Workflow data processing method and device, storage medium and electronic equipment

Abstract

The invention provides a workflow data processing method and device, a computer storage medium and electronic equipment, and relates to the technical field of computer software. The method comprises the following steps: in response to an execution instruction of a first workflow node, obtaining first state data from a global state pool and analyzing the first state data to a node execution environment of the first workflow node to obtain first execution data; storing the first execution data to a global state pool; when the second workflow node is executed, obtaining second state data from the global state pool and analyzing the second state data to obtain second execution data, and storing the second execution data to the global state pool; the second state data comprises the first execution data and the first state data, and the first workflow node and the second workflow node are workflow nodes in the same branch or different branch structures of the workflow topological structure. According to the method and the device, data transmission across workflow nodes and across branch structure nodes can be realized, the flexibility of a workflow execution process is improved, and the arrangement difficulty of complex workflow tasks is reduced.

Description

Background Art

[0002] With the rapid development of computer technology and the increasing demand for industrial production and office automation, it is becoming increasingly important to use workflow to connect multiple system operations of software systems to achieve automated execution. Specifically, workflow is to drive the orderly operation of software through workflow logic represented by computers, so as to automate the processing process and enable users and various application tools to coordinate with each other to complete a task.

[0003] In the related technical solutions, there are mainly two methods for automated workflow execution:

[0004] First, it is implemented based on the node execution status + rule engine driven method. In this method, for the directed graph structure of A->B, each workflow node has two core states: success / failure. When workflow node A shows success, the execution result of workflow node A flows to the adjacent subsequent workflow node B; when workflow node A shows failure, it will retry or stop.

[0005] Secondly, based on the above implementation, the execution result of workflow node A is transmitted to the adjacent subsequent workflow node B, and also includes status data, so that workflow node B can refer to it based on the status data.

[0006] However, the data flows in the above schemes all rely on the directed graph restricted by the workflow system to proceed sequentially, that is, the data flows are heavily dependent on the execution flow restricted by the directed graph, resulting in the inability of data between workflow nodes to interact across nodes and branches, poor flexibility and difficulty in implementing more complex tasks. Summary of the invention

[0007] The present disclosure provides a workflow data processing method, a workflow data processing device, a computer storage medium and an electronic device, thereby realizing data transmission across workflow nodes and across branch structure nodes, breaking through the time and space limitations of data flow, thereby improving the flexibility of the workflow execution process and reducing the difficulty of arranging complex workflow tasks, thereby realizing more complex tasks.

[0008] In a first aspect, an embodiment of the present disclosure provides a workflow data processing method, the method comprising: in response to an execution instruction for a first workflow node, obtaining first state data from a global state pool, and parsing the first state data into a node execution environment of the first workflow node to obtain first execution data of the first workflow node; storing the first execution data in the global state pool; in response to an execution instruction for a second workflow node, obtaining second state data from the global state pool, and parsing the second state data into a node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data in the global state pool, the second state data comprising the first execution data and the first state data; wherein the first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0009] In a second aspect, an embodiment of the present disclosure provides a workflow data processing device, which includes: a first data acquisition module, which is used to respond to an execution instruction for a first workflow node, obtain first state data from a global state pool, and parse the first state data into a node execution environment of the first workflow node to obtain first execution data of the first workflow node; a storage module, which is used to store the first execution data in the global state pool; a second data acquisition module, which is used to respond to an execution instruction for a second workflow node, obtain second state data from the global state pool, and parse the second state data into a node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data in the global state pool, and the second state data includes the first execution data and the first state data; wherein the first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0010] In a third aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the above workflow data processing method when executed by a processor.

[0011] In a fourth aspect, an embodiment of the present disclosure provides an electronic device, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the above workflow data processing method by executing the executable instructions.

[0012] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, including a computer program, which is executed by a processor to implement the above workflow data processing method.

[0013] The technical solution disclosed in this disclosure has the following beneficial effects:

[0014] The above-mentioned workflow data processing method obtains first state data from the global state pool in response to an execution instruction for the first workflow node, and parses the first state data into the node execution environment of the first workflow node to obtain first execution data of the first workflow node; stores the first execution data in the global state pool; obtains second state data from the global state pool in response to an execution instruction for the second workflow node, and parses the second state data into the node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data in the global state pool, and the second state data includes the first execution data and the first state data; wherein the first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0015] On the one hand, by setting a global state pool, this method enables each workflow node in the workflow topology structure to interact with the global state pool, thus breaking through the time and space limitations of data flow caused by the heavy reliance on the previous workflow node when executing traditional automated workflow nodes, and thus realizing the data interaction process across nodes and branch structures. On the other hand, this method greatly improves the flexibility of the execution process of automated workflows through the global state pool, while greatly reducing the difficulty of choreographing and implementing complex automated workflows, thereby realizing more complex automated tasks.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic diagram of a workflow based on a directed graph model in this exemplary embodiment is shown;

[0019] Figure 2 An architectural diagram showing a workflow data processing system in this exemplary embodiment;

[0020] Figure 3 A flowchart showing a workflow data processing method in this exemplary embodiment is shown;

[0021] Figure 4 A flow chart of a method for determining the control logic of a first workflow node in this exemplary embodiment is shown;

[0022] Figure 5 A schematic diagram of workflow data processing in which a first workflow node and a second workflow node are in the same branch structure in this exemplary embodiment is shown;

[0023] Figure 6 A schematic diagram of workflow data processing in which a first workflow node and a second workflow node are in different branch structures in this exemplary embodiment is shown;

[0024] Figure 7 A schematic diagram of the structure of a workflow data processing device in this exemplary embodiment is shown;

[0025] Figure 8 The structure diagram of an electronic device in this exemplary embodiment is schematically shown. DETAILED DESCRIPTION

[0026] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, exemplary embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the exemplary embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0027] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0028] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the steps. For example, some steps may be decomposed, while some steps may be combined or partially combined, so the actual execution order may change according to the actual situation.

[0029] With the rapid development of computer technology and the increasing demand for industrial production and office automation, it is becoming increasingly important to use workflow to connect multiple system operations of software systems to achieve automated execution. Specifically, workflow is to drive the orderly operation of software through workflow logic represented by computers, so as to automate the processing process and enable users and various application tools to coordinate with each other to complete a task.

[0030] In the related technical solutions, there are mainly two methods for automated workflow execution:

[0031] First, the method based on node execution status + rule engine driven.

[0032] In this method, each workflow node has only two core states: success / failure. Taking the directed graph model of A—>B—>C as an example, when the execution result of workflow node A is a success state, the data of workflow node A flows to workflow node B; conversely, when the execution result of workflow node A is a failure state, workflow node A needs to re-execute the process or stop working, and so on to workflow node C. It can be seen that this method only focuses on the logic and state of each workflow node itself.

[0033] Second, add status management data based on the above technical solution.

[0034] Taking the directed graph model of A—>B—>C as an example, when the execution result of workflow node A is a success, the data of workflow node A is transmitted to workflow node B, and state management data is also included so that workflow node B can refer to the state management data for data execution and processing.

[0035] However, in the data processing process of implementing the workflow in the above-mentioned related technical solutions, the data flow is heavily dependent on the directed graph model provided by the workflow system, so that the data flow is heavily dependent on the execution flow defined by the directed graph model. Figure 1 An exemplary description is given.

[0036] Figure 1 A schematic diagram of a workflow based on a directed graph model in this exemplary embodiment is shown schematically, referring to Figure 1 The topological structure displayed by the directed graph model includes various workflow nodes and execution flows for displaying data flow. In the directed graph model, when workflow node A is displayed as successful, the corresponding data flow follows the execution flow, and the execution result of workflow node A flows to the adjacent subsequent workflow node B. Similarly, the execution result of workflow node B flows to the adjacent subsequent workflow node C.

[0037] By the above Figure 1 It can be seen that the relevant technical solutions can only realize data interaction between adjacent workflow nodes, for example, it can only realize data transmission from A to B and from B to C, while workflow node C cannot directly use the execution status data of workflow node A and can only rely on the transmission of workflow node B. Therefore, the data flow in the workflow is completely dependent on the execution flow, and the two are coupled with each other. On the one hand, the above method cannot perform data interaction across nodes and branches, making it difficult for existing workflow systems to implement complex tasks. On the other hand, the above method cannot flexibly control the logical arrangement of the workflow.

[0038] This is because the state data only exists between adjacent workflow nodes, and there is no global maintenance space, which results in the state of a workflow node being unable to be perceived by other workflow nodes in a wider space. However, for a workflow, the relationship between workflow nodes is not just the order of the topology shown in the directed graph model, but also the relationship between different branches (such as Figure 1 Various indirect relationships will also be generated between nodes in different execution time intervals (for example, workflow node B and workflow node D are in different branches) or even between nodes in different execution time intervals (for example, workflow node B and workflow node E are in different execution time intervals). However, the above-mentioned related technical solutions cannot realize the propagation of state data in the entire workflow execution space. Therefore, in actual use, the above-mentioned existing solution workflow cannot realize workflow tasks with more complex logic, especially workflow tasks with more intermediate state data between workflow nodes and more frequent state judgment operations.

[0039] In view of the above problems, the exemplary embodiments of the present disclosure propose a workflow data processing method, which can set a global state pool so that each workflow node in the workflow topology structure can realize data interaction with the global state pool, thereby breaking through the time and space limitations of data flow caused by the heavy reliance on the previous workflow node when executing the traditional automated workflow node, and thus realizing the data interaction process across nodes and branch structures. On the other hand, the method greatly improves the flexibility of the execution process of the automated workflow through the global state pool, and at the same time greatly reduces the difficulty of arranging and realizing complex automated workflows, thereby realizing more complex automated tasks.

[0040] The following will be combined Figure 2 , a workflow data processing method and device proposed in the present disclosure is applied to Figure 2 The exemplary application environment is illustrated in the system architecture.

[0041] like Figure 2 As shown, it is a schematic diagram of an application scenario provided by an embodiment of the present application. In this scenario, a terminal device 201 and a server 202 may be included. The server 202 may be, for example, a workflow engine.

[0042] The terminal device 201 can be, for example, a mobile phone, a tablet computer (PAD), a laptop computer, a desktop computer, a smart TV, a smart vehicle-mounted device, a smart wearable device, a smart TV, and an aircraft, etc., any device related to workflow data processing. The terminal device 201 can be installed with a target application, and the target application can have functions such as triggering workflow startup and displaying workflow execution results. The application involved in the embodiment of the present application can be a software client, or a client such as a web page or a small program. The server 202 is a server corresponding to the software or a web page, a small program, etc., and does not limit the specific type of the client.

[0043] The server 202 may be a background server of the target application, used to provide corresponding background services for it, such as workflow data processing services, etc. It may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, i.e., content delivery networks (CDNs), and big data and artificial intelligence platforms, but is not limited thereto.

[0044] It should be noted that the workflow data processing method in the embodiment of the present application can be executed by the terminal device 201 or the server 202 alone, or can be executed by the server 202 and the terminal device 201 together. This application is not specifically limited here. Among them, the server 202 and the terminal device 201 can both include one or more processors, memories, and interactive I / O interfaces, etc. The memories of the server 202 and the terminal device 201 can also store program instructions required to be executed in the workflow data processing method provided in the embodiment of the present application, and these program instructions can be used to implement the workflow data processing process provided in the embodiment of the present application when executed by the processor.

[0045] It should be noted that when the workflow data processing method provided in the embodiment of the present application is executed by the server 202 or the terminal device 201 alone, the above-mentioned application scenario may also only include a single device of the server 202 or the terminal device 201, or the server 202 and the terminal device 201 may also be considered to be the same device. Of course, in actual application, when the workflow data processing method provided in the embodiment of the present application is jointly executed by the server 202 and the terminal device 201, the server 202 and the terminal device 201 may also be the same device, that is, the server 202 and the terminal device 201 may be different functional modules of the same device, or virtual devices virtualized from the same physical device.

[0046] In the embodiment of the present application, the terminal device 201 and the server 202 can be directly or indirectly connected to each other through one or more networks 203. The network 203 can be a wired network or a wireless network. For example, the wireless network can be a mobile cellular network or a wireless fidelity (Wireless-Fidelity, WIFI) network. Of course, it can also be other possible networks, which are not limited in the embodiment of the present application. It should be noted that Figure 2 The figure is only an example. In fact, the number of terminal devices and servers is not limited and is not specifically limited in the embodiments of the present application.

[0047] For example, in an exemplary embodiment, a user can set or adjust the workflow topology structure and trigger a workflow start operation through the terminal device 201. The above-mentioned server 202 can respond to an execution instruction for a first workflow node, obtain first state data from a global state pool, and parse the first state data into a node execution environment of the first workflow node to obtain first execution data of the first workflow node; store the first execution data in the global state pool; respond to an execution instruction for a second workflow node, obtain second state data from the global state pool, and parse the second state data into a node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data in the global state pool, and the second state data includes the first execution data and the first state data; wherein, the first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure, or, the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0048] It should be noted that the first workflow node and the second workflow node included in the above workflow topology structure do not mean that the workflow topology structure only includes two workflow nodes. It can include any number of nodes, and the embodiment of the present disclosure does not impose any special restrictions on this.

[0049] Below, in combination with the application scenarios described above, the method provided by the exemplary implementation of the present application is described with reference to the accompanying drawings. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principle of the present application, and the implementation of the present application is not limited in this respect. It should be noted that the following method can be executed by the above terminal device or server, or by the terminal device and the server together. Here, the server execution is specifically used as an example for illustration.

[0050] Figure 3 For a flowchart of the workflow data processing method provided in the embodiment of the present application, see Figure 3 As shown, the method can be executed by a computer device, which can be Figure 2 The server shown in the figure is implemented based on a workflow topology structure composed of a first workflow node and a second workflow node, and the second workflow node is executed after the first workflow node. Figure 3 The specific implementation process shown is as follows: Step S301-Step S303:

[0051] Step S301: In response to an execution instruction for a first workflow node, first state data is obtained from a global state pool, and the first state data is parsed into a node execution environment of the first workflow node to obtain first execution data of the first workflow node.

[0052] Step S302: Store the first execution data into the global state pool.

[0053] Step S303, in response to the execution instruction for the second workflow node, obtain the second state data from the global state pool, and parse the second state data into the node execution environment of the second workflow node to obtain the second execution data of the second workflow node, so as to store the second execution data into the global state pool, and the second state data includes the first execution data and the first state data.

[0054] The first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0055] In the technical solutions provided in some embodiments of the present disclosure, by responding to an execution instruction for a first workflow node, obtaining first state data from a global state pool, and parsing the first state data into a node execution environment of the first workflow node, first execution data of the first workflow node is obtained; the first execution data is stored in the global state pool; in response to an execution instruction for a second workflow node, second state data is obtained from the global state pool, and the second state data is parsed into a node execution environment of the second workflow node, second execution data of the second workflow node is obtained, and the second execution data is stored in the global state pool, the second state data includes the first execution data and the first state data; wherein, the first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or, the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure. On the one hand, by setting a global state pool, this method enables each workflow node in the workflow topology structure to interact with the global state pool, thus breaking through the time and space limitations of data flow caused by the heavy reliance on the previous workflow node when executing traditional automated workflow nodes, and thus realizing the data interaction process across nodes and branch structures. On the other hand, this method greatly improves the flexibility of the execution process of automated workflows through the global state pool, while greatly reducing the difficulty of choreographing and implementing complex automated workflows, thereby realizing more complex automated tasks.

[0056] The following will be combined with specific embodiments to Figure 3 The specific implementation methods of each step in the embodiment shown are described in detail:

[0057] In step S301, in response to an execution instruction for a first workflow node, first state data is obtained from a global state pool, and the first state data is parsed into a node execution environment of the first workflow node to obtain first execution data of the first workflow node.

[0058] The workflow topology is the basic structure of workflow execution, which consists of two parts: multiple workflow nodes and the execution flow relationship between the execution order of each workflow node. It is also usually called a directed graph model. For example, Figure 1 The workflow topology structure shown includes workflow nodes A, B, C, D, and E. The workflow topology structure represents the execution order between workflow nodes A, B, C, D, and E during the workflow execution process. For example, after workflow node B is executed, workflow node C can be started for execution.

[0059] The workflow can be a workflow in any application scenario. For example, if the workflow is a leave application process for enterprise employees, the corresponding workflow nodes A, B, C, D, and E can correspond to: employee on leave—team leader—department manager—general manager—chairman.

[0060] The first state data in step S301 is all state data stored in the global state pool, for example, it may be state data generated after the execution of a workflow node in the workflow topology structure is completed.

[0061] Exemplarily, upon receiving an execution instruction for a first workflow node, the computer device may obtain first state data from a global state pool, and parse the obtained first state data into a node execution environment of the first workflow node, thereby executing a core execution program of the first workflow node.

[0062] Before executing step S301 to obtain the first state data from the global state pool in response to the execution instruction for the first workflow node, it is also necessary to judge the control logic of the first workflow node to determine whether to execute the first workflow node.

[0063] In an optional embodiment of the present disclosure, in response to a start instruction for a first workflow node, target state data is obtained from a global state pool; a judgment result for the first workflow node is determined based on the target state data and a pre-configured node execution rule; if the judgment result is execution, an execution instruction for the first workflow node is generated.

[0064] The execution result can be execute, skip, stop, etc.

[0065] Exemplarily, when the workflow is executed to the first workflow node, it is first necessary to perform a control logic judgment on the first workflow node, that is, it is necessary to judge whether the first workflow node is executed. Specifically, the judgment result for the first workflow node can be determined by the target state data obtained from the global state pool and the pre-configured node execution rule, so that when the judgment result is execution, an execution instruction for the first workflow node is generated, so as to start the execution process of the first workflow node by responding to the execution instruction for the first workflow node.

[0066] On the contrary, if the judgment result for the first workflow node is to skip according to the target state data and the pre-configured node execution rule, the first workflow node will be skipped to determine the next workflow node to be executed based on the workflow topology. Figure 1 As shown, when the first workflow node is Node B, if its judgment result is skipped, it jumps to the workflow node C to determine the judgment result corresponding to the workflow node C.

[0067] In another embodiment, if the judgment result for the first workflow node is determined to be stop based on the target state data and the pre-configured node execution rule, the workflow will no longer continue to execute, thereby exiting the workflow execution process, or pausing to wait for the next instruction.

[0068] Based on the above-mentioned embodiments, a method for judging the control logic of the first workflow node is also provided, which will be combined with Figure 4 , the above-mentioned process of judging the control logic of the first workflow node will be described in an exemplary manner. Figure 4 A flowchart of a method for judging a control logic of a first workflow node in this exemplary embodiment is shown, referring to Figure 4 As shown, the method includes the following steps S401-S405:

[0069] In step S401, in response to the start instruction of the first workflow node, it is determined whether the first workflow node is an initial workflow node.

[0070] The initial workflow node is the entry node of the workflow, that is, the first workflow node to start the workflow. Taking the workflow as the leave application process of enterprise employees as an example, the initial workflow node usually triggers the enterprise employees who apply for leave.

[0071] For example, before the workflow is started, the workflow program automatically triggers the workflow initialization or manually initializes it, so that the data in the global state pool only contains the initial state data. Taking the workflow of personnel file management as an example, the initial state data in the global state pool can be the basic information of the user's name, birth date, and gender.

[0072] In an optional embodiment of the present disclosure, if the first workflow node is an initial workflow node of the workflow topology structure, step S402 is executed to obtain initial state data from the global state pool.

[0073] Then, step S403 is executed to determine a judgment result for the first workflow node according to the initial state data and the pre-configured node execution rule.

[0074] In the above embodiment, when the first workflow node is the initial workflow node, the global state pool only includes the default state value after the initialization operation, that is, the initial state data. Therefore, the judgment result of whether to execute the first workflow node is determined by the initial state data and the node execution rule.

[0075] On the contrary, in another optional embodiment of the present disclosure, if the first workflow node is the first other workflow node of the workflow topology structure, step S404 is executed to obtain the intermediate state data from the global state pool. Then, step S405 is executed to determine the judgment result for the first workflow node according to the intermediate state data and the pre-configured node execution rule.

[0076] The first other workflow node is any workflow node in the workflow topology structure except the initial workflow node. The intermediate state data is a set of execution data generated by the previous workflow nodes of the other workflow nodes, and the intermediate state data includes the initial state data. The previous workflow node is the workflow node that was executed before the first workflow node.

[0077] For ease of understanding, we will combine Figure 1 The workflow topology shown in FIG. 1 is used to illustrate the above embodiment. Figure 1 As shown, workflow node A is the initial workflow node, and workflow nodes B, C, D, and E are all first other workflow nodes.

[0078] When the first workflow node is workflow node A, a control logic judgment is performed based on the default initial state data of the workflow and the preset node execution rules to determine whether to execute workflow node A. Assuming that the first workflow node is workflow node B, a control logic judgment is performed based on the initial state data, the newly added state data generated after the execution of workflow node A is completed, and the preset node execution rules to determine whether to execute workflow node B.

[0079] Through the above-mentioned embodiments, all the state data contained in the global state pool are used as a reference for the judgment of the execution of subsequent workflow nodes, breaking the limitation of the related technical solutions that only control logic judgment can be performed according to the previous workflow node, thereby realizing the arrangement and execution of workflows more flexibly and accurately.

[0080] In step S302, the first execution data is stored in the global state pool.

[0081] Exemplarily, the first execution data generated in step S201 is also stored in the global state pool, so that other workflow nodes except the first workflow node can obtain the first execution data from the global state pool.

[0082] When storing the first execution data in the global state pool, the stored data needs to be structured. That is, in order to ensure that no matter which workflow engine is used or which node execution method is adopted, the state data can be obtained from the global state pool based on the program code and parsed, in an optional embodiment of the present disclosure, the execution data corresponding to multiple workflow nodes in the workflow topology structure are stored in the global state pool in the target data format.

[0083] The target data format can be any one of JSON format, YAML format or other common formats. However, when storing data in the global state pool, it is necessary to ensure that the data in the global state pool is stored in a unified format to achieve structured storage of data.

[0084] In an optional embodiment of the present disclosure, the first execution data includes one or more of the intermediate state data generated by the first workflow node during the execution process and the execution result data generated by the first workflow node after the execution is completed.

[0085] Exemplarily, after determining to execute the first workflow node based on any of the above embodiments, the core program of the first workflow node is started for execution to load the first state data obtained from the global state pool and parse it into the node execution environment of the first workflow node. During the execution process, the first workflow node will generate some intermediate state data and / or execution result data after the execution is completed.

[0086] When the first state data includes at least intermediate state data generated by the first workflow node during execution, in an optional embodiment of the present disclosure, initial intermediate state data generated by the first workflow node during execution is obtained; target intermediate state data is determined from the initial intermediate state data; and the target intermediate state data is stored in a global state pool.

[0087] The target intermediate state data is data associated with a second other workflow node, and the second other workflow node is any workflow node in the workflow topology structure except the first workflow node.

[0088] Exemplarily, in addition to storing all intermediate state data generated during the execution of the first workflow node into the global state pool, only the target intermediate state data associated with the second other workflow nodes can be stored in the global state pool. Figure 1 Workflow node A can store its status data that is valuable to workflow nodes B, C, D, and E during execution in the global status pool, and only eliminate status data that has data value or has no data value for workflow node A, that is, it does not need to be stored in the global status pool, so as to achieve the technical effect of saving global state pool resources.

[0089] In step S303, in response to an execution instruction for the second workflow node, second state data is obtained from the global state pool, and the second state data is parsed into the node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data in the global state pool, and the second state data includes the first execution data and the first state data.

[0090] The first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0091] Exemplarily, when the workflow transfers to the second workflow node, the computer device obtains the second state data from the global state pool in response to the execution instruction for the second workflow node, and parses the second state data into the node execution environment of the second workflow node to obtain the second execution data of the second workflow node.

[0092] The second state data refers to the state data generated after the execution of the previous workflow node of the second workflow node, and can also refer to all the state data in the global state pool. For example, for the A—>B—>C workflow topology structure, if the second workflow node is workflow node C, then the second state data is the state data generated after the execution of workflow nodes A and B, that is, all the state data in the current global state pool.

[0093] Depend on Figure 3 It can be seen from the illustrated embodiment that, in the workflow process, all workflow nodes can implement data interaction with the global state pool, thereby ensuring the globality of the global state pool.

[0094] Furthermore, the global state pool is also dynamic.

[0095] The data stored in the global state pool changes in real time, and its life cycle is longer than the workflow execution instance. Its dynamic nature is mainly reflected in two aspects:

[0096] First, the state data generated by each workflow node during execution can be dynamically stored in the global state pool, so that the structured state data stored in the global state pool changes in real time.

[0097] Second, each workflow node can modify the state data in the global state pool.

[0098] In an optional embodiment of the present disclosure, after the first state data is stored in the global state pool in the above step S302, in response to the first execution data being modified to third execution data in the node execution environment of the first workflow node, the first state data in the global state pool is updated to the third execution data, so that the second workflow node obtains the third execution data from the global state pool.

[0099] Exemplarily, for the first workflow node, it can modify the generated first execution data to obtain modified third execution data, and store the third execution data in the global state pool for updating. When the second workflow node extracts state data from the global state pool, it is the updated third execution data.

[0100] Furthermore, the global state pool is also open.

[0101] Exemplarily, the state data in the global state pool can be open to the outside world while ensuring the security of the execution process. That is, in addition to supporting the dynamic modification of the data in the global state pool during the execution of all workflow nodes, it can also be open to the outside world.

[0102] The following embodiments take the first workflow node as an example. In an optional embodiment of the present disclosure, after the first state data is stored in the global state pool in the above step S302, the method further includes: in response to receiving a third-party system to modify the first execution data to the fourth execution data, updating the first execution data in the global state pool to the fourth execution data, so that the second workflow node obtains the fourth execution data from the global state pool.

[0103] Among them, the third-party system is an external system or operation source.

[0104] Exemplarily, the global state pool can also be opened to external systems or operation sources to receive a third-party system to modify the first execution data into fourth execution data, and then update the fourth execution data to the global state pool so that the subsequent second workflow node can obtain the fourth execution data from the global state pool.

[0105] It should be noted that in order to ensure the security of data in the global state pool, the state modification can be opened only to trusted systems / operation sources, such as a whitelist system.

[0106] Furthermore, the global state pool is also unique.

[0107] In an optional embodiment of the present disclosure, there is one and only one workflow instance in the global state pool, and the workflow instance is an instance generated based on each workflow node in the workflow topology structure executing the workflow once.

[0108] Exemplarily, in order to simplify the process of workflow nodes accessing the global state pool and ensure data security, usually a global state pool only corresponds to the state data of each workflow node in a workflow instance.

[0109] Taking the leave process as an example, employee a can trigger the leave process, and a corresponding leave workflow instance for employee a is generated; at the same time, employee b can also trigger the leave process, and a corresponding leave workflow instance for employee a is generated. The above employee a's leave workflow instance and employee b's leave workflow instance are stored in two different global state pools.

[0110] In this embodiment, when the initial workflow node starts the workflow, a new global state pool is correspondingly generated, and the global state pool stores the initial state data.

[0111] The entire workflow data processing process of the workflow data processing method according to the exemplary embodiment of the present disclosure will be described in detail below in combination with two embodiments.

[0112] Embodiment 1: The first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure.

[0113] Reference Figure 5 For the workflow topology shown in FIG. 1 , assuming that workflow node B depends on the data of workflow node A (i.e., the data of workflow node A is associated with workflow node B); and workflow node C does not depend on the data of workflow node A, i.e., the data of workflow node A is not associated with workflow node C, then:

[0114] First, the workflow program itself or manually initializes the global state pool so that the global state pool only contains initial state data.

[0115] When the workflow transfers to the initial workflow node A, the initial state data is obtained from the global state pool, and the control logic judgment is performed based on the initial state data and the pre-set node execution rules. When determining to execute workflow node A, the initial state data is parsed into the node execution environment of workflow node A to obtain the execution data of workflow node A.

[0116] Then, the execution data of the workflow node A is stored in the global state pool. At this time, the global state pool contains the above initial state data and the execution data of the newly added workflow node A.

[0117] Since the subsequent nodes of workflow node A are workflow node B and workflow node C, all data can be obtained from the global state pool for workflow node B and workflow node C, namely the above initial state data and the execution data of the newly added workflow node A, so as to give priority to determining whether to execute. In the case of execution, the core programs of workflow node B and workflow node C are started.

[0118] During the running of workflow nodes B and C, data in the global state pool will be loaded. Since workflow node B depends on the data of workflow node A, workflow node B will be executed based on the data of workflow node A. For example, in the leave process, when the department manager's leave approval decision is: do not agree to employee A's leave, when the workflow flows to the general manager node, the general manager will make a corresponding leave approval decision based on the department manager's leave result.

[0119] However, workflow node C does not depend on the data of workflow node A. After obtaining all data from the global state pool, the data of workflow node A can be ignored for execution.

[0120] Finally, after the execution of workflow node B and workflow node C, the execution results are automatically updated to the global state pool, thus completing a workflow instance. Workflow node A and workflow node B are workflow nodes in the same branch structure in the workflow topology structure, and there is a direct execution sequence relationship, but they can exchange data through the global state pool to complete cross-node data transmission.

[0121] During the above workflow process, the data in the global status pool is continuously updated, ultimately driving the completion of the entire automated workflow.

[0122] Embodiment 2: The first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0123] In this embodiment, take the automatic execution, i.e. steady-state detection alarm scenario, as an example. Figure 6 The two branch structures in the workflow topology structure shown are branch N1 and branch N2.

[0124] Among them, the current workflow node D on the N1 branch is executing a loop check program. In each loop cycle, data will be re-read from the global state pool to determine the S value in the global state pool. If it meets the preset range, the loop execution will be maintained. If it is out of the preset range, a warning message will be issued immediately.

[0125] The current workflow node E on the N2 branch executes normally, reads data from the global state pool, and starts the automation program execution. During the execution process, the program generates an intermediate state S value and updates the intermediate state S value to the global state pool in real time.

[0126] At this time, in a cyclic inspection cycle, the intermediate state S value is read from the global state pool, and the intermediate state S value can be judged, so that a warning message is immediately issued when the intermediate state S value deviates from the preset range, and the staff will handle it after receiving the alarm information.

[0127] In this embodiment, workflow node D and workflow node E are workflow nodes in different branch structures in the workflow topology structure, and do not have a direct execution sequence relationship. They only interact with data through the global state pool, thereby completing data transfer across workflow branch structures based on an indirect communication relationship.

[0128] In order to implement the above workflow data processing method, an embodiment of the present disclosure provides a workflow data processing device. Figure 7 A schematic architecture diagram of a workflow data processing device is schematically shown.

[0129] The workflow data processing device 700 includes a first data acquisition module 701 , a storage module 702 and a second data acquisition module 703 .

[0130] The first data acquisition module 701 is used to obtain first state data from the global state pool in response to an execution instruction for the first workflow node, and parse the first state data into the node execution environment of the first workflow node to obtain first execution data of the first workflow node; the storage module 702 is used to store the first execution data into the global state pool; the second data acquisition module 703 is used to obtain second state data from the global state pool in response to an execution instruction for the second workflow node, and parse the second state data into the node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data into the global state pool, and the second state data includes the first execution data and the first state data;

[0131] The first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

[0132] In an optional embodiment of the present disclosure, the device may also include a processing module and an instruction generation module, the processing module is used to obtain target state data from the global state pool in response to a startup instruction for the first workflow node; determine the judgment result for the first workflow node based on the target state data and pre-configured node execution rules; the instruction generation module is used to generate an execution instruction for the first workflow node if the judgment result is execution.

[0133] In an optional embodiment of the present disclosure, the processing module is specifically configured to obtain initial state data from a global state pool if the first workflow node is an initial workflow node of the workflow topology structure, and determine the initial state data as target state data;

[0134] The processing module is specifically used to obtain intermediate state data from the global state pool if the first workflow node is the first other workflow node of the workflow topology structure, and determine the intermediate state data as the target state data; wherein the intermediate state data is a set of execution data generated by a preceding workflow node based on the first other workflow node, and the intermediate state data includes initial state data.

[0135] In an optional embodiment of the present disclosure, the first state data includes one or more of the intermediate state data generated by the first workflow node during execution and the execution result data generated by the first workflow node after execution is completed.

[0136] In an optional embodiment of the present disclosure, the first state data includes at least intermediate state data generated by the first workflow node during the execution process, and the storage module 702 is used to obtain the initial intermediate state data generated by the first workflow node during the execution process; determine the target intermediate state data from the initial intermediate state data; the target intermediate state data is data that has an association relationship with a second other workflow node, and the second other workflow node is any workflow node in the workflow topology structure except the first workflow node; and store the target intermediate state data in the global state pool.

[0137] In an optional embodiment of the present disclosure, the device may also include a data update module, which is used to update the first execution data in the global state pool to the third execution data in response to modifying the first execution data to the third execution data in the node execution environment of the first workflow node, so that the second workflow node obtains the third execution data from the global state pool.

[0138] In an optional embodiment of the present disclosure, the data update module is used to update the first execution data in the global state pool to the fourth execution data in response to receiving a third-party system modifying the first execution data to the fourth execution data, so that the second workflow node obtains the fourth execution data from the global state pool.

[0139] In an optional embodiment of the present disclosure, the storage module 702 may also be used to store the execution data corresponding to multiple workflow nodes in the workflow topology structure in the global state pool in a target data format.

[0140] In an optional embodiment of the present disclosure, there is one and only one workflow instance in the global state pool, and the workflow instance is an instance generated based on each workflow node in the workflow topology structure executing the workflow once.

[0141] The workflow data processing device 700 provided in the embodiment of the present disclosure can execute the technical solution of the workflow data processing method in any of the above-mentioned embodiments. Its implementation principle and beneficial effects are similar to the implementation principle and beneficial effects of the workflow data processing method. Please refer to the implementation principle and beneficial effects of the workflow data processing method, and no further details will be given here.

[0142] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present specification.

[0143] The program product for implementing the above method according to an embodiment of the present invention may adopt a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device.

[0144] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0145] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0146] The program code contained on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, radio frequency (RF), etc., or any suitable combination of the foregoing.

[0147] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet Service Provider).

[0148] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0149] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "system".

[0150] Refer to the following Figure 8 An electronic device 800 according to this embodiment of the present invention will be described. Figure 8 The electronic device 800 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0151] like Figure 8 As shown, the electronic device 800 is in the form of a general computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one storage unit 820, a bus 830 connecting different system components (including the storage unit 820 and the processing unit 810), and a display unit 840.

[0152] The storage unit stores program codes, which can be executed by the processing unit 810, so that the processing unit 810 performs the steps of various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification. For example, the processing unit 810 can perform the following steps: Figure 3 Steps S301 to S303 shown in FIG.

[0153] The storage unit 820 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 8201 and / or a cache memory unit 8202 , and may further include a read-only memory unit (ROM) 8203 .

[0154] The storage unit 820 may also include a program / utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0155] Bus 830 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0156] The electronic device 800 may also communicate with one or more external devices 1000 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 800, and / or communicate with any device that enables the electronic device 800 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 850. Furthermore, the electronic device 800 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 860. As shown, the network adapter 860 communicates with other modules of the electronic device 800 via a bus 830. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, disk arrays (Redundant Arrays of Independent Disks, RAID) systems, tape drives, and data backup storage systems.

[0157] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0158] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0159] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0160] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0161] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A workflow data processing method, characterized in that: include: In response to an execution instruction for a first workflow node, first state data is acquired from a global state pool, and the first state data is parsed into a node execution environment of the first workflow node to obtain first execution data of the first workflow node; storing the first execution data into the global state pool; In response to an execution instruction for a second workflow node, second state data is obtained from the global state pool, and the second state data is parsed into a node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data into the global state pool, wherein the second state data includes the first execution data and the first state data; The first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

2. The method according to claim 1, characterized in that Before acquiring the structural state data from the global state pool in response to the execution instruction for the first workflow node, the method further includes: In response to a start instruction for the first workflow node, acquiring target state data from the global state pool; Determining a judgment result for the first workflow node according to the target state data and a pre-configured node execution rule; If the judgment result is execution, an execution instruction for the first workflow node is generated.

3. The method according to claim 2, characterized in that The step of acquiring target state data from the global state pool in response to the start instruction for the first workflow node includes: If the first workflow node is an initial workflow node of the workflow topology structure, initial state data is obtained from the global state pool, and the initial state data is determined as the target state data; If the first workflow node is the first other workflow node of the workflow topology structure, intermediate state data is obtained from the global state pool, and the intermediate state data is determined as the target state data; wherein the intermediate state data is a set of execution data generated by a preceding workflow node based on the first other workflow node, and the intermediate state data includes initial state data.

4. The method according to claim 1, characterized in that: The first state data includes one or more of intermediate state data generated by the first workflow node during execution and execution result data generated by the first workflow node after execution is completed.

5. The method according to claim 4, characterized in that The first state data at least includes intermediate state data generated during the execution of the first workflow node, and storing the first state data in the global state pool includes: Acquire initial intermediate state data generated during the execution of the first workflow node; Determining target intermediate state data from the initial intermediate state data; the target intermediate state data is data associated with a second other workflow node, and the second other workflow node is any workflow node in the workflow topology structure except the first workflow node; The target intermediate state data is stored in the global state pool.

6. The method according to claim 1 or 5, characterized in that: After storing the first state data in the global state pool, the method further includes: In response to modifying the first execution data to third execution data in the node execution environment of the first workflow node, the first execution data in the global state pool is updated to the third execution data so that the second workflow node obtains the third execution data from the global state pool.

7. The method according to claim 1 or 5, characterized in that: After storing the first state data in the global state pool, the method further includes: In response to receiving a third-party system modifying the first execution data into fourth execution data, the first execution data in the global state pool is updated to the fourth execution data, so that the second workflow node obtains the fourth execution data from the global state pool.

8. The method according to claim 1, characterized in that The method further comprises: The execution data corresponding to each workflow node in the workflow topology structure is stored in the global state pool in a target data format.

9. The method according to claim 1, characterized in that: There is one and only one workflow instance in the global state pool, and the workflow instance is an instance generated based on each workflow node in the workflow topology structure executing a workflow.

10. A workflow data processing device, characterized in that: include: A first data acquisition module, configured to acquire first state data from a global state pool in response to an execution instruction for a first workflow node, and parse the first state data into a node execution environment of the first workflow node to obtain first execution data of the first workflow node; A storage module, used for storing the first execution data into the global state pool; a second data acquisition module, configured to acquire second state data from the global state pool in response to an execution instruction for a second workflow node, and parse the second state data into a node execution environment of the second workflow node to obtain second execution data of the second workflow node, so as to store the second execution data into the global state pool, wherein the second state data includes the first execution data and the first state data; The first workflow node and the second workflow node are workflow nodes in the same branch structure in the workflow topology structure and the second workflow node is executed after the first workflow node, or the first workflow node and the second workflow node are workflow nodes in different branch structures in the workflow topology structure.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the workflow data processing method according to any one of claims 1 to 9 is implemented.

12. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; Wherein, the processor is configured to execute the workflow data processing method according to any one of claims 1 to 9 by executing the executable instructions.

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