Interaction method for constructing data processing flow in graphical user interface

Abstract

The invention discloses an interaction method for constructing a data processing flow in a graphical user interface. According to the method, a data block capable of adapting to multi-industry requirements is provided as a unified interaction component, so that a user can intuitively construct a data processing network by recursively adding the block, visually connecting the configured data flow and automatically executing an updating mode. The core of the method is that multiple types of data blocks are provided, and different numbers and different types of format units and logic units are predefined in different types of data blocks to respectively match specific data processing requirements of different industries such as finance, medical treatment, logistics and the like, so that wide cross-industry adaptability is realized. Based on the unified interaction normal form, the invention further realizes the template multiplexing of the data processing network, supports multi-user collaborative editing and compiles and outputs the data processing network as an embedded code or an executable program.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer human-computer interaction, and in particular to a method and system for constructing a data processing flow through visual interaction in a graphical user interface. BACKGROUND

[0002] Current data processing software generally adopts a discrete operation mode of "menu-dialog", and users need to switch between different interfaces to configure data sources, processing logic and output targets. This mode causes the interruption of the operation flow, the non-intuitive data processing logic, the low efficiency of configuration and the error-prone. At the same time, the data model of the existing tool is usually fixed and single, which cannot be flexibly adapted to the specific data format and processing logic of different industries. For example, the financial industry needs to process high-frequency two-dimensional table data, the medical industry needs to process image files and structured medical records at the same time, and the Internet of Things industry needs to process continuous time series data flow. The existing technology lacks a solution that can provide native support for these diverse industries through a unified interaction paradigm, resulting in a rigid system, poor reusability and high development cost when applied across industries. SUMMARY

[0003] The purpose of the present application is to overcome the dual defects of discrete interaction mode and rigid data model in the prior art, and to provide an interactive method for constructing a data processing flow in a graphical user interface. This method not only pursues the innovation of the interactive experience, but also strives to fundamentally improve the cross-industry adaptability of the solution by providing a series of pre-defined core components for different industries, and naturally derives a series of advanced features such as automation, reusability, collaboration and productization.

[0004] To achieve the above-mentioned purpose, the present application adopts the following technical solutions: An interactive method for constructing a data processing flow in a graphical user interface, characterized in that it comprises the following steps: Step S100: providing industry-adapted data blocks. Presenting data blocks in the graphical user interface. The key is that the method provides multiple types of data blocks. Different types of data blocks have different combinations of different numbers and types of data format units and logic units pre-defined therein to match the specific data processing needs of different industries. For example, a data block pre-defined for the financial industry may have a set of units for processing two-dimensional tables; a block pre-defined for the medical industry may have two sets of units for processing images and tables respectively; a block pre-defined for the Internet of Things industry has a set of units for processing real-time data flow; Step S200: recursively adding data blocks. In response to the user's addition operation, the user selects the required type of block from the block library and adds it to the interface. This operation is recursive, and the user can continuously expand the flow based on the existing blocks; Step S300: configuring logic with data source through visual operation. For at least one data block as the current block, in response to the configuration operation of the user: S310: setting processing rule: setting a processing rule for the logic unit of the current block; S320: specifying data input source: through a visual connection operation (including dragging a connection line and menu selection), the data input source of the logic unit of the current block is specified as the data format unit of another data block; Step S400: automatic execution and update. In response to the trigger, the configured current block is automatically executed, so that the logic unit reads the connected source data, processes the result data and outputs the result data to the data format unit of the current block and updates the display; By recursively adding and configuring multiple data blocks, a data processing network can be constructed, and data can be automatically transmitted and processed along the connection relationship in the network; The method further comprises advanced functions: saving the configured data processing network as a template file and reconstructing reuse; supporting multi-user collaborative editing of the same data processing network; converting the data processing network into embedded code or executable program. Advantages

[0005] Compared with the prior art, the present application brings systematic and multi-level technical progress: 1. Fundamental improvement of interaction efficiency and process transparency: through the continuous interaction of "unified control" and "visual connection", the discrete menu and dialog box are replaced, so that the process construction becomes a coherent and immersive process. At the same time, the entire data processing process is completely presented in an intuitive topological structure and is self-evident; 2. Precise multi-industry data adaptability and solution portability: by providing a variety of pre-defined, industry-specific data blocks, the present application enables the same set of interactive systems to precisely adapt to the specific needs of different fields such as finance, medicine, logistics and Internet of Things. Users do not need to modify the underlying architecture, but only need to select the appropriate block to quickly build a professional process, greatly improving the practicality and promotional value of the technology; 3. Natural integration and collaboration of advanced functions: based on the above unified and flexible interaction paradigm, complex network construction, template reuse, multi-user collaboration and code compilation output can be seamlessly integrated, forming a strong technical synergy effect, providing a whole value far beyond the simple superposition of individual functions. BRIEF DESCRIPTION OF DRAWINGS

[0006] The following is explained: Figure 1 : System initial interface and data block library schematic diagram; Figure 2: Schematic diagram of the internal structure of a data block (examples from multiple industries); Figure 3 : Schematic diagram of two implementation methods for visual connection operations; Figure 4 : Schematic diagram of automatic execution and update of data processing network; Figure 5 Templated reuse flowchart; Figure 6 : A diagram illustrating multi-user collaborative editing; Figure 7 : Flowchart of code compilation output. Detailed Implementation

[0007] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0008] 1. System initialization and core components (supporting claims 1 and 2) like Figure 1 As shown, after the system starts, a data block library (106) is provided next to the canvas (101) area of ​​the graphical user interface (100). This block library contains various predefined types of data blocks, such as "financial transaction blocks", "medical imaging blocks", and "Internet of Things sensor blocks". Users can drag and drop the required blocks from the library onto the canvas (101) according to their business scenarios. For example, they can first drag in a "financial transaction block" as the initial data block (102). One of the key innovations of this invention is that the internal structure of these data blocks is customized for specific industries. For example... Figure 2 As shown: a, a predefined block for the financial industry (102), which integrates a set of logical units (102a) and a set of data format units (102b), which are optimized for displaying and processing two-dimensional tabular data in CSV or Excel format; b is a predefined block for the medical industry, which integrates two sets of unit pairs: the first set of logical units (102a-1) and data format units (102b-1) is used to process image files in formats such as DICOM; the second set of logical units (102a-2) and data format units (102b-2) is used to process structured patient information tables. c is a predefined block for the Internet of Things industry, which integrates a set of logic units (102a) and data format units (102b). The data format unit is specifically designed to receive, cache, and display real-time sensor data streams in JSON format. This "one industry, one block" design is a direct manifestation of claim 2 and the core of achieving clear and efficient cross-industry adaptation.

[0009] 2. Process construction and visual configuration (supporting claims 1 and 3) The user drags another "data statistics block" from the block repository (106) onto the canvas as the subsequent data block (104). The user then configures block (104): First, the user selects "Monthly Summary" as the processing rule in their logical unit; Next, as Figure 3 As shown, users need to perform a visual connection operation to specify the data source. This invention supports two preferred methods: • Method A (Drag and Drop): Suitable for scenarios with simple network structures and intuitive connections. Users can drag a visual connection line (105) from block (104) to the data format unit of the target block (102); • Method B (Menu Selection): When the data processing network becomes larger and more complex, making it difficult to accurately locate the target by dragging, users can click on the connection anchor point to bring up a menu or list and select the target from all available data blocks. This configuration process completes the construction of the data processing network.

[0010] 3. Automated execution and advanced functions (supporting claims 3, 4, 5, and 6) Once configured, the user triggers execution. The system automatically drives the process, such as... Figure 4 As shown, data flows from the source block (102) to the processing block (104), and the results are automatically updated to the display area of ​​(104). Based on this core interaction, advanced functions are enabled: • Template reuse Figure 5 ): Corresponding to claim 4, the user can Figure 4 The configured network shown is saved as a template. When it is necessary to analyze the data of the new month, the entire process can be reconstructed with one click by calling this template. It can be executed automatically by only updating the source data of block (102), realizing the efficient reuse of processing logic; Multi-user collaborative editing ( Figure 6 Corresponding to claim 5, in a team environment, user A (data analyst) and user B (business expert) can simultaneously edit the same data processing network. User A is responsible for configuring the cleaning rules of the "data statistics block" (104), while user B is responsible for maintaining the data quality of the "financial transaction block" (102), thus achieving efficient distributed collaboration. • Code compilation output ( Figure 7Corresponding to claim 6, the user wishes to deploy this data analysis process as an automated script. He selects the entire network, chooses "Generate Python Script" to output the logic, and the system parses the network topology and rules, generating an equivalent, independently executable Python code file, thus bridging the path from visual design to product deployment.

[0011] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An interactive method for constructing a data processing flow in a graphical user interface, characterized in that, include: The graphical user interface presents data blocks, wherein each data block integrates at least one set of data format units and logic units; In response to the user's add operation, add data blocks to the interface; For at least one data block that is the current block, respond to the user's configuration operation: a) Define a processing rule for its logic unit; b) By means of a visual connection operation, the data input source of the logical unit of the current block is specified as the data format unit of another data block; In response to a trigger, the current block with the pre-defined rules is automatically executed, causing its logic unit to read data from the data format unit of the other connected data block. After processing, the result data is output to the current block's own data format unit for updating and display.

2. The method as described in claim 1, characterized in that: The method provides multiple types of data blocks, each with a predefined combination of different numbers and types of data format units and logical units to match the specific data processing needs of different industries.

3. The method as described in claim 1, characterized in that: A data processing network is constructed by recursively adding and configuring multiple data blocks and establishing visual connections between them. When execution is triggered, data can be automatically transmitted along the connections configured in the data processing network and processed sequentially by the logical units of each level of data block.

4. The method as described in claim 3, characterized in that, The method further includes: Save the configured data processing network, which consists of multiple data blocks and visual connection lines between them, as a template file. In response to a user requesting the template file, the data processing network is reconstructed in the graphical user interface; By updating the data format unit of any data block in the network, the network is triggered to execute automatically, thereby reusing the data processing logic embedded in the template.

5. The method as described in claim 3, characterized in that: During the construction of the data processing network, the multiple data blocks allow different users to add and edit the configuration of their respective logical units and data input sources.

6. The method as described in claim 3, characterized in that, The method further includes an output generation step: It provides multiple output logics, which are used to convert the structure and rules of the data processing network or a subset thereof into the target application format; In response to the user's selection of an output logic and the specification of all or part of the data processing network as source data, a transformation operation is performed to generate the corresponding target content; The target application format includes, but is not limited to, embedded code snippets or standalone executable programs.

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