A page data binding method and system in a low-code environment

Abstract

The present invention relates to a method and system for binding page data in a low-code environment, the method comprising: a page includes one or more components arranged in a page layout mode; a component set is bound based on a data binding mode and one or more of a data source set; a page's access changes to a data source are determined based on historical page access data; and a page data binding mode is updated based on access changes. The present invention dynamically updates the refresh frequency based on the dynamic changes in the data source and the page's access to the data source, actively updates the data source, predicts changes in data source access based on real-time monitoring of the data source, and adaptively changes the storage space in advance to improve access efficiency.

Description

[Technical field]

[0001] The present invention belongs to the field of low-code development technology, and in particular, relates to a page data binding method and system in a low-code environment. [Background technology]

[0002] A low-code environment refers to a software development platform that allows developers to create applications through a graphical interface and model-driven logic without writing a lot of code. Low-code defines the logic of an application through a model-driven approach, and users can implement business logic by configuring properties and setting rules instead of writing code. Based on the user's design and configuration on the visual interface, the platform automatically generates the corresponding code, reducing the workload of manual code writing. Integration and scalability: allows integration with existing enterprise systems and databases, and also supports extending functions through APIs and custom code. Multi-platform support: supports deployment of applications across multiple platforms and devices, including Web, mobile devices, and desktop applications. Rapid iteration and deployment: simplifies the development, testing, and deployment process of applications, making iteration and release of new versions faster. Providing a user-friendly interface, even non-technical users can build applications through a low-code platform, lowering the threshold for software development. The goal of a low-code environment is to improve development efficiency, shorten project delivery time, reduce costs, and enable business experts to participate more directly in the application building process. Suitable for rapid development of prototypes, building internal tools, customizing existing applications, and meeting specific business needs. In a low-code environment, page data binding is a core function that allows developers to associate page elements with data sources in a visual way, and update the data source bound to the client through the inherent refresh frequency, thereby realizing automatic data update and interaction. The low-code platform makes data binding more intuitive and efficient, greatly reducing the workload of manually writing data synchronization code in traditional development. In the low-code platform, two-way data binding is currently used to achieve data synchronization between the page view and the model data source. When the state of the data source changes, the page view is automatically updated, and vice versa. This mechanism simplifies the development process and improves development efficiency. Through simple configuration, data can flow to page components, and the data of page components can flow to another component to realize two-way data flow; cloud services also provide strong back-end support for low-code platforms, including databases, message queues, caches and other infrastructure, and also provide automated deployment and operation and maintenance capabilities.

[0003] With the rapid development of information technology, enterprises have an increasing demand for rapid development and deployment of applications. Low-code development platforms have received widespread attention for their fast development cycles and simplified development processes. In low-code platforms, data binding is usually a key step in the development process, which involves how to effectively connect user interface components with back-end data sources. Traditional data binding methods often use an inherent data refresh frequency, which depends on the data communication mode between the data source and the client. The data source is updated passively, and the allocation of storage space also depends on the inherent allocation method of the operating system or application interface. When there are multiple page views working in parallel on the client, it is impossible to dynamically balance the allocation of storage space within multiple pages and between different components of the page. The fixed data binding mode reduces access efficiency;

[0004] In order to solve the problems in the prior art, the present invention proposes a page data binding method and system in a low-code environment, which dynamically updates the refresh frequency based on the dynamic changes of the data source and the access of the page to the data source, actively updates the data source, and predicts the changes in the access to the page data source based on real-time monitoring of the data source, and makes adaptive changes to the storage space in advance to improve access efficiency. [Summary of the invention]

[0005] In order to solve the above problems in the prior art, the present invention proposes a page data binding method and system in a low-code environment, the method comprising:

[0006] Step S1: The page contains one or more components arranged in a page layout manner ; Components based on data binding and data source collection One or more bindings in ;

[0007] Step S2: Determine the change of page access to the data source based on the page historical access data; the step specifically includes the following steps:

[0008] Step S21: Obtain historical page access data; divide the historical page access data into time intervals; determine each time interval Each component For each data source Number of visits ; and constitutes a time interval corresponding to The visit count matrix ; Based on the access count matrix, we get the access ratio matrix ; Perform differential processing on the access ratio matrix to obtain the differential access ratio matrix ;

[0009] Step S22: When the refresh frequencies of all data sources are the same, and the number of components in the page is less than the component number threshold and / or the average number of data sources bound to the components is less than the average binding threshold, for each differential access proportion matrix , the differential access ratio matrix All elements in Sort by numerical value from small to large to form an increasing sequence ;in: is the number of elements in an increasing sequence; using the exponential function Fit the elements in the increasing sequence and determine the corresponding fitting function The value of; get the corresponding differential access ratio matrix of , determine the index With time interval of the following trends: ; , and is a constant; the change trend includes increasing, decreasing and maintaining; otherwise, an exponential change trend is determined for each data source respectively;

[0010] Determining the index change trend for each data source respectively specifically includes the following steps:

[0011] Step S221: Obtain an unprocessed differential access ratio matrix ;

[0012] Step S222: Obtain an unprocessed data source ;

[0013] Step S223: For each element , determine whether it is an empty value, if not empty, then the element Add data source In the corresponding temporary collection; when When empty, it indicates that for the component No data source is bound ;

[0014] Step S224: If there is an unprocessed data source , then return to step S222; otherwise, proceed to the next step;

[0015] Step S225: For each data source The corresponding temporary collection, sort all the elements in the temporary collection in order of value from small to large to form an increasing sequence ;in: is the number of elements in an increasing sequence; using the exponential function Fit the elements in the increasing sequence and determine the corresponding fitting function The value of; get the corresponding differential access ratio matrix With data source of ;

[0016] Step S226: If there is an unprocessed differential access ratio matrix , then return to step S221; otherwise, determine the index of the following trends: ; , and is a constant; the change trend includes increasing, decreasing and maintaining;

[0017] Step S3: Update the page data binding mode based on the access change; wherein: the page data binding mode includes the data source refresh frequency; specifically: when the index When the index trend is increasing, increase the refresh frequency of the corresponding data source; when the index change trend is determined for each data source, When the trend of change is increasing, improve and data source The corresponding refresh frequency; when When the trend is decreasing, reduce and data source The corresponding refresh rate.

[0018] Furthermore, the page is used for manufacturing site equipment management, logistics site, park management or order management.

[0019] Furthermore, the page is used for a mobile client, and the data source is set on the same or different server.

[0020] Furthermore, the mobile client sets multiple pages in parallel.

[0021] Furthermore, the storage space of the data source includes a low-speed storage space and a high-speed storage space.

[0022] Furthermore, the high-speed storage space is one or more of cache, memory, flash memory, and volatile storage space.

[0023] Furthermore, the low-speed storage space is one or more of a hard disk, a magnetic disk, a non-volatile storage space, and a cloud storage.

[0024] Furthermore, the server is a cloud server.

[0025] Furthermore, the server is an Internet of Things server.

[0026] A page data binding system in a low-code environment, wherein the page data binding system in a low-code environment is used to implement the page data binding method in the low-code environment.

[0027] The beneficial effects of the present invention include:

[0028] (1) Dynamically update the refresh frequency based on the dynamic changes of the data source and the page's access to the data source, and actively update the data source; discover the differential changes in the access situation in the page through fitting based on the exponential function, and use different refresh frequencies for different data sources, thereby fundamentally reducing data synchronization overhead and improving access efficiency;

[0029] Furthermore, a bidirectional model is set to discover the first prediction relationship from the client side, and simultaneously discover the second prediction relationship from both the client side and the data source side, and adaptively change the storage space in advance through the bidirectional association;

[0030] (2) Based on real-time monitoring of the data source, changes in page data source access are predicted, and adaptive changes to the storage space are made in advance. From the perspective of the data source and components, the space allocation method of the low-speed storage space is updated based on the real-time data source projection vector, so that the low-speed storage space allocated by the data source is dynamically adjusted as different pages use the data source. The low-speed storage space is effectively allocated among the data sources, and the space allocation method of the high-speed storage space is updated based on the real-time component projection vector. This allows the high-speed storage space to be effectively allocated among the components, realizing the adaptive allocation adjustment of the storage space during the binding process.

Brief Description of the Drawings

[0031] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present application, but do not constitute an improper limitation of the present invention. In the drawings:

[0032] Figure 1 Schematic diagram of the page data binding method in the low-code environment provided by the present invention. [Specific implementation method]

[0033] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments, wherein the illustrative embodiments and descriptions are only used to explain the present invention but are not intended to limit the present invention.

[0034] The present invention proposes a page data binding method and system in a low-code environment, as shown in the attached Figure 1 As shown, the method comprises the following steps:

[0035] Step S1: The page contains one or more component sets arranged in a page layout manner ; Components are based on binding methods and data source collections One or more of the following are bound; where: ; is the number of data sources, equal to ;

[0036] Preferably: the binding method is to associate component attributes with data source fields based on data binding rules; automatically associate page components with data sources according to preset data binding rules; provide an attribute panel to allow developers to select component attributes and select corresponding data sources from a data source list for binding; the bound data source is saved in a storage space, the storage space includes a low-speed storage space and a high-speed storage space; the saving includes associated saving (building a quick connection, creating a direct access channel, etc.);

[0037] Furthermore, the data source is one or more of a database, an API interface, a data server, a big data service platform, a data class, a data cluster, a data table or other data services.

[0038] Preferred: The page editor provides a view interface, allowing developers to quickly build page layouts by dragging components from the component library onto the canvas; the component library includes various pre-made UI components, such as text boxes, buttons, lists, charts, etc.;

[0039] Preferably: the page is used for manufacturing site equipment management, logistics site, park management, order management, etc.;

[0040] Preferably: the page is used for a mobile client, and the data source is set on the Internet of Things server;

[0041] Preferably: the mobile client sets multiple pages in parallel;

[0042] Preferably: the plurality of pages and their components share storage space; the shared storage space includes a low-speed storage space and a high-speed storage space;

[0043] Preferably: the high-speed storage space is one or more of cache, memory, flash memory, and volatile storage space;

[0044] The low-speed storage space is one or more of a hard disk, a magnetic disk, a non-volatile storage space, a cloud storage, a magnetic tape, and a disk array;

[0045] Step S2: Determine the change of page access to the data source based on the page historical access data; the step specifically includes the following steps:

[0046] Step S21: Obtain historical page access data; divide the historical page access data into time intervals; determine each time interval Each component For each data source Number of visits , and constitutes a time interval corresponding to The visit count matrix ; Based on the access count matrix, we get the access ratio matrix ; Perform differential processing on the access ratio matrix to obtain the differential access ratio matrix ;

[0047] Preferably: Before entering the next step, normalize the differential access ratio matrix to In numerical space;

[0048] Step S22: When the refresh frequencies of all data sources are different, and the number of components in the page is less than the component number threshold or the average number of data sources bound to the components is less than the average binding threshold, for each differential access proportion matrix , the differential access ratio matrix All elements in Sort by numerical value from small to large to form an increasing sequence ;in: is the number of elements in an increasing sequence; using the exponential function For elements in increasing sequence ( As , the element number is ) to fit and determine the corresponding The value of; get the corresponding differential access ratio matrix of , determine the index of the following trends: ; , and is a constant; the change trend includes increasing, decreasing and maintaining; otherwise, an exponential change trend is determined for each data source respectively;

[0049] Determining the index change trend for each data source respectively specifically includes the following steps:

[0050] Step S221: Obtain an unprocessed differential access ratio matrix ;

[0051] Step S222: Obtain an unprocessed data source ;

[0052] Step S223: For each element , determine whether it is an empty value, if not empty, then the element Add data source In the corresponding temporary collection; when When empty, it indicates that for the component No data source is bound ; Of course, the default value can also be used;

[0053] Step S224: If there is an unprocessed data source , then return to step S222; otherwise, proceed to the next step;

[0054] Step S225: For each data source The corresponding temporary collection, sort all the elements in the temporary collection in order of value from small to large to form an increasing sequence ;in: is the number of elements in an increasing sequence; using the exponential function For elements in increasing sequence ( As , the element number is ) to fit and determine the corresponding Repeat the above steps to obtain the matrix corresponding to each differential access ratio With data source of ;in: ; , and is a constant; the change trend includes increasing, decreasing and maintaining;

[0055] Step S226: If there is an unprocessed differential access ratio matrix , then return to step S221; repeat the above steps to obtain the matrix corresponding to each differential access ratio With data source of , respectively determine the index ;

[0056] When the change trend is increasing or decreasing, the step S2 further includes step S23;

[0057] Step S23: Determine a first proportion association relationship or a second proportion association relationship that reflects the projection of the data source update status on the page-bound data source; specifically, it includes the following steps:

[0058] Step S231: For each data source Get time interval The percentage of partial updates within ; The local update ratio For data source The ratio of the updated data volume to the total data volume within the time interval; obtain the global update ratio based on the local update ratio ; Build a data source proportion vector based on the global update proportion ; Perform differential processing on the data source proportion vector to obtain the differential data source proportion vector ;

[0059] Preferably: Preferably: Before entering the next step, the differential data source ratio vector is normalized to In numerical space;

[0060] Alternative: The local update ratio is the data source The number of updates within the time interval; of course, other combinations can also be used, which will not be repeated here;

[0061] Step S232: The differential access ratio matrix Perform row projection to obtain the data source projection vector. ;

[0062] Further: the step S232 further includes: converting the differential access ratio matrix Perform column projection to obtain the component projection vector , ;

[0063] Step S233: Determine the data source projection vector based on the page history access data And the differential data source ratio vector The first proportion relationship between ; Specifically: Projection vector for data source Each element in , and each and The relationship between the elements , expressed as ; thus forming the first proportion relationship ; The first proportion relationship reflects the projection of the data source update status on the page-bound data source;

[0064] Alternative: Determine the first proportion relationship based on the artificial intelligence model; As the input data of the artificial intelligence model, As output data, the artificial intelligence model is trained to form right predictions;

[0065] Preferably: the artificial intelligence model is a supervised training model;

[0066] Preferably, the artificial intelligence model is a neural network model;

[0067] Alternatively: determining the first proportion association relationship based on a bidirectional model; the bidirectional model includes a first model and a second model; the first model projects a vector for a data source Each of Determine each and The relationship between the elements , expressed as ; thus forming the first relationship As the first model; the second model for each component , based on the differential access ratio matrix The second relationship As the second model; construct a bidirectional model based on the first model and the second model Indicating the first proportion association relationship; specifically comprising the following steps:

[0068] Step S233A1: Construct the first model, project vectors for the data source Each of Determine each and The first relationship between the elements in , ;constitute As the first model;

[0069] Step S233A2: Construct a second model, for each component, based on the differential access ratio matrix Determine the second relationship ,constitute As the second model; specifically:

[0070] Formula (1) is used to construct ;in: is a constant, is the coefficient matrix to be estimated, is the margin of error; is the number of data sources;

[0071] (1);

[0072] Preferred: coefficient matrix By minimizing the residual sum of squares, we can estimate and find a constant matrix that makes the actual monitoring value and the predicted value of the second model If the sum of squares of the residuals is the smallest, the constant matrix is ​​used as the coefficient matrix;

[0073] Preferably: the coefficient matrix is ​​determined by the least squares method;

[0074] Step S233A3: construct a bidirectional model, based on the first model and the second model, construct a bidirectional model indicating the first proportion association relationship; specifically: construct a third relationship based on formula (2) =( ) as a bidirectional model; using the bidirectional model to indicate the first proportion association relationship ;

[0075] (2);

[0076] Alternative: Construct a third relationship based on formula (3) =( ) as a bidirectional model; using the bidirectional model to indicate the first proportion association relationship ;in: and is the weight coefficient;

[0077] (3);

[0078] Alternatively, the step S233 is specifically as follows: determining the component projection vector based on the page history access data And the differential data source ratio vector The second proportion relationship between ; Specifically: for the component projection vector Each of , and each and The relationship between the elements , expressed as ; thus forming the second proportion relationship ;

[0079] It is understandable that the alternative method in step S233A1 to step S233A3 is adopted to determine the second proportion association relationship in a similar way using a bidirectional model; of course, the first proportion association relationship and the second proportion association relationship can be further coupled to obtain the final first proportion association relationship;

[0080] Step S234: Monitor the data update status of the data source in real time to obtain the local update ratio within the latest time period. , the latest time period is called ; Determine the global update ratio and data source ratio vector in turn, and construct the real-time differential data source ratio vector ;

[0081] Preferably: the latest time period is smaller than the time interval; of course, the latest time period can be achieved by overlapping the latest time period with part of the historical time interval t;

[0082] Step S235: Based on the real-time differential data source proportion vector Correlation with the first proportion Determine the projection vector of the real-time data source ;

[0083] Alternative: Based on real-time differential data source proportion vector The relationship between the second proportion Determine the real-time component projection vector ;

[0084] Step S3: updating the page data binding mode based on the change trend; wherein: the page data binding mode includes a data source refresh frequency; the data in the data source is stored in the high-speed storage space and the low-speed storage space of the client where the page is located based on the refresh frequency corresponding to the data source; when the change trend is increasing, the refresh frequency corresponding to the data source is increased; when the refresh frequencies for all data sources are the same, when the change trend is increasing, it indicates an obvious change in access to the data source, and the difference in access changes for different data sources is also stronger, indicating that a higher refresh frequency is needed, on the contrary, when the change trend is decreasing, it indicates that the change in access to different data sources is balanced, and no response to the refresh frequency will not lead to a significant reduction in access efficiency, so that the refresh frequency under the current data binding mode can be maintained; at this time, even if the refresh frequencies for all data sources are different, if the number of components in the page is less than the component number threshold or the average number of data sources bound to the components is less than the average binding threshold, the refresh frequencies of all data sources can be adjusted consistently; the increase here can be a proportional increase or an increase with a certain granularity;

[0085] Preferably: when the change trend is decreasing, the refresh frequency corresponding to the data source is reduced; it can also be used to reduce the refresh frequency corresponding to the data source when the retention time is long enough;

[0086] Alternative: When the refresh rates for all data sources are different, determine the index The changing trend of When the trend is increasing, increase the data source The corresponding refresh frequency; when When the trend is decreasing, reduce and data source Corresponding refresh rate;

[0087] Further, the step S3 also includes: the page data binding method also includes the bound high-speed storage space size (or space allocation method) and the low-speed storage space size (or space allocation method); updating the page data binding method, including: updating the space allocation method of the low-speed storage space based on the real-time data source projection vector; updating the space allocation method of the high-speed storage space based on the real-time component projection vector; the allocation of the low-speed storage space is more closely related to the data source, which determines whether the data of the data source can be obtained at a relatively fast speed, that is, the response speed of the data source is affected by the allocation method; and the high-speed storage space is more closely related to the component. When the memory space of the component is relatively certain, the change of the page replacement storage space will cause the component storage space to be incompatible with its access situation (related to the data source update) when the page corresponds to sufficient high-speed storage space; different projection vectors are used to affect the allocation method of different types of storage space;

[0088] The space allocation method of updating the low-speed storage space based on the real-time data source projection vector is specifically: calculating the updated low-speed storage space , so that ;in: Is the data source The size of the allocated slow storage space; Is the data source After the adjustment of the slow storage space, the adjustment factor for the data The storage of updated data may result in more frequent data replacement, while the opposite effect is that for data sources with frequently updated data, access to their bound data sources will have better access efficiency due to the larger low-speed storage space;

[0089] Preferably: the low-speed storage space is one or more of a hard disk, a magnetic disk, and a non-volatile storage space;

[0090] The space allocation method of updating the high-speed storage space based on the real-time component projection vector is specifically: calculating the updated high-speed storage space , so that ;in: It is a component The size of the low-speed storage space; It is a component Similarly, after the high-speed storage space is adjusted, the adjustment factor for the component The storage of updated data may result in more frequent data replacement, while the opposite effect is that for data sources with frequently updated data, access to their bound data sources will have better access efficiency due to the larger high-speed storage space;

[0091] Preferably: the high-speed storage space is one or more of a cache, a memory, and a volatile storage space;

[0092] Furthermore, when the high-speed storage space allocated to the page is of a fixed size, in order to manage the memory space allocated to all components in the page in a memory pool manner, an object pool and a shared memory pool space are created for each component; if the shared memory pool space can satisfy all the high-speed storage spaces added after the update, then the process proceeds to step S3A1; otherwise, the process proceeds to step S3A2;

[0093] Step S3A1: For any component If the size of the high-speed storage space after the update is less than or equal to the size before the update, the size before the update is maintained; for any component If the updated high-speed storage space size is larger than the size before the update, the storage space is requested from the shared memory pool and allocated to the component. To meet the updated high-speed storage space size;

[0094] Step S3A2: For all components Updated high-speed storage space Normalize and set ;in: Refers to the pre-update component The size of the high-speed storage space; find and The one with the largest difference , release its object pool into the shared memory pool; reset its memory pool space equal to ; Return to step S3A1;

[0095] The space allocation method of updating the low-speed storage space based on the real-time data source projection vector makes the low-speed storage space allocated by the data source dynamically adjusted according to the use of the data source by different pages, and the low-speed storage space is effectively allocated among the data sources. The space allocation method of updating the high-speed storage space based on the real-time component projection vector makes the high-speed storage space effectively allocated among the components.

[0096] Preferred: Set up a data synchronization module in the Vue.js framework of v-model, create a two-way data flow between form input elements or components, so that the data in the user interface and application logic can be synchronized. When the user input changes, the corresponding JavaScript data will be automatically updated; conversely, when the JavaScript data changes, the UI will also be updated accordingly; use the modifier Vue.js to implement two-way data binding between parent and child components, simplifying the process of parent components passing data to child components and receiving modified data from child components; set up custom events Vue.js to implement two-way data binding between components through custom events, parent components pass data to child components through props, and when child components modify data, they pass the modified data to parent components through custom events;

[0097] Preferred: Centralized data storage management is provided through the Vuex state management library. Defining states and mutations in Vuex can achieve global two-way data binding.

[0098] A computer program (also referred to as a program, software, software application, script, or code) can be written in any form of a programming language, including an assembled or interpreted language, a declarative or procedural language, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program, or in multiple collaborative files (e.g., files storing one or more modules, subroutines, or code portions). A computer program can be deployed to execute on one computer or on multiple computers located at one site or distributed across multiple sites and interconnected by a communication network.

[0099] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0101] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0102] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A page data binding method in a low-code environment, characterized in that: The method comprises: Step S1: The page contains one or more components arranged in a page layout manner ; Components based on data binding and data source collection One or more bindings in ; Step S2: Determine the change of page access to the data source based on the page historical access data; the step specifically includes the following steps: Step S21: Obtain historical page access data; divide the historical access data into time intervals; determine each time interval Each component For each data source Number of visits ; and constitutes a time interval corresponding to The number of visits matrix ; Get the access ratio matrix based on the access number matrix ; Perform differential processing on the access ratio matrix to obtain the differential access ratio matrix ; Step S22: When the refresh frequencies of all data sources are the same, and the number of components in the page is less than the component number threshold and / or the average number of data sources bound to the components is less than the average binding threshold, for each differential access proportion matrix , the differential access ratio matrix All elements in Sort by numerical value from small to large to form an increasing sequence ;in: is the element number in the increasing sequence; otherwise, the exponential trend is determined for each data source separately; Determining the index change trend for each data source respectively specifically includes the following steps: Step S221: Obtain an unprocessed differential access ratio matrix ; Step S222: Obtain an unprocessed data source ; Step S223: For each element , determine whether it is an empty value, if not empty, then the element Add data source In the corresponding temporary collection; when When empty, it indicates that for the component No data source is bound ; Step S224: If there is an unprocessed data source , then return to step S222; otherwise, proceed to the next step; Step S225: For each data source The corresponding temporary collection, sort all the elements in the temporary collection in order of value from small to large to form an increasing sequence ; Among them: using exponential function Fit the elements in the increasing sequence and determine the corresponding fitting function The value of; get the corresponding differential access ratio matrix With data source of ; Step S226: If there is an unprocessed differential access ratio matrix , then return to step S221; otherwise, determine the index of the following trends: ; , and is a constant; the change trend includes increasing, decreasing and maintaining; Step S3: Update the page data binding mode based on the access change; wherein: the page data binding mode includes the data source refresh frequency; specifically: when the index When the trend of the change is increasing, increase the refresh frequency of the data source; when When the trend is decreasing, reduce and data source The corresponding refresh rate.

2. The method for binding page data in a low-code environment according to claim 1, characterized in that: The page is used for manufacturing site equipment management, logistics site management, park management or order management.

3. The method for binding page data in a low-code environment according to claim 2, characterized in that: The page is used for a mobile client, and the data source is set on the same or different server.

4. The method for binding page data in a low-code environment according to claim 3 is characterized in that: The mobile client sets multiple pages in parallel.

5. The method for binding page data in a low-code environment according to claim 4 is characterized in that: The storage space of the data source includes a low-speed storage space and a high-speed storage space.

6. The method for binding page data in a low-code environment according to claim 5, characterized in that: The high-speed storage space is one or more of a cache, a memory, a flash memory, and a volatile storage space.

7. The method for binding page data in a low-code environment according to claim 6, characterized in that: The low-speed storage space is one or more of a hard disk, a magnetic disk, a non-volatile storage space, and a cloud storage.

8. The method for binding page data in a low-code environment according to claim 7, characterized in that: The server is a cloud server.

9. The method for binding page data in a low-code environment according to claim 7, characterized in that: The server is an Internet of Things server.

10. A page data binding system in a low-code environment, characterized in that: The page data binding system in the low-code environment is used to implement the page data binding method in the low-code environment described in any one of claims 1 to 9.

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