CN118034665A

CN118034665A - Low-code platform-oriented data processing method and device, electronic equipment and medium

Info

Publication number: CN118034665A
Application number: CN202311767420.8A
Authority: CN
Inventors: 律小娇
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2023-12-20
Filing date: 2023-12-20
Publication date: 2024-05-14

Abstract

The disclosure provides a low-code platform-oriented data processing method and device, electronic equipment and medium, which relate to the field of data processing, in particular to the fields of low-code development, visual development and the like. The specific implementation scheme is as follows: acquiring data processing examples respectively corresponding to a plurality of execution nodes in the canvas; determining the execution sequence of a plurality of data processing examples according to the connection relation of a plurality of execution nodes; and executing the plurality of data processing examples through the shared data pool according to the execution sequence of the plurality of data processing examples, and processing the input data to obtain output data.

Description

Low-code platform-oriented data processing method and device, electronic equipment and medium

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to the technical field of low code development, visual development, and the like. In particular, the disclosure relates to a data processing method and device, an electronic device and a computer readable storage medium for a low code platform.

Background

A Low Code Development Platform (LCDP) is a development platform that can quickly generate applications without or with little code.

With the development of technology, more and more enterprises choose to use low-code development platforms for the development of business applications.

Disclosure of Invention

The disclosure provides a data processing method and device for a low-code platform, electronic equipment and a computer readable storage medium.

According to a first aspect of the present disclosure, there is provided a data processing method for a low code platform, the method comprising:

Acquiring data processing examples respectively corresponding to a plurality of execution nodes in the canvas;

Determining the execution sequence of a plurality of data processing examples according to the connection relation of a plurality of execution nodes;

And executing the plurality of data processing examples through the shared data pool according to the execution sequence of the plurality of data processing examples, and processing the input data to obtain output data.

According to a second aspect of the present disclosure there is provided a low code platform oriented data processing apparatus, the apparatus comprising:

the data acquisition module is used for acquiring data processing examples corresponding to a plurality of execution nodes in the canvas respectively;

the first execution module is used for determining the execution sequence of a plurality of data processing examples according to the connection relation of a plurality of execution nodes;

And the second execution module is used for executing the plurality of data processing examples through the shared data pool according to the execution sequence of the plurality of data processing examples and processing the input data to obtain output data.

According to a third aspect of the present disclosure, there is provided an electronic device comprising:

At least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the low code platform oriented data processing method.

According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the above-described low code platform-oriented data processing method.

According to a fifth aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the low code platform oriented data processing method described above.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow chart of a low code platform oriented data processing method provided in an embodiment of the present disclosure;

FIG. 2 is a schematic diagram illustrating the composition of an initialized visual interface in a low-code platform-oriented data processing method according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of canvas functionality in a low code platform oriented data processing method provided by an embodiment of the present disclosure;

FIG. 4 is a flowchart illustrating some steps of a low code platform oriented data processing method according to an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of a visual interface in a low code platform oriented data processing method according to an embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a low code platform oriented data processing apparatus according to an embodiment of the present disclosure;

FIG. 7 is a block diagram of an electronic device for implementing a low code platform oriented data processing method of an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In some related technologies, nodes are configured on a visual interaction platform, node relationships are set, then a result is exported to generate a function containing processing logic on a low-code platform, and codes are executed on a third-party library, so that time waste of users and waste of computing resources are caused by frequent platform switching.

The embodiment of the disclosure provides a data processing method and device for a low-code platform, electronic equipment and a computer readable storage medium, and aims to solve at least one of the technical problems in the prior art.

The data processing method for the low-code platform provided by the embodiment of the disclosure may be executed by electronic devices such as a terminal device or a server, where the terminal device may be a vehicle-mounted device, a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal digital assistant (Personal DIGITAL ASSISTANT, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, and the method may be implemented by a processor invoking computer readable program instructions stored in a memory. Or the method may be performed by a server.

Fig. 1 shows a flowchart of a low code platform oriented data processing method according to an embodiment of the present disclosure. As shown in fig. 1, the low code platform oriented data processing method provided by the embodiment of the present disclosure may include step S110, step S120, and step S130.

In step S110, data processing examples corresponding to a plurality of execution nodes in the canvas are obtained;

in step S120, determining an execution order of the plurality of data processing instances according to the connection relationships of the plurality of execution nodes;

In step S130, the plurality of data processing instances are executed by sharing the data pool according to the execution order of the plurality of data processing instances, and the input data is processed to obtain the output data.

For example, the data processing method provided by the embodiments of the present disclosure may be used for a low code platform.

The low-code platform is a platform for low-code development, the low-code development is an application development method, fewer codes are used for delivering application programs at a high speed, the codes which are not wanted to be developed by a platform user are automatically generated, and the code development efficiency is improved.

In some possible implementations, in step S110, the canvas may be a canvas of a visual interface of a low code platform on which drawing of shapes may be implemented by an input tool such as a mouse.

In some possible implementations, the execution node of the canvas may refer to a particular shape drawn on the canvas. The data processing instance corresponding to each execution node may be a pre-generated data processing instance generated according to logic corresponding to the execution node that processes data.

In some possible implementations, the data processing instance corresponding to the execution node is stored in an executor corresponding to the low code platform.

In some specific implementations, the executing node corresponds to an Action instance registered through ActionRegister (Action buffer).

In some possible implementations, in step S120, the connection relation of the plurality of execution nodes may be determined according to a connection tool drawn between the execution nodes. In case there is a connection tool between two execution nodes, the execution order of the two execution nodes is adjacent.

In some specific implementations, the connection tool may be a connection line with an arrow, which connects two execution nodes, and the direction of the arrow is the execution sequence direction of the data processing instance corresponding to the execution node.

In some possible implementations, the connection relationship between the plurality of execution nodes may include a plurality of parallel linear relationships, that is, the execution node a may connect the execution node B and the execution node C at the same time, and the execution node B and the execution node C are respectively connected with other execution nodes, so that the execution sequence of the data processing instance corresponding to the execution node also includes a plurality of parallel execution sequences.

In some possible implementations, in step S130, the executor of the low code platform may perform a data processing instance through the shared data pool, and process the input data to obtain the output data.

The input data may be preset, and is used for inputting data of the data processing instance with the first execution sequence; the output data may be data of a last data processing instance of the execution sequence.

In the data processing method for the low-code platform provided by the embodiment of the disclosure, input data is processed by acquiring the data processing instance corresponding to the execution node in the canvas, and output data is acquired, that is, by setting the execution node in the canvas, the data processing instance corresponding to the execution node can be automatically processed according to the execution node without switching the execution platform, on one hand, the platform user can conveniently adjust the execution node in the canvas in real time according to the data processing execution result (such as the acquired output data), and the development efficiency of the platform user is improved; on the other hand, the occupation of the platform switching on the computing resources is reduced, so that more computing resources can be used for processing the input data, and the data processing efficiency is improved.

The data processing method for the low-code platform provided by the embodiment of the disclosure is specifically described below.

As described above, the canvas may be a canvas of a visual interface of the low code platform, which may be an interface generated upon opening of the low code platform.

In response to a platform user opening the low code platform, the designer of the low code platform may generate an initialized visual interface, FIG. 2 shows a schematic composition of an initialized visual interface, as shown in FIG. 2, comprising a canvas and a node selection panel.

In some possible implementations, the canvas may be a blank canvas. The node selection panel may include node icons corresponding to a plurality of functional nodes, the node icons corresponding to the functional nodes may be vector icons that may be drawn in the canvas, the node icons corresponding to different functional nodes may be different, and each functional node corresponds to one data processing logic.

In some possible implementations, the functional node may include a start node, which is a node for indicating to start data processing, whose execution order of the corresponding data processing instances is generally located in the first bit.

In some possible implementations, the functional nodes may include an end node, which is a node for indicating that the data processing is ended, and the execution sequence of the corresponding data processing instance is generally located in the last bit.

In some possible implementations, the functional nodes may include a logical control node, which is a node for performing a loop, whether or not, etc. logical control.

In some possible implementations, the functional nodes may include variable nodes, which are nodes that are used to implement processing of the variables, such as assigning values to the variables, and the like.

In some possible implementations, the functional nodes may include entity nodes, which are nodes for processing the implementing entity, such as defining the entity, etc.

In some possible implementations, the functional nodes may include service nodes, which are nodes for enabling invocation of external services for processing data.

In some possible implementations, the functional nodes may include a sending mail node, which is a node for implementing sending information by way of mail.

In some possible implementations, the functional nodes may include a sending information node, which is a node for implementing sending information using a non-mail manner.

In some possible implementations, the functional nodes may further include other nodes that may implement data processing logic, which is not described herein, and any data processing logic is within the scope of the embodiments of the present disclosure.

In some possible implementations, in response to a selected operation for a node icon, an execution node is generated at the canvas and a data processing instance corresponding to the execution node is generated according to data processing logic corresponding to the node icon.

The selecting operation for the node icon may be clicking the node icon or dragging the node icon to the canvas. In the case where the node icon corresponding to the function node is a vector icon that can be drawn in the canvas, the vector icon corresponding to the function node may be drawn in the canvas as an execution node.

In some possible implementations, the platform user may change the size, color, etc. of the execution node through the drawing editing function of the canvas to distinguish the execution node from other execution nodes.

In some possible implementations, the canvas may include other functions in addition to drawing the execution nodes.

FIG. 3 illustrates a schematic diagram of functions that a canvas may include, as shown in FIG. 3, as well as wire drawing, node deletion, node dragging, etc. at the canvas.

The connection line drawing refers to that in response to drawing operation of drawing connection lines between two execution nodes, connection lines with arrows for connecting the execution nodes are generated on canvas, and the arrow directions of the connection lines are used for indicating the execution sequence of data processing examples corresponding to the execution nodes.

In some possible implementations, a drawing operation of drawing a connection line between two execution nodes may be implemented by moving between the two execution nodes by long pressing a mouse, a direction of an arrow may be determined according to a direction of the mouse movement (may be an arrow direction consistent with the direction of the mouse movement), and a connection line with an arrow connecting the two execution nodes is generated between the two execution nodes.

The connection line may be a straight line, and the connected arrow is used to indicate an execution sequence of the data processing instance corresponding to the execution node, and the execution sequence of the data processing instance corresponding to the execution node located in the start direction of the arrow precedes the execution sequence of the data processing instance corresponding to the execution node located in the end direction of the arrow.

In some possible implementations, the execution node and the connection line associated with the execution node are deleted at the canvas in response to a delete operation to delete the execution node.

The deleting operation of deleting the executing node can be to click the executing node by using a right button of a mouse, and select to delete on the jumped-out menu interface. A connection associated with an executing node refers to a connection where the beginning or ending of a connection is the executing node.

In some possible implementations, in response to a drag operation that drags an execution node, a position of the execution node at the canvas is modified and a connection line associated with the execution node is regenerated.

The drag operation of dragging the execution node can drag the execution node by pressing the left mouse button for a long time, so that the execution node moves on the canvas, the position of the execution node corresponding to the drag operation at the moment of releasing the left mouse button is taken as the position of the execution node corresponding to the drag operation, and the execution node is regenerated as a connecting line for starting or ending connection on the canvas according to the new position of the execution node.

After the canvas draws the execution node, a data processing instance corresponding to the execution node is required to be generated according to the data processing logic corresponding to the execution node.

FIG. 4 is a flow chart illustrating an implementation manner of generating a data processing instance corresponding to an execution node according to data processing logic corresponding to the execution node, and as shown in FIG. 4, generating the data processing instance corresponding to the execution node according to the data processing logic corresponding to the execution node may include step S410 and step S420.

In step S410, in response to the configuration node operation for configuring the execution node, a configuration panel for configuring data processing parameters corresponding to the execution node is generated on the visual interface according to the data processing logic corresponding to the execution node;

in step S420, in response to receiving the data processing parameters input to the configuration panel, a data processing instance corresponding to the execution node is generated according to the data processing logic corresponding to the execution node and the data processing parameters.

In some possible implementations, in step S410, the node configuration operation that configures the execution node may be a double-clicking of the execution node of the canvas.

The data processing logic corresponding to the executing node is the data processing logic corresponding to the functional node to which the executing node belongs.

The generation of the configuration panel corresponding to the execution node in the visual interface according to the data processing logic corresponding to the execution node may be the generation of the configuration panel convenient for developing the user input data processing parameters according to the data processing logic corresponding to the execution node and the data processing parameters required by the execution of the data processing logic.

In some specific implementations, names of data processing parameters required by execution of the data processing logic may be displayed on the configuration panel, and an input box may be set at a corresponding position, so that a platform user may conveniently input the corresponding data processing parameters.

In some possible implementations, when the execution node already has a data processing instance, the data processing parameter corresponding to the execution node may be determined according to the data processing instance corresponding to the execution node, and the data processing parameter is displayed at a corresponding position of the configuration panel, so that the platform user may acquire the data processing parameter corresponding to the execution node and modify the data processing parameter.

In some possible implementations, in step S420, in the case of receiving the data processing parameters input by the platform user, the corresponding data processing parameters are written into the corresponding positions of the data processing logic, and the data processing instance corresponding to the execution node is generated.

In some possible implementations, the visual interface may include other functional panels in addition to the configuration panel. FIG. 5 shows a schematic diagram of functional panels included in a visual interface, which may also include a source code panel, a pseudocode panel, a debug panel, a history version panel, as shown in FIG. 5.

In some possible implementations, in response to a view source code operation of viewing source codes corresponding to the execution nodes, generating source codes corresponding to the execution nodes and written in a preset coding language according to data processing examples corresponding to the execution nodes; and generating a source code panel on the visual interface, and displaying the source code corresponding to the execution node on the source code panel.

The source code written in the preset encoding language corresponding to the execution node is generated according to the data processing instance corresponding to the execution node, and the source code written in the preset encoding language corresponding to the function node is generated in advance according to the data processing logic corresponding to the function node. And writing the data processing parameters corresponding to the execution nodes into source codes corresponding to the function nodes corresponding to the execution nodes to generate source codes corresponding to the execution nodes.

The source code panel is generated on the visual interface by hiding the configuration panel, generating the source code panel at the position of the configuration panel, and displaying the source code corresponding to the execution node on the source code panel.

In some possible implementations, in response to a checking pseudo code operation of checking the pseudo code corresponding to the execution node, generating the pseudo code corresponding to the execution node according to the data processing instance corresponding to the execution node; and generating a pseudo code panel on the visual interface, and displaying the pseudo code corresponding to the execution node on the pseudo code panel.

The generating the pseudo code corresponding to the execution node according to the data processing instance corresponding to the execution node may be generating the pseudo code corresponding to the function node in advance according to the data processing logic corresponding to the function node. And writing the data processing parameters corresponding to the execution nodes into the pseudo codes corresponding to the functional nodes corresponding to the execution nodes to generate the pseudo codes corresponding to the execution nodes.

The generation of the pseudo code panel on the visual interface may be to hide the configuration panel, generate the pseudo code panel at the position of the configuration panel, and display the pseudo code corresponding to the execution node on the pseudo code panel.

In some possible implementations, a debug panel is generated at the visual interface, a plurality of data processing instances are executed through a shared data pool according to the execution sequence of the plurality of data processing instances, input data is processed to obtain output data, and a processing procedure for processing the input data to obtain the output data is displayed at the debug panel.

In some specific implementations, according to the execution sequence of the multiple data processing instances, the multiple data processing instances are executed through the shared data pool, and the specific implementation of processing the input data to obtain the output data may be to execute source codes corresponding to the multiple data processing instances according to the execution sequence of the multiple data processing instances, process the input data, and display debug logs generated in the execution process of the source codes on a debug panel.

Generating the debug panel in the visual interface may be hiding the configuration panel, generating the debug panel in the position of the configuration panel, and displaying the debug log generated in the execution process of the source codes on the debug panel.

In some possible implementations, in response to the saving operation, saving the canvas and the data execution instance corresponding to the at least one execution node included in the canvas as a snapshot, and saving snapshot information of the snapshot, the snapshot information including a time of saving the snapshot; responding to a viewing history operation of viewing a history version, generating a history version panel on a visual interface, and displaying snapshot information of the stored snapshot on the history version panel; and responding to the operation of clicking the snapshot information, and generating a canvas according to the snapshot corresponding to the snapshot information.

The saving operation may be to click a save button or a shortcut key, save the canvas as a snapshot, that is, save the current status screenshot of the canvas as a snapshot, or save one or more execution nodes included in the canvas and connection relations of the execution nodes, and generate a snapshot.

The data execution instance corresponding to the execution node can be stored as data corresponding to the snapshot, and the time of generating the snapshot and the user log of executing the snapshot generating operation are stored as snapshot information corresponding to the snapshot.

The snapshot generation canvas corresponding to the snapshot information can be used for directly restoring the corresponding execution nodes of the snapshot and the connection relation between the execution nodes, and the data execution instance corresponding to the execution nodes is given to the data execution nodes.

In some possible implementations, the visual interface may also include an access parameter debugging panel.

The access debugging panel is used for debugging the value, the data type and the data type of the input data of the data processing instance with the first input execution sequence.

In some possible implementations, according to the execution sequence of the plurality of data processing instances, the processing the input data to obtain the output data by executing the plurality of data processing instances through the shared data pool may be to use the input data as the input data of the data processing instance with the first execution sequence, use the output data of each data processing instance as the input data of the data processing instance with the execution sequence located at the subsequent bit, and process the input data of the data processing instance according to the data processing instance through the shared data pool to obtain the output data of each data processing instance.

Based on the same principle as the method shown in fig. 1, fig. 6 shows a schematic structural diagram of a low-code platform oriented data processing apparatus provided by an embodiment of the present disclosure, and as shown in fig. 6, the low-code platform oriented data processing apparatus 60 may include:

a data obtaining module 610, configured to obtain data processing instances corresponding to a plurality of execution nodes in the canvas, respectively;

A first execution module 620, configured to determine an execution order of the plurality of data processing instances according to a connection relationship of the plurality of execution nodes;

The second execution module 630 is configured to execute the plurality of data processing instances by sharing the data pool according to an execution sequence of the plurality of data processing instances, and process the input data to obtain output data.

In the data processing device provided by the embodiment of the disclosure, input data is processed by acquiring the data processing instance corresponding to the execution node in the canvas, and output data is acquired, that is, by setting the execution node in the canvas, the input data can be automatically processed according to the data processing instance corresponding to the execution node without switching the execution platform, on one hand, the platform user can conveniently adjust the execution node in the canvas in real time according to the data processing execution result (such as the acquired output data), and the development efficiency of the platform user is improved; on the other hand, the occupation of the platform switching on the computing resources is reduced, so that more computing resources can be used for processing the input data, and the data processing efficiency is improved.

In some possible implementations, the second execution module 630 is further configured to: and processing the input data of the data processing examples according to the data processing examples by sharing a data pool to obtain the output data of each data processing example.

In some possible implementations, the data processing apparatus further includes: the visualization module is used for generating a visual interface; the visual interface comprises a canvas and a node selection panel, wherein the node selection panel comprises node icons corresponding to a plurality of functional nodes, and each functional node corresponds to one data processing logic; and the instance generating module is used for responding to the selected operation aiming at the node icon, generating an executing node on the canvas and generating a data processing instance corresponding to the executing node according to the data processing logic corresponding to the node icon.

In some possible implementations, the data processing apparatus further includes: and the connecting line drawing module is used for responding to the drawing operation of drawing connecting lines between the two execution nodes, generating the connecting lines with arrows for connecting the execution nodes at the canvas, and the arrow directions of the connecting lines are used for indicating the execution sequence of the data processing examples corresponding to the execution nodes.

In some possible implementations, the data processing apparatus further includes: the node deleting module is used for deleting the execution node and the connecting line related to the execution node in the canvas in response to the deleting operation of deleting the execution node; and the node dragging module is used for responding to the dragging operation of dragging the execution node, modifying the position of the execution node on the canvas and regenerating the connecting line related to the execution node.

In some possible implementations, the instance generation module includes: a node generating unit for generating an executing node at the canvas; the configuration panel unit is used for responding to the configuration node operation of the configuration execution node and generating a configuration panel of the configuration data processing parameters corresponding to the execution node on the visual interface according to the data processing logic corresponding to the execution node; and the configuration parameter unit is used for responding to the received data processing parameters input into the configuration panel and generating a data processing instance corresponding to the execution node according to the data processing logic corresponding to the execution node and the data processing parameters.

In some possible implementations, the configuration panel unit is further configured to: and under the condition that the corresponding data processing examples exist in the execution node, acquiring the data processing parameters corresponding to the execution node, and displaying the data processing parameters on the configuration panel.

In some possible implementations, the data processing apparatus further includes: the source code checking module is used for responding to the checking source code operation corresponding to the source code of the checking execution node, and generating source codes which correspond to the execution node and are written by using a preset coding language according to the data processing instance corresponding to the execution node; and generating a source code panel on the visual interface, and displaying the source code corresponding to the execution node on the source code panel.

In some possible implementations, the data processing apparatus further includes: the pseudo code checking module is used for responding to the checking pseudo code operation of the pseudo code corresponding to the checking execution node and generating the pseudo code corresponding to the execution node according to the data processing instance corresponding to the execution node; and generating a pseudo code panel on the visual interface, and displaying the pseudo code corresponding to the execution node on the pseudo code panel.

In some possible implementations, the data processing apparatus further includes: the history version module is used for responding to the save operation, saving the canvas and the data execution examples corresponding to the at least one execution node included in the canvas as snapshots, saving snapshot information of the snapshots, wherein the snapshot information comprises the time for saving the snapshots; responding to a viewing history operation of viewing a history version, generating a history version panel on a visual interface, and displaying snapshot information of the stored snapshot on the history version panel; and responding to the operation of clicking the snapshot information, and generating a canvas according to the snapshot corresponding to the snapshot information.

In some possible implementations, the functional nodes include at least one of a start node for indicating a start of the process, an end node for indicating an end of the process, a service node for indicating a call to an external service, and a variable node for processing the variable.

In some possible implementations, the second execution module 630 is further configured to: generating a debugging panel on the visual interface, executing a plurality of data processing examples through a shared data pool according to the execution sequence of the plurality of data processing examples, processing input data to obtain output data, and displaying the processing procedure of processing the input data to obtain the output data on the debugging panel.

It will be appreciated that the above-described modules of the low code platform oriented data processing apparatus in the embodiments of the present disclosure have the functionality to implement the corresponding steps of the low code platform oriented data processing method in the embodiment shown in fig. 1. The functions can be realized by hardware, and can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the functions described above. The modules may be software and/or hardware, and each module may be implemented separately or may be implemented by integrating multiple modules. The functional description of each module of the low-code platform-oriented data processing apparatus may be specifically referred to the corresponding description of the low-code platform-oriented data processing method in the embodiment shown in fig. 1, which is not repeated herein.

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the related user personal information all conform to the regulations of related laws and regulations, and the public sequence is not violated.

According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

The electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a low code platform oriented data processing method as provided by embodiments of the present disclosure.

Compared with the prior art, the electronic equipment processes the input data by acquiring the data processing examples corresponding to the execution nodes in the canvas to acquire the output data, namely, by setting the execution nodes in the canvas, the input data can be automatically processed according to the data processing examples corresponding to the execution nodes without switching the execution platform, on one hand, the platform user can conveniently adjust the execution nodes in the canvas in real time according to the data processing execution results (such as the acquired output data), and the development efficiency of the platform user is improved; on the other hand, the occupation of the platform switching on the computing resources is reduced, so that more computing resources can be used for processing the input data, and the data processing efficiency is improved.

The readable storage medium is a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform a low code platform oriented data processing method as provided by an embodiment of the present disclosure.

Compared with the prior art, the readable storage medium processes input data by acquiring the data processing examples corresponding to the execution nodes in the canvas to acquire output data, namely, by setting the execution nodes in the canvas, the input data can be automatically processed according to the data processing examples corresponding to the execution nodes without switching the execution platform, on one hand, the platform user can conveniently adjust the execution nodes in the canvas in real time according to the data processing execution results (such as the acquired output data), and the development efficiency of the platform user is improved; on the other hand, the occupation of the platform switching on the computing resources is reduced, so that more computing resources can be used for processing the input data, and the data processing efficiency is improved.

The computer program product comprises a computer program which, when executed by a processor, implements a low code platform oriented data processing method as provided by embodiments of the present disclosure.

Compared with the prior art, the computer program product processes the input data by acquiring the data processing examples corresponding to the execution nodes in the canvas to acquire the output data, namely, the execution nodes in the canvas are arranged, the data processing examples corresponding to the execution nodes can be automatically processed according to the execution nodes without switching the execution platform, on one hand, the platform user can conveniently adjust the execution nodes in the canvas in real time according to the data processing execution results (such as the acquired output data), and the development efficiency of the platform user is improved; on the other hand, the occupation of the platform switching on the computing resources is reduced, so that more computing resources can be used for processing the input data, and the data processing efficiency is improved.

Fig. 7 shows a schematic block diagram of an example electronic device 800 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 7, the apparatus 700 includes a computing unit 701 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 may also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.

Various components in device 700 are connected to I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, etc.; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, an optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The computing unit 701 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 701 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as a low code platform oriented data processing method. For example, in some embodiments, the low code platform oriented data processing method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 700 via ROM 702 and/or communication unit 709. When a computer program is loaded into RAM 703 and executed by computing unit 701, one or more steps of the low code platform oriented data processing method described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the low code platform oriented data processing method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims

1. A data processing method facing to a low-code platform comprises the following steps:

2. The method of claim 1, wherein the processing the input data to obtain the output data by executing the plurality of data processing instances by sharing a data pool according to an execution order of the plurality of data processing instances comprises:

And taking the input data as the input data of the data processing examples with the first execution sequence, taking the output data of each data processing example as the input data of the data processing examples with the execution sequence positioned at the subsequent position, and processing the input data of the data processing examples according to the data processing examples through a shared data pool to acquire the output data of each data processing example.

3. The method of claim 1, wherein prior to obtaining the behavior instances respectively corresponding to the plurality of execution nodes in the canvas, further comprising:

generating a visual interface; the visual interface comprises a canvas and a node selection panel, wherein the node selection panel comprises node icons corresponding to a plurality of functional nodes, and each functional node corresponds to one data processing logic;

and generating an execution node on the canvas in response to the selected operation for the node icon, and generating a data processing instance corresponding to the execution node according to the data processing logic corresponding to the node icon.

4. The method of claim 3, wherein after the generating the data processing instance corresponding to the executing node according to the data processing logic corresponding to the node icon, further comprises:

and generating a connecting line with an arrow for connecting the execution nodes on the canvas in response to the drawing operation of drawing the connecting line between the two execution nodes, wherein the arrow direction of the connecting line is used for indicating the execution sequence of the data processing examples corresponding to the execution nodes.

5. The method of claim 4, wherein after the generating the data processing instance corresponding to the executing node according to the data processing logic corresponding to the node icon, further comprises:

deleting the execution node and the connection line related to the execution node in the canvas in response to a deletion operation of deleting the execution node;

and in response to a drag operation of dragging the execution node, modifying the position of the execution node on the canvas, and regenerating a connecting line related to the execution node.

6. The method of claim 3, wherein the generating an execution node at the canvas and generating a data processing instance corresponding to the execution node according to the data processing logic corresponding to the node icon comprises:

generating an execution node at the canvas;

Responding to configuration node operation for configuring the execution node, and generating a configuration panel of configuration data processing parameters corresponding to the execution node on the visual interface according to data processing logic corresponding to the execution node;

and responding to the received data processing parameters input into the configuration panel, and generating a data processing instance corresponding to the execution node according to the data processing logic corresponding to the execution node and the data processing parameters.

7. The method of claim 6, wherein the generating, at the visualization interface, a configuration panel of configuration data processing parameters corresponding to the execution node according to data processing logic corresponding to the execution node comprises:

and under the condition that the corresponding data processing instance exists in the execution node, acquiring the data processing parameter corresponding to the execution node, and displaying the data processing parameter on the configuration panel.

8. The method of claim 3, wherein after the generating the data processing instance corresponding to the executing node according to the data processing logic corresponding to the node icon, further comprises:

Responding to the source code checking operation of the source code corresponding to the execution node, and generating source codes which correspond to the execution node and are written by using a preset coding language according to the data processing instance corresponding to the execution node;

and generating a source code panel on the visual interface, and displaying source codes corresponding to the execution nodes on the source code panel.

9. The method of claim 3, wherein after the generating the data processing instance corresponding to the executing node according to the data processing logic corresponding to the node icon, further comprises:

Generating pseudo codes corresponding to the execution nodes according to the data processing examples corresponding to the execution nodes in response to pseudo code checking operation of checking the pseudo codes corresponding to the execution nodes;

and generating a pseudo code panel on the visual interface, and displaying the pseudo code corresponding to the execution node on the pseudo code panel.

10. The method of claim 3, wherein after the generating the data processing instance corresponding to the executing node according to the data processing logic corresponding to the node icon, further comprises:

Responding to a save operation, saving the canvas and the data execution instance corresponding to at least one execution node included in the canvas as a snapshot, and saving snapshot information of the snapshot, wherein the snapshot information comprises the time for saving the snapshot;

responding to a viewing history operation of viewing a history version, generating a history version panel on the visual interface, and displaying snapshot information of the stored snapshot on the history version panel;

And responding to the operation of clicking the snapshot information, and generating canvas according to the snapshot corresponding to the snapshot information.

11. A method according to claim 3, wherein the functional nodes comprise at least one of a start node for indicating a start of processing, an end node for indicating an end of processing, a service node for indicating a call to an external service, a variable node for processing a variable.

12. A method according to claim 3, wherein said processing input data to obtain output data by executing a plurality of said data processing instances by sharing a data pool according to an execution order of a plurality of said data processing instances comprises:

Generating a debugging panel on the visual interface, executing a plurality of data processing examples through a shared data pool according to the execution sequence of the plurality of data processing examples, processing input data to obtain output data, and displaying the processing process of processing the input data to obtain the output data on the debugging panel.

13. A low code platform oriented data processing apparatus comprising:

14. The apparatus of claim 13, the second execution module further to: and taking the input data as the input data of the data processing examples with the first execution sequence, taking the output data of each data processing example as the input data of the data processing examples with the execution sequence positioned at the subsequent position, and processing the input data of the data processing examples according to the data processing examples through a shared data pool to acquire the output data of each data processing example.

15. The apparatus of claim 13, wherein the data processing apparatus further comprises:

The visualization module is used for generating a visual interface; the visual interface comprises a canvas and a node selection panel, wherein the node selection panel comprises node icons corresponding to a plurality of functional nodes, and each functional node corresponds to one data processing logic;

And the instance generating module is used for responding to the selected operation aiming at the node icon, generating an executing node on the canvas and generating a data processing instance corresponding to the executing node according to the data processing logic corresponding to the node icon.

16. The apparatus of claim 15, wherein the data processing apparatus further comprises:

and the connecting line drawing module is used for responding to the drawing operation of drawing connecting lines between the two execution nodes, generating connecting lines with arrows for connecting the execution nodes on the canvas, wherein the arrow directions of the connecting lines are used for indicating the execution sequence of the data processing examples corresponding to the execution nodes.

17. The apparatus of claim 16, wherein the data processing apparatus further comprises:

a node deleting module, configured to delete, in response to a delete operation to delete the execution node, the execution node and a connection line related to the execution node at the canvas;

And the node dragging module is used for responding to the dragging operation of dragging the execution node, modifying the position of the execution node on the canvas and regenerating a connecting line related to the execution node.

18. The apparatus of claim 15, wherein the instance generation module comprises:

a node generating unit for generating an executing node on the canvas;

a configuration panel unit, configured to respond to a configuration node operation for configuring the execution node, and generate a configuration panel of configuration data processing parameters corresponding to the execution node at the visual interface according to data processing logic corresponding to the execution node;

And the configuration parameter unit is used for responding to the received data processing parameters input into the configuration panel and generating a data processing instance corresponding to the execution node according to the data processing logic corresponding to the execution node and the data processing parameters.

19. The apparatus of claim 18, wherein the configuration panel unit is further to: and under the condition that the corresponding data processing instance exists in the execution node, acquiring the data processing parameter corresponding to the execution node, and displaying the data processing parameter on the configuration panel.

20. The apparatus of claim 15, wherein the data processing apparatus further comprises:

The source code checking module is used for responding to the checking source code operation of the source code corresponding to the executing node, and generating the source code which corresponds to the executing node and is written by using a preset coding language according to the data processing instance corresponding to the executing node; generating a source code panel on the visual interface, and displaying the source codes corresponding to the execution nodes on the source code panel.

21. The apparatus of claim 15, wherein the data processing apparatus further comprises:

The pseudo code checking module is used for responding to the checking pseudo code operation of the pseudo code corresponding to the execution node and generating the pseudo code corresponding to the execution node according to the data processing instance corresponding to the execution node; and generating a pseudo code panel on the visual interface, and displaying the pseudo code corresponding to the execution node on the pseudo code panel.

22. The apparatus of claim 15, wherein the data processing apparatus further comprises:

The historical version module is used for responding to a saving operation, saving the canvas and the data execution instance corresponding to at least one execution node included in the canvas as a snapshot, and saving snapshot information of the snapshot, wherein the snapshot information comprises the time for saving the snapshot; responding to a viewing history operation of viewing a history version, generating a history version panel on the visual interface, and displaying snapshot information of the stored snapshot on the history version panel; and responding to the operation of clicking the snapshot information, and generating canvas according to the snapshot corresponding to the snapshot information.

23. The apparatus of claim 15, wherein the functional nodes comprise at least one of a start node for indicating a start of processing, an end node for indicating an end of processing, a service node for indicating a call to an external service, and a variable node for processing a variable.

24. The apparatus of claim 15, wherein the second execution module is further to: generating a debugging panel on the visual interface, executing a plurality of data processing examples through a shared data pool according to the execution sequence of the plurality of data processing examples, processing input data to obtain output data, and displaying the processing process of processing the input data to obtain the output data on the debugging panel.

25. An electronic device, comprising:

At least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-12.

26. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-12.

27. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any of claims 1-12.