CN113722324B - Report generation method and device based on artificial intelligence, electronic equipment and medium - Google Patents
Report generation method and device based on artificial intelligence, electronic equipment and medium Download PDFInfo
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- CN113722324B CN113722324B CN202111007327.8A CN202111007327A CN113722324B CN 113722324 B CN113722324 B CN 113722324B CN 202111007327 A CN202111007327 A CN 202111007327A CN 113722324 B CN113722324 B CN 113722324B
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention relates to the technical field of artificial intelligence, and provides a report generation method, a report generation device, electronic equipment and a report generation medium based on artificial intelligence, wherein the method comprises the following steps: when the login interface is detected to be input with the user ID, acquiring pre-configured database information based on the authority level of the user ID; determining table structure information of a configured database based on pre-configured database information, and creating a plurality of class objects according to the table structure information; inquiring an association table of each class object according to a plurality of inquiry fields in report generation information aiming at each class object to obtain a target data set; a target report is generated based on a plurality of target datasets for a plurality of class objects. According to the invention, the data corresponding to each query field is queried according to the table relation of the associated table of each class object, and all data tables in each database are not required to be queried once, so that the query efficiency of the data required by the report is improved, and the report generation efficiency is further improved.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a report generation method, a report generation device, electronic equipment and a report generation medium based on artificial intelligence.
Background
The report forms can be used for processing and statistical analysis of various data, and are widely applied to various fields of medical treatment, management, statistical financial accounting, finance and the like, the data in each report form come from different databases and different data tables, and the prior art obtains the data required by generating the report forms by scanning each data table in each database in turn.
However, when the prior art acquires the data required for generating the report, the association relationship between a plurality of databases and a plurality of data tables cannot be known, all the data tables in each database need to be scanned, the scanned data volume is large, the data required for generating the report is acquired slowly, and the efficiency of generating the report is low.
Therefore, there is a need for a method for generating a report rapidly and accurately.
Disclosure of Invention
In view of the above, it is necessary to provide a report generating method, device, electronic equipment and medium based on artificial intelligence, which queries the data corresponding to each query field of the data required by the report according to the table relation of the association table of each class object, without querying all the data tables in each database once, thereby improving the query efficiency and further improving the report generating efficiency.
The first aspect of the invention provides an artificial intelligence-based report generation method, which comprises the following steps:
analyzing the received report generation request to obtain report generation information, wherein the report generation information comprises a plurality of query fields;
when detecting that a user ID is input on a login interface, identifying the authority level of the user ID, and acquiring pre-configured database information based on the authority level of the user ID;
determining the table structure information of a configured database based on the pre-configured database information, and creating a plurality of class objects according to the table relation in the table structure information;
inquiring an association table of each class object according to the plurality of inquiry fields in the report generation information aiming at each class object to obtain a target data set of each class object;
and generating a target report based on a plurality of target data sets of the plurality of class objects.
Optionally, the determining the table structure information of the configured database based on the preconfigured database information includes:
analyzing the configured database information to obtain at least one database name;
sequentially calling a database reading instruction corresponding to each database name, and responding to the database reading instruction corresponding to each database to read the table structure information in the corresponding database;
And traversing and executing the reading of the table structure information of each database until the reading of the table structure information of a plurality of databases corresponding to the database names is completed, and determining the read table structure information of each database corresponding to each database name as the table structure information of the configured database.
Optionally, the querying the association table of each class object according to the query fields in the report generating information, to obtain the target data set of each class object includes:
acquiring a first association relationship among the plurality of query fields from the report generation information;
classifying the plurality of query fields according to the first association relationship to obtain a plurality of types of query fields;
when each type of query field contains one query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query of a plurality of query fields in the multi-type query field is completed, obtaining a plurality of first data, and performing first logic calculation on the plurality of first data according to a second association relationship among the multi-type query fields to obtain a target data set of each type of object.
Optionally, the method further comprises:
when a plurality of query fields are contained in each type of query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query on a plurality of query fields in each type of query field is completed, and obtaining a plurality of second data;
identifying a third association relationship among the plurality of query fields in each type of query field, and performing second logic calculation on the plurality of second data according to the third association relationship among the plurality of query fields in each type of query field to obtain third data corresponding to each type of query field;
traversing and executing the query and the second logic calculation of the plurality of query fields in each type of query fields until the query of the plurality of types of query fields is completed, and obtaining a plurality of third data;
and performing third logic calculation on the plurality of third data according to a second association relation among the multi-class query fields to obtain a target data set of each class object.
Optionally, the method further comprises:
identifying whether an association table of each class object is empty;
If the association table of each class object is empty, determining that the association table of each class object only comprises a mother table; or alternatively
If the association table of each class object is not empty, determining that the association table of each class object comprises at least one mother table and at least one sub-table.
Optionally, the querying the association table of each class object according to each query field in the query fields of each class in turn includes:
when the association table of each class object is not empty, determining the table relation between a mother table and a sub-table in the association table;
and based on the table relation between the mother table and the sub table in the association table, sequentially adopting a preset query method to query the association table of each class object aiming at each query field in each class of query fields until the data corresponding to each query field is queried, and ending the query on the association table.
Optionally, the generating the target report based on the multiple target data sets of the multiple class objects includes:
converting each data in the plurality of target data sets into a standard SQL language to obtain an SQL language set;
encrypting the SQL language set by adopting a preset encryption algorithm;
Compressing the SQL language set after encryption processing, and storing the compressed SQL language set into a memory;
determining an interface message form according to the template style in the report generation information;
configuring a report template corresponding to the template style according to the interface message form;
analyzing the report template and determining the position coordinates of each query field;
and writing the compressed SQL language set into the report template through the memory according to the position coordinates of a plurality of query fields to generate a target report.
A second aspect of the present invention provides an artificial intelligence based report generating apparatus, the apparatus comprising:
the analysis module is used for analyzing the received report generation request and obtaining report generation information, wherein the report generation information comprises a plurality of query fields;
the identification module is used for identifying the authority level of the user ID when the user ID is input on the login interface, and acquiring pre-configured database information based on the authority level of the user ID;
the creation module is used for determining the table structure information of the configured database based on the pre-configured database information and creating a plurality of class objects according to the table relation in the table structure information;
The query module is used for querying the association table of each class object according to the plurality of query fields in the report generation information aiming at each class object to obtain a target data set of each class object;
and the generating module is used for generating a target report based on a plurality of target data sets of the class objects.
A third aspect of the present invention provides an electronic device comprising a processor and a memory, the processor being configured to implement the artificial intelligence based report generation method when executing a computer program stored in the memory.
A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the artificial intelligence based report generation method.
In summary, according to the report generating method, device, electronic equipment and medium based on artificial intelligence, on one hand, the authority level of each user ID is identified, and the pre-configured database information is directly obtained, so that the range of the database which is queried according to the query field is effectively reduced, and the query efficiency and accuracy of data required by generating the report are improved; on the other hand, the table structure information is created as the class object, and the table structure information with the association relation is packaged, so that the subsequent inquiry of the table data is facilitated, meanwhile, the source of each data is easy to determine when the table structure information is called, the class object corresponding to each data is fast determined by operation and maintenance personnel, and the operation and maintenance efficiency is improved; finally, according to the table relation of the association table of each class object, the data corresponding to each query field is queried, all data tables in each database do not need to be queried once, the query efficiency of the data required by the report is improved, and the report generation efficiency is further improved.
Drawings
FIG. 1 is a flowchart of an artificial intelligence based report generating method according to an embodiment of the present invention.
Fig. 2 is a block diagram of an artificial intelligence based report generating apparatus according to a second embodiment of the present invention.
Fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
Example 1
FIG. 1 is a flowchart of an artificial intelligence based report generating method according to an embodiment of the present invention.
In this embodiment, the report generating method based on artificial intelligence may be applied to an electronic device, and for an electronic device that needs to perform report generating based on artificial intelligence, the function of report generating based on artificial intelligence provided by the method of the present invention may be directly integrated on the electronic device, or may be run in the electronic device in the form of a software development kit (Software Development Kit, SDK).
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning, deep learning and other directions.
As shown in FIG. 1, the report generating method based on artificial intelligence specifically includes the following steps, the order of the steps in the flowchart may be changed according to different requirements, and some may be omitted.
S11, analyzing the received report generation request to obtain report generation information, wherein the report generation information comprises a plurality of query fields.
In this embodiment, the report may perform various data processing and statistical analysis, and is widely applied to numerous fields such as medical treatment, management, statistics finance, and the like, when a user needs to generate a report, a report generation request is initiated to a server through a client, specifically, the client may be a smart phone, an IPAD, or other existing smart devices, the server may be a report generation subsystem, and in the report generation process, the client may send a report generation request to the report generation subsystem, where the report generation subsystem is configured to receive the report generation request sent by the client.
In this embodiment, for the medical field, data such as medication information, cost information, personal health information, inspection information, prescription information, etc. are statistically analyzed to generate various reports related to medical treatment. Meanwhile, various generated reports are subjected to safety processing, such as encryption processing, so that the safety of medical data is ensured.
In this embodiment, when the report generating subsystem receives the report generating request, the report generating subsystem analyzes a message of the report generating request to obtain message information carried by the message, and obtains report generating information from the message information, where the message generating information includes a plurality of query fields, association relationships among the plurality of query fields, and other information such as a template style.
And S12, when the user ID is detected to be input on the login interface, identifying the authority level of the user ID, and acquiring the pre-configured database information based on the authority level of the user ID.
In this embodiment, the preset database configuration information includes database names, database call interfaces, database authority levels, database identification codes, table relations in the database, and other configuration information related to the database.
In an alternative embodiment, the obtaining the pre-configured database information based on the authority level of the user ID includes:
acquiring a calling interface based on the authority level of the user ID;
identifying a database name corresponding to the calling interface, wherein the database name comprises one or more than one database name;
and acquiring the pre-configured database information corresponding to the authority level of the user ID through a corresponding calling interface according to each database name.
In this embodiment, the user ID is used to uniquely identify identity information of each user, and database information configured by different user IDs is different, specifically, the database information is preset according to authority levels of each user, and by identifying authority levels of each user ID, the preconfigured database information is directly obtained, so that the range of a database queried according to a query field is effectively reduced, and the query efficiency and accuracy of data required for generating a report are improved.
In this embodiment, if the database is a medical database, the medical database includes medical data, such as personal health records, prescriptions, and inspection reports.
The medical data may be medical text, and the medical text may be a medical electronic record (Electronic Healthcare Record), an electronic personal health record, a series of electronic records with preservation and backup values, such as medical records, electrocardiography, medical images, and the like.
S13, determining the table structure information of the configured database based on the pre-configured database information, and creating a plurality of class objects according to the table relation in the table structure information.
In this embodiment, the table structure information refers to an association relationship between a plurality of tables in a plurality of databases, and specifically, the table structure information includes a table relationship, where the table relationship includes a table name, a table field, and the like of each table; the class objects are automatically generated by using a python tool according to the table relation in the table structure information, specifically, the table structure information is input into the python tool, and the python tool is automatically executed to create a plurality of class objects, wherein the python tool is an existing class creating tool, and the specific creation process is not described in detail herein.
In this embodiment, the plurality of class objects are automatically executed and generated by the existing python tool, so that a phenomenon of high error rate caused by complex table structure information when the class objects are manually created according to the table structure information is effectively avoided, and the accuracy of the created plurality of class objects is ensured.
In an alternative embodiment, the determining the table structure information of the configured database based on the pre-configured database information includes:
analyzing the configured database information to obtain at least one database name;
sequentially calling a database reading instruction corresponding to each database name, and responding to the database reading instruction corresponding to each database to read the table structure information in the corresponding database;
and traversing and executing the reading of the table structure information of each database until the reading of the table structure information of a plurality of databases corresponding to the database names is completed, and determining the read table structure information of each database corresponding to each database name as the table structure information of the configured database.
In this embodiment, since one or more database names may exist in the configured database information, each database name corresponds to one database, and the database reading instruction corresponding to each database is different, specifically, the database reading instruction corresponding to each database is determined according to the structure of the data table in each database, and in this embodiment, the table structure information of the configured database is obtained by reading the table structure information among the plurality of data tables in the plurality of databases in the preconfigured database information by using the corresponding database reading instruction, so that the table structure information of the database is more accurate, and the accuracy and efficiency of the target report generated later are further improved.
In an alternative embodiment, after said determining table structure information of the configured database based on said pre-configured database information, the method further comprises:
extracting a table structure in the table structure information; and storing the table structure into a preset hash table.
In this embodiment, since the hash table can greatly reduce the time consumed for storing and searching data, by storing the table structure in a preset hash table, subsequent and rapid query of the table structure is facilitated, and the query efficiency and management efficiency of the table structure are improved.
In this embodiment, the table structure information is created as the class object, and the table structure information with the association relationship is encapsulated, so that the subsequent query of the form data is facilitated, and meanwhile, the source of each data is easy to determine when the table structure information is called, so that the operation and maintenance personnel are assisted to quickly determine the class object corresponding to each data, and the operation and maintenance efficiency is improved.
S14, inquiring the association table of each class object according to the plurality of inquiry fields in the report generation information aiming at each class object to obtain a target data set of each class object.
In this embodiment, the association table of each class object refers to an association relationship between a field in each table and other tables. For example, M in table a may be found in table a, or may be found in table C associated with table a.
In an optional embodiment, the querying the association table of each class object according to the plurality of query fields in the report generating information, to obtain the target data set of each class object includes:
acquiring a first association relationship among the plurality of query fields from the report generation information;
classifying the plurality of query fields according to the first association relationship to obtain a plurality of types of query fields;
when each type of query field contains one query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query of a plurality of query fields in the multi-type query field is completed, obtaining a plurality of first data, and performing first logic calculation on the plurality of first data according to a second association relationship among the multi-type query fields to obtain a target data set of each type of object.
In this embodiment, the first association relationship refers to a first layer relationship between a plurality of query fields, where the first layer relationship between the plurality of query fields is preset by a user according to a report requirement, and may include an intersection relationship, a union relationship, and the like, and the first logic operation is determined according to a second association relationship between multiple types of query fields.
Illustratively, the plurality of query fields are: five grades, class A, chinese score and mathematics score, and three types of query fields are obtained according to the first association relation among the query fields: the first type of query field is: five-grade-class-a-chinese achievements; the second type of query field is: five years-math achievement, wherein the second association relation between the multi-class query fields is intersection calculation of the first data corresponding to the query of the multi-class query fields.
Further, the method further comprises:
when a plurality of query fields are contained in each type of query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query on a plurality of query fields in each type of query field is completed, and obtaining a plurality of second data;
identifying a third association relationship among the plurality of query fields in each type of query field, and performing second logic calculation on the plurality of second data according to the third association relationship among the plurality of query fields in each type of query field to obtain third data corresponding to each type of query field;
traversing and executing the query and the second logic calculation of the plurality of query fields in each type of query fields until the query of the plurality of types of query fields is completed, and obtaining a plurality of third data;
And performing third logic calculation on the plurality of third data according to a second association relation among the multi-class query fields to obtain a target data set of each class object.
In this embodiment, the third association refers to a second-layer relationship between multiple query fields in the query fields of each type, and specifically, the third association includes other relationships such as a union relationship and an intersection relationship.
In an alternative embodiment, before said querying the association table of each of said class objects according to said plurality of query fields in said report generating information, identifying whether the association table of each of said class objects is empty; if the association table of each class object is empty, determining that the association table of each class object only comprises a mother table, and if the association table of each class object is not empty, determining that the association table of each class object comprises at least one mother table and at least one sub-table.
Specifically, the table relationship between the mother table and the child table may be one or more of the following combinations: one mother table corresponds to one sub-table; one mother table corresponds to a plurality of sub-tables; the plurality of mother tables correspond to the plurality of sub-tables; the plurality of sub-tables corresponds to the plurality of sub-tables.
Further, the querying the association table of each class object according to each query field in the query fields of each class in turn includes:
identifying whether an association table of each class object is empty;
when the association table of each class object is empty, sequentially inquiring the association table of each class object according to each inquiry field in each inquiry field; or alternatively
When the association table of each class object is not empty, determining the table relation between a mother table and a sub-table in the association table; and based on the table relation between the mother table and the sub table in the association table, sequentially adopting a preset query method to query the association table of each class object aiming at each query field in each class of query fields until the data corresponding to each query field is queried, and ending the query on the association table.
In this embodiment, a query method may be preset, where the preset query method may be a backtracking method, and the backtracking method starts from the beginning of the mother table and searches the whole association table in a depth-first manner until the data corresponding to each query field is queried. For example, when the table relationship between the mother table and the sub-table is one-to-many, judging whether the data corresponding to each query field is queried in the mother table for each query field, and when the data corresponding to each query field is not queried in the mother table, continuing to search the rest multiple sub-tables according to the one-to-many table relationship between the mother table and the sub-table until the data corresponding to each query field is queried, and ending the query on the association table.
In this embodiment, the data corresponding to each query field is queried according to the table relationship of the association table of each class object, so that all data tables in each database do not need to be queried once, thereby improving the query efficiency of the data required by the report and further improving the report generation efficiency.
And S15, generating a target report based on a plurality of target data sets of the plurality of class objects.
In this embodiment, the target report is generated based on the queried data after querying the database according to a plurality of query fields set by the user in the report generation information.
In an alternative embodiment, the generating the target report based on the plurality of target data sets of the plurality of class objects includes:
determining an interface message form according to the template style in the report generation information;
configuring a report template corresponding to the template style according to the interface message form;
analyzing the report template and determining the position coordinates of each query field;
and writing the target data sets into the report module according to the position coordinates of the query fields to generate a target report.
In this embodiment, the report template is set by the user according to the own needs.
Further, the writing the plurality of target data sets into the reporting module includes:
converting each data in the plurality of target data sets into a standard SQL language to obtain an SQL language set;
encrypting the SQL language set by adopting a preset encryption algorithm;
compressing the SQL language set after encryption processing, and storing the compressed SQL language set into a memory;
and writing the compressed SQL language set into the report template through the memory to generate a target report.
Further, after generating the target report, the method further comprises:
and exporting the target report form into a CSV format report form.
In this embodiment, the target report may be converted into a report in a plain text file format, i.e., a report in a CSV format, and since CSV is a plain text file, it is convenient for subsequent importing into a spreadsheet or a database for storage, thereby improving the use efficiency of the report.
In this embodiment, because the readability of the standard SQL language is strong, by converting each data in the plurality of target data sets into the standard SQL language, the efficiency of writing the SQL language set into the report template in the following process is improved, so that the report generation efficiency is further improved, meanwhile, the SQL language set is encrypted, the data security in the report is improved, and the SQL language set is compressed, so that the memory space is saved, the running speed of the server is ensured, the writing efficiency of the SQL language set is improved, and the report generation efficiency is further improved.
In summary, according to the report generating method based on artificial intelligence in the embodiment, on one hand, by identifying the authority level of each user ID, the preconfigured database information is directly obtained, so that the range of the database which is queried according to the query field is effectively reduced, and the query efficiency and accuracy of the data required for generating the report are improved; on the other hand, the table structure information is created as the class object, and the table structure information with the association relation is packaged, so that the subsequent inquiry of the table data is facilitated, meanwhile, the source of each data is easy to determine when the table structure information is called, the class object corresponding to each data is fast determined by operation and maintenance personnel, and the operation and maintenance efficiency is improved; finally, according to the table relation of the association table of each class object, the data corresponding to each query field is queried, all data tables in each database do not need to be queried once, the query efficiency of the data required by the report is improved, and the report generation efficiency is further improved.
Example two
Fig. 2 is a block diagram of an artificial intelligence based report generating apparatus according to a second embodiment of the present invention.
In some embodiments, the artificial intelligence based report generating device 20 may include a plurality of functional modules consisting of program code segments. Program code for each of the program segments in the artificial intelligence based report generating apparatus 20 may be stored in a memory of the electronic device and executed by the at least one processor to perform (see FIG. 1 for details) the functions of artificial intelligence based report generation.
In this embodiment, the report generating device 20 based on artificial intelligence may be divided into a plurality of functional modules according to the functions performed by the report generating device. The functional module may include: parsing module 201, recognition module 202, creation module 203, query module 204, and generation module 205. The module referred to herein is a series of computer readable instructions capable of being executed by at least one processor and of performing a fixed function, stored in a memory. In the present embodiment, the functions of the respective modules will be described in detail in the following embodiments.
The parsing module 201 is configured to parse the received report generation request to obtain report generation information, where the report generation information includes a plurality of query fields.
In this embodiment, the report may perform processing and statistical analysis on various data, and is widely applied to numerous fields such as management, statistics finance and finance, where when a user needs to generate a report, a report generation request is initiated to a server through a client, specifically, the client may be a smart phone, an IPAD or other existing smart devices, the server may be a report generation subsystem, and in the report generation process, the client may send a report generation request to the report generation subsystem, where the report generation subsystem is configured to receive the report generation request sent by the client.
In this embodiment, for the medical field, data such as medication information, cost information, personal health information, inspection information, prescription information, etc. are statistically analyzed to generate various reports related to medical treatment. Meanwhile, various generated reports are subjected to safety processing, such as encryption processing, so that the safety of medical data is ensured.
In this embodiment, when the report generating subsystem receives the report generating request, the report generating subsystem analyzes a message of the report generating request to obtain message information carried by the message, and obtains report generating information from the message information, where the message generating information includes a plurality of query fields, association relationships among the plurality of query fields, and other information such as a template style.
The identification module 202 is configured to identify a permission level of a user ID when it is detected that the user ID is entered on the login interface, and obtain pre-configured database information based on the permission level of the user ID.
In this embodiment, the preset database configuration information includes database names, database call interfaces, database authority levels, database identification codes, table relations in the database, and other configuration information related to the database.
In an alternative embodiment, the identification module 202 obtaining pre-configured database information based on the authority level of the user ID comprises:
acquiring a calling interface based on the authority level of the user ID;
identifying a database name corresponding to the calling interface, wherein the database name comprises one or more than one database name;
and acquiring the pre-configured database information corresponding to the authority level of the user ID through a corresponding calling interface according to each database name.
In this embodiment, the user ID is used to uniquely identify identity information of each user, and database information configured by different user IDs is different, specifically, the database information is preset according to authority levels of each user, and by identifying authority levels of each user ID, the preconfigured database information is directly obtained, so that the range of a database queried according to a query field is effectively reduced, and the query efficiency and accuracy of data required for generating a report are improved.
In this embodiment, if the database is a medical database, the medical database includes medical data, such as personal health records, prescriptions, and inspection reports.
The medical data may be medical text, and the medical text may be a medical electronic record (Electronic Healthcare Record), an electronic personal health record, a series of electronic records with preservation and backup values, such as medical records, electrocardiography, medical images, and the like.
A creating module 203, configured to determine table structure information of the configured database based on the preconfigured database information, and create a plurality of class objects according to table relationships in the table structure information.
In this embodiment, the table structure information refers to an association relationship between a plurality of tables in a plurality of databases, and specifically, the table structure information includes a table relationship, where the table relationship includes a table name, a table field, and the like of each table; the class objects are automatically generated by using a python tool according to the table relation in the table structure information, specifically, the table structure information is input into the python tool, and the python tool is automatically executed to create a plurality of class objects, wherein the python tool is an existing class creating tool, and the specific creation process is not described in detail herein.
In this embodiment, the plurality of class objects are automatically executed and generated by the existing python tool, so that a phenomenon of high error rate caused by complex table structure information when the class objects are manually created according to the table structure information is effectively avoided, and the accuracy of the created plurality of class objects is ensured.
In an alternative embodiment, the creating module 203 determines the table structure information of the configured database based on the preconfigured database information includes:
analyzing the configured database information to obtain at least one database name;
sequentially calling a database reading instruction corresponding to each database name, and responding to the database reading instruction corresponding to each database to read the table structure information in the corresponding database;
and traversing and executing the reading of the table structure information of each database until the reading of the table structure information of a plurality of databases corresponding to the database names is completed, and determining the read table structure information of each database corresponding to each database name as the table structure information of the configured database.
In this embodiment, since one or more database names may exist in the configured database information, each database name corresponds to one database, and the database reading instruction corresponding to each database is different, specifically, the database reading instruction corresponding to each database is determined according to the structure of the data table in each database, and in this embodiment, the table structure information of the configured database is obtained by reading the table structure information among the plurality of data tables in the plurality of databases in the preconfigured database information by using the corresponding database reading instruction, so that the table structure information of the database is more accurate, and the accuracy and efficiency of the target report generated later are further improved.
In an alternative embodiment, after determining the table structure information of the configured database based on the pre-configured database information, extracting a table structure in the table structure information; and storing the table structure into a preset hash table.
In this embodiment, since the hash table can greatly reduce the time consumed for storing and searching data, by storing the table structure in a preset hash table, subsequent and rapid query of the table structure is facilitated, and the query efficiency and management efficiency of the table structure are improved.
In this embodiment, the table structure information is created as the class object, and the table structure information with the association relationship is encapsulated, so that the subsequent query of the form data is facilitated, and meanwhile, the source of each data is easy to determine when the table structure information is called, so that the operation and maintenance personnel are assisted to quickly determine the class object corresponding to each data, and the operation and maintenance efficiency is improved.
And a query module 204, configured to query, for each class object, an association table of each class object according to the multiple query fields in the report generation information, so as to obtain a target dataset of each class object.
In this embodiment, the association table of each class object refers to an association relationship between a field in each table and other tables. For example, M in table a may be found in table a, or may be found in table C associated with table a.
In an alternative embodiment, the querying module 204 queries the association table of each class object according to the plurality of query fields in the report generating information, and obtaining the target dataset of each class object includes:
acquiring a first association relationship among the plurality of query fields from the report generation information;
classifying the plurality of query fields according to the first association relationship to obtain a plurality of types of query fields;
when each type of query field contains one query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query of a plurality of query fields in the multi-type query field is completed, obtaining a plurality of first data, and performing first logic calculation on the plurality of first data according to a second association relationship among the multi-type query fields to obtain a target data set of each type of object.
In this embodiment, the first association relationship refers to a first layer relationship between a plurality of query fields, where the first layer relationship between the plurality of query fields is preset by a user according to a report requirement, and may include an intersection relationship, a union relationship, and the like, and the first logic operation is determined according to a second association relationship between multiple types of query fields.
Illustratively, the plurality of query fields are: five grades, class A, chinese score and mathematics score, and three types of query fields are obtained according to the first association relation among the query fields: the first type of query field is: five-grade-class-a-chinese achievements; the second type of query field is: five years-math achievement, wherein the second association relation between the multi-class query fields is intersection calculation of the first data corresponding to the query of the multi-class query fields.
Further, when each type of the query field contains a plurality of query fields, sequentially querying the association table of each type of the object according to each query field in each type of the query fields until the query of a plurality of query fields in each type of the query fields is completed, so as to obtain a plurality of second data; identifying a third association relationship among the plurality of query fields in each type of query field, and performing second logic calculation on the plurality of second data according to the third association relationship among the plurality of query fields in each type of query field to obtain third data corresponding to each type of query field; traversing and executing the query and the second logic calculation of the plurality of query fields in each type of query fields until the query of the plurality of types of query fields is completed, and obtaining a plurality of third data; and performing third logic calculation on the plurality of third data according to a second association relation among the multi-class query fields to obtain a target data set of each class object.
In this embodiment, the third association refers to a second-layer relationship between multiple query fields in the query fields of each type, and specifically, the third association includes other relationships such as a union relationship and an intersection relationship.
In an alternative embodiment, before said querying the association table of each of said class objects according to said plurality of query fields in said report generating information, identifying whether the association table of each of said class objects is empty; if the association table of each class object is empty, determining that the association table of each class object only comprises a mother table, and if the association table of each class object is not empty, determining that the association table of each class object comprises at least one mother table and at least one sub-table.
Specifically, the table relationship between the mother table and the child table may be one or more of the following combinations: one mother table corresponds to one sub-table; one mother table corresponds to a plurality of sub-tables; the plurality of mother tables correspond to the plurality of sub-tables; the plurality of sub-tables corresponds to the plurality of sub-tables.
Further, the querying the association table of each class object according to each query field in the query fields of each class in turn includes:
Identifying whether an association table of each class object is empty;
when the association table of each class object is empty, sequentially inquiring the association table of each class object according to each inquiry field in each inquiry field; or alternatively
When the association table of each class object is not empty, determining the table relation between a mother table and a sub-table in the association table; and based on the table relation between the mother table and the sub table in the association table, sequentially adopting a preset query method to query the association table of each class object aiming at each query field in each class of query fields until the data corresponding to each query field is queried, and ending the query on the association table.
In this embodiment, a query method may be preset, where the preset query method may be a backtracking method, and the backtracking method starts from the beginning of the mother table and searches the whole association table in a depth-first manner until the data corresponding to each query field is queried. For example, when the table relationship between the mother table and the sub-table is one-to-many, judging whether the data corresponding to each query field is queried in the mother table for each query field, and when the data corresponding to each query field is not queried in the mother table, continuing to search the rest multiple sub-tables according to the one-to-many table relationship between the mother table and the sub-table until the data corresponding to each query field is queried, and ending the query on the association table.
In this embodiment, the data corresponding to each query field is queried according to the table relationship of the association table of each class object, so that all data tables in each database do not need to be queried once, thereby improving the query efficiency of the data required by the report and further improving the report generation efficiency.
And the generating module 205 is configured to generate a target report based on a plurality of target data sets of the plurality of class objects.
In this embodiment, the target report is generated based on the queried data after querying the database according to a plurality of query fields set by the user in the report generation information.
In an alternative embodiment, the generating module 205 generates the target report based on the plurality of target data sets of the plurality of class objects includes:
determining an interface message form according to the template style in the report generation information;
configuring a report template corresponding to the template style according to the interface message form;
analyzing the report template and determining the position coordinates of each query field;
and writing the target data sets into the report module according to the position coordinates of the query fields to generate a target report.
In this embodiment, the report template is set by the user according to the own needs.
Further, the writing the plurality of target data sets into the reporting module includes:
converting each data in the plurality of target data sets into a standard SQL language to obtain an SQL language set;
encrypting the SQL language set by adopting a preset encryption algorithm;
compressing the SQL language set after encryption processing, and storing the compressed SQL language set into a memory;
and writing the compressed SQL language set into the report template through the memory to generate a target report.
Further, after generating the target report, the target report is exported as a CSV format report.
In this embodiment, the target report may be converted into a report in a plain text file format, i.e., a report in a CSV format, and since CSV is a plain text file, it is convenient for subsequent importing into a spreadsheet or a database for storage, thereby improving the use efficiency of the report.
In this embodiment, because the readability of the standard SQL language is strong, by converting each data in the plurality of target data sets into the standard SQL language, the efficiency of writing the SQL language set into the report template in the following process is improved, so that the report generation efficiency is further improved, meanwhile, the SQL language set is encrypted, the data security in the report is improved, and the SQL language set is compressed, so that the memory space is saved, the running speed of the server is ensured, the writing efficiency of the SQL language set is improved, and the report generation efficiency is further improved.
In summary, according to the report generating device based on artificial intelligence in this embodiment, on one hand, by identifying the authority level of each user ID, the preconfigured database information is directly obtained, so that the range of the database which is queried according to the query field is effectively reduced, and the query efficiency and accuracy of the data required for generating the report are improved; on the other hand, the table structure information is created as the class object, and the table structure information with the association relation is packaged, so that the subsequent inquiry of the table data is facilitated, meanwhile, the source of each data is easy to determine when the table structure information is called, the class object corresponding to each data is fast determined by operation and maintenance personnel, and the operation and maintenance efficiency is improved; finally, according to the table relation of the association table of each class object, the data corresponding to each query field is queried, all data tables in each database do not need to be queried once, the query efficiency of the data required by the report is improved, and the report generation efficiency is further improved.
Example III
Fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention. In the preferred embodiment of the invention, the electronic device 3 comprises a memory 31, at least one processor 32, at least one communication bus 33 and a transceiver 34.
It will be appreciated by those skilled in the art that the configuration of the electronic device shown in fig. 3 is not limiting of the embodiments of the present invention, and that either a bus-type configuration or a star-type configuration is possible, and that the electronic device 3 may also include more or less other hardware or software than that shown, or a different arrangement of components.
In some embodiments, the electronic device 3 is an electronic device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and its hardware includes, but is not limited to, a microprocessor, an application specific integrated circuit, a programmable gate array, a digital processor, an embedded device, and the like. The electronic device 3 may further include a client device, where the client device includes, but is not limited to, any electronic product that can interact with a client by way of a keyboard, a mouse, a remote control, a touch pad, or a voice control device, such as a personal computer, a tablet computer, a smart phone, a digital camera, etc.
It should be noted that the electronic device 3 is only used as an example, and other electronic products that may be present in the present invention or may be present in the future are also included in the scope of the present invention by way of reference.
In some embodiments, the memory 31 is used to store program code and various data, such as the artificial intelligence based report generating device 20 installed in the electronic device 3, and to enable high speed, automatic access to programs or data during operation of the electronic device 3. The Memory 31 includes Read-Only Memory (ROM), programmable Read-Only Memory (PROM), erasable programmable Read-Only Memory (EPROM), one-time programmable Read-Only Memory (One-time Programmable Read-Only Memory, OTPROM), electrically erasable rewritable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic tape Memory, or any other medium that can be used for computer-readable carrying or storing data.
In some embodiments, the at least one processor 32 may be comprised of an integrated circuit, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The at least one processor 32 is a Control Unit (Control Unit) of the electronic device 3, connects the respective components of the entire electronic device 3 using various interfaces and lines, and executes various functions of the electronic device 3 and processes data by running or executing programs or modules stored in the memory 31 and calling data stored in the memory 31.
In some embodiments, the at least one communication bus 33 is arranged to enable connected communication between the memory 31 and the at least one processor 32 or the like.
Although not shown, the electronic device 3 may further include a power source (such as a battery) for powering the various components, and optionally, the power source may be logically connected to the at least one processor 32 via a power management device, thereby implementing functions such as managing charging, discharging, and power consumption by the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 3 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The integrated units implemented in the form of software functional modules described above may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device, etc.) or a processor (processor) to perform portions of the methods described in the various embodiments of the invention.
In a further embodiment, in connection with fig. 2, the at least one processor 32 may execute the operating means of the electronic device 3 as well as various types of applications installed (e.g., the artificial intelligence based report generating means 20), program code, etc., such as the various modules described above.
The memory 31 has program code stored therein, and the at least one processor 32 can invoke the program code stored in the memory 31 to perform related functions. For example, the various modules depicted in FIG. 2 are program code stored in the memory 31 and executed by the at least one processor 32 to perform the functions of the various modules for purposes of artificial intelligence based report generation.
Illustratively, the program code may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 32 to perform the present application. The one or more modules/units may be a series of computer readable instruction segments capable of performing the specified functions, which instruction segments describe the execution of the program code in the electronic device 3. For example, the program code may be partitioned into a parsing module 201, an identification module 202, a creation module 203, a query module 204, and a generation module 205.
In one embodiment of the invention, the memory 31 stores a plurality of computer readable instructions that are executed by the at least one processor 32 to implement functions of artificial intelligence based report generation.
Specifically, the specific implementation method of the above instruction by the at least one processor 32 may refer to the description of the relevant steps in the corresponding embodiment of fig. 1, which is not repeated herein.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it will be obvious that the term "comprising" does not exclude other elements or that the singular does not exclude a plurality. The units or means stated in the invention may also be implemented by one unit or means, either by software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (9)
1. A report generation method based on artificial intelligence, the method comprising:
analyzing the received report generation request to obtain report generation information, wherein the report generation information comprises a plurality of query fields;
when detecting that the user ID is input on the login interface, identifying the authority level of the user ID, and acquiring the pre-configured database information based on the authority level of the user ID, wherein the method comprises the following steps: acquiring a calling interface based on the authority level of the user ID; identifying a database name corresponding to the calling interface, wherein the database name comprises one or more than one database name; acquiring preset database information corresponding to the authority level of the user ID through a corresponding calling interface according to each database name;
determining the table structure information of a configured database based on the pre-configured database information, and creating a plurality of class objects according to the table relation in the table structure information;
For each class object, querying an association table of each class object according to the query fields in the report generation information to obtain a target data set of each class object, wherein the target data set comprises: acquiring a first association relationship among the plurality of query fields from the report generation information; classifying the plurality of query fields according to the first association relationship to obtain a plurality of types of query fields; when each type of query field contains one query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query of a plurality of query fields in the multi-type query field is completed, obtaining a plurality of first data, and performing first logic calculation on the plurality of first data according to a second association relationship among the multi-type query fields to obtain a target data set of each type of object, wherein the first association relationship and the second association relationship respectively comprise an intersection relationship and a union relationship among the plurality of query fields, and the first logic calculation is determined according to the second association relationship among the multi-type query fields;
And generating a target report based on a plurality of target data sets of the plurality of class objects.
2. The artificial intelligence based report generating method as claimed in claim 1, wherein said determining table structure information of the configured database based on the pre-configured database information comprises:
analyzing the configured database information to obtain at least one database name;
sequentially calling a database reading instruction corresponding to each database name, and responding to the database reading instruction corresponding to each database to read the table structure information in the corresponding database;
and traversing and executing the reading of the table structure information of each database until the reading of the table structure information of a plurality of databases corresponding to the database names is completed, and determining the read table structure information of each database corresponding to each database name as the table structure information of the configured database.
3. The artificial intelligence based report generating method of claim 1, wherein the method further comprises:
when a plurality of query fields are contained in each type of query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query on a plurality of query fields in each type of query field is completed, and obtaining a plurality of second data;
Identifying a third association relationship among the plurality of query fields in each type of query field, and performing second logic calculation on the plurality of second data according to the third association relationship among the plurality of query fields in each type of query field to obtain third data corresponding to each type of query field;
traversing and executing the query and the second logic calculation of the plurality of query fields in each type of query fields until the query of the plurality of types of query fields is completed, and obtaining a plurality of third data;
and performing third logic calculation on the plurality of third data according to a second association relation among the multi-class query fields to obtain a target data set of each class object.
4. The artificial intelligence based report generating method of claim 3, wherein the method further comprises:
identifying whether an association table of each class object is empty;
if the association table of each class object is empty, determining that the association table of each class object only comprises a mother table; or alternatively
If the association table of each class object is not empty, determining that the association table of each class object comprises at least one mother table and at least one sub-table.
5. The artificial intelligence based report generating method as claimed in claim 4, wherein said querying the association table of each of the class objects sequentially according to each of the query fields of each class comprises:
when the association table of each class object is not empty, determining the table relation between a mother table and a sub-table in the association table;
and based on the table relation between the mother table and the sub table in the association table, sequentially adopting a preset query method to query the association table of each class object aiming at each query field in each class of query fields until the data corresponding to each query field is queried, and ending the query on the association table.
6. The artificial intelligence based report generating method of claim 1, wherein the generating a target report based on the plurality of target data sets of the plurality of class objects comprises:
converting each data in the plurality of target data sets into a standard SQL language to obtain an SQL language set;
encrypting the SQL language set by adopting a preset encryption algorithm;
compressing the SQL language set after encryption processing, and storing the compressed SQL language set into a memory;
Determining an interface message form according to the template style in the report generation information;
configuring a report template corresponding to the template style according to the interface message form;
analyzing the report template and determining the position coordinates of each query field;
and writing the compressed SQL language set into the report template through the memory according to the position coordinates of a plurality of query fields to generate a target report.
7. An artificial intelligence based report generating apparatus, the apparatus comprising:
the analysis module is used for analyzing the received report generation request and obtaining report generation information, wherein the report generation information comprises a plurality of query fields;
the identification module is used for identifying the authority level of the user ID when the user ID is input on the login interface, and acquiring the pre-configured database information based on the authority level of the user ID, and comprises the following steps: acquiring a calling interface based on the authority level of the user ID; identifying a database name corresponding to the calling interface, wherein the database name comprises one or more than one database name; acquiring preset database information corresponding to the authority level of the user ID through a corresponding calling interface according to each database name;
The creation module is used for determining the table structure information of the configured database based on the pre-configured database information and creating a plurality of class objects according to the table relation in the table structure information;
the query module is configured to query, for each class object, an association table of each class object according to the multiple query fields in the report generation information, to obtain a target dataset of each class object, and includes: acquiring a first association relationship among the plurality of query fields from the report generation information; classifying the plurality of query fields according to the first association relationship to obtain a plurality of types of query fields; when each type of query field contains one query field, sequentially querying an association table of each type of object according to each query field in each type of query field until the query of a plurality of query fields in the multi-type query field is completed, obtaining a plurality of first data, and performing first logic calculation on the plurality of first data according to a second association relationship among the multi-type query fields to obtain a target data set of each type of object, wherein the first association relationship and the second association relationship respectively comprise an intersection relationship and a union relationship among the plurality of query fields, and the first logic calculation is determined according to the second association relationship among the multi-type query fields;
And the generating module is used for generating a target report based on a plurality of target data sets of the class objects.
8. An electronic device comprising a processor and a memory, wherein the processor is configured to implement the artificial intelligence based report generation method of any one of claims 1 to 6 when executing a computer program stored in the memory.
9. A computer readable storage medium having a computer program stored thereon, which when executed by a processor implements the artificial intelligence based report generating method of any of claims 1 to 6.
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