CN115329759A - Information processing method, device, equipment and storage medium - Google Patents
Information processing method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN115329759A CN115329759A CN202211264888.0A CN202211264888A CN115329759A CN 115329759 A CN115329759 A CN 115329759A CN 202211264888 A CN202211264888 A CN 202211264888A CN 115329759 A CN115329759 A CN 115329759A
- Authority
- CN
- China
- Prior art keywords
- keyword
- parent
- target
- determining
- keywords
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/103—Formatting, i.e. changing of presentation of documents
- G06F40/117—Tagging; Marking up; Designating a block; Setting of attributes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/12—Use of codes for handling textual entities
- G06F40/151—Transformation
- G06F40/154—Tree transformation for tree-structured or markup documents, e.g. XSLT, XSL-FO or stylesheets
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/186—Templates
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides an information processing method, an information processing device, information processing equipment and a storage medium, which belong to the technical field of analyzing result sets fed back by an API (application program interface), and the method comprises the following steps: acquiring a result set fed back by a first API, wherein the result set comprises a plurality of keywords and service values of the keywords, and the keywords have parent-child relationships; determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of a parent keyword of the keyword; acquiring a target identifier of a target keyword; determining a target root keyword in the parent-child relationship tree set based on the target identifier; and determining the business value of the target keyword based on the business value of the target root keyword. The information processing method, the device, the equipment and the storage medium provided by the invention are used for improving the flexibility of obtaining the service value.
Description
Technical Field
The present invention relates to the field of technologies for parsing a result set fed back by an API, and in particular, to an information processing method, apparatus, device, and storage medium.
Background
Currently, in some process flows, the functions of functional blocks are interdependent in data. For example, to implement the function of the B function module, it needs to rely on the result set returned by the a function module, that is, the B function module needs to select relevant data from the result set returned by the a function module, and supply the data to the B function module for use, so that the B function module can implement its function. An Application Program Interface (API) may be included in the a-function module, and the result set fed back to the B-function module through the API may be a json object. In the case where the result set is a json object, the B function module needs to acquire a business value (value) of a Key (Key) from the result set and implement the function of the B function module based on the business value.
In the related art, the B function module obtains a service value from the result set by the following method: the method comprises the steps of obtaining template values corresponding to keywords from json data templates agreed by a B function module and an A function module in advance, carrying out hard coding on the template values through a json toolkit and the keywords to obtain a code logic block, calling an API (application programming interface) of the A function module to receive a result set returned by the API of the A function module, and further obtaining service values of the keywords from the API result set based on the code logic block.
In the related art, when the B function module also needs to obtain the service value of the keyword in the result set returned by the API of the C function module, the B function module and the C function module also need to obtain the template value corresponding to the keyword from the json data template agreed in advance, and the template value is hard-coded by the json toolkit and the keyword to obtain the code logic block. Thus resulting in poor flexibility in obtaining the traffic value (B function).
Disclosure of Invention
The invention provides an information processing method, an information processing device, information processing equipment and a storage medium, which are used for overcoming the defect of poor flexibility in acquiring a service value in the prior art and achieving the purpose of improving the flexibility in acquiring the service value.
The invention provides an information processing method, which comprises the following steps: acquiring a result set fed back by a first API, wherein the result set comprises a plurality of keywords and service values of the keywords, and the keywords have a parent-child relationship; determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of the parent keyword of the keyword; acquiring a target identifier of a target keyword; determining a target root keyword in the parent-child relationship tree set based on the target identifier; and determining the business value of the target keyword based on the business value of the target root keyword.
According to the information processing method provided by the invention, the determination of the parent-child relationship tree set based on the result set comprises the following steps: analyzing the result set to obtain a character string set with a parent-child tree relationship; splitting the character string set to obtain an array of each keyword, wherein the array comprises a plurality of attributes of the keyword, and the plurality of attributes comprise the keyword, a parent keyword of the keyword, a hierarchy of the keyword, a type of a service value of the keyword and the number of the service values; and determining a parent-child relationship tree set based on the array of each keyword.
According to the information processing method provided by the invention, the character string set comprises a plurality of initial attribute information adopting a first identifier interval, and the initial attribute information comprises a plurality of attributes adopting a second identifier interval; splitting the character string set to obtain an array of each keyword, wherein the splitting comprises the following steps: splitting the character string set based on the first identifier to obtain initial attribute information of each keyword; and splitting the initial attribute information of each keyword based on the second identifier to obtain an array of each keyword.
According to the information processing method provided by the invention, the determining of the parent-child relationship tree set based on the array of each keyword comprises the following steps: determining target attribute information of each keyword based on the array of each keyword, wherein the target attribute information comprises an identifier of the keyword and an identifier of a parent keyword of the keyword; and through a recursive algorithm, associating the identifier of the keyword in the target attribute information of each keyword with the identifier of the parent keyword of the keyword, and determining a parent-child relationship tree set.
According to an information processing method provided by the present invention, the determining target attribute information of a keyword based on an array of keywords comprises: determining the identifier of the keyword through a preset algorithm; determining the identification of a parent keyword of the keyword through a preset algorithm; and determining the identifier of the keyword, the identifier of the parent keyword and a plurality of attributes in the array of the keyword as target attribute information of the keyword.
According to the information processing method provided by the invention, the target root keyword is determined in the parent-child relationship tree set based on the target identifier, and the method comprises the following steps: determining all father keywords of the target keywords in the parent-child relationship tree set based on the target identification through a tree up-conversion algorithm, wherein the tree up-conversion algorithm is the inverse process of the recursive algorithm; and determining the keywords with the middle levels as the first preset levels in all the parent keywords as target root keywords.
According to the information processing method provided by the invention, the business value of the target keyword is determined based on the business value of the target root keyword, and the method comprises the following steps: acquiring a business value of the target root keyword from the result set through a preset tool kit; judging whether the type of the service value of the ith parent keyword is a first type or not according to the ith parent keyword in all the parent keywords; if yes, performing type conversion on the service value of the ith father keyword to obtain a conversion result corresponding to the first type, and determining the service value of the ith-1 father keyword in the conversion result; otherwise, determining the service value corresponding to the hierarchy of the ith-1 father keyword in the service values of the ith father keyword as the service value of the ith-1 father keyword; initially, i = N, the nth parent keyword is a target keyword, and N is equal to the total number of all parent keywords; at the end, i =1, the 0 th parent key is the target key, and the first type is the object type or the array type.
According to an information processing method provided by the invention, the step of determining the business value of the i-1 th parent key in the conversion result comprises the following steps: and determining the business value corresponding to the hierarchy of the (i-1) th parent keyword in the conversion result as the business value of the (i-1) th parent keyword.
According to the information processing method provided by the invention, the target identification of the target keyword is obtained, and the method comprises the following steps: sending the parent-child relationship tree set to the display device so that the display device displays the parent-child relationship tree based on the parent-child relationship tree set; receiving attribute information of a target keyword sent by display equipment after responding to selection operation of the target keyword in a parent-child relationship tree; and acquiring the target identification of the target keyword from the attribute information.
The present invention also provides an information processing apparatus comprising:
the first obtaining module is used for obtaining a result set fed back by the first API, the result set comprises a plurality of keywords and service values of the keywords, and the keywords have parent-child relationships;
the first determining module is used for determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of a parent keyword of the keyword;
the second acquisition module is used for acquiring a target identifier of the target keyword;
the second determining module is used for determining a target root keyword in the parent-child relationship tree set based on the target identifier;
and the third determining module is used for determining the business value of the target keyword based on the business value of the target root keyword.
According to the information processing apparatus provided by the present invention, the first determining module is specifically configured to: analyzing the result set to obtain a character string set with a parent-child tree relationship; splitting the character string set to obtain an array of each keyword, wherein the array comprises a plurality of attributes of the keyword, and the plurality of attributes comprise the keyword, a parent keyword of the keyword, the hierarchy of the keyword, the type of a service value of the keyword and the number of the service values; and determining a parent-child relationship tree set based on the array of each keyword.
According to an information processing apparatus provided by the present invention, a character string set includes a plurality of pieces of initial attribute information at intervals of a first identifier, and the initial attribute information includes a plurality of attributes at intervals of a second identifier; the first determining module is specifically configured to: splitting the character string set based on the first identifier to obtain initial attribute information of each keyword; and splitting the initial attribute information of each keyword based on the second identifier to obtain an array of each keyword.
According to the information processing apparatus provided by the present invention, the first determining module is specifically configured to: determining target attribute information of each keyword based on the array of each keyword, wherein the target attribute information comprises an identifier of the keyword and an identifier of a parent keyword of the keyword; and through a recursive algorithm, associating the identifier of the keyword in the target attribute information of each keyword with the identifier of the parent keyword of the keyword, and determining a parent-child relationship tree set.
According to the information processing apparatus provided by the present invention, the first determining module is specifically configured to: determining the identifier of the keyword through a preset algorithm; determining the identification of a parent keyword of the keyword through a preset algorithm; and determining the identifier of the keyword, the identifier of the parent keyword and a plurality of attributes in the array of the keyword as target attribute information of the keyword.
According to the information processing apparatus provided by the present invention, the second determining module is specifically configured to: determining all father keywords of the target keywords in the parent-child relationship tree set based on the target identification through a tree up-conversion algorithm, wherein the tree up-conversion algorithm is the inverse process of the recursive algorithm; and determining the keywords with the middle levels as the first preset levels in all the parent keywords as target root keywords.
According to the information processing apparatus provided by the present invention, the third determining module is specifically configured to: acquiring a business value of the target root keyword from the result set through a preset toolkit; judging whether the type of the business value of the ith parent keyword is a first type or not aiming at the ith parent keyword in all the parent keywords; if yes, performing type conversion on the service value of the ith father keyword to obtain a conversion result corresponding to the first type, and determining the service value of the ith-1 father keyword in the conversion result; otherwise, determining the service value corresponding to the hierarchy of the ith-1 father keyword in the service values of the ith father keyword as the service value of the ith-1 father keyword; initially, i = N, the nth parent keyword is a target keyword, and N is equal to the total number of all parent keywords; at the end, i =1, the 0 th parent key is the target key, and the first type is the object type or the array type.
According to the information processing apparatus provided by the present invention, the third determining module is specifically configured to: and determining the business value corresponding to the hierarchy of the (i-1) th parent keyword in the conversion result as the business value of the (i-1) th parent keyword.
According to the information processing apparatus provided by the present invention, the second obtaining module is specifically configured to: sending the parent-child relationship tree set to the display device so that the display device displays the parent-child relationship tree based on the parent-child relationship tree set; receiving attribute information of a target keyword sent by a display device after responding to a selection operation of the target keyword in a parent-child relationship tree; and acquiring the target identification of the target keyword from the attribute information.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein when the processor executes the program, the processor realizes any one of the information processing methods.
The present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements any of the information processing methods described above.
The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements any of the information processing methods described above.
The invention provides an information processing method, an information processing device, information processing equipment and a storage medium.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of an information processing method provided by the present invention;
FIG. 2 is a schematic flow chart of obtaining a string set according to the present invention;
FIG. 3 is a flow chart illustrating the determination of the business value of a target keyword provided by the present invention;
FIG. 4 is a schematic diagram of an information processing apparatus according to the present invention;
fig. 5 is a schematic physical structure diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Currently, the result set returned by an API may be a json object. In the case that the result set returned by the API is a json object, there are 2 ways to parse the result set returned by the API to obtain the business value of the keyword.
In the mode 1, a template value corresponding to a keyword is obtained from a json data template agreed by a B function module and an A function module in advance, the template value is hard-coded through a json toolkit and the keyword to obtain a code logic block, the API of the A function module is called to receive a result set returned by the API of the A function module, and then the service value of the keyword is obtained from the API result set based on the code logic block.
In the method 1, even if the B function module needs to acquire the service value of the keyword in the result set returned by the API of the C function module, the B function module and the C function module must acquire the template value corresponding to the keyword from the json data template agreed in advance, and the template value is hard-coded by the json toolkit and the keyword to obtain the code logic block. Thus resulting in poor flexibility in obtaining the traffic value (B function). In the method 1, when the result set returned by the API changes, some keywords in the corresponding json data template may change, and the code logic block must be modified to adapt to the new json data template, which may cause a series of maintenance problems, resulting in increased maintenance cost.
Mode 2,1, obtaining a template value corresponding to a keyword from a json data template agreed by a B function module and an A function module in advance, manually embedding the keyword in the json data template into a database (or a configuration file), writing a code logic block according to the keyword in the database (or the configuration file), obtaining the template value corresponding to the keyword in the json data template through the code logic block, calling an API of the A function module, receiving a result set returned by the API of the A function module, and obtaining a service value of the keyword from the API result set based on the code logic block.
In the method 2, the keyword in the json data template is manually built into the database (or the configuration file), the code logic block is written according to the keyword in the database (or the configuration file), and the service value of the keyword is obtained from the API result set based on the code logic block, which results in poor flexibility of obtaining the service value (B function module). Moreover, in the method 2, when the result set returned by the API changes, some keywords in the corresponding json data template may change, so that the data in the database (or configuration file) needs to be modified to adapt to the new json data template. Under the condition that the data in the database is modified based on the configurable operation of the database, the keywords in the data need to be manually adjusted, and whether the adjusted keywords can obtain an accurate service value or not is verified. In the mode 2, a series of safety problems may be caused by the configurable operation based on the database, so that the data in the database has potential safety hazards, and the safety of the database is reduced.
In the invention, in order to improve flexibility of acquiring a service value, the inventor thinks of a general information processing method, which can acquire a service value of a keyword in a result set returned by an API of any other functional module, and does not need to acquire the service value in the result set based on a json data template agreed by two functional modules in advance and a code logic block obtained by hard coding, thereby improving flexibility of acquiring the service value.
The information processing method provided by the present invention will be described with reference to specific embodiments.
Fig. 1 is a schematic flow chart of an information processing method provided by the present invention. As shown in fig. 1, the method provided by this embodiment includes:
s101, a result set fed back by the first API is obtained, and the result set comprises a plurality of keywords and service values of the keywords.
Alternatively, in the present invention, the execution subject of the information processing method may be an electronic device, or may be an information processing apparatus provided in the electronic device.
The information processing apparatus may be implemented by a combination of software and/or hardware. For example, the information processing apparatus may be a functional module having an API.
The first API may be an API on a function module in other devices, or may be an API on a function module in the electronic device.
And if the first API is the API on the functional module in the electronic equipment, the functional module where the first API is located is not the information processing device. Illustratively, the result set is as follows.
{
“area”：{“value”:“9600000”},
“country”:“china”，
“address”:{
“province”:{
"name": shanxi province,
“city”：[
{ "name": "the city of west anns" },
{ "name": 'Chuanchuan city of Cuochuan' }
] }}}
For example, the keywords in the result set include: "area", "value", "count", "city", "name", and the like.
For example, the traffic value of "area" is { "value": 9600000"}," traffic value of "county" is "china".
Multiple keywords have a parent-child relationship.
For example, in the result set, the keyword "address" is the parent of the keyword "progress", and the keyword "progress" is the child of the keyword "address".
S102, determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of the parent keyword of the keyword. Based on the above result set, an exemplary set of parent-child relationship trees can be as follows.
JsonList:[
JsonEntity:{
Id:“1”，
ParentId:“0”，
Key:“area”，
Level:“1”，
Type:“object”，
Children:[
Id：“2”，
ParentId:“1”，
Key:“value”，
Level:“2”，
Type:“string”，
Children:[]]},
JsonEntity: {
Id:“3”，
ParentId:“0”，
Key:“country”，
Level:“1”，
Type:“string”，
Children:[]},
JsonEntity:{
Id:“4”，
ParentId:“0”，
Key:“address”，
Level:“1”，
Type:“object”,
Children:[
Id：“5”，
ParentId:“4”，
Key:“province”，
Level:“2”，
Type:“object”，
Children:[
Id:“6”，
ParentId:“5”，
Key:“name”，
Level:“3”，
Type:“string”,
Children:[]],
Children:[
Id：“6”，
ParentId:“4”，
Key：“city”，
Level：“3”，
Type：“array”，
Children:[
“Id”：“7”，
“ParentId”:“6”，
Key=“name”，
Level=“4”，
Type=“string”，
Children:[]],
Children:[
“Id”：“8”，
“ParentId”:“6”，
Key=“name”，
Level=“4”，
Type=“string”，
Children:[]]]]}}
In the parent-child relationship tree set, the identifier (Id) of the keyword "area" is 1, and the identifier (ParentId) of the parent keyword of the keyword is 0.
S103, acquiring a target identifier of the target keyword.
Optionally, the target keyword is any one of a plurality of keywords.
And S104, determining a target root keyword in the parent-child relationship tree set based on the target identifier.
The target root key is a root node of the target key.
For example, in the case where the target keyword is city, the target root keyword is address.
And S105, determining the business value of the target keyword based on the business value of the target root keyword.
In the information processing method provided in the embodiment of fig. 1, the tree set of the parent-child relationship is determined based on the result set, the target identifier of the target keyword is obtained, the target root keyword is determined in the tree set of the parent-child relationship based on the target identifier, and the service value of the target keyword is determined based on the service value of the target root keyword.
Different from the prior art, in the prior art, hard coding is required, the workload of coding is increased, the invasion to the code is high, and the later expansion is difficult. In the application, hard coding is not needed, the workload of coding is reduced, the intrusiveness to codes is reduced, and the later expansion is easy.
In addition, the information processing method provided by the application also has the following beneficial effects:
(1) And decoupling the functional modules. Since the service value does not need to be obtained based on the json data template agreed in advance between the two function modules, for example, the B function module may analyze and obtain the service value in the result set returned by the API of the a function module and the service value in the result set returned by the API of the C function module.
(2) And a database or a configuration file is abandoned, so that excessive manual intervention is reduced, and the safety and stability of the system are improved. In other words, in the application, the operation of the database (or the configuration file) and the source data in the database (or the configuration file) are not required, and the analysis can be directly performed in the memory, so that excessive manual intervention is reduced, and the safety and the stability of the system are improved.
(3) The capability of dynamic adaptation of the data source enables maintenance cost to be reduced after online. Compared with the prior art, in the related art, after the code of the B function module is on line to a production environment or has been formally released to an external network, if a result set fed back by the API of the a function module changes, the function of the B function module cannot be realized, and the problem that the function of the B function module cannot be realized cannot be solved by non-code type change at present, so that a new version of the B function module is usually required to be applied to release to re-adapt the changed result set, which results in increasing the flow cost and the time cost, reducing the availability of four versions 9 of the B function module, and improving the maintenance cost. In the application, after the information processing method provided by the application is formally put on line to a production environment or formally released to an external network, if the result set changes every time, the problem can be solved through non-code change, time is not spent on applying and releasing the version to adapt to the changed result set again, the availability of four 9 versions of the B function module is improved, and the maintenance cost is reduced.
(4) The method is applied to the Robot Process Automation (RPA) technology, so that the robot can have higher-level capability based on the adept capability of the robot. Its ability to excel is for example: optical Character Recognition (OCR) capability, natural Language Processing (NLP) capability.
In some embodiments, obtaining a target identification of the target keyword comprises:
sending the parent-child relationship tree set to the display device so that the display device displays the parent-child relationship tree based on the parent-child relationship tree set;
receiving attribute information of a target keyword sent by display equipment after responding to selection operation of the target keyword in a parent-child relationship tree;
and acquiring the target identification of the target keyword from the attribute information.
Further, after determining the business value of the target keyword, the business value of the target keyword may also be sent to the display device, so that the display device displays the business value of the target keyword.
Alternatively, the display device may be a display of the front end. And after receiving the parent-child relationship tree set, the display device displays the parent-child relationship tree based on the parent-child relationship tree set through the front-end tree component.
On the basis of the set of parent-child relationship trees, the parent-child relationship trees are as follows.
area
value
country
address
province
name
city
name
name
Optionally, the attribute information of the target keyword may further include the target keyword, a hierarchy of the target keyword, an identifier of a parent keyword of the target keyword, a type of a business value of the target keyword, and the like.
In the application, a parent-child relationship tree set is sent to a display device, so that the display device displays a parent-child relationship tree based on the parent-child relationship tree set, and attribute information of a target keyword sent by the display device after responding to a selection operation of the target keyword in the parent-child relationship tree is received; and acquiring the target identifier of the target keyword from the attribute information, so that the user display equipment can obtain the service value of any target keyword, and the user experience is improved.
In some embodiments, determining the set of parent-child relationship trees, based on the result set, comprises:
analyzing the result set to obtain a character string set with a parent-child tree relationship;
splitting the character string set to obtain an array of each keyword, wherein the array comprises a plurality of attributes of the keyword, and the plurality of attributes comprise the keyword, a parent keyword of the keyword, the hierarchy of the keyword, the type of a service value of the keyword and the number of the service values;
and determining a parent-child relationship tree set based on the array of each keyword.
The character string set comprises a plurality of initial attribute information adopting first identifier intervals, and the initial attribute information comprises a plurality of attributes adopting second identifier intervals.
Optionally, the initial attribute information includes the second identifier, and may further include the first identifier.
Alternatively, the first identifier may be "|", and the second identifier may be "-".
Alternatively, the type of the business value may be an object type, an array type, an integer type, a string type, a boolean type, a long integer type, or the like. Alternatively, object may be used to represent object type, array may be used to represent array type, integer may be used to represent integer, string may be used to represent string type, boolean may be used to represent boolean type, and long integer may be used to represent long integer.
Based on the above result set, an exemplary set of strings is:
|root-area-object-1-0|area-value-string-2-0|root-country-string-1-0|root-address-object-1-0|address-province-object-2-0|province-name-string-3-0|province-city-array-3-1|city-name-string-4-0|city-name-string-4-0。
in the string set, A-B-C-D-E represents initial attribute information. Wherein A, B, C, D, E represent a plurality of attributes. Alternatively, B denotes a keyword, a denotes a parent keyword of the keyword, C denotes a type of a business value of the keyword, D denotes a hierarchy of the keyword, and E denotes the number of business values. For example, root-area-object-1-0 indicates that the keyword is area, the parent keyword of the keyword is root, the type of the business value of the keyword is an object type, the hierarchy of the keyword is 1, and the number of business values is 0.
The character string set includes initial attribute information of each keyword.
The process of obtaining the initial attribute information of each keyword will be described below with reference to fig. 2.
Fig. 2 is a schematic flow chart of obtaining initial attribute information of each keyword according to the present invention. As shown in fig. 2, the method provided in this embodiment includes:
s201, setting a level L.
Initially, L =0.
S202, acquiring a keyword set from the target information through a preset function.
The target information may be a result set, or may be a service value whose type is an object type or a numerical type.
The result set is a jeson object. In the case where the result set is as shown in the result set, "area", "count", "address" are included in the keyword set.
S203, the ith keyword is obtained from the keyword set.
And S204, acquiring the service value of the ith keyword from the result set.
S205, under the condition that the business value of the ith keyword is the object type, setting the hierarchy of the ith keyword as L +1, setting the type of the business value as the object type and setting the number of the business values as the first number.
Wherein the first number is 0.
S206, combining the hierarchy of the ith keyword, the object type, the number of the service values, the ith keyword and the parent keyword of the ith keyword based on the first identifier and the second identifier to obtain the initial attribute information of the ith keyword.
Optionally, the hierarchy of the ith keyword, the object type, the number of service values, the ith keyword and the parent keyword of the ith keyword may be combined according to the rule of | a-B-C-D-E to obtain the initial attribute information of the ith keyword.
S207 and L +1, determining the service value of the ith keyword as target information, and repeatedly executing S202 and the method steps after S202.
And S208, under the condition that the service value of the ith keyword is an array type, setting the hierarchy of the ith keyword as L +1, setting the type of the service value as the array type, and setting the number of the service values as the number obtained by a preset size function (size function).
S209, combining the hierarchy of the ith keyword, the array type, the number of the service values, the ith keyword and the parent keyword of the ith keyword based on the first identifier and the second identifier to obtain the initial attribute information of the ith keyword.
Specifically, the execution method of S209 is similar to the execution method of S206, and the execution process of S209 is not described herein again.
S210, traversing keywords in the service value of the ith keyword to obtain the service value of each keyword, executing S207 when the type of the service value is an object type, and executing S208 when the type of the service value is an array type.
S211, under the condition that the service value of the ith keyword is integer, character string type, boolean type and long integer, setting the hierarchy of the ith keyword as L +1, setting the type of the service value as integer and setting the number of the service values as first number.
S212, combining the hierarchy of the ith keyword, the type of the service value, the number of the service values, the ith keyword and the parent keyword of the ith keyword based on the first identifier and the second identifier to obtain the initial attribute information of the ith keyword.
It should be noted that, in the process of executing the loop, initially, the ith keyword is the first keyword in the result set (for example, area in the result set), and when the ith keyword is the last keyword in the result set (for example, the last name in the result set).
In some embodiments, splitting the string set to obtain an array of keywords includes: splitting the character string set based on the first identifier to obtain initial attribute information of each keyword; and splitting the initial attribute information of each keyword based on the second identifier to obtain an array of each keyword.
After the splitting process is performed on the set of strings based on the first identifier on the basis of the result set, as shown below.
|root-area-object-1-0
| area -value-string-2-0
|root-country-string-1-0
|root-address-object-1-0
| address-province-object-2-0
| province -name-string-3-0
| province -city-array-3-1
| city-name-string-4-0
| city-name-string-4-0
For example, based on the second identifier, splitting the initial attribute information | root-count-string-1-0 of the key to obtain an array of keys ("count") [ root, count, string,1,0].
In some embodiments, determining the set of parent-child relationship trees based on the array of keywords comprises: determining target attribute information of each keyword based on the array of each keyword, wherein the target attribute information comprises an identifier of the keyword and an identifier of a parent keyword of the keyword; and through a recursive algorithm, associating the identifier of the keyword in the target attribute information of each keyword with the identifier of the parent keyword of the keyword, and determining a parent-child relationship tree set.
In some embodiments, the determining target attribute information for a keyword based on an array of keywords comprises: determining the identifier of the keyword through a preset algorithm; determining the identification of a parent keyword of the keyword through a preset algorithm; and determining the identifier of the keyword, the identifier of the parent keyword and a plurality of attributes in the array of the keyword as target attribute information of the keyword.
In some embodiments, determining the target root key in the set of parent-child relationship trees based on the target identification comprises: determining all father keywords of the target keywords in the parent-child relationship tree set based on the target identification through a tree up-conversion algorithm, wherein the tree up-conversion algorithm is the inverse process of the recursive algorithm; and determining the keywords with the middle levels as the first preset levels in all the parent keywords as target root keywords.
The first preset level may be 1.
In some embodiments, determining the business value of the target keyword based on the business value of the target root keyword comprises:
acquiring a business value of the target root keyword from the result set through a preset toolkit;
judging whether the type of the business value of the ith parent keyword is a first type or not aiming at the ith parent keyword in all the parent keywords; if yes, performing type conversion on the service value of the ith parent keyword to obtain a conversion result corresponding to the first type, and determining the service value of the (i-1) th parent keyword in the conversion result; otherwise, determining the service value corresponding to the hierarchy of the (i-1) th father keyword in the service value of the ith father keyword as the service value of the (i-1) th father keyword;
initially, i = N, the nth parent keyword is a target keyword, and N is equal to the total number of all parent keywords; at the end, i =1, the 0 th parent keyword is a target keyword, and the first type is an object type or an array type.
Wherein, the preset toolkit is a json toolkit.
For example, on the basis of the set of parent-child relationship trees, in the case that the target keyword is "city", all the parent keywords of the target keyword include "progress" and "address", where address is the target root keyword.
Specifically, determining the business value of the i-1 th parent key in the conversion result includes: and determining the business value corresponding to the hierarchy of the ith-1 th parent keyword in the conversion result as the business value of the ith-1 st parent keyword.
The process of determining the business value of the target keyword is described below with reference to fig. 3.
Fig. 3 is a schematic flow chart of determining a business value of a target keyword according to the present invention. As shown in fig. 3, the method provided by this embodiment includes:
s301, acquiring the business value of the target root keyword from the result set through a preset toolkit.
S302, judging whether the service value of the ith parent keyword in all the parent keywords of the target keyword is of the first type.
If so, perform S303, otherwise perform S304.
Initially, i = N, N equals the total number of all parent keys, the nth parent key being the target root key.
S303, performing type conversion on the service value of the ith father keyword to obtain a conversion result corresponding to the first type, and determining the service value of the ith-1 father keyword in the conversion result.
S304, determining the business value corresponding to the hierarchy of the (i-1) th father keyword in the business values of the (i) th father keyword as the business value of the (i-1) th father keyword.
In the FIG. 3 embodiment, the ith parent key is the parent key of the (i-1) th parent key. In the case of executing S304, the business value at the ith parent key is of the second type.
Optionally, the second type is an integer, a string type, a boolean type, or a long integer.
S305, judging whether i-1 is equal to 0.
If yes, go to step S307, otherwise go to step S308.
S306, determining the business value of the i-1 th father keyword as the business value of the target keyword.
S307, updating i in S302 to i-1, and repeatedly executing S302 to S307.
The information processing apparatus provided by the present invention is described below, and the information processing apparatus described below and the information processing method described above may be referred to in correspondence with each other.
Fig. 4 is a schematic structural diagram of an information processing apparatus provided by the present invention. As shown in fig. 4, the information processing apparatus includes:
a first obtaining module 410, configured to obtain a result set fed back by the first API, where the result set includes multiple keywords and service values of the keywords, and the keywords have a parent-child relationship;
a first determining module 420, configured to determine a parent-child relationship tree set based on the result set, where the parent-child relationship tree set includes an identifier of each keyword and an identifier of a parent keyword of the keyword;
a second obtaining module 430, configured to obtain a target identifier of the target keyword;
a second determining module 440, configured to determine a target root keyword in the parent-child relationship tree set based on the target identifier;
a third determining module 450, configured to determine a business value of the target keyword based on the business value of the target root keyword.
According to the information processing apparatus provided by the present invention, the first determining module 420 is specifically configured to: analyzing the result set to obtain a character string set with a parent-child tree relationship; splitting the character string set to obtain an array of each keyword, wherein the array comprises a plurality of attributes of the keyword, and the plurality of attributes comprise the keyword, a parent keyword of the keyword, the hierarchy of the keyword, the type of a service value of the keyword and the number of the service values; and determining a parent-child relationship tree set based on the array of each keyword.
According to an information processing apparatus provided by the present invention, a character string set includes a plurality of pieces of initial attribute information at intervals of a first identifier, and the initial attribute information includes a plurality of attributes at intervals of a second identifier; the first determining module 420 is specifically configured to: splitting the character string set based on the first identifier to obtain initial attribute information of each keyword; and splitting the initial attribute information of each keyword based on the second identifier to obtain an array of each keyword.
According to the information processing apparatus provided by the present invention, the first determining module 420 is specifically configured to: determining target attribute information of each keyword based on the array of each keyword, wherein the target attribute information comprises an identifier of the keyword and an identifier of a parent keyword of the keyword; and through a recursive algorithm, associating the identifier of the keyword in the target attribute information of each keyword with the identifier of the parent keyword of the keyword, and determining a parent-child relationship tree set.
According to the information processing apparatus provided by the present invention, the first determining module 420 is specifically configured to: determining the identifier of the keyword through a preset algorithm; determining the identification of a parent keyword of the keyword through a preset algorithm; and determining the identifier of the keyword, the identifier of the parent keyword and a plurality of attributes in the array of the keyword as target attribute information of the keyword.
According to the information processing apparatus provided by the present invention, the second determining module 440 is specifically configured to: determining all father keywords of the target keywords in the parent-child relationship tree set based on the target identification through a tree up-conversion algorithm, wherein the tree up-conversion algorithm is the inverse process of the recursive algorithm; and determining the keywords with the middle levels as the first preset levels in all the parent keywords as target root keywords.
According to the information processing apparatus provided by the present invention, the third determining module 450 is specifically configured to: acquiring a business value of the target root keyword from the result set through a preset tool kit; judging whether the type of the business value of the ith parent keyword is a first type or not aiming at the ith parent keyword in all the parent keywords; if yes, performing type conversion on the service value of the ith father keyword to obtain a conversion result corresponding to the first type, and determining the service value of the ith-1 father keyword in the conversion result; otherwise, determining the service value corresponding to the hierarchy of the ith-1 father keyword in the service values of the ith father keyword as the service value of the ith-1 father keyword; initially, i = N, the nth parent keyword is a target keyword, and N is equal to the total number of all parent keywords; at the end, i =1, the 0 th parent keyword is a target keyword, and the first type is an object type or an array type.
According to the information processing apparatus provided by the present invention, the third determining module 450 is specifically configured to: and determining the business value corresponding to the hierarchy of the (i-1) th parent keyword in the conversion result as the business value of the (i-1) th parent keyword.
According to the information processing apparatus provided by the present invention, the second obtaining module 430 is specifically configured to: sending the parent-child relationship tree set to the display device so that the display device displays the parent-child relationship tree based on the parent-child relationship tree set; receiving attribute information of a target keyword sent by a display device after responding to a selection operation of the target keyword in a parent-child relationship tree; and acquiring the target identification of the target keyword from the attribute information.
Fig. 5 is a schematic physical structure diagram of an electronic device provided in the present invention. As shown in fig. 5, the electronic device may include: a processor (processor) 510, a communication Interface (Communications Interface) 520, a memory (memory) 530 and a communication bus 540, wherein the processor 510, the communication Interface 520 and the memory 530 communicate with each other via the communication bus 540. Processor 510 may call logic instructions in memory 530 to perform an information handling method comprising: acquiring a result set fed back by a first API, wherein the result set comprises a plurality of keywords and service values of the keywords, and the keywords have a parent-child relationship; determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of the parent keyword of the keyword; acquiring a target identifier of a target keyword; determining a target root keyword in the parent-child relationship tree set based on the target identifier; and determining the business value of the target keyword based on the business value of the target root keyword.
In addition, the logic instructions in the memory 530 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the method of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product including a computer program, the computer program being storable on a non-transitory computer-readable storage medium, the computer program, when executed by a processor, being capable of executing an information processing method provided by the above methods, the method including: acquiring a result set fed back by a first API, wherein the result set comprises a plurality of keywords and service values of the keywords, and the keywords have parent-child relationships; determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of the parent keyword of the keyword; acquiring a target identifier of a target keyword; determining a target root keyword in the parent-child relationship tree set based on the target identifier; and determining the business value of the target keyword based on the business value of the target root keyword.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program, which when executed by a processor, implements an information processing method provided by the above methods, the method including: acquiring a result set fed back by a first API, wherein the result set comprises a plurality of keywords and service values of the keywords, and the keywords have a parent-child relationship; determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of the parent keyword of the keyword; acquiring a target identifier of a target keyword; determining a target root keyword in the parent-child relationship tree set based on the target identifier; and determining the business value of the target keyword based on the business value of the target root keyword.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on the understanding, the above technical solutions substantially or otherwise contributing to the prior art may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method of various embodiments or some parts of embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (12)
1. An information processing method, characterized by comprising:
obtaining a result set fed back by a first API, wherein the result set comprises a plurality of keywords and service values of the keywords, and the keywords have a parent-child relationship;
determining a parent-child relationship tree set based on the result set, wherein the parent-child relationship tree set comprises the identification of each keyword and the identification of the parent keyword of the keyword;
acquiring a target identifier of a target keyword;
determining a target root keyword in the parent-child relationship tree set based on the target identifier;
and determining the business value of the target keyword based on the business value of the target root keyword.
2. The information processing method of claim 1, wherein determining a set of parent-child relationship trees based on the result set comprises:
analyzing the result set to obtain a character string set with a parent-child tree relationship;
splitting the character string set to obtain an array of each keyword, wherein the array comprises a plurality of attributes of the keywords, and the attributes comprise the keywords, parent keywords of the keywords, the hierarchy of the keywords, the types of the service values of the keywords and the number of the service values;
and determining the parent-child relationship tree set based on the array of the keywords.
3. The information processing method according to claim 2, wherein the set of character strings includes a plurality of pieces of initial attribute information in a first identifier interval, and the initial attribute information includes a plurality of attributes in a second identifier interval;
splitting the character string set to obtain an array of each keyword, including:
splitting the character string set based on the first identifier to obtain initial attribute information of each keyword;
and splitting the initial attribute information of each keyword based on the second identifier to obtain an array of each keyword.
4. The information processing method according to claim 2, wherein the determining the set of parent-child relationship trees based on the array of keywords comprises:
determining target attribute information of each keyword based on the array of each keyword, wherein the target attribute information comprises an identifier of the keyword and an identifier of a parent keyword of the keyword;
and through a recursive algorithm, associating the identifier of the keyword in the target attribute information of each keyword with the identifier of the parent keyword of the keyword, and determining the parent-child relationship tree set.
5. The information processing method according to claim 4, wherein determining the target attribute information of the keyword based on the array of keywords comprises:
determining the identifier of the keyword through a preset algorithm;
determining the identifier of the parent keyword of the keyword through a preset algorithm;
and determining the identifier of the keyword, the identifier of the parent keyword and a plurality of attributes in the array of the keyword as target attribute information of the keyword.
6. The information processing method according to claim 5, wherein the determining a target root key in the set of parent-child relationship trees based on the target identifier comprises:
determining all father keywords of the target keywords in the parent-child relationship tree set based on the target identification through a tree up-conversion algorithm, wherein the tree up-conversion algorithm is an inverse process of a recursive algorithm;
and determining the keywords with the middle levels as the first preset levels in all the parent keywords as the target root keywords.
7. The information processing method of claim 6, wherein the determining the business value of the target keyword based on the business value of the target root keyword comprises:
acquiring the service value of the target root keyword from the result set through a preset toolkit;
judging whether the type of the business value of the ith parent keyword is a first type or not aiming at the ith parent keyword in all the parent keywords; if yes, performing type conversion on the service value of the ith parent keyword to obtain a conversion result corresponding to the first type, and determining the service value of the (i-1) th parent keyword in the conversion result; otherwise, determining the service value corresponding to the hierarchy of the i-1 th parent keyword in the service values of the i-th parent keyword as the service value of the i-1 th parent keyword;
initially, i = N, the nth parent key is the target key, and N is equal to the total number of all the parent keys; when the process is finished, i =1, the 0 th parent keyword is the target keyword, and the first type is an object type or an array type.
8. The information processing method of claim 7, wherein the determining the business value of the i-1 th parent key in the conversion result comprises:
and determining the business value corresponding to the hierarchy of the (i-1) th parent keyword in the conversion result as the business value of the (i-1) th parent keyword.
9. The information processing method according to any one of claims 1 to 5, wherein the obtaining of the target identifier of the target keyword includes:
sending the parent-child relationship tree set to a display device so that the display device displays a parent-child relationship tree based on the parent-child relationship tree set;
receiving attribute information of the target keyword sent by the display device after responding to the selection operation of the target keyword in the parent-child relationship tree;
and acquiring the target identification of the target keyword from the attribute information.
10. An information processing apparatus characterized by comprising:
the first obtaining module is used for obtaining a result set fed back by a first API (application program interface), wherein the result set comprises a plurality of keywords and service values of the keywords, and the keywords have parent-child relationships;
a first determining module, configured to determine a parent-child relationship tree set based on the result set, where the parent-child relationship tree set includes an identifier of each keyword and an identifier of a parent keyword of the keyword;
the second acquisition module is used for acquiring a target identifier of the target keyword;
a second determining module, configured to determine a target root keyword in the parent-child relationship tree set based on the target identifier;
and the third determining module is used for determining the business value of the target keyword based on the business value of the target root keyword.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the information processing method according to any one of claims 1 to 9 when executing the program.
12. A non-transitory computer-readable storage medium on which a computer program is stored, the computer program implementing the information processing method according to any one of claims 1 to 9 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211264888.0A CN115329759B (en) | 2022-10-17 | 2022-10-17 | Information processing method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211264888.0A CN115329759B (en) | 2022-10-17 | 2022-10-17 | Information processing method, device, equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115329759A true CN115329759A (en) | 2022-11-11 |
| CN115329759B CN115329759B (en) | 2023-03-24 |
Family
ID=83915398
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211264888.0A Active CN115329759B (en) | 2022-10-17 | 2022-10-17 | Information processing method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115329759B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116522871A (en) * | 2023-07-05 | 2023-08-01 | 鹏城实验室 | Data format conversion method, device, equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180336487A1 (en) * | 2017-05-17 | 2018-11-22 | Microsoft Technology Licensing, Llc | Tree ensemble explainability system |
| CN109902434A (en) * | 2019-03-18 | 2019-06-18 | 浙江工业大学 | Service data visual modeling and matching process towards REST framework style under cloud computing environment |
| CN110059085A (en) * | 2019-03-18 | 2019-07-26 | 浙江工业大学 | A kind of parsing of JSON data and modeling method of web oriented 2.0 |
| CN111046630A (en) * | 2019-12-06 | 2020-04-21 | 中国科学院计算技术研究所 | Syntax tree extraction method of JSON data |
| CN111552840A (en) * | 2020-05-06 | 2020-08-18 | 山东汇贸电子口岸有限公司 | Method for converting JSON data into tree-shaped hierarchical data |
| CN112416356A (en) * | 2020-11-12 | 2021-02-26 | 北京三快在线科技有限公司 | JSON character string processing method, device, equipment and storage medium |
| CN114995869A (en) * | 2022-05-31 | 2022-09-02 | 济南浪潮数据技术有限公司 | Configuration file analysis method, device, equipment and medium |
-
2022
- 2022-10-17 CN CN202211264888.0A patent/CN115329759B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180336487A1 (en) * | 2017-05-17 | 2018-11-22 | Microsoft Technology Licensing, Llc | Tree ensemble explainability system |
| CN109902434A (en) * | 2019-03-18 | 2019-06-18 | 浙江工业大学 | Service data visual modeling and matching process towards REST framework style under cloud computing environment |
| CN110059085A (en) * | 2019-03-18 | 2019-07-26 | 浙江工业大学 | A kind of parsing of JSON data and modeling method of web oriented 2.0 |
| CN111046630A (en) * | 2019-12-06 | 2020-04-21 | 中国科学院计算技术研究所 | Syntax tree extraction method of JSON data |
| CN111552840A (en) * | 2020-05-06 | 2020-08-18 | 山东汇贸电子口岸有限公司 | Method for converting JSON data into tree-shaped hierarchical data |
| CN112416356A (en) * | 2020-11-12 | 2021-02-26 | 北京三快在线科技有限公司 | JSON character string processing method, device, equipment and storage medium |
| CN114995869A (en) * | 2022-05-31 | 2022-09-02 | 济南浪潮数据技术有限公司 | Configuration file analysis method, device, equipment and medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116522871A (en) * | 2023-07-05 | 2023-08-01 | 鹏城实验室 | Data format conversion method, device, equipment and storage medium |
| CN116522871B (en) * | 2023-07-05 | 2024-01-09 | 鹏城实验室 | Data format conversion method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115329759B (en) | 2023-03-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113536081B (en) | Data center data management method and system based on artificial intelligence | |
| CN111198813A (en) | Interface testing method and device | |
| CN115329759B (en) | Information processing method, device, equipment and storage medium | |
| CN112860356A (en) | API call control method and device, electronic equipment and storage medium | |
| CN112256318A (en) | Construction method and equipment for dependent product | |
| CN110688305B (en) | Test environment synchronization method, device, medium and electronic equipment | |
| CN113094125A (en) | Business process processing method, device, server and storage medium | |
| CN111124883B (en) | Test case library introduction method, system and equipment based on tree form | |
| CN110297820B (en) | Data processing method, device, equipment and storage medium | |
| CN117055851A (en) | Software architecture recovery method and device, electronic equipment and storage medium | |
| CN106843822B (en) | Execution code generation method and equipment | |
| CN112947907A (en) | Method for creating code branch | |
| CN116303013A (en) | Source code analysis method, device, electronic equipment and storage medium | |
| CN115907400A (en) | Work order processing method and device | |
| CN113448852A (en) | Test case obtaining method and device, electronic equipment and storage medium | |
| CN113626281A (en) | Slow SQL statement tracking method and device, electronic equipment and storage medium | |
| CN111679899A (en) | Task scheduling method, device, platform equipment and storage medium | |
| CN111610964A (en) | Encoding rule generation method and device | |
| CN114611155B (en) | Data management node verification method, device, equipment and medium | |
| CN113626409B (en) | Test data processing method, device, equipment and storage medium | |
| CN115309612B (en) | Method and device for monitoring data | |
| CN118132789A (en) | Data processing method and device | |
| CN115237420A (en) | Code generation method and device, electronic equipment and computer readable storage medium | |
| CN114202311A (en) | Method and device for determining actual control person of enterprise, electronic equipment and storage medium | |
| CN115981657A (en) | Code generation method and device, electronic equipment and readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |