suppose that the front-end developer drags the form component X on the low compilation platform and binds API5, API6 and API7 to it, that is, API5, API6 and API7 are the first API. If the front-end developer configures API5 to call API6, and API6 to call API7, that is, the call status of API5, API6 and API7 are all continuous calls; if the front-end developer configures API5 to call API6 and API7 does not involve any calls, then the call status of API5 and API6 is continuous calls, and the call status of API7 is discontinuous calls; if the front-end developer configures API5, API6 and API7 not to involve any calls, then the call status of API5, API6 and API7 is discontinuous calls.

[0098] S304: If the calling state is a continuous calling, the accumulated sum of the request return durations of the first API is used as the form response duration of the target interactive form under the first API.

[0099] In the embodiment of the present application, for ease of understanding, the API5, API6 and API7 bound to the form component X are continued to be called continuously as an example. The cumulative sum of the request return times of API5, API6 and API7 can be used as the form response time of the target interactive form under the first API.

[0100] In addition, if API5 and API6 bound to form component X are called continuously, and API7 is called discontinuously, the cumulative sum of the request return time of API5 and API6 is first calculated, and then the cumulative sum is further calculated with the request return time of API7, such as weighted average, to obtain the form response time of the target interactive form under the first API.

[0101] S305: If the calling state is a discontinuous calling, a calculation is performed on the request return time of the first API, and the corresponding calculation result is used as the form response time of the target interactive form under the first API.

[0102] In the embodiment of the present application, for ease of understanding, the API5, API6 and API7 bound to the form component X are all non-continuous calls. Then, operations can be performed on the request return time of API5, API6 and API7, such as weighted average, to obtain the form response time of the target interactive form under the first API.

[0103] The processing method provided in the embodiment of the present application, for a target application in the construction stage of a low-compilation platform, after determining the target interaction form with an API bound to the target application, obtains the call status of the target interaction form to the first API to which it is bound, and determines the form response time of the target interaction form under the first API, so as to estimate the response performance.

[0104] This application embodiment provides another processing method, see Figure 5 The method flow chart shown in the figure comprises the following steps:

[0105] S401, determining a target interaction form bound to an application program interface API under a target application, where the target application is an unpublished application of a low-compilation platform.

[0106] S402: Obtain a business indicator of a first API to which the target interactive form is bound, and determine a response performance of the target interactive form under the first API based at least on the business indicator of the first API.

[0107] S403: Determine a second API that is similar to the first API.

[0108] In the embodiment of the present application, an automatic collection task can be designed to monitor and analyze the call status of each API in the running environment, and the call status includes request and return data, and the request and return data include two types of data: request data and return data. For request data and return data, both include attributes and attribute values.

[0109] For the published interactive form application on the low-compilation platform, the application can monitor the call status of each API bound to its interactive form in its operating environment, write the call status to the call log, and report the call log in real time. In the embodiment of the present application, the call logs of each API reported by each application can be synthesized, and then the call logs can be parsed to obtain the request and return data corresponding to each API. In this way, the request and return data corresponding to the first API and other APIs can be obtained.

[0110] For the first API and any other API, the attributes and attribute values ​​in the two API request data, as well as the attributes and attribute values ​​in the returned data are compared respectively to determine the similarity between the two APIs in terms of attributes and attribute values. For example, if 90% of the attribute names and types of the first API and a certain API are exactly the same, and the attribute values ​​of the same attributes also overlap many times, then the similarity between the two APIs is very high.

[0111] For ease of understanding, it is further assumed that the first API is API1, and API1 is bound to the interactive forms of the published form application E and form application F. Assuming that both application E and application F report API call logs within a certain period of time, the request and return data corresponding to API1 can be obtained by parsing the call logs of application E and application F. Assuming that API1 is called p times by application E and q times by application F, the request and return data corresponding to API1 obtained by parsing include p+q items, and each request and return data includes attributes and attribute values ​​in the request data, and attributes and attribute values ​​in the return data.

[0112] Similarly, for other APIs except API1, their corresponding request and return data can also be obtained by parsing the call logs reported by the published form application bound to it. Assume that the other API is API2, and API2 is bound by the published form application G and form application H at the same time. Assume that application G and application H both report call logs for APIs in a certain period of time, so by parsing the call logs of application G and application H, the request and return data corresponding to API2 can be obtained. Assuming that API2 is called s times by application G and t times by application H, the request and return data corresponding to API2 obtained by parsing contains s+t items, and each request and return data contains the attributes and attribute values ​​in the request data, as well as the attributes and attribute values ​​in the return data.

[0113] Based on this, in order to obtain the similarity between API1 and API2, the attributes and attribute values ​​in the p+q request data corresponding to API1 and the s+t request data corresponding to API2 can be compared to determine the proportion of attributes in the request data whose attribute names and types are exactly the same between API1 and API2 (hereinafter referred to as the first proportion), and the proportion of overlapping attribute values ​​of the same attributes (hereinafter referred to as the second proportion). Continue to compare the attributes and attribute values ​​in the p+q return data corresponding to API1 and the s+t return data corresponding to API2 to determine the proportion of attributes in the return data whose attribute names and types are exactly the same between API1 and API2 (hereinafter referred to as the third proportion), and the proportion of overlapping attribute values ​​of the same attributes (hereinafter referred to as the fourth proportion). Thus, the similarity of the attributes of API1 and API2 is determined based on the first proportion and the third proportion, and the similarity of the attribute values ​​of API1 and API2 is determined based on the second proportion and the fourth proportion, and then the similarity of the attributes and the similarity of the attribute values ​​are comprehensively determined to determine the similarity between API1 and API2.

[0114] It should be noted that the first proportion and the third proportion are both positively correlated with the similarity of attributes, the second proportion and the fourth proportion are both positively correlated with the similarity of attribute values, the similarity of attributes and the similarity of attribute values ​​are also positively correlated with the similarity between APIs, and the calculation method of the similarity of attribute values, the similarity of attribute values, and the similarity between APIs can be set according to the actual scenario, for example, a weighted average method can be used for processing, which is not limited here.

[0115] It should also be noted that in some scenarios, existing similarity algorithms, such as the shortest edit distance algorithm, can also be used to calculate the similarity between APIs. Continuing with the above-mentioned API1 and API2 as an example, for the attributes and attribute values ​​in the p+q request data corresponding to API1 and the s+t request data corresponding to API2, the shortest edit distance algorithm can be used to calculate the similarity between API1 and API2 in the request data dimension; and for the attributes and attribute values ​​in the p+q return data corresponding to API1 and the s+t return data corresponding to API2, the shortest edit distance algorithm can be used to calculate the similarity between API1 and API2 in the return data dimension; and then the similarity in the request data dimension and the similarity in the request data dimension are combined to determine the similarity between API1 and API2, for example, a weighted average method can be used to determine it, and this application does not limit this.

[0116] After obtaining the similarity between API1 and API2 based on this, it can be determined whether API2 and API have similarity based on the similarity. For example, a threshold can be set. If the threshold is higher than the threshold, it can be determined that API2 and API have similarity, otherwise, they do not.

[0117] S404: Obtain a business indicator of the second API, and determine a response performance of the target interactive form under the second API at least based on the business indicator of the second API.

[0118] In the embodiment of the present application, the method for obtaining the business indicators of the second API and the method for determining the response performance of the target interaction form under the second API can refer to the method for obtaining the business indicators of the first API and the method for determining the response performance of the target interaction form under the first API, which will not be repeated here.

[0119] S405 , by comparing the response performance of the target interactive form under the first API and the second API, selecting a target API with the best response performance from the first API and the second API.

[0120] In the embodiment of the present application, the response performance is further expressed in terms of response level. The response levels of the first API and the second API are compared, and the API with the higher response level is used as the target API and recommended to the user.

[0121] On this basis, when the target API is the first API, output corresponding prompt information based on the first API; or

[0122] When the target API is the second API, corresponding recommendation information is output based on the second API.

[0123] In the embodiment of the present application, for the form solution selected by the user of the low compilation platform, if the solution currently selected by the user is the best, no other API will be recommended, and the user can be prompted that the solution currently selected is the best solution. On the contrary, if there are other better solutions, an API with better response performance will be recommended to the user, so that the user can optimize and adjust the form solution, and finally build a high-quality form application.

[0124] The processing method provided in the embodiment of the present application, on the one hand, supports the rapid evaluation of the response performance of the form solution selected by the user during the application building phase, and can also recommend the API solution with the best response performance to the user based on similarity analysis and API performance indicator analysis, thereby improving the efficiency of application building.

[0125] As an implementation method for determining a second API having similarity to a first API, the present application embodiment provides another processing method, see Figure 6 The method flow chart shown in the figure comprises the following steps:

[0126] S501, determining a target interaction form bound to an application program interface API under a target application, where the target application is an unpublished application of a low-compilation platform.

[0127] S502: Obtain a business indicator of a first API to which the target interactive form is bound, and determine a response performance of the target interactive form under the first API based at least on the business indicator of the first API.

[0128] S503, calling an API similarity library, where the similarity between two APIs in the API similarity library is determined by analyzing the request and return data in the call logs of the two APIs by the published applications on the low compilation platform.

[0129] In an embodiment of the present application, tasks may be automatically collected to monitor and analyze the calling status of each API in the operating environment, so as to construct an API similarity library, which contains the similarities between APIs.

[0130] For an interactive form application that has been published on a low-compilation platform, the application can monitor the call status of each API bound to its interactive form in its operating environment, write the call status to the call log, and report the call log in real time. In the embodiment of the present application, the call logs of each API reported by each application can be synthesized, and then the call logs can be parsed to obtain the request and return data corresponding to each API.

[0131] For any two APIs that obtain request and return data, similarity analysis can be performed on the two APIs. For the specific analysis process, reference can be made to the analysis process of the similarity between API1 and API2 in the above embodiment, so as to obtain the similarity between the two APIs.

[0132] S504: Determine in the API similarity library an API whose similarity with the first API meets a corresponding threshold as the second API.

[0133] In the embodiment of the present application, an API having a similarity with the first API higher than a corresponding threshold value may be retrieved in the API similarity library as the second API.

[0134] S505: Obtain a business indicator of the second API, and determine the response performance of the target interactive form under the second API at least based on the business indicator of the second API.

[0135] S506 , by comparing the response performance of the target interactive form under the first API and the second API, selecting a target API with the best response performance from the first API and the second API.

[0136] In the embodiment of the present application, by pre-building API similarity, an API similar to the first API bound to the target interactive form can be quickly obtained, so as to quickly recommend the API solution with the best response performance to the user, thereby significantly improving the efficiency of application building.

[0137] See also Figure 7 The processing scenario shown. Design an automatic collection task to collect API call logs, automatically monitor and analyze the API call status in the running environment, and calculate API business indicators (i.e. performance indicators) such as request duration and accuracy of request return data to build an API business indicator library; on the other hand, perform similarity analysis on different APIs based on request and return data to generate API similarity relationship data (i.e. similarity between APIs) to build an API similarity library.

[0138] The user (front-end developer) builds an interactive form application on a low-compilation platform. During the construction process, the interactive form is generated by dragging the form component and binding the API. Since the dynamic data interaction performance of the interactive form mainly depends on the business performance of the bound API, the business indicators of the API are obtained from the API business indicator library according to the identifier of the API bound to the interactive form selected by the user, and then the response performance of the interactive form under the API is estimated.

[0139] In addition, according to the identifier of the API bound to the interactive form selected by the user, similar APIs are retrieved from the API similarity library, and the business indicators of the API are obtained from the API business indicator library, so as to estimate the response performance of the interactive form under the API. By comparing the response performance of the API bound to the interactive form selected by the user and the response performance of similar APIs, the API with the best performance is recommended to the user. If the solution currently selected by the user is already the best, no other APIs will be recommended, and the user can be prompted that the solution currently selected is already the best solution. On the contrary, if there are other better solutions, APIs with better response performance are recommended to the user, so that the user can optimize and adjust the form solution, and finally build a high-quality form application.

[0140] Corresponding to the processing method provided in the above embodiment, the embodiment of the present application provides a processing device, such as Figure 8 As shown, the device comprises:

[0141] A form determination module 10 is used to determine a target interactive form bound to an application program interface API under a target application, where the target application is an unpublished application of a low-compilation platform;

[0142] The performance determination module 20 is used to obtain the business indicator of the first API bound to the target interactive form, and determine the response performance of the target interactive form under the first API based on at least the business indicator of the first API.

[0143] In another embodiment of the processing device disclosed in the present application, the performance determination module 20 obtains the business indicator of the first API bound to the target interactive form, including:

[0144] Calling an API business indicator library, the business indicator of each API in the business indicator library is determined by clustering statistics and analyzing the call logs of each API by the published applications of the low compilation platform; determining the business indicator of the first API in the API business indicator library.

[0145] In another embodiment of the processing device disclosed in the present application, the business indicator at least includes the request return time, and the performance determination module 20 determines the response performance of the target interactive form under the first API based on at least the business indicator of the first API, including:

[0146] Obtain the calling status of the target interactive form to the first API; if the calling status is a continuous calling, use the accumulated sum of the request return durations of the first API as the form response duration of the target interactive form under the first API; if the calling status is a discontinuous calling, perform an operation on the request return duration of the first API, and use the corresponding operation result as the form response duration of the target interactive form under the first API.

[0147] In another embodiment of the processing device disclosed in the present application, the performance determination module 20 is further configured to:

[0148] Determine a second API that is similar to the first API; obtain business indicators of the second API, and determine the response performance of a target interactive form under the second API at least based on the business indicators of the second API; and select a target API with the best response performance from the first API and the second API by comparing the response performance of the target interactive form under the first API and the second API.

[0149] In another embodiment of the processing device disclosed in the present application, the performance determination module 20 determines the second API having similarity with the first API, including:

[0150] Calling an API similarity library, the similarity of two APIs in the API similarity library is determined by analyzing the request and return data in the call logs of the two APIs by the published applications of the low compilation platform; determining an API in the API similarity library whose similarity with the first API meets the corresponding threshold as the second API.

[0151] In another embodiment of the processing device disclosed in the present application, the performance determination module 20 is further configured to:

[0152] When the target API is the first API, output corresponding prompt information based on the first API; or

[0153] When the target API is the second API, corresponding recommendation information is output based on the second API.

[0154] The detailed functions of each module in the embodiment of the present application can be found in the corresponding disclosed part of the above-mentioned information processing method embodiment, which will not be repeated here.

[0155] Corresponding to the above processing method, the present application also discloses a storage medium, which stores computer program code, and the processing method of the above embodiment is implemented when the computer program code is executed.

[0156] The above is a detailed introduction to a processing method, device, electronic device and storage medium provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

[0157] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0158] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device that includes a series of elements is inherent to the elements, or also includes elements inherent to these processes, methods, articles or devices. In the absence of further restrictions, the elements defined by the sentence "including a..." do not exclude the presence of other identical elements in the process, method, article or device that includes the elements.

[0159] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A processing method, the method comprising: Determine a target interaction form bound to an application program interface API under a target application, wherein the target application is an unpublished application of a low-compilation platform; Obtaining a business indicator of a first API to which the target interactive form is bound, and determining a response performance of the target interactive form under the first API at least based on the business indicator of the first API; The business indicator at least includes a request return time, and determining the response performance of the target interactive form under the first API at least based on the business indicator of the first API includes: Obtaining a calling status of the target interactive form to the first API; If the calling state is a continuous calling, the accumulated sum of the request return durations of the first API is used as the form response duration of the target interactive form under the first API; If the calling state is a discontinuous calling, a calculation is performed on the request return duration of the first API, and the corresponding calculation result is used as the form response duration of the target interactive form under the first API.

2. According to the method of claim 1, obtaining the business indicator of the first API bound to the target interactive form comprises: Calling an API business indicator library, wherein the business indicator of each API in the business indicator library is determined by clustering and statistically analyzing the call logs of each API by the published applications of the low-compilation platform; Determine the business indicator of the first API in the API business indicator library.

3. The method according to claim 1, further comprising: Determining a second API having similarity to the first API; Obtaining a business indicator of the second API, and determining a response performance of the target interactive form under the second API at least based on the business indicator of the second API; By comparing the response performance of the target interactive form under the first API and the second API, a target API with the best response performance is selected from the first API and the second API.

4. The method according to claim 3, wherein determining the second API having similarity with the first API comprises: Calling an API similarity library, wherein the similarity between two APIs in the API similarity library is determined by analyzing request and return data in a call log of the two APIs by a published application of the low-compilation platform; An API whose similarity with the first API meets a corresponding threshold is determined in the API similarity library as the second API.

5. The method according to claim 3, further comprising: When the target API is the first API, outputting corresponding prompt information based on the first API; or When the target API is the second API, corresponding recommendation information is output based on the second API.

6. A processing device, comprising: A form determination module, used to determine a target interactive form bound to an application program interface API under a target application, wherein the target application is an unpublished application of a low-compilation platform; a performance determination module, configured to obtain a business indicator of a first API to which the target interactive form is bound, and determine a response performance of the target interactive form under the first API based at least on the business indicator of the first API; The business indicator at least includes a request return time, and the performance determination module is used to determine the response performance of the target interactive form under the first API based on at least the business indicator of the first API, including: Obtaining a calling status of the target interactive form to the first API; If the calling state is a continuous calling, the accumulated sum of the request return durations of the first API is used as the form response duration of the target interactive form under the first API; If the calling state is a discontinuous calling, a calculation is performed on the request return duration of the first API, and the corresponding calculation result is used as the form response duration of the target interactive form under the first API.

7. The device according to claim 6, wherein the performance determination module obtains the business indicator of the first API bound to the target interactive form, comprising: Calling an API business indicator library, wherein the business indicator of each API in the business indicator library is determined by clustering and statistically analyzing the call logs of each API by the published applications of the low-compilation platform; determining the business indicator of the first API in the API business indicator library.

8. An electronic device, comprising: A memory, used to store applications and data generated by the operation of the applications; A processor is used to execute the application program to implement the following functions: determining a target interaction form bound to an application program interface API under a target application, wherein the target application is an unpublished application of a low-compilation platform; obtaining a business indicator of a first API bound to the target interaction form, and determining a response performance of the target interaction form under the first API based at least on the business indicator of the first API; The business indicator at least includes a request return time, and determining the response performance of the target interactive form under the first API at least based on the business indicator of the first API includes: Obtaining a calling status of the target interactive form to the first API; If the calling state is a continuous calling, the accumulated sum of the request return durations of the first API is used as the form response duration of the target interactive form under the first API; If the calling state is a discontinuous calling, a calculation is performed on the request return duration of the first API, and the corresponding calculation result is used as the form response duration of the target interactive form under the first API.

9. A storage medium storing computer program code, wherein the computer program code, when executed, implements the processing method according to any one of claims 1 to 5.

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