CN116546278A - Data processing method, device, electronic equipment and storage medium - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44204—Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/21—Server components or server architectures
- H04N21/218—Source of audio or video content, e.g. local disk arrays
- H04N21/2187—Live feed
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/24—Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth, upstream requests
- H04N21/2407—Monitoring of transmitted content, e.g. distribution time, number of downloads
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/47—End-user applications
- H04N21/478—Supplemental services, e.g. displaying phone caller identification, shopping application
- H04N21/4788—Supplemental services, e.g. displaying phone caller identification, shopping application communicating with other users, e.g. chatting
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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Abstract
The disclosure relates to a data processing method, a device, an electronic device and a storage medium, wherein the method comprises the following steps: acquiring a preset interface use case; acquiring noise data corresponding to the interface use cases; acquiring actual response data and expected response data corresponding to the interface use cases; analyzing each first field in the actual response data to obtain a first analysis result; analyzing each second field in the expected response data to obtain a second analysis result; and determining a data processing result based on the first analysis result, the second analysis result and the noise data, wherein the data processing result is obtained by comparing all field information of the actual response data with all field information of the expected response data and automatically reducing noise, and has higher accuracy and higher data processing efficiency.
Description
Technical Field
The present disclosure relates to data processing technology, and in particular, to a data processing method, apparatus, electronic device, and storage medium.
Background
With the development of internet technology, the application scale of software is wider and the development period is shorter and shorter, and the interfaces involved in the software are more and more, so that the management of the interfaces in the software is more and more important. The interfaces include interfaces between the software system and other systems external to the system, as well as interfaces between various sub-modules within the system. At present, when an interface is managed, data analysis is often required to be performed on the call condition of the interface manually, namely, related staff analyze check fields in the call result of the interface, and then compare and check the analyzed check fields to judge whether the expected condition is met, so that the data processing efficiency is lower.
Disclosure of Invention
The disclosure provides a data processing method, a data processing device, an electronic device and a storage medium, so as to at least solve the problem of low data processing efficiency in the related art. The technical scheme of the present disclosure is as follows:
according to a first aspect of an embodiment of the present disclosure, there is provided a data processing method, including:
acquiring a preset interface use case;
acquiring noise data corresponding to the interface use cases;
acquiring actual response data and expected response data corresponding to the interface use cases;
analyzing each first field in the actual response data to obtain a first analysis result; analyzing each second field in the expected response data to obtain a second analysis result;
and determining a data processing result based on the first analysis result, the second analysis result and the noise data.
Optionally, parsing each first field in the actual response data to obtain a first parsing result, including:
for each first field in the actual response data: under the condition that the field type of the first field is a first preset type, determining a field value corresponding to the first field; under the condition that the field type of the first field is a second preset type, sorting the first elements corresponding to the first field, and determining the sorted first elements; obtaining a first analysis result based on the field value corresponding to the first field and the ordered first elements;
Analyzing each second field in the expected response data to obtain a second analysis result, wherein the second analysis result comprises the following steps:
for each second field in the expected response data: under the condition that the field type of the second field is the first preset type, determining a field value corresponding to the second field; under the condition that the field type of the second field is a second preset type, sorting the second elements corresponding to the second field, and determining the sorted second elements; obtaining a second analysis result based on the field value corresponding to the second field and the ordered second elements;
the first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
Optionally, obtaining noise data corresponding to the interface use case includes:
based on request parameters carried by the interface use cases, initiating a request to a normal interface which passes the investigation, and acquiring first response data and second response data returned by the normal interface;
noise data is determined based on the first response data and the second response data.
Optionally, determining noise data based on the first response data and the second response data includes:
Analyzing each third field in the first response data to obtain a third analysis result; analyzing each fourth field in the second response data to obtain a fourth analysis result;
and comparing the third analysis result with the fourth analysis result to determine noise data.
Optionally, parsing each third field in the first response data to determine a third parsing result includes:
for each third field in the first response data: under the condition that the field type of the third field is the first preset type, determining a field value corresponding to the third field; under the condition that the field type of the third field is a second preset type, sorting the third elements corresponding to the third field, and determining the sorted third elements; obtaining a third analysis result based on the field value corresponding to the third field and the ordered third element;
analyzing each fourth field in the second response data to determine a fourth analysis result, including:
for each fourth field in the second response data: determining a field value corresponding to the fourth field under the condition that the field type of the fourth field is the first preset type; under the condition that the field type of the fourth field is a second preset type, sorting the fourth elements corresponding to the fourth field, and determining the sorted fourth elements; obtaining a fourth analysis result based on the field value corresponding to the fourth field and the ordered fourth element;
The first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
Optionally, acquiring actual response data and expected response data corresponding to the interface use case includes:
based on request parameters carried by the interface use cases, initiating a request to an interface to be checked, and acquiring actual response data returned by the interface to be checked;
based on the request parameters, a request is initiated to the normal interface which passes the investigation, and expected response data returned by the normal interface is obtained; or acquiring expected response data carried by the interface use case.
Optionally, determining the data processing result based on the first analysis result, the second analysis result, and the noise data includes:
comparing the first analysis result with the second analysis result to determine a comparison result;
and determining a data processing result based on the noise data and the comparison result.
According to a second aspect of embodiments of the present disclosure, there is provided a data processing apparatus comprising:
the test case acquisition module is configured to acquire a preset interface case;
the noise data determining module is configured to acquire noise data corresponding to the interface use cases;
The response data determining module is configured to acquire actual response data and expected response data corresponding to the interface use cases;
the analysis result determining module is configured to analyze each first field in the actual response data to obtain a first analysis result; analyzing each second field in the expected response data to obtain a second analysis result;
and the test result determining module is configured to determine a data processing result based on the first analysis result, the second analysis result and the noise data.
Optionally, the analysis result determining module includes:
a first parsing processing unit configured to, for each first field in the actual response data: under the condition that the field type of the first field is a first preset type, determining a field value corresponding to the first field; under the condition that the field type of the first field is a second preset type, sorting the first elements corresponding to the first field, and determining the sorted first elements; obtaining a first analysis result based on the field value corresponding to the first field and the ordered first elements;
a second parsing processing unit configured to, for each second field in the expected response data: under the condition that the field type of the second field is the first preset type, determining a field value corresponding to the second field; under the condition that the field type of the second field is a second preset type, sorting the second elements corresponding to the second field, and determining the sorted second elements; obtaining a second analysis result based on the field value corresponding to the second field and the ordered second elements;
The first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
Optionally, the noise data determining module includes:
the first data acquisition unit is configured to initiate a request to a normal interface which passes the investigation based on a request parameter carried by the interface use case, and acquire first response data and second response data returned by the normal interface;
and a noise data determination unit configured to determine noise data based on the first response data and the second response data.
Optionally, the noise data determining unit includes:
the analysis processing subunit is configured to analyze each third field in the first response data to obtain a third analysis result; analyzing each fourth field in the second response data to obtain a fourth analysis result;
and the data determining subunit is configured to compare the third analysis result with the fourth analysis result and determine noise data.
Optionally, the parsing processing subunit is further configured to, for each third field in the first response data: under the condition that the field type of the third field is the first preset type, determining a field value corresponding to the third field; under the condition that the field type of the third field is a second preset type, sorting the third elements corresponding to the third field, and determining the sorted third elements; obtaining a third analysis result based on the field value corresponding to the third field and the ordered third element;
For each fourth field in the second response data: determining a field value corresponding to the fourth field under the condition that the field type of the fourth field is the first preset type; under the condition that the field type of the fourth field is a second preset type, sorting the fourth elements corresponding to the fourth field, and determining the sorted fourth elements; obtaining a fourth analysis result based on the field value corresponding to the fourth field and the ordered fourth element;
the first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
Optionally, the response data determining module includes:
the second data acquisition unit is configured to initiate a request to the interface to be checked based on the request parameters carried by the interface use case, and acquire actual response data returned by the interface to be checked;
the third data acquisition unit is configured to initiate a request to the normal interface which passes the investigation based on the request parameters, and acquire expected response data returned by the normal interface; or acquiring expected response data carried by the interface use case.
Optionally, the test result determining module includes:
The comparison processing unit is configured to compare the first analysis result with the second analysis result and determine a comparison result;
and a result determination unit configured to determine a data processing result based on the noise data and the comparison result.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement a data processing method as described above.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform a data processing method as described above.
According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product comprising a computer program or computer instructions, characterized in that the computer program or computer instructions, when executed by a processor, implement the data processing method as described above.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:
after the preset interface use case is obtained, noise data corresponding to the interface use case is obtained, and the noise data is used for indicating inherent interference data in the test process. And then acquiring actual response data and expected response data corresponding to the interface use cases, wherein the actual response data is used for indicating a data processing result of the interface to be checked, the expected response data is used for indicating a standard data processing result, and the expected response data provides reference data for the actual response data. And further analyzing each first field in the actual response data to obtain a first analysis result, and analyzing each second field in the expected response data to obtain a second analysis result, namely, the first analysis result is a full-field analysis result of the actual response data, so that all field information of the actual response data can be accurately reflected, and the second analysis result is a full-field analysis result of the expected response data, so that all field information of the expected response data can be accurately reflected. And then according to the first analysis result, the second analysis result and the noise data, determining a data processing result, wherein the data processing result is obtained by comparing all field information of the actual response data with all field information of the expected response data and automatically reducing noise, and has higher accuracy and higher data processing efficiency.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure and do not constitute an undue limitation on the disclosure.
FIG. 1 is a flowchart illustrating a method of data processing according to an exemplary embodiment;
FIG. 2 is a flow chart II illustrating a method of data processing according to an exemplary embodiment;
FIG. 3 is an architecture diagram illustrating a data processing method according to an example embodiment;
FIG. 4 is a block diagram of a data processing apparatus according to an exemplary embodiment;
fig. 5 is a block diagram of a terminal according to an exemplary embodiment.
Detailed Description
In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
It should be noted that, the user information and data related to the present disclosure are information and data authorized by the user or sufficiently authorized by each party.
Fig. 1 is a flowchart illustrating a data processing method according to an exemplary embodiment, where the data processing method may be used in a server, where the server may be an independent physical server, or may be a server cluster or a distributed system formed by a plurality of physical servers, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network ), and basic cloud computing services such as big data and artificial intelligence platforms. The data processing method may include the following steps.
In step S11, a preset interface use case is acquired.
The interface use case is a description document used for describing business logic in the interface call flow.
Specifically, the interface use cases are configured in advance, and when the interface to be inspected is managed, the interface use case corresponding to the interface to be inspected is selected from the configured interface use cases, so that the preset interface use case is obtained.
In step S12, noise data corresponding to the interface use case is acquired.
The noise data are used for indicating inherent interference data in the data process, and the noise data can interfere with the data processing result to influence the accuracy of the data processing result.
In some embodiments, the interface use case may carry noise data, so that the noise data in the interface use case is extracted, and the noise data corresponding to the interface use case is obtained.
In some embodiments, the interface use case may be obtained through the data processing result of the normal interface, that is, step S12 includes:
in step S121, a request is initiated to the normal interface that has passed the investigation based on the request parameter carried by the interface use case, and the first response data and the second response data returned by the normal interface are obtained.
The interface use case often carries request parameters, and a request can be initiated to a related interface by using the request parameters, so that a function/service/program corresponding to the related interface processes the request, and a request processing result is returned. The request parameters carried by the interface use case include, but are not limited to, an interface address, an interface name and service data, wherein the interface address can be the address of a server where the interface is located; the interface names are used for distinguishing interfaces and play a role of interface identification; the service data is data input to the interface, that is to say, the target interface can be accurately determined through the interface address and the interface name, so that the service data can be sent to the target interface, the target interface receives the service data, and a request processing result is returned.
The normal interface is an interface through which the checked result passes. Further, the normal interface may be an interface that has been checked and has passed the check result and has the same function as the interface to be checked.
Specifically, request parameters carried by the interface use cases are extracted, a target interface, namely a normal interface which passes the investigation, is determined, a request is initiated to the normal interface, and after the normal interface receives the request, the request is processed, so that a request processing result, namely first response data and second response data, is obtained.
In one possible implementation manner, a request parameter in an interface use case is extracted, a first request is initiated to a normal interface according to the request parameter, first response data returned by the normal interface is obtained, a second request is initiated to the normal interface, and second response data returned by the normal interface is obtained.
In a possible implementation manner, a request parameter in an interface use case is extracted, a request is initiated to a normal interface according to the request parameter, the request carries a related identifier, and the related identifier is used for indicating the interface to process the request twice successively, so that after the normal interface receives the request, first response data and second response data are obtained, and the first response data and the second response data are returned.
In step S122, noise data is determined based on the first response data and the second response data.
Specifically, after the first response data and the second response data are acquired, the first response data and the second response data are compared, and noise data are determined. The first response data and the second response data returned by the normal interface are obtained by initiating a request to the normal interface, and the normal interface is an examined interface without problems, so that the response data of the interface has accuracy and stability, the first response data and the second response data are compared, and noise data existing in the test process can be accurately determined.
In some embodiments, step S122 includes:
in step S1221, each third field in the first response data is parsed, and a third parsing result is obtained; and analyzing each fourth field in the second response data to obtain a fourth analysis result.
In step S1222, the third analysis result and the fourth analysis result are compared to determine noise data.
Wherein each field in the first response data is denoted as a third field and each field in the second response data is denoted as a fourth field.
Specifically, after the first response data is obtained, each third field in the first response data is parsed to obtain a third parsing result, and each fourth field in the second response data is parsed to obtain a fourth parsing result, that is, the third parsing result is a full-field parsing result of the first response data, all field information of the first response data can be accurately reflected, and the fourth parsing result is a full-field parsing result of the second response data, all field information of the second response data can be accurately reflected. And comparing the third analysis result with the fourth analysis result, so that the noise data can be accurately determined.
In some embodiments, in parsing the first response data, the full fields in the first response data are parsed, i.e., for each third field in the first response data: under the condition that the field type of the third field is the first preset type, determining a field value corresponding to the third field; under the condition that the field type of the third field is a second preset type, sorting the third elements corresponding to the third field, and determining the sorted third elements; and obtaining a third analysis result based on the field value corresponding to the third field and the ordered third element. The first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
The first preset type is a basic data type, the integer type comprises byte (byte type, used for representing an integer), short (short integer, used for representing an integer), int (integer, used for representing an integer), long (long integer, used for representing an integer), the floating point type comprises float (single-precision floating point number), double (double-precision floating point number), the logic type comprises boolean (boolean type), and the character type comprises char (character string type).
The second preset type includes at least one of dictionary type and array type. Dictionary types belong to key-value types (key-value), wherein keys are required to be unique, values can be any type, the dictionary types are defined by { }, internal elements are in the form of key-value combination, elements are separated by commas, and if d = { "name": "A", "length": "B", "width": "C" }, that is, related information of an article A is stored in a dictionary d, and the dictionary has three items of name, length and width. Where "name", "length", "width" are keys and "a", "B", "C" are values. The array type is used for storing a plurality of data of the same type, and the array type is represented by [ ], for example, there is an array= [10,20,34], wherein 10,20,34 is an element in the array.
When the third field in the first response data is analyzed, the field value of the third field is unique under the condition that the field type of the third field is the first preset type, so that further processing is not needed, the field value can be directly used for subsequent comparison, and the field value of the third field is taken. And when the field type of the third field is a second preset type, that is, the third field is of a dictionary type or an array type, a plurality of third elements may exist in the field at this time, so that the third elements corresponding to the third field are subjected to sorting processing, wherein the sorting rule may be a preset rule, for example, from small to large or from large to small, after sorting processing is performed according to the set sorting rule, the third elements which are sequentially arranged, namely, the third elements after sorting are obtained, and then a third analysis result is determined according to the determined field value and the third elements after sorting.
In one possible implementation manner, a sequence of judging exists between the first preset type and the second preset type, namely whether the third field is the first preset type is judged first, if so, the analysis of the field is terminated without processing; if the first field is not the first preset type, further determining whether the third field is the dictionary type, if so, sorting the keys and the values, and sequentially taking the elements according to the sorted third element; and if the element is not the dictionary type, sorting the group elements for the group type, and sequentially taking the elements according to the sorted third element.
Specifically, a current analysis field is sequentially selected from a third field of the first response data, and when the current analysis field is of a first preset type, the analysis of the current analysis field is terminated, and the next current analysis field is sequentially selected; under the condition that the current analysis field is of dictionary type, sorting keys and values corresponding to the current analysis field, sequentially taking out the sorted third elements, and sequentially selecting the next current analysis field; and under the condition that the current analysis field is of an array type, sorting third elements in the current analysis field array, sequentially taking out the sorted third elements, and sequentially selecting the next current analysis field. And under the condition that the next current analysis field does not exist, sequentially taking out the ordered third elements according to the field value of the third field of the first preset type and the field value of the third field of the first preset type to obtain a third analysis result.
For example, the first response data includes 3 fields, namely, field 1, field 2 and field 3, where the field 1 located in the first bit is parsed, whether the field 1 is of a first preset type is determined, and if the field 1 is of the first preset type, the field value of the field 1 is taken as a. Then, the field 2 of the second bit is analyzed, whether the field 2 is of a first preset type is judged, whether the field 2 is of a dictionary type is determined, whether the field 2 is of a dictionary type is further judged, the key and the value in the field 2 are subjected to sorting processing, and third elements such as b, c and d after sorting processing are sequentially taken. Then, analyzing the field 3 of the third bit, judging whether the field 3 is of a first preset type, determining that the field 3 is not of the first preset type, further judging whether the field 3 is of a dictionary type, determining that the field 3 is not of the dictionary type, if the field 3 is of an array type, ordering array elements of the field 3, namely third elements, sequentially taking the elements after ordering, such as 10, 20 and 34, and ordering the extracted field values and the ordered third elements according to the field sequence of the field 1, the field 2 and the field 3 to obtain a third analysis result, such as A, b, c, d,10, 20 and 34.
In some embodiments, in parsing the second response data, the full field in the second response data is parsed, i.e., for each fourth field in the second response data: determining a field value corresponding to the fourth field under the condition that the field type of the fourth field is the first preset type; under the condition that the field type of the fourth field is a second preset type, sorting the fourth elements corresponding to the fourth field, and determining the sorted fourth elements; and obtaining a fourth analysis result based on the field value corresponding to the fourth field and the ordered fourth element.
When the fourth field in the second response data is analyzed, the field value of the fourth field is unique under the condition that the field type of the fourth field is the first preset type, so that further processing is not needed, the field value can be directly used for subsequent comparison, and the field value of the fourth field is taken. And when the field type of the fourth field is a second preset type, that is, the fourth field is of a dictionary type or an array type, a plurality of fourth elements may exist in the field at this time, so that the fourth elements corresponding to the fourth field are subjected to sorting processing, wherein the sorting rule may be a preset rule, for example, from small to large or from large to small, after sorting processing is performed according to the set sorting rule, the fourth elements which are sequentially arranged, namely, the sorted fourth elements are obtained, and then a fourth analysis result is determined according to the determined field value and the sorted fourth elements.
In one possible implementation manner, judging whether the fourth field is of a first preset type, if so, not processing the fourth field, and ending the analysis of the fourth field; if the fourth field is not of the first preset type, further determining whether the fourth field is of the dictionary type, if so, sorting the keys and the values, sequentially taking the elements according to the sorted fourth elements, if not, sorting the elements of the groups, and sequentially taking the elements according to the sorted fourth elements.
Specifically, a current analysis field is sequentially selected from a fourth field of the second response data, and when the current analysis field is of a first preset type, the analysis of the current analysis field is terminated, and the next current analysis field is sequentially selected; under the condition that the current analysis field is of dictionary type, sorting keys and values corresponding to the current analysis field, sequentially taking out the sorted fourth elements, and sequentially selecting the next current analysis field; and under the condition that the current analysis field is of an array type, sorting fourth elements in the current analysis field array, sequentially taking out the sorted fourth elements, and sequentially selecting the next current analysis field. And under the condition that the next current analysis field does not exist, sequentially taking out the ordered fourth elements according to the field value of the fourth field of the first preset type to obtain a fourth analysis result.
After the third analysis result and the fourth analysis result are obtained, comparing the data in the third analysis result with the data in the fourth analysis result, and determining noise data according to the difference between the third analysis result and the fourth analysis result. For example, if the time stamp in the third analysis result is different from the time stamp in the fourth analysis result, the time stamp is determined as noise data. After the noise data is acquired, the noise data is stored, and the interface noise file is updated by using the noise data.
In step S13, actual response data and expected response data corresponding to the interface use case are acquired.
In this step, the actual response data is used to indicate the request processing result of the interface to be examined, the expected response data is used to indicate the standard request processing result, and the expected response data provides the reference data for the actual response data.
In some embodiments, step S13 includes:
in step S131, a request is initiated to the interface to be inspected based on the request parameters carried by the interface use case, and the actual response data returned by the interface to be inspected is obtained.
In step S132, a request is initiated to the normal interface that has passed the investigation based on the request parameter, and the expected response data returned by the normal interface is acquired.
In this step, after the interface use case is obtained, the request parameters of the interface use case are extracted, where the request parameters include not only the interface name and the interface address of the interface to be checked, but also the interface name and the interface address of the normal interface, so that service data can be sent to the interface to be checked according to the request parameters, and after the data to be checked is received into the service data, the service data is processed, so as to determine actual response data, and the actual response data is returned to the server. Further, sending the service data to the normal interface, after the normal interface receives the service data, processing the service data, determining expected response data, and returning the expected response data to the server.
In this embodiment, a reference environment is provided for the interface to be examined through the normal interface, which is favorable for accurately acquiring the expected response data in real time. For interfaces with unfixed expected results, the normal interfaces can provide more accurate reference data for the interfaces to be checked, and are favorable for accurately checking the interfaces to be checked.
In some embodiments, step S13 includes:
in step S131, a request is initiated to the interface to be inspected based on the request parameters carried by the interface use case, and the actual response data returned by the interface to be inspected is obtained.
In step S133, expected response data carried by the interface use case is acquired.
In this embodiment, the interface use case carries a request parameter related to the interface to be checked, and the interface name and the interface address of the interface to be checked can be determined by using the request parameter, so as to send service data to the interface to be checked, and after the interface to be checked receives the service data, the service data is processed, so as to determine actual response data, and the actual response data is returned to the server. Further, the interface use case also carries expected response data, so that the expected response data can be extracted from the interface use case. When the expected response data is relatively fixed, the expected response data is directly written into the interface use case, and the expected response data can be rapidly, conveniently and accurately determined.
In step S14, each first field in the actual response data is parsed, and a first parsing result is obtained; and analyzing each second field in the expected response data to obtain a second analysis result.
Wherein each field in the actual response data is noted as a first field and each field in the expected response data is noted as a second field.
Specifically, after the actual response data is obtained, each first field in the actual response data is parsed to obtain a first parsing result, and each second field in the expected response data is parsed to obtain a second parsing result, that is, the first parsing result is a full-field parsing result of the actual response data, all field information of the actual response data can be accurately reflected, the second parsing result is a full-field parsing result of the expected response data, and all field information of the expected response data can be accurately reflected.
In some embodiments, step S14 comprises:
in step S141, for each first field in the actual response data: under the condition that the field type of the first field is a first preset type, determining a field value corresponding to the first field; under the condition that the field type of the first field is a second preset type, sorting the first elements corresponding to the first field, and determining the sorted first elements; and obtaining a first analysis result based on the field value corresponding to the first field and the ordered first element. The first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
When the first field in the actual response data is analyzed, the field value of the first field is unique under the condition that the field type of the first field is the first preset type, so that further processing is not needed, the field value can be directly used for subsequent comparison, and the field value of the first field is taken. When the field type of the first field is the second preset type, that is, the first field is of a dictionary type or an array type, a plurality of first elements may exist in the field at this time, so that the first elements corresponding to the first field are subjected to sorting processing, wherein the sorting rule may be a preset rule, for example, from small to large or from large to small, after sorting processing is performed according to the set sorting rule, the first elements in sequence, that is, the first elements after sorting, are obtained, and then, according to the determined field value and the first elements after sorting, the first analysis result is determined.
In one possible implementation manner, a sequence of judging exists between the first preset type and the second preset type, namely whether the first field is the first preset type is judged first, if so, the analysis of the field is terminated without processing; if the first field is not the first preset type, further determining whether the first field is the dictionary type, and if so, determining whether the first field is the dictionary type; the keys and the values are ordered, the elements are sequentially fetched according to the ordered first elements, if the elements are not dictionary types, the elements are ordered in a group type, and the elements are sequentially fetched according to the ordered first elements.
Specifically, a current analysis field is sequentially selected from a first field of actual response data, analysis of the current analysis field is terminated under the condition that the current analysis field is of a first preset type, and a next current analysis field is sequentially selected; under the condition that the current analysis field is of a dictionary type, ordering keys and values corresponding to the current analysis field, sequentially taking out ordered first elements, and sequentially selecting the next current analysis field; and under the condition that the current analysis field is of an array type, ordering the first elements in the array of the current analysis field, sequentially taking out the ordered first elements, and sequentially selecting the next current analysis field. And under the condition that the next current analysis field does not exist, sequentially taking out the sequenced first elements according to the field value of the first field of the first preset type to obtain a first analysis result.
In step S142, for each second field in the expected response data: under the condition that the field type of the second field is the first preset type, determining a field value corresponding to the second field; under the condition that the field type of the second field is a second preset type, sorting the second elements corresponding to the second field, and determining the sorted second elements; and obtaining a second analysis result based on the field value corresponding to the second field and the ordered second elements.
When the second field in the expected response data is analyzed, the field value of the second field is unique under the condition that the field type of the second field is the first preset type, so that further processing is not needed, the field value can be directly used for subsequent comparison, and the field value of the second field is taken. And under the condition that the field type of the second field is a second preset type, namely the second field is a dictionary type or an array type, a plurality of second elements possibly exist in the field at the moment, and therefore the second elements corresponding to the second field are subjected to sorting processing, wherein the sorting rule can be a preset rule, for example, the sorting processing is carried out according to the set sorting rule from small to large or from large to small, the second elements which are sequentially arranged, namely the sorted second elements, are obtained, and then a second analysis result is determined according to the determined field value and the sorted second elements.
In one possible implementation manner, a sequence of judging exists between the first preset type and the second preset type, namely whether the second field is the first preset type is judged first, if so, the analysis of the field is terminated without processing; if the second field is not the first preset type, further determining whether the second field is the dictionary type, if so, sorting the keys and the values, and sequentially taking the elements according to the sorted second elements; and if the element is not the dictionary type, sorting the group elements for the group type, and sequentially taking the elements according to the sorted second elements.
Specifically, a current analysis field is sequentially selected from a second field of expected response data, analysis of the current analysis field is terminated under the condition that the current analysis field is of a first preset type, and a next current analysis field is sequentially selected; under the condition that the current analysis field is of dictionary type, sorting keys and values corresponding to the current analysis field, sequentially taking out the sorted second elements, and sequentially selecting the next current analysis field; and under the condition that the current analysis field is of an array type, ordering the second elements in the array of the current analysis field, sequentially taking out the ordered second elements, and sequentially selecting the next current analysis field. And under the condition that the next current analysis field does not exist, sequentially taking out the ordered second elements according to the field value of the second field of the first preset type to obtain a second analysis result.
In step S15, a data processing result is determined based on the first analysis result, the second analysis result, and the noise data.
Specifically, noise data can be obtained from a stored interface noise file, after a first analysis result, a second analysis result and the noise data are obtained, a data processing result is determined according to the first analysis result, the second analysis result and the noise data, and the interface test data is a result for reducing noise interference and is a result of full-field assertion, so that higher accuracy is achieved.
In some embodiments, step S15 includes:
in step S151, the first analysis result and the second analysis result are compared, and a comparison result is determined.
In step S152, a data processing result is determined based on the noise data and the comparison result.
Specifically, after a first analysis result and a second analysis result are obtained, the first analysis result and the second analysis result are compared, a comparison result is determined, then the comparison result is sorted according to noise data, and the noise data in the comparison result is deleted under the condition that the comparison result contains the noise data, so that the comparison result is obtained.
In some embodiments, the noise data is deleted from the first analysis result to obtain first noise processing data, the noise data is deleted from the second analysis result to obtain second noise processing data, and the first noise processing data and the second noise processing data are compared to determine a data processing result.
In one possible implementation, the base processing module is used to obtain the first response data and the second response data, as in S1 in fig. 2: the basic processing module extracts the request parameters from the interface use case, then initiates a request 1 to the normal interface to obtain first response data, namely a response 1, and initiates a request 2 to the normal interface to obtain second response data, namely a response 2. That is, as shown in fig. 3, the basic processing module is mainly used for making a flow request and acquiring a response.
Further, the data processing module is utilized to analyze the response data, the noise processing module is utilized to acquire noise data, and the noise file is updated. As in S2 in fig. 2: noise processing module and S3: and the data processing module is shown. After obtaining the response 1 and the response 2, analyzing the JSON (JavaScript Object Notation, which is a lightweight data exchange format) strings of the response 1 and the response 2 by using a data processing module, if the current analysis field is selected from the response 1, judging whether the current analysis field is of a basic type, namely a first preset type, if so, stopping analyzing the current analysis field, and obtaining the next current analysis field; if the current analysis field is not the basic type, further judging whether the current analysis field is the dictionary type, if so, sequencing keys and values, and sequentially taking elements to obtain the next current analysis field; and if the analysis result is not the dictionary type, sequencing the array elements for the array type, sequentially taking the elements, and then obtaining the next current analysis field, thereby obtaining a third analysis result. And the data processing module is used for analyzing the response 2 to obtain a fourth analysis result, comparing the third analysis result with the fourth analysis result to obtain a noise field, and updating the interface noise file by using the noise field. That is, as shown in fig. 3, the noise processing module is mainly used to perform comparison of response data to acquire a noise file, such as acquiring the noise file using DIFF (computer term, which is used to compare text files). The data processing module comprises a basic type processing sub-module, a dictionary type processing sub-module and an array type processing sub-module which are used for analyzing and processing fields of different types.
Further, the actual response data and the expected response data are asserted using the response comparison module. As shown in fig. 2, the response comparison module extracts a request parameter from the interface use case, then initiates a request to the interface to be checked to obtain actual response data returned by the interface to be checked, extracts expected response data from the interface use case, processes the actual response data by using the data processing module to obtain a first analysis result, processes the expected response data by using the data processing module to obtain a second analysis result, compares the first analysis result, the second analysis result and noise data in the noise file to obtain a data processing result, and uses S5: and executing the report and outputting a data processing result. That is, as shown in fig. 3, the response comparison module is mainly used for comparing the interface response, i.e., the actual response data, with the expected response data, and outputting (report) the obtained data processing result. Therefore, through the coordination of the basic processing module, the noise processing module, the data processing module and the response comparison module, automatic noise reduction and full-field assertion are realized, automatic assertion is realized, and data processing efficiency is improved.
In the above embodiment, after the preset interface use case is obtained, noise data corresponding to the interface use case is obtained, where the noise data is used to indicate inherent interference data in the test process. And then acquiring actual response data and expected response data corresponding to the interface use cases, wherein the actual response data is used for indicating a request processing result of the interface to be checked, the expected response data is used for indicating a standard request processing result, and the expected response data provides reference data for the actual response data. And further analyzing each first field in the actual response data to obtain a first analysis result, and analyzing each second field in the expected response data to obtain a second analysis result, namely, the first analysis result is a full-field analysis result of the actual response data, so that all field information of the actual response data can be accurately reflected, and the second analysis result is a full-field analysis result of the expected response data, so that all field information of the expected response data can be accurately reflected. And then according to the first analysis result, the second analysis result and the noise data, determining a data processing result, wherein the data processing result is obtained by comparing all field information of the actual response data with all field information of the expected response data and automatically reducing noise, and has the advantages of higher accuracy, higher degree of automation and effectively improving the test efficiency.
Fig. 4 is a block diagram of a data processing apparatus according to an exemplary embodiment. The device comprises a test case acquisition module 41, a noise data determination module 42, a response data determination module 43, an analysis result determination module 44 and a test result determination module 45.
The test case acquisition module 41 is configured to acquire a preset interface case;
a noise data determining module 42 configured to obtain noise data corresponding to the interface use case;
a response data determining module 43 configured to obtain actual response data and expected response data corresponding to the interface use case;
the analysis result determining module 44 is configured to analyze each first field in the actual response data to obtain a first analysis result; analyzing each second field in the expected response data to obtain a second analysis result;
the test result determining module 45 is configured to determine a data processing result based on the first analysis result, the second analysis result, and the noise data.
In an exemplary embodiment of the present disclosure, the parsing result determining module includes:
a first parsing processing unit configured to, for each first field in the actual response data: under the condition that the field type of the first field is a first preset type, determining a field value corresponding to the first field; under the condition that the field type of the first field is a second preset type, sorting the first elements corresponding to the first field, and determining the sorted first elements; obtaining a first analysis result based on the field value corresponding to the first field and the ordered first elements;
A second parsing processing unit configured to, for each second field in the expected response data: under the condition that the field type of the second field is the first preset type, determining a field value corresponding to the second field; under the condition that the field type of the second field is a second preset type, sorting the second elements corresponding to the second field, and determining the sorted second elements; obtaining a second analysis result based on the field value corresponding to the second field and the ordered second elements;
the first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
In an exemplary embodiment of the present disclosure, a noise data determination module includes:
the first data acquisition unit is configured to initiate a request to a normal interface which passes the investigation based on a request parameter carried by the interface use case, and acquire first response data and second response data returned by the normal interface;
and a noise data determination unit configured to determine noise data based on the first response data and the second response data.
In an exemplary embodiment of the present disclosure, a noise data determining unit includes:
The analysis processing subunit is configured to analyze each third field in the first response data to obtain a third analysis result; analyzing each fourth field in the second response data to obtain a fourth analysis result;
and the data determining subunit is configured to compare the third analysis result with the fourth analysis result and determine noise data.
In an exemplary embodiment of the present disclosure, the parsing processing subunit is further configured to, for each third field in the first response data: under the condition that the field type of the third field is the first preset type, determining a field value corresponding to the third field; under the condition that the field type of the third field is a second preset type, sorting the third elements corresponding to the third field, and determining the sorted third elements; obtaining a third analysis result based on the field value corresponding to the third field and the ordered third element;
for each fourth field in the second response data: determining a field value corresponding to the fourth field under the condition that the field type of the fourth field is the first preset type; under the condition that the field type of the fourth field is a second preset type, sorting the fourth elements corresponding to the fourth field, and determining the sorted fourth elements; obtaining a fourth analysis result based on the field value corresponding to the fourth field and the ordered fourth element;
The first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type includes at least one of dictionary type and array type.
In an exemplary embodiment of the present disclosure, a response data determination module includes:
the second data acquisition unit is configured to initiate a request to the interface to be checked based on the request parameters carried by the interface use case, and acquire actual response data returned by the interface to be checked;
the third data acquisition unit is configured to initiate a request to the normal interface which passes the investigation based on the request parameters, and acquire expected response data returned by the normal interface; or acquiring expected response data carried by the interface use case.
In an exemplary embodiment of the present disclosure, a test result determination module includes:
the comparison processing unit is configured to compare the first analysis result with the second analysis result and determine a comparison result;
and a result determination unit configured to determine a data processing result based on the noise data and the comparison result.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Fig. 5 is a schematic diagram of an electronic device according to an exemplary embodiment. Referring to fig. 5, electronic device 500 includes a processing component 522 that further includes one or more processors and memory resources represented by memory 532 for storing instructions, such as applications, executable by processing component 522. The application programs stored in the memory 532 may include one or more modules each corresponding to a set of instructions. Further, the processing component 522 is configured to execute instructions to perform the implementation of the interface test described above.
The electronic device 500 may also include a power component 526 configured to perform power management of the electronic device 500, a wired or wireless network interface 550 configured to connect the electronic device 500 to a network, and an input output (I/O) interface 558. The electronic device 500 may operate based on an operating system stored in the memory 532, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.
In an exemplary embodiment, a storage medium is also provided comprising instructions that, when executed by a processor of an electronic device, enable the electronic device to perform the data processing method according to any one of the method embodiments described above. Alternatively, the storage medium may be a non-transitory computer readable storage medium, which may be, for example, ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.
In an exemplary embodiment, a computer program product is also provided, which comprises readable program code executable by a processor of an electronic device to perform the above-described data processing method applied to the electronic device. Alternatively, the program code may be stored in a storage medium of an electronic device, which may be a non-transitory computer readable storage medium, such as ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method of data processing, comprising:
acquiring a preset interface use case;
acquiring noise data corresponding to the interface use case;
acquiring actual response data and expected response data corresponding to the interface use case;
analyzing each first field in the actual response data to obtain a first analysis result; analyzing each second field in the expected response data to obtain a second analysis result;
and determining a data processing result based on the first analysis result, the second analysis result and the noise data.
2. The method of claim 1, wherein parsing each first field in the actual response data to obtain a first parsing result comprises:
for each first field in the actual response data: determining a field value corresponding to the first field under the condition that the field type of the first field is a first preset type; under the condition that the field type of the first field is a second preset type, sorting the first elements corresponding to the first field, and determining the sorted first elements; obtaining the first analysis result based on the field value corresponding to the first field and the ordered first element;
Analyzing each second field in the expected response data to obtain a second analysis result, wherein the second analysis result comprises:
for each second field in the expected response data: determining a field value corresponding to the second field under the condition that the field type of the second field is the first preset type; when the field type of the second field is the second preset type, sorting the second elements corresponding to the second field, and determining the sorted second elements; obtaining the second analysis result based on the field value corresponding to the second field and the ordered second element;
the first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type comprises at least one of dictionary type and array type.
3. The method of claim 1, wherein the obtaining noise data corresponding to the interface use case comprises:
based on the request parameters carried by the interface use cases, initiating a request to a normal interface which passes the investigation, and acquiring first response data and second response data returned by the normal interface;
The noise data is determined based on the first response data and the second response data.
4. A method according to claim 3, wherein said determining said noise data based on said first response data and said second response data comprises:
analyzing each third field in the first response data to obtain a third analysis result; analyzing each fourth field in the second response data to obtain a fourth analysis result;
and comparing the third analysis result with the fourth analysis result to determine the noise data.
5. The method of claim 4, wherein parsing each third field in the first response data to determine a third parsing result comprises:
for each third field in the first response data: determining a field value corresponding to the third field under the condition that the field type of the third field is a first preset type; when the field type of the third field is a second preset type, sorting the third elements corresponding to the third field, and determining the sorted third elements; obtaining the third analysis result based on the field value corresponding to the third field and the ordered third element;
Analyzing each fourth field in the second response data to determine a fourth analysis result, including:
for each fourth field in the second response data: determining a field value corresponding to the fourth field under the condition that the field type of the fourth field is the first preset type; when the field type of the fourth field is the second preset type, sorting the fourth elements corresponding to the fourth field, and determining the sorted fourth elements; obtaining a fourth analysis result based on the field value corresponding to the fourth field and the ordered fourth element;
the first preset type comprises at least one of an integer type, a floating point type, a logic type and a character type; the second preset type comprises at least one of dictionary type and array type.
6. The method of claim 1, wherein the obtaining actual response data and expected response data corresponding to the interface use case comprises:
based on the request parameters carried by the interface use cases, initiating a request to an interface to be checked, and acquiring the actual response data returned by the interface to be checked;
Based on the request parameters, initiating a request to a normal interface which passes the investigation, and acquiring the expected response data returned by the normal interface; or acquiring the expected response data carried by the interface use case.
7. The method of claim 1, wherein the determining a data processing result based on the first analysis result, the second analysis result, and the noise data comprises:
comparing the first analysis result with the second analysis result to determine a comparison result;
and determining the data processing result based on the noise data and the comparison result.
8. A data processing apparatus, comprising:
the test case acquisition module is configured to acquire a preset interface case;
the noise data determining module is configured to acquire noise data corresponding to the interface use case;
the response data determining module is configured to acquire actual response data and expected response data corresponding to the interface use case;
the analysis result determining module is configured to analyze each first field in the actual response data to obtain a first analysis result; analyzing each second field in the expected response data to obtain a second analysis result;
And a test result determination module configured to determine a data processing result based on the first analysis result, the second analysis result, and the noise data.
9. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the data processing method of any of claims 1 to 7.
10. A computer readable storage medium, characterized in that instructions in the computer readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the data processing method of any one of claims 1 to 7.
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