272 results about "Python language" patented technology

The invention discloses a virtualized infrastructure platform for cloud data centers, which comprises a cloud management server, a cloud resource control server and a cloud security server, the whole life cycles of various computational resources of a cloud platform are monitored and managed by the cloud management server, the various resources of the physical layer of the cloud platform are scheduled, controlled and managed by the cloud resource control server, and the cloud security server is used for establishing a cloud computation security control system in a private cloud and a secure interaction system for the private cloud and a public cloud; the cloud management server is integrated with the cloud resource control server through REST interfaces, and the cloud security server is respectively connected with the cloud management server and the cloud resource control server. The virtualized infrastructure platform for cloud data centers can realize security gateway-based unified remote virtual machine control and management, providing administrators with a unified access entrance for the management of virtual resources, and moreover, by means of directory service, the virtualized infrastructure platform for cloud data centers checks the validity of user identities; and a user can use the Python language to extend the resource scheduling control function.

The invention provides a Python code change reminding method based on abstract syntax tree node change extraction. The method comprises the following steps of: (1) obtaining source code of different-version programs of the same software; (2) generating abstract syntax trees corresponding to two versions of source programs; (3) matching the abstract syntax trees to obtain a change node, and combining change node context information to mark the node change type; (4) gathering change tuples into transactions to construct a training set; (5) mining the association relationship in the change tuples by using a data mining technology; and (6) reminding a developer of possibly occurring change positions and possible change types in the according to the programs mined association relationship. The Python code change reminding method solves the problems that in the prior art, the possible code change type cannot be reminded due to the lack of software evolution analysis aiming at the python language, and the like. The management of the software life cycle is further guided, and the software evolution controllability is improved, so that the quality of a software product can be well controlled.

The invention provides a Python resource sensitive defect code detecting method based on a depth neural network. The Python resource sensitive defect code detecting method comprises the following steps of 1, obtaining a source code of the historical version of the same software and a source code of a to-be-detected version; 2, utilizing type deduction to extract resource sensitive code modes of all versions; 3, extracting relevant characteristics of the resource sensitive code modes; 4, calculating all characteristic similarities between a defect code mode and a safe code mode and between thedefect code mode and a to-be-detected code mode to generate characteristic vectors and obtaining a training set and a testing set; 5, using the training set to train a depth neural network model to combine the characteristics, then using the mode with a testing set to calculate relevance of the depth neural network model and ranking the relevance; 6, conducting prompt, assisting development and maintenance on possibly wrong resource object operations according to a relevance ranking result in a program development and maintenance period. The Python resource sensitive defect code detecting method based on the depth neural network solves the problems that currently, an automated method aiming at Python language resource sensitive code recognition and defect code detection is lack, then the software risk is lowered, the software quality is improved, and thus the efficiency for a developer and a maintainer to develop and maintain software is improved.

An automatic detection system capable of dynamically judging XSS vulnerabilities, the system is composed of a crawler module, a dynamic vulnerability detection module and a user interaction interface. The software system introduces a library containing the browser kernel, which can simulate browser behavior to parse JavaScript and load Ajax to obtain hidden injection points and interaction points in the page, and find unconventional web submission request methods through static analysis of the page structure. Compared with the traditional static method and the method without dynamic judgment module, the coverage rate of injection point identification is greatly improved. The injection point test uses a black-box method without considering the internal logic of the server. After submitting the attack vector, it can detect whether there is any abnormality on the page by simulating the behavior of the browser, that is, it can detect whether the browser has executed the web script, and can directly judge It is more accurate to find out whether the current injection point is vulnerable. In addition, the system is completely developed in Python language, which is easy to maintain and carry out secondary development.

A simplified method for forecasting the fatigue expansion service life of an inclined crack in the center of a rectangular plate mainly comprises five steps: step I, parametric modeling; step II, meshing; step III, finite element calculation and result reduction; step IV, automatic crack expansion simulation through cycle call; and step V, crack expansion service life forecasting. The method is based on Python language, carries out ABAQUS secondary development, adopts parametric modeling, and compiles command stream software packages for modeling and analysis, can realize automatic simulation of crack expansion of the rectangular plate with the central inclined crack, is low in workload, and high in precision.

The invention provides a high-rise residential area forced arrangement scheme generation design method based on a conditional generative adversarial network. The method comprises the steps of constructing a high-rise residential area conditional generative adversarial network structure model according to a design task book; Generating a data set under supervised pairing training and calling a Python language to adjust the picture size; Performing alternate iterative training on the network until a Nash equilibrium state is reached, and taking the high-rise residential area contour picture to be planned as an input condition to obtain a high-rise residential area forced arrangement scheme total plane graph; Calling a Python language to obtain a pixel gray scale value of the total plane graph so as to construct a high-rise residential area building geometric model; And establishing a building sunshine, fire-fighting performance and urban skyline combined evaluation system through computer simulation analysis and an expert evaluation method. The high-rise residential area forced drainage design scheme can be supported to make a decision, and meanwhile subjective and objective joint evaluation is carried out on the high-rise residential area forced drainage design scheme through building sunshine, fire-fighting performance and urban skyline analysis.

The invention relates to an XSS vulnerability detection method based on simulating a browser behavior. A crawler module is contained with a core of a browser, JavaScript can be analyzed and Ajax can be loaded by simulating the browser behavior to obtain a hidden type decanting point of a page. Compared with a traditional condition, the system increases covering of the decanting point greatly. A vulnerability detection module uses a black-box detection method to detect whether an abnormal condition occurs on the page or not by simulating the browser behavior after the attack vector is improved, namely whether the browser executes a page script or not can be detected, whether a current decanting point has vulnerability or not is judged directly, and the method is more accurate compared with the traditional method. In addition, the method is exploited through the python language, the advantages of being easy to maintain and being easy to conduct secondary development are possessed, and a great application value is possessed to the detection and research of the XSS vulnerability.

The invention relates to an XSS vulnerability detection method based on simulating a browser behavior. A crawler module is contained with a core of a browser, JavaScript can be analyzed and Ajax can be loaded by simulating the browser behavior to obtain a hidden type decanting point of a page. Compared with a traditional condition, the system increases covering of the decanting point greatly. A vulnerability detection module uses a black-box detection method to detect whether an abnormal condition occurs on the page or not by simulating the browser behavior after the attack vector is improved, namely whether the browser executes a page script or not can be detected, whether a current decanting point has vulnerability or not is judged directly, and the method is more accurate compared with the traditional method. In addition, the method is exploited through the python language, the advantages of being easy to maintain and being easy to conduct secondary development are possessed, and a great application value is possessed to the detection and research of the XSS vulnerability.

The invention discloses a rock mechanics test numerical simulation method based on ABAQUS, and relates to the technical field of rock mechanics tests. Secondary development is conducted on the ABAQUSthrough a Python language, the preprocessing process (of determining model size and loading parameters and the like) and the postprocessing process (of outputting a simulation result and collecting data) are compiled, and a parameterized numerical simulation system of the rock mechanics test is established; the Drucker-Prager failure criterion considering the shearing effect is compiled in a vusdfld subprogram of the ABAQUS, a failure unit deletion algorithm is introduced to research the rock test block deformation breakage process under the load effect, the numerical simulation of the rock mechanics test process is realized, and the reasonability and effectiveness of the simulation system are verified with the granite test block three-axis compression test as the case. The rock mechanicstest numerical simulation method and a laboratory loading platform can conduct data matching according to user requirements, the modeling and analyzing efficiency is greatly improved, and meanwhile the mechanics test content is enriched.

The invention discloses a platform and a method for testing a northbound interface. The platform for testing the northbound interface comprises a test console, an element management system (EMS), an element equipment matrix, an access terminal matrix, an uplink exchanger and a network test instrument. The test console further comprises a system initialization module, a test instrument control module, an exchanger control module, a network management system (NMS) simulation module and a log module, and is implemented by programming by using a Python language. The method for testing the northbound interface comprises the following steps of initializing, configuring the modules and parameters, initiating a service, testing an interface, processing a log and the like. By the platform and the method, test automation of the northbound interface is realized, and the test smoothness and the test efficiency are improved; multi-session control and multi-connection are supported, and services can be performed repeatedly. By the method, a user can sufficiently develop the test efficacy on a test design without being limited to the environment; and the test platform is easy and convenient to maintain and the test framework is powerful so as to conveniently develop a test drive.

The invention discloses a custom script-based automated interface test method and platform. The method is characterized by: building a Web platform, which is used for configuring test projects, interfaces, cases and request parameters through a Web UI, and providing an entry of running the test cases and viewing test results; deploying automated test services, which are a set of service interfacesdeveloped by using a Python language on the basis of Django, wherein tasks are received and encapsulated by the interfaces, and encapsulated tasks are inserted into a task queue; constructing the task queue, which is a message queue realized on the basis of Redis, and used for carrying out decoupling for the automated test services and test execution components; building the test execution components, which is used for executing the test cases; and lapping a Mysql database, which is used for storing the projects, the interfaces, the cases and test scripts configured by the Web platform and the test results fed back by the test execution components. By applying the automated interface test method and platform of the invention, technical requirements of automated interface tests are reduced, a coverage rate of the automated interface tests can be increased, and manpower is saved.

The present invention discloses a Python language based Rapidio switcher logic simulation verification platform and method. The verification platform comprises: a SystemC interface function for interpreting Python semantics, a DPI interface function used by SystemC to call SystemVerilog, and a test case and a running script realized by Python. According to the present invention, an interpreter between the Python language and the SystemC language is added, so that the Python language can directly control stimulus input of a logic simulator and compare responsive output and the test case programmed by using Python can be used directly in logic simulation and applied on a Rapidio switcher. By using the above environment, the programming efficiency and reusability of the test case can be greatly improved.

The invention relates to an embedded plant light environment regulation system combining an illumination frequency and a duty ratio. The system is based on plant physiology characteristics, and obtains the growth state of the plants in real time through a camera, thereby calling the optimal regulation model of the growth stage corresponding to the growth state according to the current state of theplants, and adjusting the illumination frequency to performing supplemental lighting on the plants to achieve the purpose of further improving supplemental lighting efficiency. Firstly obtaining a large amount of experimental data, and writing a support vector machine (SVM) algorithm by using a matlab language after normalization processing to construct a prediction model of the photosynthesis rate of the plants in different environments. Then writing a genetic algorithm by using the matlab language according to the obtained prediction model to construct a supplemental lighting target value optimization model and obtain the light environment target value corresponding to the curvature maximum value of each data. And finally, writing a random forest algorithm by using a python language toconstruct a facility light environment optimization regulation model capable of being portable to an embedded device. According to the embedded facility light environment optimization regulation system combining the illumination frequency and the duty ratio, the plant photosynthesis efficiency can be effectively improved, so that the economic benefit of the facility agriculture is improved.

The invention relates to the automatic test field, especially an automatic test method and system of a WEB interface. Test cases are downloaded by an Svn server; after the number of the test cases is counted, a defined table is filled with the test cases; a class of the table is introduced through programming of the Python language; the keywords of the automatic test are customized; the keywords are written to the table header of the table; and the result information of the automatic test is stored in the table according to corresponding keywords in automatic test.

The invention discloses a method for testing Android application controls. By the method, a developer can conveniently compile a control test case, the overall development time is shortened, and the overall test level is improved. A configuration file is analyzed to find out information such as names and IDs (Identifiers) of all the controls, and different controls are endowed with different test weights to balance test speed and coverage rate. Different controls to be tested are converted into test codes from a template through a python language, and then the test codes are imported into projects for unit test. According to the method, a conventional Android application tester is helped, the workload of the tester is reduced, and working efficiency is greatly improved.

The present invention provides a method for software measurement of ground phosphate rock consumption and a phosphoric acid production parameter control method in a feed-grade calcium hydrophosphate production process. The phosphoric acid production parameter control method comprises the steps of: analyzing relevant factors for influencing consumption, based on the method theory of machine learning, transmitting and storing pulp flow real-time data and vitriol flow real-time data automatically collected by an internet-of-things collection device and pulp flow data manually collected by a lab to a cloud platform, allowing a python language-based analysis platform to be directly connected with a database to extract features based on time sequence data to perform analysis and modeling, and establishing a real-time soft measurement technology for the ground phosphate rock consumption to replace a ground phosphate rock physical measurement device with high investment and easy damaging. Theimplementation process of the method mainly comprises the steps of: pulp flow collection, vitriol flow, pulp storage tank intensity, mineral powder consumption historical data, data preprocessing, training of a gradient boosted decision tree (GBDT) regression model, and prediction of the mineral powder consumption to control phosphoric acid for generation of parameters through adoption of the trained GBDT regression model.

The invention provides a PCIe Error Enabling test method. Firstly a topological port of a PCIe device identifiable for a Python language tool is queried by using a debug tool ITP; and secondly a PCIeError Enabling test is performed. The method is suitable for an X86 server product having an XDP interface and supporting a PCIe Error Enabling function. Under the condition of starting the PCIe ErrorEnabling function, correctable errors are injected into the PCIe device to simulate PCIe device Errors occurring in an actual application; by reading the value of a register, whether the PCIe Error Enabling function is successfully realized or not is judged; and when the Error number reaches a threshold, the phenomena of disk identification incapability and the like of the server do not occur. The test method is simple in operation and relatively high in practicality, and effectively ensures the reliability and security of the server.

The embodiment of the invention provides a Python-oriented function calling path generation method and system. The method includes: acquiring an abstract syntax tree (AST) of Python source code, and traversing the abstract syntax tree to acquire key information therein; and combining control structure characteristics of a Python language to construct a corresponding function calling relationship model according to the extracted key information, carrying out storage by a tree-shaped structure, and recording calling relationships between functions to generate the function calling relationship model, wherein each node in the function calling relationship model represents one of the functions in the source code, and a child node of one of the nodes represents a branch if the child node exists,one of the nodes represents the function, which is executed in an orderly manner, if a branch of the node does not exist, and sibling nodes and parent nodes in the function calling relationship modelare in parallel relationships, and indicate multi-branch structures in the source code.

The invention discloses an automatic telnet method and system used for automatic testing. An automatic telnet testing program is programmed through the python language, and a telnetlib library and a win32ui library are adopted, so that a user does not need to record scripts, edit script languages and the like, and operators do not need to have a programming basis. The IP address of a tested device, a user name and a password are stored in the file format in the method and stored in a con.ini file under a master catalogue, when an automatic telnet test is carried out, direct reading can be achieved, automatic login of the tested device is achieved, and manual input is not needed when the test is executed. A command to be executed is directly stored in a text file in an original format, the command text file can be directly read through the automatic telnet testing program, and automatic interaction between the command text tile and the tested device is achieved. The text file is used for command transmission and storage, use of the script languages is not needed, so that great convenience is brought to repeatability tests and remote maintenance and opening of multiple terminals, manual operation time is shortened, and work efficiency is improved.

The invention discloses an embedded data acquisition and equipment control system. A software portion of the system consists of a data acquisition module, a data processing module, an equipment control module, a data storage module, a data transmission module, a data display module, a watchdog module and an embedded Web Server module. The software modules are developed by a Python language and run in a Python analyzer, development and maintenance difficulty of programs are low, modification is simple, and expandability is good. The embedded data acquisition and equipment control system can acquire various signals of digital quantity, analog quantity, an I2C (inter-integrated circuit), intelligent equipment and the like, and is capable of realizing control linkage for a relay and the intelligent equipment, configuration of the system is simple and flexible by the aid of the embedded Web Server module, remote upgrading of the system can be realized on the basis of the modules, and accordingly, the embedded data acquisition and equipment control system is applicable to places needing to acquire data and control equipment according to real-time data.

The invention discloses a method for constructing an automobile driving condition, which comprises the following steps: preprocessing data, and supplementing and modifying missing and abnormal data inautomobile driving data by adopting Python language programming; dividing kinematics segments, dividing the driving process between every two adjacent parking points during actual driving of the vehicle into short strokes, and each short stroke being composed of an idling part and a driving part; constructing an automobile driving condition, and selecting a short stroke in a random mode in a clustering result on the basis of principal component analysis and K-mean clustering analysis processing short stroke characteristic parameters. According to the method, in the construction process of theactual driving condition of the vehicle, in order to obtain the actual driving condition of the characteristic value on the corresponding road traffic, kinematics fragments are classified according to the road traffic characteristic parameters. Aiming at the defects of manual classification, the application of principal component analysis and K-mean clustering analysis methods in construction ofactual vehicle driving conditions of a certain city is researched, and the method is reasonable in design and easy to implement and has good practical value.

The invention provides an elderly portrait method used for endowment service, which comprises the following steps: collecting and establishing a database, establishing a depth learning model, trainingthe model and obtaining a user portrait model. At first, a depth learn platform is built. The invention is based on a ubuntu system, code is written in python language, a tensorflow framework is used, and GPU is used to accelerate and shorten the run time. Based on the depth learning model of a capsule neural network and a convolution neural network, through the daily behaviors of the elderly, social attributes and other information as input, through one-layer convolution network and two-layer capsule neural network processing, and then the corresponding tag of the elderly to be predicted isoutput to achieve the purpose of tags for the elderly, which can effectively position the elderly, thus laying a favorable foundation for pension services.

The invention relates to the technical field of cloud gathering environment development, a cloud-based environment development method for learning is disclosed, The programming environment, a code debug information window, a customized bluetooth remote control system, a hardware connection simulation system, a video tutorial system, a cloud storage compilation system, an IOT system, a customized code pack system and a bluetooth burner system is integrated on the IDE of the system, , Programming environments include graphical programming and Python programming, the IDE of the present inventionis located at the plate end, no longer limited to PCs, you can program anywhere, cloud compilation is used to solve the problem of tablet-side code compilation, Bluetooth burning code is used, so thatthe code burning is no longer bound by the line, the customized Bluetooth remote control panel, a hardware connection simulation panel and IOT panel are integrated, so that everything can be more intuitive, more simple, with convenient video tutorial pages and a large number of video tutorials, but also make the learning side simpler.

The invention discloses an automatic machine learning method based on reinforcement learning, which comprises the following steps of: shielding heterogeneity among different machine learning algorithmlibraries by using a unified API (Application Program Interface) interface, and calling algorithms in the different machine learning algorithm libraries in the Python language by taking Python as a programming language; modeling an automatic machine learning problem as a reinforcement learning problem, carrying out state space division on a candidate machine learning algorithm, determining a transfer relation between states, and using the Q-Learning algorithm to complete the process of searching the machine learning assembly line; carrying out metafeature extraction on the data set, searchingthe most similar data set, and accelerating the convergence process of automatic machine learning through operation information on the most similar data set. The problems that an existing automatic machine learning system is low in convergence speed and poor in expandability, and the final prediction performance cannot reach the expectation are solved.

The invention discloses an automatic driving control method based on CNN-LSTM. The automatic driving control method comprises the following steps: S1, acquiring image data and driving information of adriver at the same sampling frequency in a manner of combining a real vehicle driving or driving video recording or driving simulation system with a driving platform frame; and S2, based on a c++ language and a python language, in combination with an openCV library, automatically extracting image data to a region of interest by utilizing a Tensorflow framework, standardizing the image data into auniform size, arranging driving image data into an N * 4 two-dimensional tensor, and taking the N * 4 two-dimensional tensor as a training label Label. The automatic driving control method based on CNN-LSTM solves the problem that all road conditions cannot be covered by means of a traditional exhaustion type automatic driving algorithm due to the fact that the road conditions are complex and changeable in the prior art.