CN116107561B - Low-code-based action node rapid construction method, system and storage medium - Google Patents

Low-code-based action node rapid construction method, system and storage medium Download PDF

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CN116107561B
CN116107561B CN202310398810.6A CN202310398810A CN116107561B CN 116107561 B CN116107561 B CN 116107561B CN 202310398810 A CN202310398810 A CN 202310398810A CN 116107561 B CN116107561 B CN 116107561B
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action node
node
value
nodes
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CN116107561A (en
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蔡鑫莹
胡艳平
舒展
潘源
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Hunan Yunchang Network Technology Co ltd
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Abstract

The invention discloses a method, a system and a storage medium for quickly constructing action nodes based on low codes, wherein the method comprises the following steps: acquiring target action node information; dividing the target action node according to the basic attribute to obtain the type of the target action node; obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node; comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node; and sending the parameters of the target action node to the parameter configuration object of the target action node, and running the corresponding action factory function to obtain the registration action. According to the invention, the configuration information of the node is saved through the action node configuration file, and the action parameter configuration panel and the node data are quickly constructed, so that the construction speed of the action node is improved.

Description

Low-code-based action node rapid construction method, system and storage medium
Technical Field
The invention relates to the technical field of low codes, in particular to a method, a system and a storage medium for quickly constructing action nodes based on low codes.
Background
The low code is a visual application program development method, can accelerate and simplify application program development from a small department to a large complex task, can be deployed across platforms after one development, and simultaneously accelerates and simplifies integration of application programs, cloud, local databases and recording systems. The low-code development platform can realize enterprise digital application demand analysis, interface design, development, delivery and management, and has the characteristics of rapidness, agility and continuity. At present, a great deal of time is often spent on configuring a parameter panel of a node when the action node is developed, and development progress is delayed.
Accordingly, there is a need for improvement in the art.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a method, a system and a storage medium for quickly constructing an action node based on a low code, which can construct the action node more accurately and quickly.
The first aspect of the invention provides a method for quickly constructing an action node based on a low code, which comprises the following steps:
acquiring target action node information;
dividing the target action node according to the basic attribute to obtain the type of the target action node;
obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node;
comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node;
and sending the parameters of the target action node to the parameter configuration object of the target action node, and running the corresponding action factory function to obtain the registration action.
In this scheme, the step of comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node specifically includes:
comparing and analyzing the target action node with the nodes in the preset action node library to obtain a similarity value;
extracting the action node with the maximum similarity value and the parameters of the corresponding action node;
judging whether the number of the action nodes with the maximum similarity value is larger than 1, if not, setting the parameters of the action nodes with the maximum similarity value as the parameters of the target action nodes; if yes, numbering the action nodes corresponding to the maximum similarity value and forming a similar action node set;
acquiring memory information, execution time information and error rate information of action nodes in a similar action node set;
acquiring cost performance value information of the similar action nodes according to the memory information, execution time information and error rate information of the similar action nodes;
and setting the parameter of the similar action node with the highest cost performance value as the parameter of the target action node.
In this solution, the step of obtaining the cost performance value information of the similar action node according to the memory information, the execution time information and the error rate information of the similar action node in the centralized action node specifically includes:
setting the memory value of the similar action node as
Figure SMS_1
Execution time is set to->
Figure SMS_2
Error rate is set to->
Figure SMS_3
Wherein->
Figure SMS_4
A number representing a corresponding node parameter;
memory value of similar action node
Figure SMS_5
Respectively normalizing the execution time and the error rate to obtain normalized values of corresponding memory values +.>
Figure SMS_6
Normalized value of execution time->
Figure SMS_7
And normalized value of error rate->
Figure SMS_8
;
And obtaining the value ratio of the performance of the similar action node according to the normalized value of the memory value, the normalized value of the execution time and the normalized value of the error rate.
In this scheme, still include:
judging whether the memory value of the similar action node is larger than a preset memory value threshold value, if so, deleting the corresponding node; if not, storing;
judging whether the execution time of the similar action node is greater than a preset time threshold, if so, deleting the corresponding node; if not, storing;
judging whether the error rate of the similar action node is larger than a preset error rate threshold value, if so, deleting the corresponding node; if not, the storage is carried out.
In this scheme, still include:
extracting the maximum value in the similarity value;
judging whether the maximum similarity value is larger than a preset similarity value threshold value, if so, enabling the action node corresponding to the maximum similarity value to be effective; if not, the action node corresponding to the maximum similarity value is invalid.
In this solution, after the registration, the method further includes:
acquiring parameter information of a registered action node;
judging whether an action node which is the same as a registration action node exists in a preset action node library, if not, sending the corresponding registration action node and the parameters of the corresponding registration action node to the preset action node library for storage; if yes, the storage is not carried out.
The second aspect of the present invention provides a low-code-based rapid action node construction system, including a memory and a processor, where the memory stores a low-code-based rapid action node construction method program, and when the low-code-based rapid action node construction method program is executed by the processor, the following steps are implemented:
acquiring target action node information;
dividing the target action node according to the basic attribute to obtain the type of the target action node;
obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node;
comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node;
and sending the parameters of the target action node to the parameter configuration object of the target action node, and running the corresponding action factory function to obtain the registration action.
In this scheme, the step of comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node specifically includes:
comparing and analyzing the target action node with the nodes in the preset action node library to obtain a similarity value;
extracting the action node with the maximum similarity value and the parameters of the corresponding action node;
judging whether the number of the action nodes with the maximum similarity value is larger than 1, if not, setting the parameters of the action nodes with the maximum similarity value as the parameters of the target action nodes; if yes, numbering the action nodes corresponding to the maximum similarity value and forming a similar action node set;
acquiring memory information, execution time information and error rate information of action nodes in a similar action node set;
acquiring cost performance value information of the similar action nodes according to the memory information, execution time information and error rate information of the similar action nodes;
and setting the parameter of the similar action node with the highest cost performance value as the parameter of the target action node.
In this solution, the step of obtaining the cost performance value information of the similar action node according to the memory information, the execution time information and the error rate information of the similar action node in the centralized action node specifically includes:
setting the memory value of the similar action node as
Figure SMS_9
Execution time is set to->
Figure SMS_10
Error rate is set to->
Figure SMS_11
Wherein->
Figure SMS_12
A number representing a corresponding node parameter;
memory value of similar action node
Figure SMS_13
Respectively normalizing the execution time and the error rate to obtain normalized values of corresponding memory values +.>
Figure SMS_14
Normalized value of execution time->
Figure SMS_15
And normalized value of error rate->
Figure SMS_16
;
And obtaining the value ratio of the performance of the similar action node according to the normalized value of the memory value, the normalized value of the execution time and the normalized value of the error rate.
In this scheme, still include:
judging whether the memory value of the similar action node is larger than a preset memory value threshold value, if so, deleting the corresponding node; if not, storing;
judging whether the execution time of the similar action node is greater than a preset time threshold, if so, deleting the corresponding node; if not, storing;
judging whether the error rate of the similar action node is larger than a preset error rate threshold value, if so, deleting the corresponding node; if not, the storage is carried out.
In this scheme, still include:
extracting the maximum value in the similarity value;
judging whether the maximum similarity value is larger than a preset similarity value threshold value, if so, enabling the action node corresponding to the maximum similarity value to be effective; if not, the action node corresponding to the maximum similarity value is invalid.
In this solution, after the registration, the method further includes:
acquiring parameter information of a registered action node;
judging whether an action node which is the same as a registration action node exists in a preset action node library, if not, sending the corresponding registration action node and the parameters of the corresponding registration action node to the preset action node library for storage; if yes, the storage is not carried out.
A third aspect of the present invention provides a computer storage medium in which a low-code-based action node rapid construction method program is stored, which when executed by a processor, implements the steps of a low-code-based action node rapid construction method as described in any one of the above.
According to the low-code-based rapid construction method, system and storage medium for the action nodes, configuration information of the nodes is stored through the action node configuration file, and the action parameter configuration panel and the node data are rapidly constructed, so that the construction speed of the action nodes is improved.
Drawings
FIG. 1 is a flow chart of a low code based fast construction method for action nodes of the present invention;
FIG. 2 shows a block diagram of a low code based action node rapid build system of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
FIG. 1 shows a flow chart of a low code based fast construction method for action nodes of the present invention.
As shown in fig. 1, the invention discloses a fast construction method of action nodes based on low codes, which comprises the following steps:
s102, acquiring target action node information;
s104, dividing the target action node according to the basic attribute to obtain the type of the target action node;
s106, obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node;
s108, comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node;
s110, sending the parameters of the target action node to the parameter configuration object of the target action node, and running the corresponding action factory function to obtain the registration action.
It should be noted that, the action nodes in the preset action node library are derived from action nodes that do not violate copyright problems, such as action nodes that open copyright, custom action nodes, and the like, and the preset action node library also includes basic attributes and input parameters of the corresponding action nodes. Dividing target action nodes into different types according to basic attributes of the target action nodes during design, and determining parameter configuration objects and action factory functions of the target action nodes according to the types of the target action nodes, wherein the basic attributes comprise: the position, the size, the transparency and the like are customized according to the actual action node. Transmitting the parameters of the target action node to a parameter configuration object of the target action node, such as: the transparency parameter value corresponds to a transparency parameter configuration object, that is, the input transparency value is adjusted and stored in the corresponding transparency parameter configuration object.
According to an embodiment of the present invention, the step of comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node specifically includes:
comparing and analyzing the target action node with the nodes in the preset action node library to obtain a similarity value;
extracting the action node with the maximum similarity value and the parameters of the corresponding action node;
judging whether the number of the action nodes with the maximum similarity value is larger than 1, if not, setting the parameters of the action nodes with the maximum similarity value as the parameters of the target action nodes; if yes, numbering the action nodes corresponding to the maximum similarity value and forming a similar action node set;
acquiring memory information, execution time information and error rate information of action nodes in a similar action node set;
acquiring cost performance value information of the similar action nodes according to the memory information, execution time information and error rate information of the similar action nodes;
and setting the parameter of the similar action node with the highest cost performance value as the parameter of the target action node.
When the similarity value is 100%, the action node which is the same as the target action node exists in the preset action node library; when the similarity value is smaller than 100%, the fact that the action node which is the same as the target action node does not exist in the preset action node library is indicated. The same action node can have multiple implementation processes, and parameters in different implementation processes can be different, so that the same action node can have different parameter settings, and the action nodes corresponding to the different parameter settings are set as different action nodes and are stored respectively. The parameters of different action nodes are different, so that the memory value, execution time and error rate of the corresponding action node are different, and the execution time and error rate of the action node are determined by the data of the corresponding action node in the history use process, for example: the action node a is used 100 times in total in the history data, and when 2 errors occur, the error rate of the corresponding action node a is 2%. When the number of action nodes with the maximum similarity value is not less than 2, setting the parameter of the similar action node with the highest cost performance value as the parameter of the corresponding target action node. And if the maximum similarity value is smaller than 100%, extracting the parameter of the similar action node with the highest cost performance value, sending the parameter to the user side for revising, and setting the revised parameter of the similar action node as the parameter of the target action node.
In this solution, the step of obtaining the cost performance value information of the similar action node according to the memory information, the execution time information and the error rate information of the similar action node in the centralized action node specifically includes:
setting the memory value of the similar action node as
Figure SMS_17
Execution time is set to->
Figure SMS_18
Error rate is set to->
Figure SMS_19
Wherein->
Figure SMS_20
A number representing a corresponding node parameter;
memory value of similar action node
Figure SMS_21
Respectively normalizing the execution time and the error rate to obtain normalized values of corresponding memory values +.>
Figure SMS_22
Normalized value of execution time->
Figure SMS_23
And normalized value of error rate->
Figure SMS_24
;
And obtaining the value ratio of the performance of the similar action node according to the normalized value of the memory value, the normalized value of the execution time and the normalized value of the error rate.
It should be noted that, according to a preset normalization algorithm, wherein
Figure SMS_26
，/>
Figure SMS_30
,/>
Figure SMS_34
Wherein->
Figure SMS_28
Memory minimum expressed as action nodes in a set of similar action nodes,/>
Figure SMS_31
Memory maximum value expressed as action nodes in the similar action node set>
Figure SMS_33
Execution time minimum expressed as action nodes in a set of similar action nodes, +.>
Figure SMS_36
Maximum execution time expressed as action nodes in a set of similar action nodes; ->
Figure SMS_25
Error rate minimum value expressed as action nodes in similar action node set, +.>
Figure SMS_29
Expressed as the maximum value of error rate of action nodes in the similar action node set, the ratio of the values of the similar action nodes is set as +.>
Figure SMS_32
The formula is that
Figure SMS_35
Wherein->
Figure SMS_27
The ratio coefficient of the internal memory value in the ratio of the performance price, the ratio coefficient of the execution time in the ratio of the performance price and the ratio coefficient of the error rate in the ratio of the performance price are respectively represented, and the ratio coefficient is set by a person skilled in the art according to actual requirements.
According to an embodiment of the present invention, further comprising:
judging whether the memory value of the similar action node is larger than a preset memory value threshold value, if so, deleting the corresponding node; if not, storing;
judging whether the execution time of the similar action node is greater than a preset time threshold, if so, deleting the corresponding node; if not, storing;
judging whether the error rate of the similar action node is larger than a preset error rate threshold value, if so, deleting the corresponding node; if not, the storage is carried out.
It should be noted that, the execution time of the similar action node is an average value of each execution time of the corresponding action node in the history use process; the error rate of the similar action nodes is the ratio of the number of errors of the corresponding action nodes in the history use process to the total number of times of use. If the preset time threshold is 20 seconds, when the execution time of the similar action node is longer than 20 seconds, the corresponding similar action node is unqualified, and the corresponding action node is deleted; if the node is qualified, storing the corresponding similar action node. The preset memory value threshold, the preset time threshold and the preset error rate threshold are set by corresponding technicians according to actual requirements.
According to an embodiment of the present invention, further comprising:
extracting the maximum value in the similarity value;
judging whether the maximum similarity value is larger than a preset similarity value threshold value, if so, enabling the action node corresponding to the maximum similarity value to be effective; if not, the action node corresponding to the maximum similarity value is invalid.
It should be noted that, for example, if the preset similarity value threshold is 70%, it is useful to indicate that the parameters corresponding to the similar action nodes only when the maximum value in the similarity values is greater than 70%; otherwise, the parameters corresponding to the similar action nodes are useless. More specifically, when the similarity value is 100%, the corresponding similar action node is the same as the target action node, and the corresponding parameter can be directly used without modification; when the similarity value is smaller than 100% and larger than a preset similarity value threshold, the parameters corresponding to the similar action nodes can be used partially, and modification is convenient; when the similarity value is smaller than a preset similarity value threshold, the parameters corresponding to the similar action nodes are not usable, and the parameters cannot provide assistance for constructing the action nodes.
According to an embodiment of the present invention, after the registration, the method further includes:
acquiring parameter information of a registered action node;
judging whether an action node which is the same as a registration action node exists in a preset action node library, if not, sending the corresponding registration action node and the parameters of the corresponding registration action node to the preset action node library for storage; if yes, the storage is not carried out.
The registration action is a target action to be constructed, and parameters of nodes corresponding to the registration action are obtained, wherein if the parameters do not exist in a preset action node library, the corresponding registration action nodes and the corresponding parameters are sent to the corresponding action node library for storage; if so, it is stated that the same action node already exists.
According to an embodiment of the present invention, further comprising:
and updating the preset action node library based on the preset time period.
It should be noted that, the time of each update of the preset action node library is recorded, when the update time is up to the preset time period from the current time, an update prompt is triggered, and the update prompt information is sent to the preset user terminal for display, for example, the preset time period is one month, the preset action node library is updated once every month, if the update is advanced, the update prompt is performed after a time period is calculated by taking the time corresponding to the update in advance as a reference point.
According to an embodiment of the present invention, further comprising:
sending other similar action nodes to a preset similar action node alternative list for display;
and displaying the similar action nodes in the preset similar action node alternative list according to a preset ordering mode.
When other similar action nodes exist, the corresponding similar action nodes are sent to a preset similar action node alternative list for display, for example, the memory value is used for sorting, and the priority with smaller memory value is sorted; if execution time ordering is performed, priority ordering with smaller execution time is performed, and the like. When the registration action is unsatisfactory or the operation is wrong, the user can directly select the proper similar action node and the corresponding parameter from the preset similar action alternative list so as to reconstruct the action node.
According to an embodiment of the present invention, further comprising:
acquiring parameter information of action nodes in a preset action node library;
judging whether the parameters of the action nodes are in the range of the parameter configuration object of the corresponding action node, if so, the parameters of the corresponding action node are reasonable; otherwise, the method is unreasonable;
and marking the parameters of the unreasonable action nodes and sending the parameters to the user side for display.
It should be noted that, there is a standard range for each parameter in the parameter configuration object of the action node, for example, the parameter range of the color is
Figure SMS_37
If the color parameter of the action node in the preset action node library is 300, the corresponding color parameter is obviously unreasonable, so that the corresponding parameter is marked and sent to the user side for revision.
FIG. 2 shows a block diagram of a low code based action node rapid build system of the present invention.
As shown in fig. 2, a second aspect of the present invention provides a low-code-based fast acting node construction system 2, including a memory 21 and a processor 22, where the memory stores a low-code-based fast acting node construction method program, and when the low-code-based fast acting node construction method program is executed by the processor, the steps of:
acquiring target action node information;
dividing the target action node according to the basic attribute to obtain the type of the target action node;
obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node;
comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node;
and sending the parameters of the target action node to the parameter configuration object of the target action node, and running the corresponding action factory function to obtain the registration action.
It should be noted that, the action nodes in the preset action node library are derived from action nodes that do not violate copyright problems, such as action nodes that open copyright, custom action nodes, and the like, and the preset action node library also includes basic attributes and input parameters of the corresponding action nodes. Dividing target action nodes into different types according to basic attributes of the target action nodes during design, and determining parameter configuration objects and action factory functions of the target action nodes according to the types of the target action nodes, wherein the basic attributes comprise: the position, the size, the transparency and the like are customized according to the actual action node. Transmitting the parameters of the target action node to a parameter configuration object of the target action node, such as: the transparency parameter value corresponds to a transparency parameter configuration object, that is, the input transparency value is adjusted and stored in the corresponding transparency parameter configuration object.
According to an embodiment of the present invention, the step of comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node specifically includes:
comparing and analyzing the target action node with the nodes in the preset action node library to obtain a similarity value;
extracting the action node with the maximum similarity value and the parameters of the corresponding action node;
judging whether the number of the action nodes with the maximum similarity value is larger than 1, if not, setting the parameters of the action nodes with the maximum similarity value as the parameters of the target action nodes; if yes, numbering the action nodes corresponding to the maximum similarity value and forming a similar action node set;
acquiring memory information, execution time information and error rate information of action nodes in a similar action node set;
acquiring cost performance value information of the similar action nodes according to the memory information, execution time information and error rate information of the similar action nodes;
and setting the parameter of the similar action node with the highest cost performance value as the parameter of the target action node.
When the similarity value is 100%, the action node which is the same as the target action node exists in the preset action node library; when the similarity value is smaller than 100%, the fact that the action node which is the same as the target action node does not exist in the preset action node library is indicated. The same action node can have multiple implementation processes, and parameters in different implementation processes can be different, so that the same action node can have different parameter settings, and the action nodes corresponding to the different parameter settings are set as different action nodes and are stored respectively. The parameters of different action nodes are different, so that the memory value, execution time and error rate of the corresponding action node are different, and the execution time and error rate of the action node are determined by the data of the corresponding action node in the history use process, for example: the action node a is used 100 times in total in the history data, and when 2 errors occur, the error rate of the corresponding action node a is 2%. When the number of action nodes with the maximum similarity value is not less than 2, setting the parameter of the similar action node with the highest cost performance value as the parameter of the corresponding target action node. And if the maximum similarity value is smaller than 100%, extracting the parameter of the similar action node with the highest cost performance value, sending the parameter to the user side for revising, and setting the revised parameter of the similar action node as the parameter of the target action node.
In this solution, the step of obtaining the cost performance value information of the similar action node according to the memory information, the execution time information and the error rate information of the similar action node in the centralized action node specifically includes:
setting the memory value of the similar action node as
Figure SMS_40
Execution time is set to->
Figure SMS_41
Error rate is set to->
Figure SMS_43
Wherein->
Figure SMS_39
Representing the number of the corresponding node parameter, memory value of the similar action node>
Figure SMS_42
Respectively normalizing the execution time and the error rate to obtain normalized values of corresponding memory values +.>
Figure SMS_44
Normalized value of execution time->
Figure SMS_45
And normalized value of error rate->
Figure SMS_38
;
And obtaining the value ratio of the performance of the similar action node according to the normalized value of the memory value, the normalized value of the execution time and the normalized value of the error rate.
It should be noted that, according to a preset normalization algorithm, wherein
Figure SMS_49
，/>
Figure SMS_50
,/>
Figure SMS_53
Wherein->
Figure SMS_48
Memory minimum expressed as action nodes in a set of similar action nodes,/>
Figure SMS_52
Represented as a set of action nodes of similar action nodesMaximum value of memory;>
Figure SMS_55
execution time minimum expressed as action nodes in a set of similar action nodes, +.>
Figure SMS_57
Maximum execution time expressed as action nodes in a set of similar action nodes; ->
Figure SMS_47
Error rate minimum value expressed as action nodes in similar action node set, +.>
Figure SMS_51
Expressed as the maximum value of error rate of action nodes in the similar action node set, the ratio of the values of the similar action nodes is set as +.>
Figure SMS_54
The formula is that
Figure SMS_56
Wherein->
Figure SMS_46
The ratio coefficient of the internal memory value in the ratio of the performance price, the ratio coefficient of the execution time in the ratio of the performance price and the ratio coefficient of the error rate in the ratio of the performance price are respectively represented, and the ratio coefficient is set by a person skilled in the art according to actual requirements.
According to an embodiment of the present invention, further comprising:
judging whether the memory value of the similar action node is larger than a preset memory value threshold value, if so, deleting the corresponding node; if not, storing;
judging whether the execution time of the similar action node is greater than a preset time threshold, if so, deleting the corresponding node; if not, storing;
judging whether the error rate of the similar action node is larger than a preset error rate threshold value, if so, deleting the corresponding node; if not, the storage is carried out.
It should be noted that, the execution time of the similar action node is an average value of each execution time of the corresponding action node in the history use process; the error rate of the similar action nodes is the ratio of the number of errors of the corresponding action nodes in the history use process to the total number of times of use. If the preset time threshold is 20 seconds, when the execution time of the similar action node is longer than 20 seconds, the corresponding similar action node is unqualified, and the corresponding action node is deleted; if the node is qualified, storing the corresponding similar action node. The preset memory value threshold, the preset time threshold and the preset error rate threshold are set by corresponding technicians according to actual requirements.
According to an embodiment of the present invention, further comprising:
extracting the maximum value in the similarity value;
judging whether the maximum similarity value is larger than a preset similarity value threshold value, if so, enabling the action node corresponding to the maximum similarity value to be effective; if not, the action node corresponding to the maximum similarity value is invalid.
It should be noted that, for example, if the preset similarity value threshold is 70%, it is useful to indicate that the parameters corresponding to the similar action nodes only when the maximum value in the similarity values is greater than 70%; otherwise, the parameters corresponding to the similar action nodes are useless. More specifically, when the similarity value is 100%, the corresponding similar action node is the same as the target action node, and the corresponding parameter can be directly used without modification; when the similarity value is smaller than 100% and larger than a preset similarity value threshold, the parameters corresponding to the similar action nodes can be used partially, and modification is convenient; when the similarity value is smaller than a preset similarity value threshold, the parameters corresponding to the similar action nodes are not usable, and the parameters cannot provide assistance for constructing the action nodes.
According to an embodiment of the present invention, after the registration, the method further includes:
acquiring parameter information of a registered action node;
judging whether an action node which is the same as a registration action node exists in a preset action node library, if not, sending the corresponding registration action node and the parameters of the corresponding registration action node to the preset action node library for storage; if yes, the storage is not carried out.
The registration action is a target action to be constructed, and parameters of nodes corresponding to the registration action are obtained, wherein if the parameters do not exist in a preset action node library, the corresponding registration action nodes and the corresponding parameters are sent to the corresponding action node library for storage; if so, it is stated that the same action node already exists.
According to an embodiment of the present invention, further comprising:
and updating the preset action node library based on the preset time period.
It should be noted that, the time of each update of the preset action node library is recorded, when the update time is up to the preset time period from the current time, an update prompt is triggered, and the update prompt information is sent to the preset user terminal for display, for example, the preset time period is one month, the preset action node library is updated once every month, if the update is advanced, the update prompt is performed after a time period is calculated by taking the time corresponding to the update in advance as a reference point.
According to an embodiment of the present invention, further comprising:
sending other similar action nodes to a preset similar action node alternative list for display;
and displaying the similar action nodes in the preset similar action node alternative list according to a preset ordering mode.
When other similar action nodes exist, the corresponding similar action nodes are sent to a preset similar action node alternative list for display, for example, the memory value is used for sorting, and the priority with smaller memory value is sorted; if execution time ordering is performed, priority ordering with smaller execution time is performed, and the like. When the registration action is unsatisfactory or the operation is wrong, the user can directly select the proper similar action node and the corresponding parameter from the preset similar action alternative list so as to reconstruct the action node.
According to an embodiment of the present invention, further comprising:
acquiring parameter information of action nodes in a preset action node library;
judging whether the parameters of the action nodes are in the range of the parameter configuration object of the corresponding action node, if so, the parameters of the corresponding action node are reasonable; otherwise, the method is unreasonable;
and marking the parameters of the unreasonable action nodes and sending the parameters to the user side for display.
It should be noted that, there is a standard range for each parameter in the parameter configuration object of the action node, for example, the parameter range of the color is
Figure SMS_58
If the color parameter of the action node in the preset action node library is 300, the corresponding color parameter is obviously unreasonable, so that the corresponding parameter is marked and sent to the user side for revision.
A third aspect of the present invention provides a computer storage medium in which a low-code-based action node rapid construction method program is stored, which when executed by a processor, implements the steps of a low-code-based action node rapid construction method as described in any one of the above.
The invention discloses a method, a system and a storage medium for quickly constructing action nodes based on low codes, wherein the method comprises the following steps: acquiring target action node information; dividing the target action node according to the basic attribute to obtain the type of the target action node; obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node; comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node; and sending the parameters of the target action node to the parameter configuration object of the target action node, and running the corresponding action factory function to obtain the registration action. According to the invention, the configuration information of the node is saved through the action node configuration file, and the action parameter configuration panel and the node data are quickly constructed, so that the construction speed of the action node is improved.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.

Claims (6)

1. The quick construction method of the action node based on the low codes is characterized by further comprising the following steps:
acquiring target action node information;
dividing the target action node according to the basic attribute to obtain the type of the target action node;
obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node;
comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node;
the parameters of the target action node are sent to a parameter configuration object of the target action node, and a corresponding action factory function is operated to obtain a registration action;
the step of comparing and analyzing the target action node with action nodes in a preset action node library to obtain the parameter information of the target action node specifically comprises the following steps:
comparing and analyzing the target action node with the nodes in the preset action node library to obtain a similarity value;
extracting the action node with the maximum similarity value and the parameters of the corresponding action node;
judging whether the number of the action nodes with the maximum similarity value is larger than 1, if not, setting the parameters of the action nodes with the maximum similarity value as the parameters of the target action nodes; if yes, numbering the action nodes corresponding to the maximum similarity value and forming a similar action node set;
acquiring memory information, execution time information and error rate information of action nodes in a similar action node set;
acquiring cost performance value information of the similar action nodes according to the memory information, execution time information and error rate information of the similar action nodes;
setting the parameter of the similar action node with the highest cost performance value as the parameter of the target action node;
the step of obtaining cost performance value information of the similar action nodes according to the memory information, the execution time information and the error rate information of the similar action nodes in the concentrated action nodes specifically comprises the following steps:
the memory value of the similar action node is set as A i The execution time is set to T i The error rate is set as B i Wherein i represents the number of the corresponding node parameter;
respectively carrying out normalization processing on the memory value, the execution time and the error rate of the similar action node to obtain a normalized value A of the corresponding memory value ′ i Normalized value T of execution time ′ i And normalized value of error rate B ′ i ；
Obtaining the value ratio of the performance of the similar action node according to the normalized value of the memory value, the normalized value of the execution time and the normalized value of the error rate;
setting the value ratio of similar action nodes to P i The formula is that
Figure FDA0004239147770000021
Figure FDA0004239147770000022
Wherein k is A 、k T 、k B Representing the ratio of the internal memory value in the value ratio, the execution time in the value ratio and the error rate in the value ratio respectivelyIs a duty cycle of (c).
2. The low-code based action node rapid construction method according to claim 1, further comprising:
judging whether the memory value of the similar action node is larger than a preset memory value threshold value, if so, deleting the corresponding node; if not, storing;
judging whether the execution time of the similar action node is greater than a preset time threshold, if so, deleting the corresponding node; if not, storing;
judging whether the error rate of the similar action node is larger than a preset error rate threshold value, if so, deleting the corresponding node; if not, the storage is carried out.
3. The low-code based action node rapid construction method according to claim 1, further comprising:
extracting the maximum value in the similarity value;
judging whether the maximum similarity value is larger than a preset similarity value threshold value, if so, enabling the action node corresponding to the maximum similarity value to be effective; if not, the action node corresponding to the maximum similarity value is invalid.
4. The method for quickly constructing an action node based on low codes according to claim 1, wherein after said obtaining the registration action, further comprising:
acquiring parameter information of a registered action node;
judging whether an action node which is the same as a registration action node exists in a preset action node library, if not, sending the corresponding registration action node and the parameters of the corresponding registration action node to the preset action node library for storage; if yes, the storage is not carried out.
5. The low-code-based action node rapid construction system is characterized by comprising a memory and a processor, wherein the memory stores a low-code-based action node rapid construction method program, and the low-code-based action node rapid construction method program realizes the following steps when being executed by the processor:
acquiring target action node information;
dividing the target action node according to the basic attribute to obtain the type of the target action node;
obtaining a parameter configuration object and an action factory function of the target action node according to the type of the target action node;
comparing and analyzing the target action node with action nodes in a preset action node library to obtain parameter information of the target action node;
the parameters of the target action node are sent to a parameter configuration object of the target action node, and a corresponding action factory function is operated to obtain a registration action;
the step of comparing and analyzing the target action node with action nodes in a preset action node library to obtain the parameter information of the target action node specifically comprises the following steps:
comparing and analyzing the target action node with the nodes in the preset action node library to obtain a similarity value;
extracting the action node with the maximum similarity value and the parameters of the corresponding action node;
judging whether the number of the action nodes with the maximum similarity value is larger than 1, if not, setting the parameters of the action nodes with the maximum similarity value as the parameters of the target action nodes; if yes, numbering the action nodes corresponding to the maximum similarity value and forming a similar action node set;
acquiring memory information, execution time information and error rate information of action nodes in a similar action node set;
acquiring cost performance value information of the similar action nodes according to the memory information, execution time information and error rate information of the similar action nodes;
setting the parameter of the similar action node with the highest cost performance value as the parameter of the target action node;
the step of obtaining cost performance value information of the similar action nodes according to the memory information, the execution time information and the error rate information of the similar action nodes in the concentrated action nodes specifically comprises the following steps:
the memory value of the similar action node is set as A i The execution time is set to T i The error rate is set as B i Wherein i represents the number of the corresponding node parameter;
respectively carrying out normalization processing on the memory value, the execution time and the error rate of the similar action node to obtain a normalized value A of the corresponding memory value ′ i Normalized value T of execution time ′ i And normalized value of error rate B ′ i ；
Obtaining the value ratio of the performance of the similar action node according to the normalized value of the memory value, the normalized value of the execution time and the normalized value of the error rate;
setting the value ratio of similar action nodes to P i The formula is that
Figure FDA0004239147770000041
Figure FDA0004239147770000042
Wherein k is A 、k T 、k B The ratio coefficient of the memory value in the value ratio, the ratio coefficient of the execution time in the value ratio and the ratio coefficient of the error rate in the value ratio are respectively represented.
6. A computer storage medium, wherein a low-code based action node rapid construction method program is stored in the computer storage medium, and when the low-code based action node rapid construction method program is executed by a processor, the steps of a low-code based action node rapid construction method according to any one of claims 1 to 4 are implemented.
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