CN112561692A - Data construction method and device, computer equipment and readable storage medium - Google Patents
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Abstract
The invention discloses a data construction method, a data construction device, computer equipment and a readable storage medium, which relate to the technical field of software testing and comprise the steps of establishing a client model set, and associating each client model in the client model set with preset preparation data; acquiring user information, matching a client model according to the user information, and acquiring preparation data corresponding to the user information; executing a task according to the prepared data corresponding to the user information, and synchronizing a task result to a data table; target data are generated based on the data table, and the problems that in an existing credit card test system, data structures are mostly processed according to preset parameters, data analysis aiming at user scenes is lacked, the data coverage of the structures is narrow, and the accuracy of results is affected in a subsequent test environment are solved.
Description
Technical Field
The present invention relates to the field of software testing technologies, and in particular, to a data construction method and apparatus, a computer device, and a readable storage medium.
Background
As a modern payment tool, the credit card creates more convenience for the life of people due to the characteristic of overdraft permission. Nowadays, more and more people have chosen credit cards as settlement tools in daily life. The core staging system of credit card is the main source of income of credit card, and in the construction process of the core staging system, the testing and quality assurance work becomes more important.
However, in the research of the inventor created by the present invention, in order to balance high-speed iteration and regression and multi-flow branch tests based on a large data volume, the test data related to the current matching test work of most credit card periodic services has the mode of providing test data or randomly fishing the test data by service personnel, and the like, and lacks of targeted data analysis, so that the constructed data coverage is poor, and the system quality is influenced in the subsequent process.
Disclosure of Invention
The invention aims to provide a data construction method, a data construction device, computer equipment and a readable storage medium, which are used for solving the problems that in the existing credit card test system, data construction is mostly processed according to preset parameters, data analysis aiming at user scenes is lacked, so that the constructed data coverage is narrow, and the accuracy of results is influenced in a subsequent test environment.
To achieve the above object, the present invention provides a data structuring method, comprising:
establishing a customer model set, and associating each customer model in the customer model set with preset preparation data;
acquiring user information, matching a client model according to the user information, and acquiring preparation data corresponding to the user information;
executing a task according to the prepared data corresponding to the user information, and synchronizing a task result to a data table;
target data is generated based on the data table.
Further, the establishing of the customer model set includes the following steps:
collecting user service data and basic data;
classifying the basic data by adopting a pre-trained classification model based on the user service data to obtain a classification result;
and obtaining a customer model set according to the classification result.
Further, the acquiring the user information includes the following steps:
establishing an initial customer model;
monitoring user page operation, and updating the initial client model according to the user operation to obtain an individualized client model;
and obtaining user information according to the personalized customer model.
Further, the acquiring the user information includes the following steps:
screening the client model set according to preset conditions to obtain at least one piece of basic user data;
and marking each basic user data by adopting a preset first label to obtain the user data with the first label as user information.
Further, the executing the task according to the prepared data corresponding to the user information and synchronizing the task result to the data table includes the following steps:
acquiring a task type according to the preparation data corresponding to the user information, wherein the task type comprises a basic task and a personalized task;
when the task type is a basic task, card data is obtained according to user information, an activation interface is called to execute the task, and a task result is synchronized to a data table;
and when the task type is the personalized task, card data and task data are acquired according to the user information, an interface corresponding to the task data is called to execute the task, and a task result is synchronized to a data table.
Further, before obtaining card data according to user information and invoking an activation interface to execute a task, the method comprises the following steps:
and after user information with a preset first label is screened out, calling a batch activation interface to execute a task.
Further, the generating the target data based on the data table includes the following steps:
acquiring user information and staging qualification data corresponding to the information of each user and the like according to the data table;
and visually displaying the user information and the staging qualification data by adopting a preset template to obtain target data.
To achieve the above object, the present invention also provides a data structuring apparatus comprising:
the system comprises a building module, a data processing module and a data processing module, wherein the building module is used for building a client model set and associating each client model in the client model set with preset preparation data;
the acquisition module is used for acquiring user information, matching a client model according to the user information and acquiring preparation data corresponding to the user information;
the execution module is used for executing tasks based on the prepared data corresponding to the user information and synchronizing task results to a data table;
and the generating module is used for generating target data according to the data table.
To achieve the above object, the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the steps of the above data structuring method when executing the computer program.
To achieve the above object, the present invention also provides a computer-readable storage medium including a plurality of storage media, each storage medium having stored thereon a computer program, the computer programs stored in the plurality of storage media collectively implementing the steps of the above data structuring method when executed by a processor.
According to the data construction method, the data construction device, the computer equipment and the readable storage medium, the client model set is established, then the user information is obtained, the client model is matched according to the user information to obtain the preparation data, the task is executed based on the user information and the preparation data, and finally the target data is generated based on the task result, so that the problems that in the existing credit card test system, data construction is mostly processed according to preset parameters, data analysis aiming at user scenes is lacked, the constructed data coverage is narrow, and the accuracy of the result is influenced in a subsequent test environment are solved.
Drawings
FIG. 1 is a flow chart of a first embodiment of a data construction method according to the present invention;
FIG. 2 is a flow chart of creating a set of customer models according to a first embodiment of the data construction method of the present invention;
FIG. 3 is a flowchart of obtaining user information according to a first embodiment of the data construction method of the present invention;
FIG. 4 is a flowchart illustrating another method for obtaining user information according to an embodiment of the data structuring method of the present invention;
FIG. 5 is a flowchart illustrating a data structure method according to a first embodiment of the present invention, wherein the data structure method includes executing a task according to the prepared data corresponding to the user information and synchronizing task results with a data table;
FIG. 6 is a flowchart of generating target data based on the data table according to a first embodiment of the data construction method of the present invention;
FIG. 7 is a schematic diagram of program modules of a second embodiment of the data structuring apparatus according to the present invention;
fig. 8 is a schematic diagram of a hardware structure of a computer device according to a third embodiment of the present invention.
Reference numerals:
5. data structuring device 51, structuring module 52, and acquisition module
53. Execution module 54, generation module 6, computer device
61. Memory 62, processor 63, network interface
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention provides a data construction method, a data construction device, computer equipment and a readable storage medium, which are applicable to the field and are used for providing a data construction method based on a construction module, an acquisition module, an execution module and a generation module. The invention establishes a client model set through a construction module, acquires user information through an acquisition module, matches a client model according to the user information to acquire prepared data, then executes a task by adopting an execution module based on the user information and the prepared data matched with the user information, finally generates target data by adopting a generation module based on a task result, and provides a unified data automatic construction method based on a client model and a staged service scene by establishing the client model obtained based on basic data and service data classification, thereby solving the problems that in the existing credit card test system, most data construction is processed according to preset parameters, data analysis aiming at the user scene is lacked, the constructed data coverage is narrower, and the accuracy of the result is influenced in a subsequent test environment.
Example one
Referring to fig. 1, a data construction method of this embodiment is applied to a core staging system of a credit card, and the obtained target data is used for testing the core staging system of the credit card, so as to solve the data construction problem in the testing process of the core staging system of the credit card in the prior art, and specifically includes the following steps:
s100, establishing a customer model set, and associating each customer model in the customer model set with preset preparation data;
in the scheme, a client model set is established and mainly used for obtaining preparation data aiming at service scenes and user scenes, the client model set comprises a plurality of client models, each client model is a model generated according to different actual service scenes or user scenes and is used for being matched with user information obtained in the subsequent step, and therefore the service scenes are considered in the data construction process based on the user information, and the data coverage and the matching degree are improved. Specifically, referring to fig. 2, the establishing of the client model set includes the following steps:
s110: collecting user service data and basic data;
the user service data comprises a user account and a user currency, the basic data comprises a credit card account type, and as an explanation, the existing credit card account type comprises 4 minutes, namely a 998 personal credit card account, a 997 public card account, a 996 gold card account and a 993 Jingdong card account; the currency types comprise 3 types, namely single RMB, double currency and single foreign currency cards, different account types and different currency cards are supported by different stage products, card making and classifying scenes such as single account, single card, single account, multiple cards, multiple accounts, main and auxiliary cards and the like are also included, so that the establishment of a customer model is realized by subsequently adopting a mode of classifying basic data based on service data, and besides the account types and currency types in the example, other existing commonly used accounts can also be used in the scheme.
S120: classifying the basic data by adopting a pre-trained classification model based on the user service data to obtain a classification result;
in the above steps, the classification model may adopt an existing common classification model, including but not limited to a decision tree, a random forest, a logistic regression, an artificial neural network, and the like, before the classification model is used to classify the basic data, the classification model needs to be trained, an account type, and a currency type corresponding to the user data in the existing actual scene may be collected as training data, after the training of the classification model is completed, the basic data and the service data are classified in the use process, and the classification result is simply a set of the basic data and the service data that conform to the actual service scene, and is used for matching according to the user information in the subsequent steps to obtain the preparation data of the user.
S130: and obtaining a customer model set according to the classification result.
According to the above steps S110-S120, the accounts, the types of the credit cards, and the currency types are classified, for example, but not limited to, one account of multiple cards includes one account and multiple types of card currency types, 46 classification results better conforming to the actual business scenario are obtained, each classification result corresponds to a client model, then 46 client models can be obtained, and the client model set can be obtained by collecting all the client models.
In the step S100, after the client model is built, each client model needs to be associated with corresponding preparation data, and it should be noted that the preparation data includes qualification data corresponding to each client model, so as to facilitate subsequent data construction according to the qualification data corresponding to the user.
S200: acquiring user information, matching a client model according to the user information, and acquiring preparation data corresponding to the user information;
the user information acquisition includes, but is not limited to, two forms, one is to collect manually set user information for capturing user personalized staging business and constructing personalized data, and the other is to automatically generate user information after screening out a basic model based on the client model and construct basic data, so as to serve as a preferred embodiment, the user information acquisition includes the following steps:
s211: establishing an initial customer model;
the establishment of the initial customer model can be expressed as the establishment of a front-end page, wherein the front-end page comprises but is not limited to a plurality of selectable items such as accounts, account types, currency and the like, a user can perform personalized selection on the front-end page, the addition and modification of the user are supported, a card manufacturing task page can be added, and the user directly selects the filling quantity of the corresponding customer model.
S212: monitoring user page operation, and updating the initial client model according to the user operation to obtain an individualized client model;
the initial client model established in step S211 may preset default parameters, and then update data after the user operation according to the selection operation of the user (which may be modification of configuration parameters), and may collect exclusive data according to version iteration and service requirement latitude, thereby avoiding mutual interference of the collected data.
S213: and obtaining user information according to the personalized customer model.
Based on the particularity of the scheme applied to the credit card core staging system, the acquisition of the manually adjusted user information sets the time period acquisition, and as an example, the daily fixed time acquisition can be set.
As another preferred embodiment, referring to fig. 4, the acquiring the user information includes the following steps:
s221: screening the client model set according to preset conditions to obtain at least one piece of basic user data;
the preset condition may be that a client model with a high occurrence probability (specifically, the frequency of using each client model can be counted) summarized based on the existing application scenario is used as a basic client model, user data obtained from the basic client model is basic user data, and based on the particularity of the scheme applied to the credit card core staging system, the preset condition further includes task execution time, and in the scheme, the collection task is set to be executed at regular time every day.
S222: and marking each basic user data by adopting a preset first label to obtain the user data with the first label as user information.
And marking the user information generated based on the basic client model for distinguishing the basic user information from the personalized user information so as to increase the coverage of the subsequently generated target data.
After the user information is acquired by the two acquisition modes, the client model can be matched according to the user information to acquire corresponding preparation data for subsequently executing the task and acquiring a task result.
S300: executing a task according to the prepared data corresponding to the user information, and synchronizing a task result to a data table;
in the above steps, the execution tasks include but are not limited to card making, activation, account throwing, qualification adding, customer obtaining and approval, identity information approval, quota approval and the like; each task has an associated time management and control and based on the particularity of the present solution as applied to the credit card core staging system, the synchronized task result is set to day T + 1. Specifically, the step S300 executes the task according to the prepared data corresponding to the user information, and synchronizes the task result to the data table, referring to fig. 5, including the following steps:
s310: acquiring a task type according to the preparation data corresponding to the user information, wherein the task type comprises a basic task and a personalized task;
in this scheme, the basic tasks include, but are not limited to, card making and activating tasks, which are used for a general service including each account in an existing application scenario, the personalized tasks include, but are not limited to, account throwing, qualification list adding, and payment circulation, and the personalized tasks are other tasks corresponding to each account except the basic tasks, which are not described in detail herein.
S320: judging whether the task type is a basic task or not;
s330: if yes, namely the task type is a basic task, card data are obtained according to user information, an activation interface is called to execute the task, and a task result is synchronized to a data table;
in the scheme, the smooth execution of the task is realized by directly calling each background interface corresponding to the card data, so that the whole data construction process forms a complete process, which is different from the existing staged execution.
In the two user information obtaining modes, the user information is directly generated according to the basic client model, and most of task types contained in the user information comprise the same basic tasks, so that the tasks corresponding to the users obtained in the two user information obtaining modes can be independently completed in batches, and the method comprises the following steps before card data is obtained according to the user information and an activation interface is called to execute the tasks:
s330-1: and after user information with a preset first label is screened out, calling a batch activation interface to execute a task.
In the above steps, since most of the user models generated by the basic client model include basic tasks, the batch activation interface is called, so that the task execution time can be effectively shortened, and the time for constructing data is greatly shortened.
S340: if not, namely the task type is an individualized task, card data and task data are obtained according to the user information, an interface corresponding to the task data is called to execute the task, and a task result is synchronized to a data table.
In a practical application scene, the interface used for task execution in the card data matching background can be directly called, for example, if the credit card account type corresponding to the account a is 998 personal credit card account, the personal credit card background interface is directly called to execute tasks such as account throwing or adding a qualification list.
In the above step S300, after the task is executed (e.g., activation, adding a qualification list, etc.), a card task form containing the task execution result may be generated, and the card task form is synchronized to the data table for generating the visualization target data in the following step S400.
S400: target data is generated based on the data table.
Specifically, the step of generating the target data based on the data table in the above step, referring to fig. 6, includes the following steps:
s410: acquiring user information and staging qualification data corresponding to the information of each user and the like according to the data table;
it should be noted that the target data mainly includes user information and presentation of the installment qualification data in a visualization manner, but is not limited to this, and may also include presentation of other task result tasks (especially personalized tasks).
S420: and visually displaying the user information and the staging qualification data by adopting a preset template to obtain target data.
It should be further noted that the preset template is a template for visualization presentation, and further includes that an installment query interface needs to be invoked for the user data with the first tag to ensure generation of the visualized target data.
The visual presentation of the target data is realized through the S410 and the S420, the system performs the qualification verification on the stage qualification data generated in the above steps every day and then performs the classified visual presentation according to the stage products, and the testing personnel can check the data conveniently according to the business requirements.
As a supplementary example, the complete process of the personalized data construction proposed in the above step S200 is described in detail by a specific process, which includes: in the operation of monitoring users, a data construction system adds corresponding client model names, corresponding credit card logo values and the number on a client model tab page, the client model names, the credit card logo values and the number are separated by English commas, an approval manufacture system takes out all user information on the same day in four and a half afternoons every day, and in T +1 day, the approval manufacture system synchronizes account data corresponding to constructed tasks to a result table and sets the tasks to be ended for synchronization to a data table, a user can inquire all card list records on a target data display page, and can activate, throw accounts and add list qualification data on the page.
The whole process of the basic data construction proposed in the above step S200 is described in detail by a specific process, which includes: the method comprises the steps that a universal client model and the corresponding card making quantity are inserted into a task table every day by a timing task, T +1 days are synchronized into a card list data table, a first label is adopted to mark, batch activation is conducted on marked cards, account throwing and qualification list adding are conducted, payment is conducted on part of accounts needing payment to guarantee card circulation, a installments qualification inquiry interface is called on the marked card data, classification is conducted according to installments, and the data are displayed for a user visually.
The client model and the target data can be uploaded to the block chain so as to be used as a reference sample or a training sample subsequently, the safety and the fair transparency to a user can be guaranteed by uploading the client model and the target data to the block chain, the user equipment can download the abstract information from the block chain so as to check whether the priority list is tampered, and the corresponding target data can be downloaded from the block chain subsequently and used for testing a credit card core staging system, so that a generation process is not needed, and the efficiency of the testing process is effectively improved.
The block chain referred by the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
According to the method and the system, a client model obtained based on basic data and business data classification is established, a unified data automatic construction platform based on the client model and a staging business scene is provided, data is constructed in a targeted and intelligent manner, and the time for constructing the data is shortened. Meanwhile, a client model matched with user information is utilized, so that the method is close to real users and service scenes, and test data are greatly enriched. And (4) constructing staged qualification data and visually displaying the staged qualification data in consideration of personalization and full automation (steps S200-S400), and assisting the whole research and development process such as development self-test, UI and API automatic test, regression test and service acceptance test.
Example two:
referring to fig. 7, a data structuring device 5 of the present embodiment includes: a construction module 51, an acquisition module 52, an execution module 53 and a generation module 54.
The building module 51 is used for building a client model set and associating each client model in the client model set with preset preparation data;
the obtaining module 52 is configured to obtain user information, match a client model according to the user information, and obtain preparation data corresponding to the user information;
an execution module 53, configured to execute a task based on the preparation data corresponding to the user information, and synchronize a task result to a data table;
and a generating module 54, configured to generate target data according to the data table.
The technical scheme is based on test data construction in test, a client model set is established through a construction module, user information (including acquired personalized data and basic data constructed by a basic client module) is acquired through the acquisition module in various modes, a client model is matched according to the user information so as to collect preparation data corresponding to a service scene in subsequent data construction, a unified data automatic construction method based on the client model and a staging service scene is provided, then an execution module is adopted to execute tasks based on the user information and the preparation data, finally a generation module is adopted to generate target data based on task results, personalized and full-automatic construction of staging qualification data is considered and visual display is realized, and the problems that most data constructions are processed according to preset parameters and lack of data analysis aiming at the user scene in the existing credit card test system are solved, the data coverage of the structure is narrow, and the accuracy of the result is affected in the subsequent test environment.
In the scheme, an execution module acquires a task type in a task execution process, executes a basic task or a personalized task according to the task type, and acquires card data according to user information when the task type is the basic task, and invokes a card making interface and an activation interface to execute the task; if the task type is an individualized task, card data and task data are obtained according to user information, and an interface corresponding to the task data is called to execute the task; meanwhile, the batch activation interface can be called for the user information with the preset first label to execute the task, the task execution time can be effectively shortened, the data construction time is further shortened, and the efficiency is improved.
Example three:
in order to achieve the above object, the present invention further provides a computer device 6, where the computer device may include a plurality of computer devices, components of the data constructing apparatus 5 in the second embodiment may be distributed in different computer devices 6, and the computer device 6 may be a smartphone, a tablet computer, a notebook computer, a desktop computer, a rack-mounted server, a blade server, a tower server, or a rack-mounted server (including an independent server or a server cluster formed by a plurality of servers) that executes programs, and the like. The computer device of the embodiment at least includes but is not limited to: a memory 61, a processor 62, a network interface 63, and a data construction device 5, which may be communicatively connected to each other through a system bus, as shown in fig. 8. It should be noted that fig. 8 only shows a computer device with components, but it should be understood that not all of the shown components are required to be implemented, and more or fewer components may be implemented instead.
In the present embodiment, the memory 61 includes at least one type of computer-readable storage medium including a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the memory 61 may be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. In other embodiments, the memory 61 may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the computer device. Of course, the memory 61 may also include both internal and external storage devices of the computer device. In this embodiment, the memory 61 is generally used for storing an operating system and various types of application software installed in the computer device, such as a program code of the data constructing apparatus 5 of the first embodiment. Further, the memory 61 may also be used to temporarily store various types of data that have been output or are to be output.
Processor 62 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 62 is typically used to control the overall operation of the computer device. In this embodiment, the processor 62 is configured to execute the program code stored in the memory 61 or process data, for example, execute a data constructing apparatus, so as to implement the data constructing method of the first embodiment.
The network interface 63 may comprise a wireless network interface or a wired network interface, and the network interface 53 is typically used to establish a communication connection between the computer device 6 and other computer devices 6. For example, the network interface 63 is used to connect the computer device 6 to an external terminal via a network, establish a data transmission channel and a communication connection between the computer device 6 and the external terminal, and the like. The network may be a wireless or wired network such as an Intranet (Intranet), the Internet (Internet), a Global System of Mobile communication (GSM), Wideband Code Division Multiple Access (WCDMA), a 4G network, a 5G network, Bluetooth (Bluetooth), Wi-Fi, and the like.
It is noted that fig. 8 only shows the computer device 6 with components 61-63, but it is to be understood that not all shown components are required to be implemented, and that more or less components may be implemented instead.
In this embodiment, the data constructing apparatus 5 stored in the memory 61 can also be divided into one or more program modules, and the one or more program modules are stored in the memory 61 and executed by one or more processors (in this embodiment, the processor 62) to complete the present invention.
Example four:
to achieve the above objects, the present invention also provides a computer-readable storage medium including a plurality of storage media such as a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, which when executed by a processor 63, implements corresponding functions. The computer readable storage medium of the embodiment is used for storing the data constructing apparatus 5, and when being executed by the processor 63, the computer readable storage medium implements the data constructing method of the first embodiment.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A method of data construction, comprising:
establishing a customer model set, and associating each customer model in the customer model set with preset preparation data;
acquiring user information, matching a client model according to the user information, and acquiring preparation data corresponding to the user information;
executing a task according to the prepared data corresponding to the user information, and synchronizing a task result to a data table;
target data is generated based on the data table.
2. The data construction method of claim 1, wherein the building a set of customer models comprises the following:
collecting user service data and basic data;
classifying the basic data by adopting a pre-trained classification model based on the user service data to obtain a classification result;
and obtaining a customer model set according to the classification result.
3. The data construction method according to claim 1, wherein the obtaining user information comprises:
establishing an initial customer model;
monitoring user page operation, and updating the initial client model according to the user operation to obtain an individualized client model;
and obtaining user information according to the personalized customer model.
4. The data construction method according to claim 1, wherein the obtaining user information comprises:
screening the client model set according to preset conditions to obtain at least one piece of basic user data;
and marking each basic user data by adopting a preset first label to obtain the user data with the first label as user information.
5. The data construction method according to claim 1, wherein the performing a task according to the preparation data corresponding to the user information and synchronizing a task result to a data table comprises the steps of:
acquiring a task type according to the preparation data corresponding to the user information, wherein the task type comprises a basic task and a personalized task;
when the task type is a basic task, card data is obtained according to user information, an activation interface is called to execute the task, and a task result is synchronized to a data table;
and when the task type is the personalized task, card data and task data are acquired according to the user information, an interface corresponding to the task data is called to execute the task, and a task result is synchronized to a data table.
6. The data construction method according to claim 5, characterized in that before acquiring card data according to user information and calling an activation interface to execute tasks, the method comprises the following steps:
and after user information with a preset first label is screened out, calling a batch activation interface to execute a task.
7. The data construction method according to claim 1, wherein the generating target data based on the data table comprises the following steps:
acquiring user information and staging qualification data corresponding to the information of each user and the like according to the data table;
and visually displaying the user information and the staging qualification data by adopting a preset template to obtain target data.
8. A data construction apparatus, comprising:
the construction module is used for establishing a client model set and associating each client model in the client model set with preset preparation data;
the acquisition module is used for acquiring user information, matching a client model according to the user information and acquiring preparation data corresponding to the user information;
the execution module is used for executing tasks based on the prepared data corresponding to the user information and synchronizing task results to a data table;
and the generating module is used for generating target data according to the data table.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the data construction method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium comprising a plurality of storage media, each storage medium having a computer program stored thereon, wherein the computer programs stored in the plurality of storage media, when executed by a processor, collectively implement the steps of the data construction method of any one of claims 1 to 7.
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