Data processing method and device, computer program product and electronic equipment

Abstract

The invention relates to the technical field of computers, in particular to a data processing method and device, a computer program product and electronic equipment. The data processing method comprises the steps of obtaining attribute rules corresponding to a data extraction plug-in, wherein the attribute rules at least comprise a first type of rules and a second type of rules; acquiring a data request sent to the server by the terminal equipment and return data corresponding to the data request by utilizing the data extraction plug-in, and performing rule matching on the data request and the return data based on the first class of rules so as to determine a target data request according to a matching result; analyzing target return data corresponding to the target data request according to a second type of rules, and extracting target data from an analysis result; and generating a data processing result according to the attribute information of the target data request and the target data. The data extraction efficiency can be improved, and the data extraction accuracy is improved.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically, to a data processing method, a data processing apparatus, a computer program product, and an electronic device. Background Technology

[0002] Network debugging agents can record and examine request data between terminal devices and the internet for analysis, debugging, and modification. However, traditional data extraction methods rely on manually browsing request lists to extract requests and corresponding response data, which is inefficient, prone to data omission, and unable to accurately obtain the required data.

[0003] It should be noted that the information in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this disclosure is to provide a data processing method and apparatus, computer program product and electronic device, thereby improving data extraction efficiency and accuracy to at least a certain extent.

[0005] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part by practice of this disclosure.

[0006] According to one aspect of this disclosure, a data processing method is provided, applied to a terminal device equipped with a debugging agent, the debugging agent integrating a data extraction plugin; the method includes: obtaining attribute rules corresponding to the data extraction plugin, the attribute rules including at least a first type of rule and a second type of rule; using the data extraction plugin to obtain a data request sent by the terminal device to a server and the corresponding return data, and performing rule matching on the data request and the return data based on the first type of rule to determine a target data request based on the matching result; parsing the target return data corresponding to the target data request according to the second type of rule, and extracting target data from the parsing result; and generating a data processing result based on the attribute information of the target data request and the target data.

[0007] In one exemplary embodiment, the method further includes: responding to a triggering operation of a debugging agent, creating a UI object for a data extraction plugin, the UI object including a text box component; and associating the UI object with a preset tab of the debugging agent.

[0008] In one exemplary embodiment, obtaining the attribute rules corresponding to the data extraction plugin includes: obtaining the configuration file corresponding to the text box component, the configuration file being used to store the attribute rules corresponding to the text box component; initializing the interface object based on the configuration file, and obtaining the attribute rules corresponding to the data extraction plugin according to the attribute rules corresponding to the text box component.

[0009] In one exemplary embodiment, the method further includes: responding to an input event for the text box component, obtaining the input content corresponding to the input event, and updating the attribute rules corresponding to the text box component based on the input content.

[0010] In one exemplary embodiment, a data extraction plugin is used to obtain a data request sent by a terminal device to a server and the corresponding return data, and rule matching is performed on the data request and the return data based on a first type of rule to determine a target data request based on the matching result. This includes: obtaining a data request using the data extraction plugin; performing rule matching on the data request based on the first type of rule; and obtaining candidate data requests that conform to the first type of rule based on the matching result; obtaining the return data corresponding to the candidate data request; performing rule matching on the return data based on the first type of rule; and determining the target data request from the candidate data requests based on the matching result.

[0011] In one exemplary embodiment, the first type of rules includes interface filtering rules; performing rule matching on data requests and returned data based on the first type of rules to determine the target data request according to the matching result includes: performing rule matching on data requests based on interface filtering rules, and obtaining candidate data requests that conform to the interface filtering rules according to the matching result; performing rule matching on the returned data corresponding to the candidate data requests based on interface filtering rules; if the returned data corresponding to the candidate data requests matches the interface filtering rules, then the candidate data requests are determined to be the target data requests.

[0012] In one exemplary embodiment, the data request and returned data are matched according to a first type of rule to determine the target data request based on the matching result. The method further includes: determining the data to be processed corresponding to the target returned data based on the attribute information of the target data request and / or the target returned data.

[0013] In one exemplary embodiment, the first type of rule further includes content display rules; determining the data to be processed corresponding to the target returned data based on the attribute information of the target data request and / or the target returned data includes: extracting content description data from the target returned data according to the content display rules; calling a preset method to extract the request time data corresponding to the target data request; and determining the data to be processed based on the attribute information of the target data request, the target returned data, the content description data, and the request time data.

[0014] In one exemplary embodiment, the second type of rules includes data filtering rules; parsing the target returned data corresponding to the target data request according to the second type of rules, and extracting the target data from the parsing results, includes: extracting a first key field from the data filtering rules according to preset rules, the first key field being used to describe the filtering items; parsing the data to be processed, and obtaining a second key field corresponding to the first key field from the parsing results; and determining the target data based on the first key field and the second key field.

[0015] In one exemplary embodiment, the method further includes: if there are multiple target data requests, generating pending data corresponding to the target return data of each target data request, and presenting each pending data through a debugging agent; in response to a selection operation, determining the target pending data corresponding to the selection operation from each pending data.

[0016] In one exemplary embodiment, the second type of rules includes file naming rules; the method further includes: parsing the file naming rules and obtaining the file name from the parsing result; creating a file with the file name and importing the data processing result into the file.

[0017] According to one aspect of this disclosure, a data processing apparatus is provided, applied to a terminal device equipped with a debugging agent, the debugging agent integrating a data extraction plugin. The apparatus includes: a rule acquisition module, used to acquire attribute rules corresponding to the data extraction plugin, the attribute rules including at least a first type of rule and a second type of rule; a first data processing module, used to acquire data requests sent by the terminal device to a server and corresponding return data using the data extraction plugin, and to perform rule matching on the data requests and return data based on the first type of rule to determine a target data request based on the matching result; a second data processing module, used to parse the target return data corresponding to the target data request according to the second type of rule, and to extract target data from the parsing result; and a result generation module, used to generate a data processing result based on the attribute information of the target data request and the target data.

[0018] According to one aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements any of the above methods.

[0019] According to one aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform a method of any of the above by executing the executable instructions.

[0020] The data processing method in the exemplary embodiments of this disclosure includes, on the one hand, a debugging agent integrated with a data extraction plugin. This plugin acquires the attribute rules corresponding to the text box component of the data extraction plugin, uses the plugin to obtain the data request sent from the terminal device to the server and the corresponding returned data, and performs rule matching on the data request and returned data based on the first type of rule in the attribute rules. The target data request is determined based on the matching result, enabling efficient extraction of data requests that meet the requirements based on attribute rules, thus improving the efficiency of data request extraction compared to manual browsing. On the other hand, the target returned data corresponding to the target data request is parsed according to the second type of rule, and the target data is extracted from the parsing result. This allows for the extraction of the required field data from the server's response data, improving the accuracy and relevance of the extracted data.

[0021] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0022] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation.

[0023] Figure 1 An application environment according to an exemplary embodiment of this disclosure is shown.

[0024] Figure 2 A flowchart of a data processing method according to an exemplary embodiment of the present disclosure is shown.

[0025] Figure 3 A flowchart illustrating an implementation of a data extraction plugin for integrating a debugging agent according to an exemplary embodiment of the present disclosure is shown.

[0026] Figure 4 A flowchart illustrating an implementation of attribute rules for a data extraction plugin according to an exemplary embodiment of the present disclosure is shown.

[0027] Figure 5 A flowchart illustrating an implementation of an attribute rule for updating a text box component according to an exemplary embodiment of the present disclosure is shown.

[0028] Figure 6 A flowchart illustrating an implementation of determining a target data request according to an exemplary embodiment of the present disclosure is shown.

[0029] Figure 7 A flowchart illustrating a method for determining a target data request according to an exemplary embodiment of the present disclosure is shown.

[0030] Figure 8 A flowchart illustrating a method for determining the data to be processed corresponding to the target returned data according to an exemplary embodiment of the present disclosure is shown.

[0031] Figure 9 A schematic diagram is shown illustrating a UI list displayed in an interface object based on a data extraction plugin capturing target data requests, according to an exemplary embodiment of the present disclosure.

[0032] Figure 10 A flowchart illustrating an implementation method for extracting target data according to an exemplary embodiment of the present disclosure is shown.

[0033] Figure 11 A schematic diagram of the composition of a data processing apparatus according to an exemplary embodiment of the present disclosure is shown.

[0034] Figure 12 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown.

[0035] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0036] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore their detailed description will be omitted.

[0037] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known structures, methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0038] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more software-hardened modules, or in different network and / or processor devices and / or microcontroller devices.

[0039] The data processing method provided by the exemplary embodiments of this disclosure can be applied to, for example... Figure 1 The application environment shown. For example... Figure 1 As shown, the terminal device 11 can be equipped with a client such as a browser. The webpage displayed in the browser can be called the front-end page. The browser communicates with the server 12 through the network, sends data requests to the server 12, and the server 12 returns interface data to the browser. The browser renders the page according to the returned interface data and finally displays the front-end page on the terminal device 11 for users to view.

[0040] The Hypertext Transfer Protocol (HTTP) is a request-response protocol that specifies what messages a client might send to a server and what responses it might receive. Debugging proxies (such as HTTP debugging proxies) can record and examine HTTP communication between terminal devices and servers to view all the data for analysis, debugging, or modification.

[0041] The server 12 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server 12 can execute background tasks. The terminal device 11 can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, IoT device, or portable wearable device. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle devices. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The terminal device 11 can also be referred to as a mobile terminal, electronic device, or mobile device; the exemplary embodiments of this disclosure do not limit the type of terminal device 11.

[0042] Traditional data extraction methods require manual browsing of a request list to select the desired data request, followed by extraction of the corresponding response data. However, this method necessitates filtering and selection by the user, resulting in low efficiency, potential omissions, and the inability to extract the full response data of each request, thus affecting the accuracy of the extracted data.

[0043] In an exemplary embodiment of this disclosure, by integrating a data extraction plugin into the debugging agent, the terminal device can efficiently and accurately extract useful data based on the debugging agent using the data extraction plugin.

[0044] refer to Figure 2The flowchart shown is an exemplary embodiment of the data processing method of this disclosure, which is applied to a terminal device with a debugging agent installed. The debugging agent integrates a data extraction plugin. This disclosure does not limit the specific form of the debugging agent, and any debugging agent that can realize network debugging function is applicable to this disclosure.

[0045] like Figure 2 As shown, the data processing method includes steps S210 to S240, as detailed below:

[0046] In step S210, the attribute rules corresponding to the data extraction plugin are obtained. The attribute rules include at least the first type of rules and the second type of rules.

[0047] In the exemplary embodiments of this disclosure, the data extraction plugin is a program used to filter data requests and corresponding return data sent from a terminal device to a server, and to select data requests and related data that meet the requirements. The data extraction plugin can be a program written in accordance with a certain application programming interface specification. The exemplary embodiments of this disclosure do not limit the specific form of the data extraction plugin.

[0048] The data extraction plugin can be integrated into the debugging agent's code, or its file path can be configured in the debugging agent's installation directory. The exemplary embodiments of this disclosure do not impose any special restrictions on the integration method of the data extraction plugin.

[0049] Attribute rules refer to the rule information that the data extraction plugin relies on for data filtering. These rules can be pre-defined. The first type of rule is used to filter requests, that is, to filter out data requests that meet the rules from all data requests sent from the terminal device to the server. The second type of rule is used to filter data, that is, to further filter the data requests filtered by the first type of rule, the second type of rule can be used to further filter out the desired data.

[0050] It should be noted that the attribute rules corresponding to the data extraction plugin can be dynamically adjusted according to actual needs to adapt to the data extraction requirements.

[0051] In step S220, the data extraction plugin is used to obtain the data request sent by the terminal device to the server and the corresponding return data. The data request and return data are then matched according to the first type of rule to determine the target data request based on the matching result.

[0052] In an exemplary embodiment of this disclosure, the data extraction plugin can acquire data requests sent from a terminal device to a server and obtain the corresponding return data. Specifically, the data extraction plugin can acquire data requests and return data through event listening. For example, it can listen for communication events between the terminal device and the server; if data communication exists between the terminal device and the server, it triggers request capture to obtain the corresponding data information (data request, return data).

[0053] Specifically, the system can perform rule matching on the data request based on the first type of rule, and perform rule matching on the returned data based on the first type of rule, thereby obtaining the target data request that meets the requirements from the data request based on the matching results of the two matches.

[0054] In step S230, the target returned data corresponding to the target data request is parsed according to the second type of rule, and the target data is extracted from the parsing result.

[0055] In an exemplary embodiment of this disclosure, after extracting the target data request using the first type of rules, the returned target data can be further parsed using the second type of rules to extract the target data that conforms to the second type of rules. In traditional data extraction methods, all fields of the returned data are typically extracted, requiring manual differentiation of different fields. The second type of rules filters out the expected target data from the all-field data, improving the accuracy of data extraction and facilitating intuitive manual review.

[0056] In step S240, data processing results are generated based on the attribute information requested by the target data and the target data.

[0057] In an exemplary embodiment of this disclosure, the attribute information of the target data request is information used to describe the target data request, including but not limited to the complete URL (uniform resource location) of the target data request, the complete request body data, the request initiation time, etc.

[0058] Among them, it can generate data processing results based on the attribute information requested by the target data and the target data. It can also concatenate the attribute information and the target data into a predetermined format to obtain the data processing results, which are convenient for users to view intuitively.

[0059] The data processing method in the exemplary embodiments of this disclosure includes, on the one hand, a debugging agent integrated with a data extraction plugin. This plugin acquires the attribute rules corresponding to the text box component of the data extraction plugin, uses the plugin to obtain the data request sent from the terminal device to the server and the corresponding returned data, and performs rule matching on the data request and returned data based on the first type of rule in the attribute rules. The target data request is determined based on the matching result, enabling efficient extraction of data requests that meet the requirements based on attribute rules, thus improving the efficiency of data request extraction compared to manual browsing. On the other hand, the target returned data corresponding to the target data request is parsed according to the second type of rule, and the target data is extracted from the parsing result. This allows for the extraction of the required field data from the server's response data, improving the accuracy and relevance of the extracted data.

[0060] In one exemplary embodiment, an implementation method for integrating a data extraction plugin into a debugging agent is provided. For example... Figure 3 As shown, exemplary embodiments of this disclosure further include:

[0061] Step S310: Respond to the trigger operation of the debug agent and create the interface object of the data extraction plugin, which includes a text box component.

[0062] Step S320: Configure the interface object to associate with the preset tab of the debug agent.

[0063] The triggering operation for the debug agent refers to the process of opening the debug agent, which in turn triggers the initialization of the data extraction interface. This involves creating the interface object of the data extraction plugin and associating it with the debug agent's preset tabs, thus displaying the data extraction plugin's interface object in the user interface. The interface object can be a container of objects that constitute the application's user interface and can be created based on a UI (User Interface) framework; there are no restrictions on this.

[0064] In a user interface object, a text box component refers to a text box used to get or set text content, allowing users to directly access or modify the content. For example, a TextBox input box determines its content by listening to the input event of the TextBox input box.

[0065] Among them, associating UI objects with preset tabs of the debugging agent can be configured by adding UI objects to preset tabs through preset function methods (such as the page.Controls.Add method), thus completing the association between UI objects and preset tabs.

[0066] As an example, the process of configuring a data extraction plugin is illustrated.

[0067] First, the file for the data extraction plugin reads the key value corresponding to the debugging agent in the system registry of the terminal device, saves it as the installation directory of the debugging agent, and then copies the file for the data extraction plugin to the Scripts folder under the security target of the debugging agent.

[0068] Next, you can integrate the debug agent's extension class into the first function (such as the Main function) of the program execution within the data extraction plugin's file. This extension class is an interface provided by the debug agent for developing custom debug agents. To implement the interface object of the data extraction plugin, you need to implement the debug agent's extension class.

[0069] Finally, the first function executed by the data extraction plugin can also listen for events (such as the Onload event). When the debug agent is turned on, the debug agent loads the data extraction plugin file in the Scripts file and triggers the event, thereby creating the interface object of the data extraction plugin and creating the preset tabs of the debug agent (such as the plugin Tab object page). The interface object is then added to the plugin Tab object page using the page.Controls.Add method.

[0070] Through the above process, the UI interface of the data extraction plugin can be presented through the debugging agent, thereby allowing menu items, tabs, or other UI elements to be safely added to the UI interface of the debugging agent.

[0071] In one exemplary embodiment, an implementation method for obtaining the attribute rules of a data extraction plugin is also provided. The attribute rules of the data extraction plugin can be obtained through a text box component of an interface object. The text box component has a corresponding configuration file for storing the attribute rules corresponding to the text box component, and the rules are determined based on the attribute rules corresponding to all text box components in the interface object. Based on this, as... Figure 4 As shown, exemplary embodiments of this disclosure may further include:

[0072] Step S410: Obtain the configuration file corresponding to the text box component.

[0073] Step S420: Initialize the interface object based on the configuration file, and obtain the attribute rules corresponding to the data extraction plugin according to the attribute rules corresponding to the text box component.

[0074] Initializing the interface object based on the configuration file refers to associating the attribute rules in the configuration file with the text box component in the interface object. For example, a person manually inputs information into the text box component, and the attribute rules in the configuration file are updated according to the input information.

[0075] As an example, the absolute path of "My Documents" in the terminal device's system can be obtained. Then, the absolute path of "My Documents" can be concatenated with a preset path according to preset rules to determine the absolute path of the configuration file corresponding to the text box component. The preset path can be configured according to actual conditions, and the preset rules can be, for example, path concatenation or other path construction methods; there are no restrictions on this.

[0076] Based on this, the existence of a configuration file for the text box component can be determined by checking the absolute path of the configuration file. If it does not exist, an empty configuration data object can be generated. If it exists, the contents of the configuration file can be read using a preset method (such as the Stream Reader method), and the file content can be deserialized to generate the configuration data object. The file content can be deserialized using a preset method (such as the JObject.Parse method), without any special restrictions.

[0077] The configuration data object can contain at least the following fields: {Attribute Rule 1, Attribute Rule 2, Attribute Rule 3, ...}. As an example, the configuration data object could be: {filter: Interface filtering rule, format: Data filtering rule, file Name: File naming rule, list Item Content: Content display rule}. Of course, the content of the configuration data object can be set according to actual needs, and there are no special restrictions on it.

[0078] Based on this, text box components corresponding to each attribute rule are created in the interface object. Each text box component is used to obtain information input by the user. Specifically, the attribute values ​​of the configuration data object can be read and assigned to the Text property of the corresponding text box component, thus initializing the interface object.

[0079] In one exemplary embodiment, an implementation method for updating the attribute rules of a text box component is also provided. For example... Figure 5 As shown, this implementation method may include:

[0080] Step S510: Respond to the input event for the text box component and obtain the input content corresponding to the input event;

[0081] Step S520: Update the attribute rules corresponding to the text box component based on the input content.

[0082] Specifically, it can automatically listen for input events of the text box component and respond to these events to obtain the corresponding input content. The input events of the text box component can be user input via an input device or file uploads; there are no restrictions.

[0083] When the attribute rules of the text box component are updated according to the input content, the system can also respond to the save operation, create a configuration object, write the updated attribute rules of the text box component into the configuration object, generate the configuration file of the configuration object, which is the configuration file of the text box component, and save the configuration file to the absolute path of the configuration file to realize the update of the configuration file of the text box component.

[0084] In one exemplary embodiment, an implementation method for determining a target data request is provided. For example... Figure 6 As shown, the data extraction plugin is used to obtain the data requests sent from the terminal device to the server and the corresponding return data. Based on the first type of rule, rule matching is performed on the data requests and return data to determine the target data request, which may include:

[0085] Step S610: Use the data extraction plugin to obtain data requests, perform rule matching on the data requests based on the first type of rules, and obtain candidate data requests that conform to the first type of rules based on the matching results.

[0086] Step S620: Obtain the returned data corresponding to the candidate data request, perform rule matching on the returned data based on the first type of rule, and determine the target data request from the candidate data requests based on the matching result.

[0087] Data requests are sent from the terminal device to the server and can be obtained by using a data extraction plugin to listen for events. The data extraction plugin can access the global object of the debug proxy and listen for the global Before Request event of the debug proxy using preset syntax. If the global Before Request event is detected, the data request is obtained, and the steps of matching the data request according to the first type of rules are executed. For example, the data extraction plugin can use C# delegate syntax to listen for the global Before Request event of the debug proxy, without specific restrictions on the listening method.

[0088] It should also be understood that a request, after being processed by the debugging proxy, will first trigger the Before Request event, and then the Before Response event. Based on the triggered Before Response event, the returned data corresponding to the data request can be obtained. In other words, the way to obtain the returned data can also be achieved by the data extraction plugin through event listening, and the returned data can be matched according to the first type of rule.

[0089] In some alternative embodiments, the first type of rules includes interface filtering rules, such as Figure 7As shown, rule matching is performed on the data request and returned data based on the first type of rules to determine the target data request based on the matching results. This may include:

[0090] Step S710: Perform rule matching on the data request based on the interface filtering rules, and obtain candidate data requests that meet the interface filtering rules according to the matching results.

[0091] Interface filtering rules can be obtained based on the absolute path corresponding to the rule attribute. Interface filtering rules are used to match data requests and their corresponding returned data to obtain target data requests where both the data request and the returned data conform to the interface filtering rules.

[0092] Specifically, if the interface filtering rule is empty, skip this step. If the interface filtering rule is not empty, a regular expression object can be created using a preset method (such as new Regex(filter)), and the complete URL attribute of the object used to store attributes and configuration information (such as a Session object) of the data request can be obtained. It can then be determined whether the complete URL attribute matches the interface filtering rule. If it does not match, skip this step; if it does match, the data request is determined as a candidate data request.

[0093] In some optional embodiments, the display properties of the Session object corresponding to the candidate data request can also be set to facilitate quick identification. For example, the "ui-color" property of the Session object can be updated to "#FFFFFF" and the "ui-backcolor" property can be updated to "#9966CC" for highlighting.

[0094] Step S720: Perform rule matching on the returned data corresponding to the candidate data request based on the interface filtering rules.

[0095] Step S730: If the returned data corresponding to the candidate data request matches the interface filtering rules, then the candidate data request is determined to be the target data request.

[0096] As mentioned earlier, a request processed by the debugging proxy will first trigger the Before Request event, and then the Before Response event. Therefore, after identifying candidate data requests, rule matching is performed on the returned data corresponding to the candidate data requests based on the interface filtering rules. The implementation method for rule matching of returned data based on interface filtering rules is detailed in the process of rule matching for data requests, and will not be elaborated here.

[0097] If the returned data of the candidate data request matches the interface filtering rules, the candidate data request is determined to be the target data request. Optionally, the string of the returned data can also be obtained and deserialized into a JSON object.

[0098] As an example, you can call the Session object's Get Response Body AsString() method to get the string of returned data and then deserialize it into a JSON object named data using JObject.Parse, without any special restrictions.

[0099] By intercepting data requests and their corresponding return data through a data extraction plugin, and using interface filtering rules to match the data requests and their return data, the efficiency of data extraction is improved.

[0100] In one exemplary embodiment, the method of performing rule matching on the data request and returned data based on the first type of rules to determine the target data request according to the matching result further includes:

[0101] Based on the attribute information requested by the target data and / or the data returned by the target, determine the data to be processed corresponding to the data returned by the target.

[0102] The data to be processed is used to extract relevant field data of the data processing result. It may include the target return data corresponding to the target data request, or the attribute information of the target return data and the target data request. After the data to be processed is determined, relevant field data can be extracted from the data to be processed to simplify the data to be processed.

[0103] In one exemplary embodiment, the first type of rules further includes content display rules, which are used to indicate the content to be displayed. For example... Figure 8 As shown, based on the attribute information of the target data request and / or the target returned data, the data to be processed corresponding to the target returned data may include:

[0104] Step S810: Extract content description data from the target returned data according to the content display rules.

[0105] Users can input information through a text box component to determine which content to display in the results, thereby obtaining the content display rules. Then, content description information that conforms to the content display rules can be extracted from the target returned data.

[0106] As an example, based on content display rules, a preset method can be called to extract content description information from the target returned data. Here, the preset method can be the `getNodeValue` method, which is used to retrieve the target data from the returned data according to filtering conditions. This method can include two parameters: a JSON object `data` and a filtering condition string. The execution flow of this method can include:

[0107] First, create a JToken object `value`, assign the JSON object `data` to `value`, and call the `str.Split('.')` method to split the filtering conditions into an array of string keys `keyList`. Then, iterate through `keyList` to retrieve the keys one by one. Finally, call `value = value[key]` to retrieve the attribute values ​​level by level. After the iteration is complete, return the final `value`. Based on this, preset methods can be called to extract content description information from the target returned data.

[0108] Based on content display rules, the required content description data can be accurately obtained from the target returned data, simplifying the data extraction results and ensuring high accuracy of data extraction.

[0109] Step S820: Call the preset method to extract the request time data corresponding to the target data request.

[0110] To facilitate a comprehensive display of the extraction results during the data extraction process, the request time data corresponding to the target data request can also be extracted to accurately indicate the time information of the target data request. In this exemplary embodiment, the request time data can be extracted using a preset algorithm; any method capable of extracting request time data is applicable, and no special limitations are imposed.

[0111] Step S830: Determine the data to be processed based on the attribute information of the target data request, the target returned data, the content description data, and the request time data.

[0112] The data to be processed, also known as the response model object, is determined based on the target data request, the target returned data, the content description data, and the request time data. It can be in the following format:

[0113] {

[0114] index: Request list sequence number,

[0115] url: The complete URL of the data request.

[0116] data: The complete string of data returned by the data request.

[0117] time: The time when the data request was initiated.

[0118] Month Day: Data request initiation time (format: xx month xx day)

[0119] Request Body: The complete request body data.

[0120] Item Content: Custom UI list description content,

[0121] };

[0122] The custom UI list description content is extracted from the data returned from the target. The above format is just an example and can be set according to actual needs; there are no special restrictions on it.

[0123] By further extracting the data to be processed through content display rules and preset methods, the efficiency of data extraction is improved, while the data to be processed is enriched, so as to obtain accurate data processing results.

[0124] In some alternative embodiments, an array object (such as a response list) can also be initialized, for example, by creating an empty array object using the new ArrayList() method. Then, the data to be processed is added to the array object as a response model object to facilitate subsequent processing.

[0125] This also allows calling the update method of the UI object to read the array object and iterate through it sequentially, updating the UI list of the UI object based on the iteration results. For example... Figure 9 The diagram illustrates a UI list displayed in an interface object, showing a request for target data captured by a data extraction plugin, including "Request Time" and "Custom (Content Description Data)". Figure 9 This is merely an example; in actual implementation, the corresponding interface object will be obtained based on the actual situation.

[0126] In one exemplary embodiment, after capturing the target data request, further data export is required, and a method for extracting the target data is also provided. For example... Figure 10 As shown, parsing the target returned data corresponding to the target data request according to the second type of rule, and extracting the target data from the parsing result may include:

[0127] Step S1010: Extract the first key field from the data filtering rules according to the preset rules. The first key field is used to describe the filter items.

[0128] The second type of rule includes data filtering rules, which are used to indicate the target data required. The default rule here can be the getNode Value method mentioned above, or it can be set according to actual needs. The first key field is equivalent to the key value in a key-value pair.

[0129] Step S1020: Parse the data to be processed and obtain the second key field corresponding to the first key field from the parsing results.

[0130] The data to be processed can be parsed according to a preset method. For example, if the data to be processed is separated by ".", it can be parsed based on ".". Of course, the parsing method can be flexibly selected. After obtaining the parsing result, the corresponding second key field can be obtained using the first key field, that is, the "value".

[0131] Step S1030: Determine the target data based on the first key field and the second key field.

[0132] After obtaining the first and second key fields, the required target data can be determined based on the first and second key fields.

[0133] As an example, the `export Response Data` method can be used to retrieve the data to be processed from the response list using a unique identifier (such as the index value). Then, `JObject.Parse` is used to deserialize the `data` property of the data to obtain a JSON object `data`. Next, `new Jobject()` is called to create an exported data object `result`. Then, the data filtering rules are obtained and split into a string array `formatList` using `format.Split(',')`. Each item in `formatList` is then iterated through and split using `formatList[i].Split('.')` to obtain the last item as the key (i.e., the first key field). Then, `getNodeValue(data,formatList[i])` is called to obtain the corresponding value (i.e., the second key field). Finally, `result.Add(key,value)` is used to add the exported data, thus determining the target data based on the first and second key fields.

[0134] By obtaining the unique identifier of the data to be processed for each target data request, and by breaking down the data filtering rules and obtaining the second key field from the parsing result of the data to be processed based on the first key field, the target data required by the user can be further extracted from the data to be processed, thereby simplifying the data processing results and avoiding the data redundancy problem that exists in the full export return data.

[0135] In an exemplary embodiment, if there are multiple target data requests, then the data to be processed corresponding to the target return data of each target data request is generated, and each data to be processed is presented through a debugging agent. Then, in response to a selection operation, the target data to be processed corresponding to the selection operation can be determined from each data to be processed.

[0136] Specifically, when there are multiple target data requests, the pending data corresponding to the target returned data of each target data request can be presented in the interface object. Users can choose which / which pending data to export, giving data processing greater flexibility and meeting different data extraction needs.

[0137] In one exemplary embodiment, an implementation method for naming data processing results is also provided. The second type of rule includes file naming rules, and this implementation method may include:

[0138] First, the file naming rules are parsed, and the filenames are obtained from the parsing results. Then, a file with the filenames is created, and the data processing results are imported into the file.

[0139] Specifically, the data processing results can be imported into a user-defined file and named according to user needs, making it convenient for users to quickly obtain the data processing results and improving the user experience of data extraction.

[0140] As an example, the `getNodeValue(data,fileName)` method can still be called to obtain the filename. Optionally, illegal characters (such as \n, \, / , :, *, ?, ", <, >, |, etc.) in the filename can be removed simultaneously. Optionally, the absolute path of the system desktop can also be obtained, and the absolute path of the file (data Path) can be concatenated according to a preset rule (such as absolute path of system desktop\unique identifier corresponding to data processing result (as indicated by index value)-filename-response.Month Day attribute value.txt), and the data processing result can be saved to the absolute path of that file. Of course, the exemplary embodiments of this disclosure can also ensure the save path in other ways, and there are no restrictions on the way the file is saved.

[0141] The data processing method in the exemplary embodiments of this disclosure includes, on the one hand, a debugging agent integrated with a data extraction plugin. This plugin acquires the attribute rules corresponding to the text box component of the data extraction plugin, uses the plugin to obtain the data request sent from the terminal device to the server and the corresponding returned data, and performs rule matching on the data request and returned data based on the first type of rule in the attribute rules. The target data request is determined based on the matching result, enabling efficient extraction of data requests that meet the requirements based on attribute rules, thus improving the efficiency of data request extraction compared to manual browsing. On the other hand, the target returned data corresponding to the target data request is parsed according to the second type of rule, and the target data is extracted from the parsing result. This allows for the extraction of the required field data from the server's response data, improving the accuracy and relevance of the extracted data.

[0142] In an exemplary embodiment of this disclosure, a data processing apparatus is also provided, applied to a terminal device equipped with a debugging agent, the debugging agent integrating a data extraction plugin. (See reference...) Figure 11 As shown, the data processing device 1100 may include a rule acquisition module 1110, a first data processing module 1120, a second data processing module 1130, and a result generation module 1140. Specifically:

[0143] The rule acquisition module 1110 is used to acquire the attribute rules corresponding to the data extraction plugin, wherein the attribute rules include at least a first type of rule and a second type of rule; the first data processing module 1120 is used to acquire the data request sent by the terminal device to the server and the return data corresponding to the data request using the data extraction plugin, and to perform rule matching on the data request and the return data based on the first type of rule, so as to determine the target data request according to the matching result; the second data processing module 1130 is used to parse the target return data corresponding to the target data request according to the second type of rule, and to extract the target data from the parsing result; the result generation module 1140 is used to generate a data processing result based on the attribute information of the target data request and the target data.

[0144] In an exemplary embodiment, the rule acquisition module 1110 is configured to perform the following actions in response to a triggering operation of a debugging agent: creating an interface object for a data extraction plugin, the interface object including a text box component; and associating the interface object with a preset tab of the debugging agent.

[0145] In one exemplary embodiment, the rule acquisition module 1110 is configured to perform the following: acquire the configuration file corresponding to the text box component, the configuration file being used to store the attribute rules corresponding to the text box component; initialize the interface object based on the configuration file; and acquire the attribute rules corresponding to the data extraction plugin according to the attribute rules corresponding to the text box component.

[0146] In one exemplary embodiment, the rule acquisition module 1110 is configured to perform: responding to an input event for the text box component, acquiring the input content corresponding to the input event, and updating the attribute rules corresponding to the text box component based on the input content.

[0147] In one exemplary embodiment, the first data processing module 1120 is configured to perform: obtaining a data request using a data extraction plugin, performing rule matching on the data request based on a first type of rule, and obtaining candidate data requests that conform to the first type of rule according to the matching result; obtaining the returned data corresponding to the candidate data request, performing rule matching on the returned data based on the first type of rule, and determining the target data request from the candidate data requests according to the matching result.

[0148] In one exemplary embodiment, the first type of rule includes interface filtering rules; the first data processing module 1220 is configured to perform: rule matching on data requests based on interface filtering rules, and obtain candidate data requests that conform to the interface filtering rules according to the matching results; perform rule matching on the returned data corresponding to the candidate data requests based on interface filtering rules; if the returned data corresponding to the candidate data requests matches the interface filtering rules, then determine the candidate data requests as target data requests.

[0149] In one exemplary embodiment, the first data processing module 1120 is configured to perform: determining the data to be processed corresponding to the target returned data based on the attribute information of the target data request and / or the target returned data.

[0150] In an exemplary embodiment, the first type of rules further includes content display rules; the first data processing module 1120 is configured to perform: extracting content description data from the target returned data according to the content display rules; calling a preset method to extract the request time data corresponding to the target data request; and determining the data to be processed based on the attribute information of the target data request, the target returned data, the content description data, and the request time data.

[0151] In an exemplary embodiment, the second type of rules includes data filtering rules; the second data processing module 1130 is configured to perform: extracting a first key field from the data filtering rules according to preset rules, the first key field being used to describe the filtering item; parsing the data to be processed and obtaining a second key field corresponding to the first key field from the parsing result; and determining the target data based on the first key field and the second key field.

[0152] In an exemplary embodiment, the second data processing module 1130 is configured to perform: if there are multiple target data requests, generate the data to be processed corresponding to the target return data of each target data request, and present each data to be processed through a debugging agent; in response to a selection operation, determine the target data to be processed corresponding to the selection operation from each data to be processed.

[0153] In one exemplary embodiment, the second type of rules includes file naming rules; the second data processing module 1130 is configured to perform: parsing the file naming rules and obtaining the file name from the parsing result; creating a file with the file name and importing the data processing result into the file.

[0154] Since the details of the various functional modules of the data processing apparatus of the exemplary embodiments of this disclosure have been described in the exemplary embodiments of the data processing method described above, they will not be repeated here.

[0155] It should be noted that although several modules or units of the data processing apparatus have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0156] Exemplary embodiments of this disclosure also provide a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the data processing method described above.

[0157] In one embodiment, the computer program product can be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid-state drive (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing the computer program, such as read-only memory, NAND flash memory, etc.

[0158] In one implementation, the computer program product can be an intangible product containing a computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, installation package, or other digital file storing the computer program.

[0159] Computer program code can be written in one or more programming languages. Examples of programming languages ​​include C, Java, and C++. Program code can execute entirely on the user's computing device, partially on the user's computing device, or as a standalone software package. It can also execute partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, such as a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via an internet connection provided by a mobile network operator).

[0160] Computer programs can be carried or transmitted via signals such as electrical, magnetic, optical, electromagnetic, and infrared rays. Electronic devices can convert the signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code is used to cause the electronic device to execute (more specifically, the processor of the electronic device to execute) the method steps of various exemplary embodiments of this disclosure, such as the data processing method described above.

[0161] Furthermore, in exemplary embodiments of this disclosure, an electronic device capable of implementing the above-described methods is also provided. Those skilled in the art will understand that various aspects of this disclosure can be implemented as systems, methods, or program products. Therefore, various aspects of this disclosure can be specifically implemented as entirely hardware embodiments, entirely software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, collectively referred to herein as "circuit," "module," or "system."

[0162] The following reference Figure 12 To describe an electronic device 1200 according to such an embodiment of the present disclosure. Figure 12 The electronic device 1200 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0163] like Figure 12 As shown, the electronic device 1200 is manifested in the form of a general-purpose computing device. The components of the electronic device 1200 may include, but are not limited to: at least one processing unit 1210, at least one storage unit 1220, a bus 1230 connecting different system components (including storage unit 1220 and processing unit 1210), and a display unit 1240.

[0164] The storage unit stores program code that can be executed by the processing unit 1210, causing the processing unit 1210 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 1210 can perform the steps shown in the exemplary embodiments described above.

[0165] Storage unit 1220 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 1221 and / or cache memory 1222, and may further include a read-only memory (ROM) 1223.

[0166] Storage unit 1220 may also include a program / utility 1224 having a set (at least one) of program modules 1225, such program modules 1225 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0167] Bus 1230 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0168] Electronic device 1200 can also communicate with one or more external devices 1300 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 1200, and / or with any device that enables electronic device 1200 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 1250. Furthermore, electronic device 1200 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 1260. As shown, network adapter 1260 communicates with other modules of electronic device 1200 via bus 1230. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 1200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0169] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0170] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0171] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A data processing method, characterized in that, The method is applied to terminal devices equipped with a debugging agent, wherein the debugging agent integrates a data extraction plugin; the method includes: Obtain the attribute rules corresponding to the data extraction plugin, wherein the attribute rules include at least a first type of rule and a second type of rule; The data extraction plugin is used to obtain the data request sent by the terminal device to the server and the return data corresponding to the data request. The data request and the return data are then matched according to the first type of rules to determine the target data request based on the matching result. The target returned data corresponding to the target data request is parsed according to the second type of rule, and the target data is extracted from the parsing result; Based on the attribute information requested by the target data and the target data, a data processing result is generated.

2. The method according to claim 1, characterized in that, The method further includes: In response to the triggering operation of the debugging agent, a UI object for the data extraction plugin is created, the UI object including a text box component; Configure the interface object to be associated with the preset tab of the debugging agent.

3. The method according to claim 2, characterized in that, The method for obtaining the attribute rules corresponding to the data extraction plugin includes: Obtain the configuration file corresponding to the text box component, the configuration file being used to store the attribute rules corresponding to the text box component; The interface object is initialized based on the configuration file, and the attribute rules corresponding to the data extraction plugin are obtained according to the attribute rules corresponding to the text box component.

4. The method according to claim 2, characterized in that, The method further includes: Respond to input events for the text box component and obtain the input content corresponding to the input event; Update the attribute rules corresponding to the text box component based on the input content.

5. The method according to claim 1, characterized in that, The step of using the data extraction plugin to obtain the data request sent by the terminal device to the server and the corresponding return data, and performing rule matching on the data request and the return data based on the first type of rules to determine the target data request based on the matching result includes: The data extraction plugin is used to obtain the data request, the data request is matched according to the first type of rule, and candidate data requests that conform to the first type of rule are obtained according to the matching result. Obtain the returned data corresponding to the candidate data request, perform rule matching on the returned data based on the first type of rule, and determine the target data request from the candidate data requests based on the matching result.

6. The method according to claim 5, characterized in that, The first type of rules includes interface filtering rules; the step of performing rule matching on the data request and the returned data based on the first type of rules, so as to determine the target data request according to the matching result, includes: The data request is matched according to the interface filtering rules, and candidate data requests that meet the interface filtering rules are obtained based on the matching results. Based on the interface filtering rules, the returned data corresponding to the candidate data request is matched according to the rules. If the returned data corresponding to the candidate data request matches the interface filtering rule, then the candidate data request is determined to be the target data request.

7. The method according to claim 1, characterized in that, The step of performing rule matching on the data request and the returned data based on the first type of rules, so as to determine the target data request according to the matching result, further includes: Based on the attribute information of the target data request and / or the target returned data, determine the data to be processed corresponding to the target returned data.

8. The method according to claim 7, characterized in that, The first type of rule also includes content display rules; the step of determining the data to be processed corresponding to the target returned data based on the attribute information of the target data request and / or the target returned data includes: Based on the content display rules, extract content description data from the target returned data; Invoke a preset method to extract the request time data corresponding to the target data request; The data to be processed is determined based on the attribute information of the target data request, the target returned data, the content description data, and the request time data.

9. The method according to claim 7, characterized in that, The second type of rules includes data filtering rules; the step of parsing the target returned data corresponding to the target data request according to the second type of rules, and extracting the target data from the parsing results, includes: The first key field is extracted from the data filtering rules according to the preset rules. The first key field is used to describe the filter item. The data to be processed is parsed, and the second key field corresponding to the first key field is obtained from the parsing result; The target data is determined based on the first key field and the second key field.

10. The method according to claim 7, characterized in that, The method further includes: If there are multiple target data requests, then generate the data to be processed corresponding to the target return data of each target data request, and present each data to be processed through the debugging agent; In response to a selection operation, the target data to be processed corresponding to the selection operation is determined from each of the data to be processed.

11. The method according to any one of claims 1 to 10, characterized in that, The second type of rules includes file naming rules; the method further includes: The file naming rules are parsed, and the filenames are obtained from the parsing results; Create a file with the specified filename and import the data processing results into the file.

12. A data processing apparatus, characterized in that, An apparatus for use on terminal devices equipped with a debugging agent, wherein the debugging agent integrates a data extraction plugin, the apparatus comprising: The rule acquisition module is used to acquire the attribute rules corresponding to the data extraction plugin, and the attribute rules include at least a first type of rule and a second type of rule. The first data processing module is used to obtain the data request sent by the terminal device to the server and the return data corresponding to the data request using the data extraction plugin, and to perform rule matching on the data request and the return data based on the first type of rules, so as to determine the target data request according to the matching result; The second data processing module is used to parse the target return data corresponding to the target data request according to the second type of rules, and extract the target data from the parsing result; The result generation module is used to generate data processing results based on the attribute information requested by the target data and the target data.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method according to any one of claims 1 to 11.

14. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 11 by executing the executable instructions.

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