Visual data flow weaving method, device and medium for zero-code platform

Abstract

The application discloses a visual data flow weaving method and device for a zero-code platform and a medium, relates to the field of zero-code data processing, and comprises the following steps: based on a trigger of a user, starting and visually displaying a data flow editor module; based on a dragging operation of the user, generating visual component nodes, data processing nodes and data source nodes; based on a trigger of the user on the visual nodes, displaying a configuration area and configuring the visual nodes through the configuration area; and based on a trigger of the user, connecting the visual nodes through connection stubs carried in the visual nodes to generate a visual data flow. The data flow relationship is presented in a visual manner, so that a developer can intuitively understand the data interaction logic among components. The input, output and events of the components can be intuitively configured through the data flow editor, thereby reducing the maintenance difficulty caused by the dispersion of configuration items.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of zero-code data processing, in particular to a visual data flow weaving method, device and medium for a zero-code platform. BACKGROUND

[0002] With the rapid development of Internet technology, various zero-code products are increasing, and various data presentation forms have also emerged. In order to accurately display data in the appropriate scene and make the constructed project more interactive, the existing data and interaction configuration is relatively scattered and complex.

[0003] In the traditional scheme, when configuring data and interaction, the data is usually obtained through interfaces, data sources, static data, etc., and is directly bound to the configuration of the related components to provide component display. Related interactions are set for single components, and some default interaction events are associated and bound with the events exposed by the components.

[0004] However, the traditional scheme has the following disadvantages:

[0005] 1. The configuration items are scattered, making it difficult to centrally and conveniently manage data flow logic, and making it difficult for secondary development.

[0006] 2. For specific data, it is easy to lose data control and unclear about the link flow of data.

[0007] 3. For a single specific component, only the data flow of the previous and next layers of the current component can be viewed, and it is difficult to view the association relationship of the overall link.

[0008] In this scenario, it is particularly important to develop an easy-to-use, extensible visual data flow weaving system to centrally manage complex data and interaction logic. SUMMARY

[0009] To solve the above problems, the present application proposes a visual data flow weaving method for a zero-code platform, comprising:

[0010] Based on the trigger of the user, start and visually display the data flow editor module; the data flow editor module includes a material area, a drawing board area, and a configuration area; the material area includes a component unit, a data processing unit, and a data source unit;

[0011] Based on the user's drag operation, the components in the component unit, the data processing functions in the data processing unit, and the data sources in the data source unit are added to the drawing board area respectively, and visual component nodes, data processing nodes, and data source nodes are generated respectively;

[0012] display the configuration area based on a user triggering the visualization node, and configure the visualization node through the configuration area; the types of the visualization node include component nodes, data processing nodes, and data source nodes; the configuration area includes at least events and related attributes for the visualization node;

[0013] based on a user triggering, connect the visualization nodes through the connection stub carried in the visualization node, and generate a visualization data flow.

[0014] In one example, the method further includes:

[0015] based on a user triggering, determine a logical test on the visualization data flow;

[0016] determine the verification rules that have been set, including basic verification rules and custom verification rules;

[0017] based on the basic verification rules, test the data type processing authority of the downstream node according to the data type output by the upstream node;

[0018] based on a user selection, determine the application scenario to which the current visualization data flow belongs, and according to the application scenario, select the corresponding custom verification rule in the corresponding rule library and add it to the current logical test;

[0019] based on the custom verification rules, test the data content processing flow of the downstream node according to the data content output by the upstream node.

[0020] In one example, based on the custom verification rules, the test on the data content processing flow of the downstream node according to the data content output by the upstream node specifically includes:

[0021] determine the data transaction content, and generate a corresponding first data fingerprint for the data transaction content based on the security sandbox set in the data flow editor module;

[0022] enter the data transaction content carrying the empty fingerprint slot into the visualization data flow;

[0023] based on the custom verification rules, determine that the downstream node is a key node according to the configuration content of the downstream node in the configuration area;

[0024] for the downstream node, receive the data transaction content output by the upstream node, perform hash calculation on the data transaction content, and obtain a second data fingerprint corresponding to the data transaction content;

[0025] match the second data fingerprint with the first data fingerprint in the security sandbox, and if the matching is successful, pass the test.

[0026] In one example, based on the custom verification rule, the data content output by the upstream node is tested according to the data content processing flow of the downstream node, specifically including:

[0027] According to the node type and the configuration content in the configuration area, it is determined that the upstream node is a data preprocessing node;

[0028] For the downstream node, the first data preprocessing result output by the upstream node is received, and the first data structural degree corresponding to the first data preprocessing result is determined;

[0029] Based on the visual data flow, it is determined whether there is a data preprocessing node upstream of the upstream node;

[0030] If there is, the closest data preprocessing node upstream of the upstream node is taken as a specified node, and the second data structural degree of the second data preprocessing result output by the specified node is determined;

[0031] If the first data structural degree is higher than the second data structural degree, the test is passed.

[0032] In one example, the method further includes:

[0033] It is determined that there are multiple downstream nodes corresponding to the same upstream node in the visual data flow;

[0034] Based on the user's triggering of the connection line between the multiple downstream nodes and the same upstream node, the configuration area is displayed;

[0035] The data flow real-time display function, data flow statistical function, and data flow playback function of the connection line are configured through the configuration area;

[0036] Among them, in the actual work of the visual data flow, the data flow real-time display function is used to display the real-time flow corresponding to each connection line at the current time; the data flow statistical function is used to display the total flow corresponding to each connection line in a preset time period; and the data flow playback function is used to display the real-time flow corresponding to each connection line at a historical time.

[0037] In one example, the method further includes:

[0038] Based on the user's triggering, the configuration area of the exception tracking sandbox is displayed, and the configuration area of the exception tracking sandbox is associated with the configuration area of the connection line;

[0039] Based on the configuration area of the anomaly tracking sandbox, the anomaly tracking function and the data stream holographic snapshot function contained in the anomaly tracking sandbox are set;

[0040] The anomaly tracking function is used to start when the real-time flow corresponding to each connection line at the current time exceeds the preset flow, triggering the data stream holographic snapshot function; the data stream holographic snapshot function is used to obtain the corresponding data stream snapshot according to the user-set frequency for the data stream of the user-set visual node and connection line.

[0041] In one example, the method further comprises:

[0042] Obtaining the function description input by the user for the required material;

[0043] Based on the function description and all materials included in the material area, a specified material is output by a large language model.

[0044] In the material area, the specified material is rendered and displayed.

[0045] In one example, the method further comprises:

[0046] For each type of visual node, a corresponding node color and a corresponding connection stake setting position are set respectively.

[0047] For the connection state between the connected visual nodes, a corresponding connection line color, connection line shape, and connection line text representation content are set.

[0048] On the other hand, the present application also proposes a visual data flow weaving device for a zero-code platform, comprising:

[0049] At least one processor; and,

[0050] A memory in communication connection with the at least one processor; wherein,

[0051] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the visual data flow weaving method for the zero-code platform as described in any of the above examples.

[0052] On the other hand, the present application also proposes a non-volatile computer storage medium storing computer executable instructions, the computer executable instructions being configured to implement the visual data flow weaving method for the zero-code platform as described in any of the above examples.

[0053] The visual data flow weaving method for the zero-code platform proposed by the present application can bring the following beneficial effects:

[0054] 1. Visualize data flow relationships to enable developers to intuitively understand the data interaction logic between components. The input, output, and events of components can be configured intuitively through the data flow editor, reducing the maintenance difficulty caused by scattered configuration items.

[0055] 2. Adopt a modular architecture to support the extension of new components and new event types. By uniformly managing data flow and interaction logic, the problem of scattered configuration items in traditional solutions is avoided, and the secondary development threshold is reduced, improving system flexibility.

[0056] 3. Provide global data state management to make data flow between components more efficient and clear. Adopting an event-driven mechanism, it supports dynamic interaction between components, such as data transfer and state synchronization.

[0057] 4. Optimize the performance of the drawing board through virtualization rendering technology, even when dragging multiple components, it can still maintain smoothness. Adopting an efficient data flow calculation method, unnecessary calculation overhead is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0058] The accompanying drawings explained here are used to provide a further understanding of the present application, and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0059] Figure 1 A flowchart of the visual data flow weaving method for the zero-code platform in the embodiments of the present application;

[0060] Figure 2 An interface diagram when the data flow editor module is started in one case in the embodiments of the present application;

[0061] Figure 3 An interface diagram after the data flow editor module contains visual nodes in one case in the embodiments of the present application;

[0062] Figure 4 An interface diagram when the data flow editor module displays the configuration area in one case in the embodiments of the present application;

[0063] Figure 5 An interface diagram when the data flow editor module performs node connection in one case in the embodiments of the present application;

[0064] Figure 6 An interface diagram when the data flow editor module node link fails in one case in the embodiments of the present application;

[0065] Figure 7For the case in the embodiment of the application, the interface schematic diagram when the data flow editor module connects multiple downstream nodes with a single upstream node;

[0066] Figure 8 For the schematic diagram of the visual data flow weaving device for the zero-code platform in the embodiment of the application. DETAILED DESCRIPTION

[0067] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described below in conjunction with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0068] The technical solutions provided by the embodiments of the present application will be described in detail below in conjunction with the drawings.

[0069] As shown in Figure 1 The embodiment of the present application provides a visual data flow weaving method for a zero-code platform, which comprises the following steps:

[0070] S101: based on the trigger of a user, starting and visualizing a data flow editor module; the data flow editor module comprises a material area, a drawing board area and a configuration area; the material area comprises a component unit, a data processing unit and a data source unit.

[0071] The data flow editor module can be set in a corresponding application program, and the user starts the application program and, in the application program, selects, drags, etc. by clicking, double-clicking, long-pressing, etc. on the corresponding buttons to start the data flow editor module.

[0072] The data flow editor module can be constructed by using AntV X6 to provide a visual data flow configuration mode based on nodes and connection lines, the user can define the data flow direction and interaction logic between components through dragging, and dynamic creation, modification and deletion of data flow nodes are allowed to realize flexible interaction relationship management and improve development and running efficiency.

[0073] The material area comprises a component unit, a data processing unit and a data source unit, and the material area mainly serves to hold corresponding materials for user selection.

[0074] The core role of the component unit is to provide visual display and consumer (which is a user who utilizes the resulting visual data flow for corresponding business handling) interaction elements, which are the part of the final presentation to the data flow consumer, for presenting the processed and converted data in an intuitive and understandable form, and allowing the consumer to perform certain operations (such as clicking, filtering).

[0075] The core role of the data processing unit is to provide data conversion, processing, calculation and logic control function modules. These units act on the original data obtained from the data source, and shape them into a format suitable for component display or to meet specific business needs.

[0076] The core role of the data source unit is to provide an entry point for connecting and obtaining raw data. These units are responsible for interacting with external systems, services or storage, and introducing data into the data flow editor.

[0077] As shown in Figure 2 , a visual state of a data flow editor module is shown. The left side is a material area, which is provided with component units, data processing units, data source units, Figure 2 , which displays the component units, which are provided with buttons, maps, dashboards, tables, column charts, gradient texts, texts and other components, of course, other components can also be set based on requirements. In order to clearly show Figure 2 the structure of the material area, the overall state of the data flow editor module is not all screenshot, only the left part of the material area and the left part of the drawing board area are displayed.

[0078] In Figure 2 , the user selects the component unit, so only the component materials included in the component unit are displayed. At the same time, when the user selects the data processing unit and the data source unit, custom, local data, blueprint jump, time to year, etc. Data processing materials can also be displayed in this material area, or test third-party components, test data components, alarm processing conditions, etc. Data source materials.

[0079] The right side of the component unit is the drawing board area, which mainly serves to carry the component layout and supports real-time rendering. It can hold the materials selected by the user in the material area and add them as nodes to the drawing board area, which is used to generate a visual data flow. In Figure 2 , the user has not added nodes to the drawing board area, so the drawing board area is still blank at this time.

[0080] The configuration area is used to display the configuration content added to the node in the drawing board area. When the user does not select the node, the configuration area is a hidden area. When the user clicks the corresponding node, the configuration area corresponding to the node is displayed. The configuration area can be arranged on the right side of the drawing board area.

[0081] The configuration area centrally manages the component attributes and is linked with the data flow editor module to ensure the transparency and controllability of the data flow.

[0082] S102: Based on the user's drag operation, the components in the component unit, the data processing functions in the data processing unit, and the data sources in the data source unit are added to the drawing board area respectively to generate visual component nodes, data processing nodes, and data source nodes.

[0083] The user adds the materials in the component unit, the data processing unit, and the data source unit to the drawing board area as nodes based on the requirements. Figure 3 As shown in the drawing, the user can add the component nodes corresponding to the component materials. Of course, the user can also add data processing nodes, data source nodes, and the like based on the requirements.

[0084] The code is modularized to reduce the redundant logic and improve the maintainability. The virtualization technology is used to optimize the drawing board rendering to support smooth dragging of a large number of components.

[0085] For each type of visual node, the corresponding node color is set to quickly distinguish different nodes.

[0086] S103: Based on the user's triggering of the visual node, the configuration area is displayed, and the visual node is configured through the configuration area. The types of the visual node include component nodes, data processing nodes, and data source nodes. The configuration area includes at least events and related attributes for the visual node.

[0087] For convenience of description, the component nodes, the data processing nodes, and the data source nodes are collectively referred to as visual nodes. As shown in the drawing, Figure 4 Taking the "column chart node" in the component node as an example, when the user selects the column chart node, the configuration area of the node is displayed on the right side. The configuration area includes at least events and related attributes. Taking the column chart node as an example, the events include input items and output events. Of course, in other nodes, the events can also include data processing and other events. The related attributes of the input items include whether to display data, and the output events include whether to click and whether to double-click. When the corresponding related data of the input items flows into the column chart node, the corresponding column chart is generated. When the user applies an action to the column chart node through the selected mode in the output event, the column chart is displayed. Similarly, Figure 2 the data processing nodes and the data source nodes are configured in the same way.Figure 4 Only the right part of the palette area and the configuration area are displayed.

[0088] Of course, for other nodes outside the component node, such as the data source node, the configuration content in the configuration area may be different, for example, when the data source node is a test data component node, the corresponding configuration content events can include update interval, input item, output item, test interface, etc.

[0089] S104: Based on the trigger of the user, the visualization nodes are connected through the connection stake carried in the visualization node to generate a visualization data flow.

[0090] As shown in Figure 5 , each visualization node carries a connection stake. For different node types, the setting position of the corresponding connection stake can be set to make the overall connection line smoother. For example, the input position of the connection stake of the custom data processing node is set at the left middle position, and the output position is set at the right lower position. Based on the user's selection, the visualization nodes are connected to generate a visualization data flow. Of course, Figure 5 the connection relationship in the figure is only an exemplary display of the connection effect and does not represent a real visualization data flow that can be run. In Figure 5 , the business logic of the visualization data flow is: clicking the button to call the interface, returning the data to the interface, and then processing the data through the custom method to meet the table data format, and then passing the data to the table, and the table displays the data.

[0091] After the user generates the visualization data flow, the user can save and exit the data flow editor module, and then click the preview button on the home page to view the successfully rendered page after the configuration is completed. At this time, for example Figure 5 , the user can click the text button on the page, trigger the interface according to the previous visualization data flow connection direction, get the background data, go to the custom data processing node, process it into the data format required by the next component, and successfully display the data in the table.

[0092] 1. The data flow relationship is presented in a visual way, so that the developer can intuitively understand the data interaction logic between components. The input, output, and events of the component can be intuitively configured through the data flow editor, reducing the maintenance difficulty caused by the dispersion of configuration items.

[0093] 2. Modular architecture is adopted to support the extension of new components and new event types. By uniformly managing the data flow and interaction logic, the problem of dispersed configuration items in traditional solutions is avoided, and the secondary development threshold is reduced, improving the flexibility of the system.

[0094] 3. Provide global data state management to make data flow between components more efficient and clear. Use event-driven mechanism to support dynamic interaction between components, such as data transfer, state synchronization, etc.

[0095] 4. Optimize the performance of the drawing board through virtualization rendering technology, even if multiple components are dragged, the performance can still be smooth. Use efficient data flow calculation method to reduce unnecessary calculation overhead.

[0096] Through actual test verification, the advantages of the embodiments of the present application compared with the traditional scheme are shown in Table 1 as follows:

[0097] Table 1 Actual test result table

[0098]

[0099] In one embodiment, after the user edits the visual data flow, the user can trigger a logical test on the visual data flow based on the user's trigger. The user's trigger can be clicking a related test button in the data flow editor module. The logical test is mainly used to test whether the visual data flow has any abnormalities in data processing logic. The trigger position can be in the data flow editor module or in the successfully rendered page.

[0100] Determine the verification rules that have been set, including basic verification rules and custom verification rules. Verification rules refer to performing corresponding actions on the obtained visual data flow through automatic scripts based on the verification process in the verification rules, so as to determine whether the visual data flow can normally execute the action. The basic verification rule refers to the rule that needs to be performed and is pre-set for all scenarios, and the custom verification rule is a verification rule defined by the user for each application scenario.

[0101] Based on the basic verification rule, the data type output by the upstream node is tested according to the data type processing authority of the downstream node. Different visual nodes can process and output different data types. For the basic verification rule, it mainly verifies whether the data authority is correct, which ensures that the visual data flow can run normally.

[0102] Based on the user's selection, the application scenario to which the current visualization data flow belongs is determined, and according to the application scenario, the corresponding custom verification rule is selected from the corresponding rule library and added to the logic test this time. When the user pre-generates some custom verification rules, they can be added to the corresponding rule library. In this rule library, the corresponding tags can also be set for each custom verification rule, and the tags are used to describe the application scenario that the custom verification rule is applicable to. When generating a visualization data flow, the user can select the current edited application scenario, and the data flow editor module can select the matching visualization nodes, custom verification rules, etc. with corresponding tags according to the scenario for preferential display, such as improving the display order or enhancing the display method.

[0103] Based on the custom verification rule, the data content output by the upstream node is tested according to the data content processing flow of the downstream node. In addition to the basic verification rule, the custom verification rule selected automatically or manually by the user can also be tested.

[0104] For the connection state between the connected visualization nodes, the corresponding connection line color, connection line shape, and connection line text representation content are set.

[0105] When testing, if the node is normal, the test passes, and a normal connection line is displayed, as shown in Figure 6 The connection line can include solid lines, dashed lines, different thicknesses, different colors, and other forms. If the test fails, a certain node in the visualization data flow cannot process the data type output by the upstream node or cannot implement the corresponding business requirements, etc., resulting in a failed test, and the node and the upstream node can be marked with "link failure" or similar text on the connection line.

[0106] Further, the application scenario can include a financial scenario, which is usually applied in e-commerce platforms, payment services, etc. The role of the visualization data flow can include: transmitting transaction data between the client and the cloud, charging user accounts according to transaction data, generating corresponding reports according to transaction data, etc. For the financial scenario, the data is often sensitive and needs to be strictly guaranteed to be consistent with the upstream and downstream data transmission.

[0107] Based on this, the data transaction content is determined, and based on the security sandbox set in the data flow editor module, the corresponding first data fingerprint is generated for the data transaction content. The data transaction content can include the user's transaction record (such as transaction amount, time, transaction item, etc.), and the security sandbox is a virtual environment that can be used for secure isolation of code or files, and its core function is to run risky operations in a controlled independent space to prevent damage to real systems or data. At this time, by isolating through the sandbox, the first data fingerprint is calculated in an independent environment to avoid interference by malicious nodes.

[0108] The data transaction content carrying the empty fingerprint slot is entered into the visual data flow. The empty fingerprint slot is a placeholder and has no actual value. The main function of the empty fingerprint slot is to store the corresponding data fingerprint later.

[0109] Based on the self-defined verification rule, according to the configuration content of the downstream node in the configuration area, it is determined that the downstream node is a key node. The key node can be a fund operation type node (such as a payment instruction generation node, a clearing and settlement triggering node, a cross-border remittance routing node, etc.), a sensitive data exposure node (such as a transaction report generation node, a customer information decryption node), and the configuration content thereof can include an account credential field, a real-time fund export interface, etc.

[0110] For the downstream node, the data transaction content output by the upstream node is received, and the data transaction content is subjected to hash calculation to obtain the second data fingerprint corresponding to the data transaction content. As a downstream node of the key node, when it receives the data transaction content output by the upstream node, it calculates the second data fingerprint itself.

[0111] The second data fingerprint is matched with the first data fingerprint in the security sandbox. If the matching is successful, the test is passed. If the matching fails, it is considered that there may be a node with data processing abnormalities in the upstream node during data transmission.

[0112] Of course, based on the demand, the corresponding attack node can also be added temporarily to attack some nodes for simple testing of the anti-attack performance of the visual data flow.

[0113] In addition to the financial scenario, common application scenarios can also include data preprocessing scenarios such as data cleaning and data structuring.

[0114] According to the node type and the configuration content in the configuration area, it is determined that the upstream node is a data preprocessing node. When the upstream node is a data preprocessing node, the output content thereof will include the preprocessing result of the data.

[0115] For the downstream node, the first data preprocessing result output by the upstream node is received, and the first data structural degree corresponding to the first data preprocessing result is determined. The data structural degree can be determined by calculating the entropy ratio of the data, for example, the degree of disorder of the data is represented by Shannon entropy, and the corresponding structural score is obtained by 1-[Shannon entropy(data) / Shannon entropy(random data)]. Of course, the data structural degree can also be corrected by combining other dimensions such as data type, for example, the data structural degree score of int, date and other mandatory type data types is increased, or the data structural degree is increased or decreased according to whether it contains mandatory fields or preset disorder fields.

[0116] Based on the visual data flow, it is determined whether there is a data preprocessing node upstream of the upstream node; if so, the closest data preprocessing node upstream of the upstream node is taken as the specified node, and the second data structural degree of the second data preprocessing result output by the specified node is determined. At this time, the downstream node can establish a temporary data connection relationship with the specified node. Since the specified node and the upstream node of the downstream node are data preprocessing nodes of the same type, both can be connected with the downstream node, and the downstream node can receive the corresponding data preprocessing result and determine the corresponding data structural degree.

[0117] If the first data structural degree is higher than the second data structural degree, it is considered that the first data preprocessing result of the upstream node is further data preprocessing on the second data preprocessing result of the specified node, which is tested. If the first data structural degree is lower, it is considered that the upstream node may not have performed the data preprocessing process normally.

[0118] In one embodiment, as shown in Figure 7 During the editing process of the visual data flow and the actual data flow running process, there may be multiple downstream nodes corresponding to the same upstream node. Among them, Figure 7 This is only an example and does not represent the actual visual data flow that can be achieved.

[0119] At this time, based on the user's triggering of the connection line between the multiple downstream nodes and the same upstream node, the configuration area is displayed. In addition to the node, the configuration area can also configure the content of the connection line, in addition to the shape and color of the connection line, the corresponding function of the connection line can also be configured.

[0120] The data flow real-time display function, the data flow statistics function, and the data flow playback function of the connection line are configured through a configuration area. For a plurality of downstream nodes corresponding to a same upstream node, performance problems caused by parallel transmission are likely to occur. Therefore, the corresponding functions are set for the data flow received on each connection line.

[0121] In actual operation of the visualized data flow, the data flow real-time display function is used to display the real-time flow corresponding to each connection line at the current time. The flow refers to the amount of data passing through the connection line per unit time. The connection line is selected instead of the node because the node can face a plurality of nodes. If the node has a problem, it is difficult to estimate which node at the other end has a synchronous problem. However, the flow monitoring on the connection line can be specific to the two nodes that transmit the data.

[0122] The data flow statistics function is used to display the total flow corresponding to each connection line in a preset time period. For example, the total flow of the connection line in the last 1 minute can be obtained.

[0123] The data flow playback function is used to display the real-time flow corresponding to each connection line at a historical time. For example, the real-time flow of the connection line 10 minutes ago is displayed.

[0124] During configuration, the user can select whether to enable each function, which connection lines to perform corresponding flow monitoring, the time length of the preset time period in the data flow statistics function and the data flow playback function, and other functions. In this way, the consumer can call the corresponding flow monitoring function to visually monitor the data flow in the actual business processing process when using the data flow.

[0125] Further, on the basis of flow monitoring, the user can be further configured with an abnormality tracking function to enable the consumer to quickly track the abnormal position in a complex environment of a plurality of downstream nodes.

[0126] Based on the trigger of the user, a configuration area of an abnormality tracking sandbox is displayed, and the configuration area of the abnormality tracking sandbox is associated with the configuration area of the connection line. The association mainly refers to which connection line is tracked by the abnormality tracking sandbox, so that the corresponding association is set. The output interface provided by the related flow parameter in the configuration area of the connection line is used to obtain the corresponding flow parameter.

[0127] Based on the configuration area of the abnormality tracking sandbox, the abnormality tracking function and the data flow holographic snapshot function contained in the abnormality tracking sandbox are set.

[0128] The abnormality tracking function is used to start when the real-time traffic of each connection line at the current time exceeds the preset traffic, triggering the data flow holographic snapshot function. That is, when the real-time traffic exceeds the preset traffic, it is considered that the data transmission process of the connection line may be abnormal, and at this time, the data flow holographic snapshot function is triggered.

[0129] The data flow holographic snapshot function is used to obtain the corresponding data flow snapshot according to the user-set frequency, for the data flow of the user-set visual node and connection line. The data flow snapshot refers to the snapshot of the data transmission process of the entire data flow (of course, if the user only sets part of the visual node, it can be for the part of the visual node) at the current time. The data flow snapshot can include the current node state (such as memory data, configuration parameters, processing time consumption), connection line state (such as the type, size, and check value of the data in transmission), and environmental context (such as system load and other external factors), so that when a real abnormality occurs, the consumption card can quickly and clearly determine the location of the abnormality.

[0130] When setting, the user can set the preset traffic that needs to be exceeded by the real-time traffic, the range of data flow snapshot, the snapshot frequency, the snapshot storage time, and the like.

[0131] In an embodiment, since there are many materials (including components, data sources, data processing, and the like) in the material area, it can be difficult for the user to quickly find the required material.

[0132] Based on this, a corresponding AI conversation function is set, which is used to quickly find the required material of the user according to the description of the user.

[0133] Specifically, the function description of the required material input by the user is obtained, and a corresponding dialog box is set in the material area. The user can input the function description in the dialog box.

[0134] First, the function description input by the user can be used as a keyword to search all materials to determine whether there is a corresponding material. If not, based on the function description and all materials included in the material area, a corresponding specified material is output by a large language model. According to the function description and all materials, a prompt word is generated, and a large language model is used to understand the intention of the user, so as to find the required material of the user in all materials. In the material area, the specified material is rendered and displayed, such as highlighted display, improved display order, shielding of other materials, and the like.

[0135] As shown in Figure 8 The embodiment of the present application also provides a visual data flow weaving device for a zero-code platform, which comprises:

[0136] at least one processor; and

[0137] a memory in communication with the at least one processor; wherein

[0138] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method for visualizing data flow weaving for a zero-code platform according to any one of the preceding embodiments.

[0139] The embodiments of the present application also provide a non-volatile computer storage medium, which stores computer executable instructions configured to implement the method for visualizing data flow weaving for a zero-code platform according to any one of the preceding embodiments.

[0140] Each of the embodiments of the present application is described in a progressive manner, and the same or similar parts of each of the embodiments can be referred to each other. Each of the embodiments mainly describes the difference from other embodiments. In particular, the device and medium embodiments are basically similar to the method embodiments, and thus the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0141] The device and medium provided by the embodiments of the present application are one-to-one corresponding to the method, and thus the device and medium also have the similar beneficial technical effects as the method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the device and medium will not be described here.

[0142] The above only describes the embodiments of the present application and is not intended to limit the present application. The present application can have various changes and modifications for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the scope of the claims of the present application.

Claims

1. A visual data flow weaving method for no-code platforms, characterized in that, include: The data flow editor module is launched and visualized based on user triggers. The data flow editor module includes a material area, a canvas area, and a configuration area; the material area includes component units, a data processing unit, and a data source unit. Based on the user's drag-and-drop operation, the components in the component unit, the data processing function in the data processing unit, and the data source in the data source unit are added to the canvas area, respectively generating visual component nodes, data processing nodes, and data source nodes; Based on user triggering of the visualization node, the configuration area is displayed, and the visualization node is configured through the configuration area; the types of visualization nodes include component nodes, data processing nodes, and data source nodes; The configuration area for the visualization node includes at least events and related attributes; Based on user triggers, the visualization nodes are connected through the connection stubs carried in the visualization nodes to generate a visualization data stream; The method further includes: Based on user triggers, a logical test is determined to be performed on the visualized data stream; Determine the established verification rules, which include basic verification rules and custom verification rules; Based on the aforementioned basic verification rules, the data type processing permissions of the upstream node and the downstream node are tested according to the data type output by the upstream node. Based on the user's selection, the application scenario to which the current visualized data stream belongs is determined, and according to the application scenario, the corresponding custom verification rule is selected from the corresponding rule base and added to the current logic test; Based on the custom verification rules, the data content output by the upstream node and the data content processing flow of the downstream node are tested. Based on the aforementioned custom verification rules, tests are conducted on the data content output by the upstream node and the data processing flow of the downstream node, specifically including: The data transaction content is determined, and a corresponding first data fingerprint is generated for the data transaction content based on the security sandbox set in the data stream editor module. The data transaction content carrying empty fingerprint slots is entered into the visualized data stream; Based on the custom verification rules, and according to the configuration content of the downstream node in the configuration area, the downstream node is determined to be a critical node; For the downstream node, the data transaction content output by the upstream node is received, and the data transaction content is hashed to obtain the second data fingerprint corresponding to the data transaction content. The second data fingerprint is matched with the first data fingerprint in the security sandbox. If the match is successful, the test is passed.

2. The visual data flow weaving method for a no-code platform according to claim 1, characterized in that, Based on the aforementioned custom verification rules, tests are conducted on the data content output by the upstream node and the data processing flow of the downstream node, specifically including: Based on the node type and the configuration content in the configuration area, the upstream node is determined to be a data preprocessing node; For downstream nodes, the first data preprocessing result output by the upstream node is received, and the first data structuring degree corresponding to the first data preprocessing result is determined; Based on the visualized data stream, determine whether there is a data preprocessing node upstream of the upstream node; If it exists, the nearest upstream data preprocessing node of the upstream node is taken as the designated node, and the second data structuring degree of the second data preprocessing result output by the designated node is determined. If the first data has a higher degree of structuring than the second data, then the test is passed.

3. The visual data flow weaving method for a no-code platform according to claim 1, characterized in that, The method further includes: It is determined that in the visualized data stream, there are multiple downstream nodes that correspond to the same upstream node; The configuration area is displayed based on user triggering of the connection lines between the multiple downstream nodes and the same upstream node; The configuration area allows you to configure the real-time data traffic display, data traffic statistics, and data traffic playback functions for the connection line. In the actual operation of the visualized data stream, the real-time data flow display function is used to display the real-time flow corresponding to each connection line at the current moment; the data flow statistics function is used to display the total flow corresponding to each connection line within a preset time period; and the data flow playback function is used to display the real-time flow corresponding to each connection line at a historical moment.

4. The visual data flow weaving method for a no-code platform according to claim 3, characterized in that, The method further includes: Based on user triggers, the configuration area of ​​the anomaly tracking sandbox is displayed, and the configuration area of ​​the anomaly tracking sandbox is associated with the configuration area of ​​the connecting line; Based on the configuration area of ​​the anomaly tracking sandbox, the anomaly tracking function and data stream holographic snapshot function contained in the anomaly tracking sandbox are configured; The anomaly tracking function is activated when the real-time traffic of each connection line exceeds a preset traffic, triggering the data stream holographic snapshot function. The data stream holographic snapshot function is used to obtain corresponding data stream snapshots of the data streams of the user-defined visualization nodes and connection lines at a frequency set by the user.

5. The visual data flow weaving method for a no-code platform according to claim 1, characterized in that, The method further includes: Obtain the user's input regarding the function description of the required material; Based on the functional description and all materials included in the material area, the corresponding specified material is output through the large language model; In the material area, the specified material is rendered and displayed.

6. The visual data flow weaving method for a no-code platform according to claim 1, characterized in that, The method further includes: For each type of visual node, set the corresponding node color and the corresponding location of the connection stake; For the connection status between connected visual nodes, set the corresponding connection line color, connection line shape, and connection line text representation.

7. A visual data stream weaving device for a no-code platform, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the visual data flow weaving method for a no-code platform as described in any one of claims 1 to 6.

8. A non-volatile computer storage medium storing computer-executable instructions, characterized in that, The computer-executable instructions are configured to implement the visual data flow weaving method for a zero-code platform as described in any one of claims 1 to 6.

Images