diff --git "a/train/u_entries_out.jsonl" "b/train/u_entries_out.jsonl" new file mode 100644--- /dev/null +++ "b/train/u_entries_out.jsonl" @@ -0,0 +1,5146 @@ +{"package": "u", "pacakge-description": "No description available on PyPI."} +{"package": "u0-stitcher", "pacakge-description": 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bootstrapRun the tests:$ fab test"} +{"package": "u20211106", "pacakge-description": "No description available on PyPI."} +{"package": "u2fval", "pacakge-description": "No description available on PyPI."} +{"package": "u2fval-client", "pacakge-description": "No description available on PyPI."} +{"package": "u2net-fast", "pacakge-description": "U2Net-FastThis library builds on theU2Net machine learning modelto provide very fast\nbackground removal for large images. This is primarily accomplished by rewriting the data preparation steps to more\neffectively utilize the GPU. Support for multiple DataLoader workers and batching has also been added.IMPORTANT!This library requires that all input images in a batch be the same size! This library does not automatically resize\nor align inputs. If you need to process mixed resolution inputs, you should either (a) set the batch size to 1 to ensure\nall images are in their own batch at the cost of some performance, or (b) pad out the dimensions of any undersized images\nbefore running them through this library.Also note that this library requires a fairly large amount of VRAM for large images/batch sizes. The total amount of VRAM\nneeded can be calculated as follows: (3 * batch_size * height * width * 4). This is because each image must be expanded into\na 3-channel (RGB) tensor of floats (4 bytes) in order to perform the necessary rescaling. The original U2Net repository does\nthis rescaling on the CPU, so it uses much less memory (but is significantly slower).InstallationThis library is available on the Python Package Index (PyPI) under the name \"u2net_fast\".PrerequisitesThe following libraries are required:torchtorchvisiontqdmpillow (or pillow-simd, which can give a significant performance boost for certain output types)Installing via the prebuilt package should automatically install all prerequisites.UsageFor example scripts, see theexamplesdirectory. Note that for all example scripts, the U2Net model weights must be\ndownloaded to theexamples/modelsdirectory. They may be obtained from the original U2Net repository following the instructions\nin theUsage for Salient Object Detectionsection.The core component of this library is the Remover class, which may be imported using:from u2net_fast.remover import RemoverThis class exposes several methods, though for most use cases only thebatch_remove_backgroundfunction will be needed.The Remover class constructor takes several arguments to customize behavior. They are listed below:model_path (defaults to {os.getcwd()}/models/u2net.pth)The path pointing to the U2Net model weights.write_concurrency (defaults to the number of CPU cores)The number of parallel workers used to write out the output images. One of the slowest steps in this library is output image encoding, so paralleling this operation as much as possible usually gives significant speedups.dataloader_workers (defaults to 4)The number of PyTorch workers to assign to loading images.batch_size (defaults to 5)The number of images to load/process each batch. If you are running out of VRAM, try reducing this size.pin_memory (defaults to False)Whether the PyTorch dataloader should pin memory. In tests this actually seemed to slightly slow down performance for whatever reason. Other systems may have better luck.background_fill (defaults to [0, 0, 0])The RGB or RGBA color used to fill the background if apply_mask=True. If this is set to a 4 element array, the output_format must support transparency.output_format (defaults to 'jpg' if background_fill is 3 elements, or 'png' if background_fill is 4 elements)The format used to write output images. This is also used as the extension for the output files. This should be a format that PIL recognizes. 'jpg' is usually significantly faster than 'png'.threshold (defaults to 0.5)The U2Net mask output is grayscale. This value (between 0 and 1) determines the threshold used to determine whether something is \"in\" or \"out\" of the mask at the boundary. This rarely needs to be changed.apply_mask (defaults to True)Whether the calculated mask should be applied to the model. If this is False, the output frombatch_remove_backgroundwill be the image masks instead of the actual masked image. If you only need masks this can lead to a significant speedup.save_output (defaults to True)Whether the final output should be saved. This almost always should be true. The only time it's useful to set to False is when benchmarking performance.Once the remover object is instantiated, you may callbatch_remove_backgroundon it like so:r = Remover()\nr.batch_remove_background()Thebatch_remove_backgroundfunction also accepts several arguments, detailed below:input_dir (defaults to {os.getcwd()/inputs)The folder to load inputs in from. This should be a folder full of images with the same dimensionsoutput_dir (defaults to {os.getcwd()/outputs)The folder to save outputs to. This is not used if save_output=False. It will be automatically created if it does not exist.image_size (defaults to the size of the first image in the input_dir)The size of the images. This is automatically inferred from the first input image but can be set manually if desired.show_progress (defaults to True)Whether a TQDM progress bar should be shown during inference. Set this to False to disable progress tracking.Advanced UsageWhile thebatch_remove_backgroundfunction is the easiest way to use this library, the different stages of the processing\npipeline can also be called manually if more fine-grained control is needed. There are three main functions thatbatch_remove_backgroundcalls, listed below. These functions can all be called on an instance of a Remover object.process_batchThis function takes in a batch sample, a U2Net model, and a tuple representing the image size. It modifies the input sample\nin place and adds the calculated masks under the 'mask' key.apply_maskThis function takes in a batch sample and a tuple representing the image size and applies the mask to the image. The 'image'\nkey in the sample is overwritten with the new masked image.write_batchThis function takes in a batch sample and an output directory and writes the image data in the 'image' key to disk.To use these functions effectively, you should initialize a dataset and dataloader like so:from u2net_fast.model import U2NET\nfrom u2net_fast.dataloader import U2Dataset\n\ndataset = U2Dataset(image_name_list=image_names)\ndataloader = DataLoader(dataset, batch_size=1 shuffle=False)U2Dataset and DataLoader are just subclasses of PyTorch's Dataset and Dataloader, so all the standard arguments are accepted.\nThe DataLoader's batch_size should be set to 1 or greater - the pipeline functions expect the batch_sample to contain a batch\ndimension. Then, set up a loop to yield samples:for batch_sample in dataloader:\n PerformancePerformance was measured on a relatively modest system (an i7 7700k, and a GTX1080). At the default settings, processing\na batch of 125 images with mask application enabled (apply_mask=True) took approximately 33 seconds, with a peak throughput of about 4.5\nimages/second.Without mask application enabled (apply_mask=False), the same batch took approximately 13 seconds with a peak throughput of\nabout 9 images/second. This performance difference was mostly due to the additional data that needed to be saved to disk when\noutputting the full masked images (3 channels for the full RGB images vs 1 channel for the grayscale masks),notthe actual\nmask application step.With result saving disabled (save_output=False), and mask application disabled, the same batch took approximately 10 seconds\nwith a peak throughput of 11.45 images/second. With mask application enabled, the same batch took approximately 14 seconds\nwith a peak throughput of about 11 images/second (though this peak was reached much later)."} +{"package": "u2p", "pacakge-description": "U2P"} +{"package": "u2parser", "pacakge-description": "A unified2 log parser which reads a file, and returns all records."} +{"package": "u2py", "pacakge-description": "u2py"} +{"package": "u2s-sdk", "pacakge-description": "No description available on PyPI."} +{"package": "u2t", "pacakge-description": "Markdown-URL-to-Title\u672c\u5de5\u5177\u7684\u529f\u80fd\u4e3a\uff1a\u81ea\u52a8\u63d0\u53d6\u526a\u8d34\u677f\u4e2d\u7684 URL \uff0c\u7136\u540e\u4f7f\u7528 requests \u83b7\u53d6\u76ee\u6807 URL \u7684\u6807\u9898\uff0c\u6839\u636e\u6807\u9898\u751f\u6210\u53ef\u76f4\u63a5\u7c98\u8d34\u7684 Markdown \u5185\u5bb9\u3002\u80cc\u666f\u5728\u4f7f\u7528 Hexo \u5199\u535a\u5ba2\u7684\u65f6\u5019\uff0c\u60f3\u7ed9\u535a\u6587\u91cc\u63d2\u5165\u4e00\u4e9b\u53c2\u8003\u6587\u732e\uff0c\u4f46\u662f\u5982\u679c\u76f4\u63a5\u7c98\u8d34 URL \u7684\u8bdd\uff0c\n\u6709\u7684\u53c2\u8003\u94fe\u63a5\u7684 URL \u975e\u5e38\u957f\uff0c\u800c\u4e14\u4f1a\u88ab URL \u7f16\u7801\uff0c\u4e0d\u592a\u5bb9\u6613\u9605\u8bfb\uff0c\u5982\u4e0b\uff1a## \u53c2\u8003\u6587\u732e\n* https://vi.stackexchange.com/questions/14114/paste-link-to-image-in-clipboard-when-editing-markdown\n* https://c.m.163.com/news/a/FJ8PBOJ000097U7R.html?spss=adap_pc&referFrom=&spssid=592b2c22f7c667bdd783e7ef59625b86&spsw=1&isFromH5Share=article\u6240\u4ee5\u5c31\u60f3\u7740\u80fd\u4e0d\u80fd\u4e3a Hexo \u5b9e\u73b0\u4e00\u4e2a\u81ea\u52a8\u5c06 URL \u8f6c\u4e3a Markdown \u5e26\u6709\u6807\u9898\u6587\u672c\u7684\u683c\u5f0f\uff0c\u4e5f\u5c31\u662f\u5982\u4e0b\uff1a## \u53c2\u8003\u6587\u732e\n* [Paste link to image in clipboard when editing Markdown - Vi and Vim Stack Exchange](https://vi.stackexchange.com/questions/14114/paste-link-to-image-in-clipboard-when-editing-markdown)\n* [\u7ee7\u5fae\u4fe1\u5c01\u7981WeTool\u540e \u817e\u8baf\u6216\u5927\u89c4\u6a21\u5c01\u7981\u7b2c\u4e09\u65b9QQ\u673a\u5668\u4eba](https://c.m.163.com/news/a/FJ8PBOJ000097U7R.html?spss=adap_pc&referFrom=&spssid=592b2c22f7c667bdd783e7ef59625b86&spsw=1&isFromH5Share=article)\u7ecf\u8fc7\u4e00\u756a\u641c\u7d22\u6682\u65f6\u6ca1\u6709\u627e\u5230\u89e3\u51b3\u65b9\u6848\uff0c\u6ca1\u6709\u529e\u6cd5\uff0c\u53ea\u597d\u51fa\u6b64\u4e0b\u7b56\uff0c\u4f7f\u7528 Python \u6765\u5bf9\u526a\u5207\u677f\u8fdb\u884c\u64cd\u4f5c\uff0c\u63d0\u53d6\u526a\u5207\u677f\u4e2d\u7684 URL \u5e76\u8f6c\u6362\u4e3a Markdown \u7684\u683c\u5f0f\u3002\u73af\u5883\u9700\u6c42Windows 10Python 3\u4f8b\u5b50\u526a\u5207\u677f\u8f93\u5165...\nhttps://baidu.com/\n...\u526a\u5207\u677f\u8f93\u51fa...\n[\u767e\u5ea6\u4e00\u4e0b\uff0c\u4f60\u5c31\u77e5\u9053](https://www.baidu.com/)\n...\u5b89\u88c5\u901a\u8fc7 PyPipip install u2t\u901a\u8fc7 GitHubgitclonehttps://github.com/WangYihang/Markdown-URL-to-Title\u4f7f\u7528\u65b9\u5f0f\u6253\u5f00\u7ec8\u7aef\uff0c\u8fd0\u884c\uff1au2t\uff0c\u6b64\u65f6\u7cfb\u7edf\u6258\u76d8\u51fa\u73b0\u56fe\u6807\u590d\u5236\u5f85\u5904\u7406\u6587\u672c\uff0c\u4e0d\u7528\u7279\u522b\u7cbe\u786e\u5730\u53ea\u590d\u5236 URL\uff0c\u672c\u7a0b\u5e8f\u4f7f\u7528\u6b63\u5219\u63d0\u53d6\u526a\u5207\u677f\u5185\u5bb9\u4e2d\u7684\u6240\u6709 URL \u5e76\u8fdb\u884c\u6279\u91cf\u5904\u7406\u6309\u5feb\u6377\u952e Ctrl + Shift + Q\u7b49\u5f85\u6570\u79d2\uff0c\u5f85 Windows \u5f39\u51fa Toast \u63d0\u793a\u6846\uff0c\u5373\u53ef\u76f4\u63a5\u8fdb\u884c\u7c98\u8d34"} +{"package": "u2x", "pacakge-description": "U2X"} +{"package": "u3606b-py", "pacakge-description": "u3606b Python driver (unofficial)This is a Python driver for the u3606b multimeter. It is based on the officialU3606B Multimeter| DC Power Supply Programming Guideand PyVISA package.PyVISAis a Python package that allows you to control measurement devices independently of the interface (GPIB, USB, Ethernet, etc.) by using a common API.The driver is not complete, but it is a good starting point for anyone who wants to control the u3606b multimeter with Python.The driver supports the following functions:Read voltageRead currentSet voltageSet currentSet output on/offSet limitsStep outputPre-requisitesPython 3.8 or higher (lower versions may work, but have not been tested)Windows:NI-VISAorNI-488.2orKeysight IO Library SuiteLinux/MAC: please refer togpib-resources-gpib-instrInstallationpipinstallu3606b_pyExamplefromu3606b_py.u3606bimportU3606Bu3606b_dev=U3606B()u3606b_dev._open()u3606b_dev._reset()u3606b_dev.sour_vol_rng(rng='8V')u3606b_dev.sour(lvl='1.0V')"} +{"package": "u3driver", "pacakge-description": "No description available on PyPI."} +{"package": "u3d-studio", "pacakge-description": "Installation\u9700\u8981Python 3.6.0\u6216\u66f4\u9ad8\u7248\u672cpip install u3d-studio\u6216\u4e0b\u8f7d/\u514b\u9686git\u5e76\u4f7f\u7528python setup.py install\u4f7f\u7528\u8bf4\u660e\u6765\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8bimportosfromu3dunpackimportAssetsManagerSAMPLES=os.path.join(os.path.dirname(os.path.abspath(__file__)),\"samples\")IMG=os.path.join(os.path.dirname(os.path.abspath(__file__)),\"images\")KTX=os.path.join(os.path.dirname(os.path.abspath(__file__)),\"ktx\")deftestTexture2d():forfinos.listdir(SAMPLES):am=AssetsManager(os.path.join(SAMPLES,f))forassetinam.assets.values():forobjinasset.objects.values():ifobj.type==\"Texture2D\":# \u89e3\u6790\u5bf9\u8c61\u6570\u636edata=obj.read()# \u786e\u4fdd\u6269\u5c55\u540d\u6b63\u786e# \u60a8\u53ef\u80fd\u53ea\u60f3\u4f7f\u7528\u56fe\u50cf/\u7eb9\u7406dest,ext=os.path.splitext(data.name)destImg=dest+\".png\"destImg=os.path.join(IMG,destImg)img=data.image.save(destImg)destKtx=os.path.join(KTX,dest)+\".ktx\"ifos.path.exists(destKtx):os.remove(destKtx)withopen(destKtx,mode='wb')asw:w.write(data.saveKtx)withopen(destKtx,mode='rb')asr:ktxData=r.read()data.writeData(ktxData)withopen(\"assets/test\",mode='wb')asw:data=asset.bundleFile.save()w.write(data)if__name__=='__main__':testTexture2d()"} +{"package": "u3id", "pacakge-description": "No description available on PyPI."} +{"package": "u4nf", "pacakge-description": "No description available on PyPI."} +{"package": "u64cmd", "pacakge-description": "u64cmd - Remote Control for your Ultimate 64/II+This Python command line tools allows you to control yourUltimate 64/Ultimate II+\ndevice via a TCP connection on port 64.It implements almost the full feature set of the DMA Socket Protocol as\nspecified in the Ultimate64source code.Feature SetUpload/Run PRG FilesUpload REU ImagesUpload/Mount Disk ImagesUpload/Activate CRT ImagesUpload/Activate Kernel ROM ImagesWrite Data Files to RAMPOKE, POKEWType Text with Petcat like Control CodesReset/PowerOff MachineOn Ultimate64: Enable/Disable VIC/Audio/Debug StreamInstallationYou need Python 3 >= Version 3.7 and Pip installedInstall stable versionpip3 install u64cmdInstall current Git versionpip3 install -U git+https://github.com/cnvogelg/u64cmd.gitRun u64cmdYou run the command with this syntax:u64cmd -h 192.168.2.1 resetThe-h|--hostoption is required to give the IP address or hostname of your\nUltimate 64/II+.The above command triggers only theresetcommand and exits. You can also\nspecify multiple commands on the command line to execute them in a row:u64cmd -h 192.168.2.1 reset load_reu blureu.img load_prg -r blureu.prgCommand DescriptionMain OptionsUsage:u64cmd [--host|-h ] ...--host|-hgives thehost_addrof the Ultime64/II+ (required). Use\nenvironment variableU64CMD_HOSTto set the value permanently.With--port|-pyou can specify the port number. The default is64. Use\nenvironment variableU64CMD_PORTto set the value permanently.More Main OptionsThe option--versionshows the release version of the tool.The option--helpgives you a command overview.Use... --helpto get detailed help on a commandThe option--dump-keycodes|-Dshows a list of known petcat control\ncommands for typing message (seetypecommand)type- Type Text on C64 KeyboardUsage:type Types the giventext.You can pass control codes in the{code}notation (similar topetcat)Use the--dump-keycodes|-Dcommand to get a list of all supported codes.Example:type \"{clr}{wht}HELLO, WORLD!{lblu}{cr}\"prg_load- Load (and Run) a PRG FileUsage:prg_load [--run] [--jump] prg_filegives the name of the PRG file you want to DMA loadadd the--run|-rswitch to automaticallyRUNthe PRG after loadingsimilar--jump|-jjumps to the load address of the PRG filereu_load- Load Data File into REUUsage:reu_load [--addr ] [--offset ] [--size ] reu_filegives the file name to be uploaded into the REU--addr|-a defines the loading address.--offset|-o sets an optional offset in the file. By default the\nwhole file starting at the first byte will be uploaded. With this command\nyou can skip bytes for the upload.--size|-s limits the transfer. This allows you to reduce the\nuploaded block. By default the whole file is transferred.Note: You can specify any value in the tool either in decimal (e.g.49152)\nor in hex (e.g.0xc000)disk_load- Load/Mount Disk ImagesUsage:disk_load [--run|-r] disk_fileis a D64 disk image to be uploaded and mountedThe optional--run|-rallows to automatically run the first file in the\nimage.crt_load- Load/Enable CRT ImagesUsage:crt_load Uploads thecrt_fileas current cartridge image and activates it.kernal_load- Load/Enable Kernal ImageUsage:kernel_load Upload thekernal_fileas the new kernal ROM.data_write- Write data into RAMUsage:data_write [--addr ] [--offset ] [--size ] data_filegives the file name to be uploaded into C64 RAM--addr|-a defines the loading address. You can specify the value\nin decimal (e.g.49152) or in hex (e.g.0xc000)--offset|-o sets an optional offset in the file. By default the\nwhole file starting at the first byte will be uploaded. With this command\nyou can skip bytes for the upload.--size|-s limits the transfer. This allows you to reduce the\nuploaded block. By default the whole file is transferred.pokeandpokew- Write values into C64 MemoryUsage:poke \npokew poke a byte or a wordvalueinto memory at addressaddrstream_on- Enable VIC/Audio/Debug Streaming (U64 only)Usage:stream_on [--duration ] [--addr|-a ] Valid stream names arevic,audio, ordebug.The optional--duration|-d allows to set the transfer duration. By\ndefault the value is set to 0 meaning infinite duration.The optional--addr|-a Valid stream names arevic,audio, ordebug.reset- Reset C64Usage:resetpoweroff- Power Off C64 (U64 only)Usage:poweroffEOF"} +{"package": "u8488a", "pacakge-description": "Unofficial driver for Keysight U8488AThis is a simple driver for Keysight U8488A power meter. There are 2 classes in this package. You can use this package individually or for USRP calibration.Install$ pip install u8488aExample Usagefrom u8488a import base\nfrom time import sleep\n\ndev = base.PowerMeter()\n# List available devices\ndevs = dev.get_device_list()\n\nif len(devs) > 0:\n dev.open_device(devs(0))\nelse:\n print(\"No device found!\")\n exit(1)\n\nprint(\"Available devices:\")\nprint(devs)\n\n# Setting frequency to 20 GHz\ndev.frequency(20e9)\n\nwhile True:\n # Read power level every second\n print(f\"Power: {dev.get_power()} dBm\")\n sleep(1)USRP TX Power Reference Level CalibrationThis package includes \"custom\" driver for USRP calibration.uhd_power_cal.pyscripts is installed with UHD installation by default. It's located under ```/usr/local/lib64/uhd/utils``.Note: If you can't find uhd folder, it's probably under this directory/usr/local/lib/$ cd /usr/local/lib64/uhd/utils/\n$ uhd_power_cal.py -d tx --meas-dev visa -o import=u8488aNote: This can only be used for TX power calibration"} +{"package": "u8darts", "pacakge-description": "Time Series Made Easy in PythonDartsis a Python library for user-friendly forecasting and anomaly detection\non time series. It contains a variety of models, from classics such as ARIMA to\ndeep neural networks. The forecasting models can all be used in the same way,\nusingfit()andpredict()functions, similar to scikit-learn.\nThe library also makes it easy to backtest models,\ncombine the predictions of several models, and take external data into account.\nDarts supports both univariate and multivariate time series and models.\nThe ML-based models can be trained on potentially large datasets containing multiple time\nseries, and some of the models offer a rich support for probabilistic forecasting.Darts also offers extensive anomaly detection capabilities.\nFor instance, it is trivial to apply PyOD models on time series to obtain anomaly scores,\nor to wrap any of Darts forecasting or filtering models to obtain fully\nfledged anomaly detection models.DocumentationQuickstartUser GuideAPI ReferenceExamplesHigh Level IntroductionsIntroductory Blog PostIntroduction video (25 minutes)Articles on Selected TopicsTraining Models on Multiple Time SeriesUsing Past and Future CovariatesTemporal Convolutional Networks and ForecastingProbabilistic ForecastingTransfer Learning for Time Series ForecastingHierarchical Forecast ReconciliationQuick InstallWe recommend to first setup a clean Python environment for your project with Python 3.8+ using your favorite tool\n(conda,venv,virtualenvwith\nor withoutvirtualenvwrapper).Once your environment is set up you can install darts using pip:pip install dartsFor more details you can refer to ourinstallation instructions.Example UsageForecastingCreate aTimeSeriesobject from a Pandas DataFrame, and split it in train/validation series:importpandasaspdfromdartsimportTimeSeries# Read a pandas DataFramedf=pd.read_csv(\"AirPassengers.csv\",delimiter=\",\")# Create a TimeSeries, specifying the time and value columnsseries=TimeSeries.from_dataframe(df,\"Month\",\"#Passengers\")# Set aside the last 36 months as a validation seriestrain,val=series[:-36],series[-36:]Fit an exponential smoothing model, and make a (probabilistic) prediction over the validation series' duration:fromdarts.modelsimportExponentialSmoothingmodel=ExponentialSmoothing()model.fit(train)prediction=model.predict(len(val),num_samples=1000)Plot the median, 5th and 95th percentiles:importmatplotlib.pyplotaspltseries.plot()prediction.plot(label=\"forecast\",low_quantile=0.05,high_quantile=0.95)plt.legend()Anomaly DetectionLoad a multivariate series, trim it, keep 2 components, split train and validation sets:fromdarts.datasetsimportETTh2Datasetseries=ETTh2Dataset().load()[:10000][[\"MUFL\",\"LULL\"]]train,val=series.split_before(0.6)Build a k-means anomaly scorer, train it on the train set\nand use it on the validation set to get anomaly scores:fromdarts.adimportKMeansScorerscorer=KMeansScorer(k=2,window=5)scorer.fit(train)anom_score=scorer.score(val)Build a binary anomaly detector and train it over train scores,\nthen use it over validation scores to get binary anomaly classification:fromdarts.adimportQuantileDetectordetector=QuantileDetector(high_quantile=0.99)detector.fit(scorer.score(train))binary_anom=detector.detect(anom_score)Plot (shifting and scaling some of the series\nto make everything appear on the same figure):importmatplotlib.pyplotaspltseries.plot()(anom_score/2.-100).plot(label=\"computed anomaly score\",c=\"orangered\",lw=3)(binary_anom*45-150).plot(label=\"detected binary anomaly\",lw=4)FeaturesForecasting Models:A large collection of forecasting models; from statistical models (such as\nARIMA) to deep learning models (such as N-BEATS). Seetable of models below.Anomaly DetectionThedarts.admodule contains a collection of anomaly scorers,\ndetectors and aggregators, which can all be combined to detect anomalies in time series.\nIt is easy to wrap any of Darts forecasting or filtering models to build\na fully fledged anomaly detection model that compares predictions with actuals.\nThePyODScorermakes it trivial to use PyOD detectors on time series.Multivariate Support:TimeSeriescan be multivariate - i.e., contain multiple time-varying\ndimensions instead of a single scalar value. Many models can consume and produce multivariate series.Multiple series training (global models):All machine learning based models (incl. all neural networks)\nsupport being trained on multiple (potentially multivariate) series. This can scale to large datasets too.Probabilistic Support:TimeSeriesobjects can (optionally) represent stochastic\ntime series; this can for instance be used to get confidence intervals, and many models support different\nflavours of probabilistic forecasting (such as estimating parametric distributions or quantiles).\nSome anomaly detection scorers are also able to exploit these predictive distributions.Past and Future Covariates support:Many models in Darts support past-observed and/or future-known\ncovariate (external data) time series as inputs for producing forecasts.Static Covariates support:In addition to time-dependent data,TimeSeriescan also contain\nstatic data for each dimension, which can be exploited by some models.Hierarchical Reconciliation:Darts offers transformers to perform reconciliation.\nThese can make the forecasts add up in a way that respects the underlying hierarchy.Regression Models:It is possible to plug-in any scikit-learn compatible model\nto obtain forecasts as functions of lagged values of the target series and covariates.Explainability:Darts has the ability toexplainsome forecasting models using Shap values.Data processing:Tools to easily apply (and revert) common transformations on\ntime series data (scaling, filling missing values, differencing, boxcox, ...)Metrics:A variety of metrics for evaluating time series' goodness of fit;\nfrom R2-scores to Mean Absolute Scaled Error.Backtesting:Utilities for simulating historical forecasts, using moving time windows.PyTorch Lightning Support:All deep learning models are implemented using PyTorch Lightning,\nsupporting among other things custom callbacks, GPUs/TPUs training and custom trainers.Filtering Models:Darts offers three filtering models:KalmanFilter,GaussianProcessFilter,\nandMovingAverageFilter, which allow to filter time series, and in some cases obtain probabilistic\ninferences of the underlying states/values.DatasetsThedarts.datasetssubmodule contains some popular time series datasets for rapid\nand reproducible experimentation.Forecasting ModelsHere's a breakdown of the forecasting models currently implemented in Darts. We are constantly working\non bringing more models and features.ModelSourcesTarget Series Support:Univariate/MultivariateCovariates Support:Past-observed/Future-known/StaticProbabilistic Forecasting:Sampled/Distribution ParametersTraining & Forecasting on Multiple SeriesBaseline Models(LocalForecastingModel)NaiveMean\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5NaiveSeasonal\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5NaiveDrift\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5NaiveMovingAverage\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5Statistical / Classic Models(LocalForecastingModel)ARIMA\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5VARIMA\ud83d\udfe5 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5AutoARIMA\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5StatsForecastAutoArima(faster AutoARIMA)Nixtla's statsforecast\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5ExponentialSmoothing\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5StatsforecastAutoETSNixtla's statsforecast\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5StatsforecastAutoCESNixtla's statsforecast\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5BATSandTBATSTBATS paper\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5ThetaandFourThetaTheta&4 Theta\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5StatsForecastAutoThetaNixtla's statsforecast\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5ProphetProphet repo\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5FFT(Fast Fourier Transform)\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5KalmanForecasterusing the Kalman filter and N4SID for system identificationN4SID paper\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5Crostonmethod\ud83d\udfe9 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe5Regression Models(GlobalForecastingModel)RegressionModel: generic wrapper around any sklearn regression model\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9LinearRegressionModel\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9RandomForest\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9LightGBMModel\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9XGBModel\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9CatBoostModel\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9PyTorch (Lightning)-based Models(GlobalForecastingModel)RNNModel(incl. LSTM and GRU); equivalent to DeepAR in its probabilistic versionDeepAR paper\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe5 \ud83d\udfe9 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9BlockRNNModel(incl. LSTM and GRU)\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9NBEATSModelN-BEATS paper\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9NHiTSModelN-HiTS paper\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9TCNModelTCN paper,DeepTCN paper,blog post\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9TransformerModel\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe5 \ud83d\udfe5\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9TFTModel(Temporal Fusion Transformer)TFT paper,PyTorch Forecasting\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9DLinearModelDLinear paper\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9NLinearModelNLinear paper\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9TiDEModelTiDE paper\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9Ensemble Models(GlobalForecastingModel): Model support is dependent on ensembled forecasting models and the ensemble model itselfNaiveEnsembleModel\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9RegressionEnsembleModel\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9 \ud83d\udfe9\ud83d\udfe9Community & ContactAnyone is welcome to join ourGitter roomto ask questions, make proposals,\ndiscuss use-cases, and more. If you spot a bug or have suggestions, GitHub issues are also welcome.If what you want to tell us is not suitable for Gitter or Github,\nfeel free to send us an email atdarts@unit8.cofor\ndarts related matters orinfo@unit8.cofor any other\ninquiries.ContributeThe development is ongoing, and we welcome suggestions, pull requests and issues on GitHub.\nAll contributors will be acknowledged on thechange log page.Before working on a contribution (a new feature or a fix),check our contribution guidelines.CitationIf you are using Darts in your scientific work, we would appreciate citations to the following JMLR paper.Darts: User-Friendly Modern Machine Learning for Time SeriesBibtex entry:@article{JMLR:v23:21-1177,\n author = {Julien Herzen and Francesco L\u00c3\u00a4ssig and Samuele Giuliano Piazzetta and Thomas Neuer and L\u00c3\u00a9o Tafti and Guillaume Raille and Tomas Van Pottelbergh and Marek Pasieka and Andrzej Skrodzki and Nicolas Huguenin and Maxime Dumonal and Jan Ko\u00c5\u203acisz and Dennis Bader and Fr\u00c3\u00a9d\u00c3\u00a9rick Gusset and Mounir Benheddi and Camila Williamson and Michal Kosinski and Matej Petrik and Ga\u00c3\u00abl Grosch},\n title = {Darts: User-Friendly Modern Machine Learning for Time Series},\n journal = {Journal of Machine Learning Research},\n year = {2022},\n volume = {23},\n number = {124},\n pages = {1-6},\n url = {http://jmlr.org/papers/v23/21-1177.html}\n}"} +{"package": "u8timeseries", "pacakge-description": "No description available on PyPI."} +{"package": "ua", "pacakge-description": "uaUser-Agent parsing and creationInstallationpip install uaUsage>>>importuaParsing>>>user_agent=ua.parse('Mozilla/5.0 (X11; Linux x86_64; rv:88.0) Gecko/20100101 Firefox/88.0')>>>>>>user_agentUserAgent(products=[Product(name='Mozilla',version='5.0',comments=['X11','Linux x86_64','rv:88.0']),Product(name='Gecko',version='20100101',comments=[]),Product(name='Firefox',version='88.0',comments=[])])>>>>>>str(user_agent)'Mozilla/5.0 (X11; Linux x86_64; rv:88.0) Gecko/20100101 Firefox/88.0'Creation>>>user_agent=ua.UserAgent(products=[ua.Product(name='SomeProduct',version='1.0',comments=['SomeComment'])])>>>>>>str(user_agent)'SomeProduct/1.0 (SomeComment)'ReferencesUser agent - WikipediaUser-Agent - HTTP | MDNRFC 7231 - Hypertext Transfer Protocol (HTTP/1.1): Semantics and Content"} +{"package": "ua2.ajax", "pacakge-description": "Django Ajax wrapper"} +{"package": "ua2.carbon", "pacakge-description": "Tools for serving statistic data to carbon/graphite server.To install package into django need:add \u2018ua2.carbon.middleware.MeasureMiddleware\u2019 at the top of MIDDLEWARE_CLASSES listinto settings.py add next lines:fromua2.carbon.loadersimportdjango_loaderdjango_loader()Usage examplesMeasure function execution timefromua2importcarbon@carbon.measure('myapp')deftest():print\"Hello World!\"Measure arbitrary block execution timefromua2importcarbondeftest():withcarbon.Profiler('myapp'):foriinrange(1,100):print\"Hello World!\"Send raw value to carbonfromua2importcarbondeftest():foriinrange(1,100):print\"Hello World!\"carbon.send('metric.hello.world',1)"} +{"package": "ua2.celery", "pacakge-description": "Extended handlers and helpers worh with celery"} +{"package": "ua2.djfab", "pacakge-description": "Generic fabric commands for all django projects"} +{"package": "ua2.fabdep", "pacakge-description": "Fabric management for external source code repositories."} +{"package": "ua2.forms", "pacakge-description": "ua.forms library wrap Django forms with custorm template-way render\nsolution."} +{"package": "ua2.jsondoc", "pacakge-description": "Classes for store ORM reference model inside json fields"} +{"package": "ua2.mongolog", "pacakge-description": "Feed logging into MongoDB"} +{"package": "ua2nx", "pacakge-description": "ua2nx is a module that converts UrbanAccess graph into NetworkX MultiDiGraph."} +{"package": "ua2.otl", "pacakge-description": "Django tool for create ont time linksInstallationFor integrate with Django need to addua2.otlto the list of installed app:INSTALLED_APPS+=('ua2.otl')and put into a root urls.py next line:url(r'^l/',include('ua2.otl.urls'))Be warning: include urls.py only compatibil with Django >= 1.8.\nFor django before 1.8 need use following solution:fromua2.otl.viewsimportotl_viewurlpatterns=urlpatterns(.....url(r'^l/(?P\\w+)/$',otl_view,name='one-time-link'),)UsingYou can useOneTimeLinkwith several scenario:redirect to view with django backresolve (with support callback)redirect to direct URL (with support callback)using view to redner responseRedirectsThere are two way to pass resulted link to OneTimeLink object:pass url resolve point with kwargspass rendered linkfromua2.otlimportOneTimeLinklink=OneTimeLink.create(resolve_name='django-url-name',resolve_kwargs={'value':1})link.save(expire=3600)Example with callback and authorization:fromua2.otlimportOntTimeLinkdefauth_callback(request,user_email):user=get_object_or_404(User,email=user_email)login(request,user)@login_requireddefpassword_restore(request):....defsend_restore_passwortd(request):link=OneTimeLink.create(resolve_name='url-password-reset')link['user_email']=request.POST.get('user_email')link.save(callback=auth_callback,expire=3600,count=1)returnHttpResponse(\"http://127.0.0.1:8000%s\"%link.url)"} +{"package": "ua2.patch", "pacakge-description": "What this package does?=======================This package provides an easy half-manual and controlled way to define and run SQL, Python and Shell script for your project.Supported backends==================- MySQL- PostgreSQLSupported Django versions=========================- Django >= 1.8Supported OS============- Linux- Ubuntu 14.04- Ubuntu 16.04Why to use this package if there is django-migrations and South?================================================================The differencies between Django migrations and ua2.patch are in purpose:- django-migrations primary purpose is to propogate changes you make to your models into your database- ua2.patch purpose is to create & maintain patches, written by big development teamThis package could be used in parallel to existing django-migrations module, or it can completely replace the job done by migrations. You, as developer, decide where you should use one or another.We are not going to replicate all migration features, the core idea of this package is to provide easy to use tool to create and maintain (SQL|Python|Shell) patches for big team of people, working in parallel on different branches.What are benefits of using ua2.patch ?======================================Simple way to automate running custom patches---------------------------------------------It is very easy to create patches for your data.Installation============Install package from pip------------------------First, install package via pip:``` examplepip install ua2.patch```And then, add it to your Django INSTALLEDAPPS:``` exampleINSTALLED_APPS = [...'ua2.patch',]```Usage examples==============Create SQL patch----------------``` example./manage.py patch nextFile .../patches/00002-johnsmith-014.sql has been createdsize: 0```Now, you can open & edit the file. *Note*: until file size is zero, it would not be applied, but will be treated as *reserved* patch for future use.Create Python patch-------------------``` example./manage.py patch next -e pyFile .../patches/00002-johnsmith-022.py has been createdsize: 0```*Note:* patch body should have function main() which returns True. If you don't return True, the system will run the patch and exit on this place, preventing other scripts to run.Create Shell patch------------------``` example./manage.py patch next -e shFile .../patches/00003-johnsmith-022.sh has been createdsize: 0```"} +{"package": "ua2.redis", "pacakge-description": "Library to make simples integration RedisDb with DjangoDatabase connect string example in django settings.py file:REDISDB={'default':{'HOST':'127.0.0.1','PORT':6379,'DB':0,'PASSWORD':'secret string'}}Example access to redis database:fromua2.redisimportRedisConnwithRedisConn()asredis:redis.set('test','value')RedisConn accept argumentdb_aliasthat point to required database\nfrom REDISDB parameters:fromua2.redisimportRedisConnwithRedisConn('db2')asredis:redis.set('test','value')"} +{"package": "ua2.table3", "pacakge-description": "UNKNOWN"} +{"package": "ua2.table3a", "pacakge-description": "UNKNOWN"} +{"package": "ua-alarm", "pacakge-description": "UA_ALARM \ud83d\udea8Elegant, modern and asynchronous UkraineAlarm API framework in PythonAboutUK\u0406\u043c\u043f\u043b\u0435\u043c\u0435\u043d\u0442\u0443\u0454api.ukrainealarm.com, \u044f\u043a\u0438\u0439 \u043f\u043e\u0432\u0435\u0440\u0442\u0430\u0454 \u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u044e \u043f\u0440\u043e\n\u043f\u043e\u0432\u0456\u0442\u0440\u044f\u043d\u0456 \u0442\u0440\u0438\u0432\u043e\u0433\u0438 \u0432 \u0423\u043a\u0440\u0430\u0457\u043d\u0456.\u041f\u043e\u0442\u0440\u0435\u0431\u0443\u0454 API-\u043a\u043b\u044e\u0447. \u041f\u043e\u0434\u0430\u0432\u0430\u0439\u0442\u0435 \u0437\u0430\u043f\u0438\u0442 \u043d\u0430 \u043e\u0442\u0440\u0438\u043c\u0430\u043d\u043d\u044f \u0447\u0435\u0440\u0435\u0437 \u0444\u043e\u0440\u043c\u0443 \u043d\u0430api.ukrainealarm.com.\u041f\u0440\u0438\u043a\u043b\u0430\u0434 \u0440\u043e\u0431\u043e\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u0457 alert_loop \u0443\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u043e\u044e \u043c\u043e\u0432\u043e\u044e, \u0437\u0430 \u0434\u0435\u0444\u043e\u043b\u0442\u043e\u043c \u0443\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0430ENImplementsapi.ukrainealarm.comAPI that returns info about Ukraine\nair raid alarms.Request API key via form onapi.ukrainealarm.com.An example of the alert_loop function in English, Ukrainian by defaultAbout text was copied fromgithub.com/PaulAnnekov/ukrainealarmInstallingpippipinstallua_alarmpoetrypoetryaddua_alarmExamplefromua_alarmimportClientasUkraineAlertApiClientimportosfromasyncioimportrun# Clear the console screenos.system('cls'ifos.name=='nt'else'clear')api_token=\"YOUR_API_KEY\"client=UkraineAlertApiClient(api_token)# Run the main functionif__name__=='__main__':try:run(client.get_alerts())exceptKeyboardInterrupt:exit()"} +{"package": "ua-api-utils", "pacakge-description": "https://github.com/urbanairship/ua-api-utils#readmeCurrently just provides a simpleuacommand line tool with a single sub-command:ua get-tokens $APP_KEY $UA_SECRETYou can also set your secret as an environment variable:UA_SECRET=... ua get-tokens $APP_KEYAnd control the filename:UA_SECRET=... ua get-tokens $APP_KEY -o some-new-file.json\nUA_SECRET=... ua get-tokens $APP_KEY -o - | gzip > yet-another-file.json.gzInstallingIn a virtualenv in safest (if you have virtualenv installed):virtualenv ua-api-utils\ncd ua-api-utils\n. bin/activate\npip install ua-api-utilsOr in your$HOMEdirectory if you have your user-site in your$PATH:pip install --user ua-api-utilsAnd of course, there\u2019s always sudo to install it globally:sudo pip install ua-api-utilsNo pip?sudo easy_install ua-api-utils"} +{"package": "ua-banktools", "pacakge-description": "ua_banktoolsA collection of Python tools and APIs for interacting with Ukrainian banks"} +{"package": "uabnlputils", "pacakge-description": "uabnlputils"} +{"package": "ua-box-api", "pacakge-description": "UA-EDS-APIProvides easy interface for making REST requests to University of Arizona Box file storage.MotivationTo make a python API that could generically interact with the REST architecture of Box.Code Examplefromua_box_apiimportua_box_apibox_api=ua_eds_api.BoxApi(config)items=box_api.get_all_items(10)Installationpip install --user ua-box-apiCreditsRyanJohannesBlandEtienneThompsonLicenseMIT"} +{"package": "ua-clarity-api", "pacakge-description": "UA-Clarity-APIProvides a simple REST implementation for use with Clarity endpoints.MotivationWas designed to implement a simple way to interact with Clarity REST architecture.FeaturesGet will do a batch get if that end point exists, otherwise it will return a response similar to what a batch get returns.Caller can add queries to get using a keyword.Caches every get to eliminate excessive get calls.All REST calls will throw an exception if they failed.Code Examplefromua_clarity_apiimportua_clarity_apiapi=ua_clarity_api.ClarityApi(host,username,password)uris_files=api.download_files(\"some file uri\")data=api.get(\"some endpoint\")Installationpipinstallua-clarity-apiTestspipinstall--updatenosecd./repocd./tests\nnoseteststest_ua_clarity_api.pyHow to UseYou'll need to instantiate a ClarityApi object with a correct host, and the username/password to access that host's endpoints.Get can retrieve resources from endpoints and can utilize queries with the \"parameters\" keyword.Put and Post can update or create new resources given the appropriate endpoint and a well-formed payload.Delete can remove a resource from an endpoint.Download_files will create temporary files from a list of file uris and returns them as a dictionary mapping of uri: tempfile.Creditssterns1raflopjrRyanJohannesBlandLicenseMIT"} +{"package": "ua-clarity-tools", "pacakge-description": "UA-Lims-ToolsProvides 2 sets of tools for use with clarity and it's endpoints: ClarityTools\nand StepTools.MotivationTo create a set of tools to assist in script writing for Clarity.FeaturesUse ClarityTools as a means of interfacing with Clarity and it's endpoints.get_samples will get all samples from a list of uris passed in.get_arts_from_samples will get all artifact uris for the list of uris passed.get_udfs will find all the udfs that should be attached to target.set_reagent_label will set the reagent_label for all artifacts passed.step_router will route a list of artifact_uris to a specified step.Use StepTools as a way of interacting with a Clarity step.*get_artifacts will return all artifacts from the step.get_process_data will retrieve the process data for the current step.get_artifact_map creates a mapping of input artifacts to output artifacts.set_artifact_udf sets the udfs of all analytes in the step.get_artifacts_previous_step will map the current steps artifact uris to an ancestor artifact from the step passed to it.get_assays will find the assays within the current protocol.## Code Examplepython\nfrom ua_lims_tools import ua_lims_tools\nclarity_api = ua_lims_tools.ClarityApi()\nstep_api = ua_lims_tools.StepTools()Installationbash\npip install ua-lims-toolsTestsbash\npip install --update nose\ncd ./repo\ncd ./tests\nnosetests test_lims_tools.pyHow to UseExamples of syntax for each methodpython\nclarity_api = ua_lims_tools.ClarityApi()\nsamples = clarity_api.get_samples(uris)get_samples gets the samples from the passed in uris.Arguments: uris is a list of sample endpoints to get.Returns: a list of Sample dataclass objects with gotten sample's data.Creditssterns1raflopjrRyanJohannesBlandLicenseMIT"} +{"package": "uaconnect", "pacakge-description": "Aboutuaconnectis the official Python library for using theAirship Real-Time Data StreamingAPI (formerly known as Connect).QuestionsThe best place to ask questions or report a problem is our support site:http://support.airship.com/RequirementsTested on Python 3.6, 3.7, 3.8, and 3.9.For tests,uaconnectalso needsMock.Running TestsTo run tests, run:$ python -m unittest discoverUsageSee theReal-Time Data Streaming Getting Started Guide, as\nwell as theReal-Time Data Streaming API docsfor more details.RTDS Event ConsumerTo consume standard events from the RTDS API, instantiate aEventConsumerobject\nwith the application key, access token, and an offset recorder. You can then open the\nconnection, and start reading events.See more about the RTDS Event Streamin our documentation here.>>> import uaconnect\n>>> consumer = uaconnect.EventConsumer(\n... app_key='application_key',\n... access_token='access_token',\n... recorder=uaconnect.FileRecorder('.offset'))\n>>> consumer.connect()\n>>> for event in consumer.read():\n... if event is None:\n... continue\n>>> print(\"Got event: {}\".format(event))\n>>> consumer.ack(event)RTDS Compliance Event ConsumerTo consume compliance events from the RTDS API, instantiate aComplianceConsumerobject\nwith the application key, master secret and an offset recorder. You can then open the\nconnection, and start reading events.See more about the RTDS Compliance Event Streamin the documentation here.>>> import uaconnect\n>>> consumer = uaconnect.EventConsumer(\n... app_key='application_key',\n... master_secret='master_secret',\n... recorder=uaconnect.FileRecorder('.offset'))\n>>> consumer.connect()\n>>> for event in consumer.read():\n... if event is None:\n... continue\n>>> print(\"Got event: {}\".format(event))\n>>> consumer.ack(event)Alternate Data Center SupportWhen instantiating aEventConsumerorComplianceConsumeryou can pass the optionalurlargument to explicitly specify the data center your project is located in. Possible\nvalues are \u201cUS\u201d, \u201cEU\u201d, or an arbitrary base url in the form ofhttp://domain.xyz/. The\nlibrary will build the URL path properly from there. If nourlis specified, \u201cUS\u201d is used.>>> import uaconnect\n>>> consumer = uaconnect.EventConsumer(\n... app_key='application_key',\n... master_secret='master_secret',\n... url='EU',\n... recorder=uaconnect.FileRecorder('.offset'))Offset recordersOffset recorders inherit from the abstract base classuaconnect.Recorder,\nimplementingread_offsetandwrite_offsetmethods. One recorder is\nincluded in the library,FileRecorder, which stores the offset on disk. In\ntheuaconnect.ext.redisrecorderpackage there is an example implementation\nof using an Redis instance to store the offset.ackcalls should be placed depending on whether in a failure scenario your\napp wishes to possibly replay an already handled event, or risk dropping one.\nFor the latter, callackas soon as the event is read; for the former, callackonly after the event has been fully handled.Advanced options when connectingAirship Real-Time Data Streaming supports a variety ofoptions when connectingto make sure that you\u2019re only consuming the data that you want.uaconnectmakes it easy to use these connection parameters and filters.Specifying offsetsOne of the advantages of Airship Real-Time Data Streaming is that you can resume from a\nspecific place in the RTDS stream. This is done by specifying theoffsetthat\u2019s associated with the event. Whileuaconnectautomatically tracks\noffsets for you withuaconnect.FileRecorder, you can also explicitly set an\noffset.>>> import uaconnect\n>>> recorder = uaconnect.FileRecorder(\".offset\") # or wherever you would like the file to exist\n>>> recorder.write_offset(\"8865499359\") # a randomly chosen offset\n>>> recorder.read_offset()\n'8865499359'An alternative here is to just write the offset explicitly into the file, or\nwhateverRecordersubclass you\u2019re using to track offsets.$ cat .offset\n886549935Now, the next time you connect, it will pick up from that last offset.If you\u2019d like to manually set the offset for a connection to a known value\ninstead of the recorder\u2019s offset, setresume_offsetlike so:>>> consumer.connect(resume_offset='123456789')Using filtersFilters are a powerful way of filtering what specific information you\u2019d like to\nsee from the RTDS stream. You can filter by event type, device type, latency\non an event, or even specific devices or notifications.For a complete list of filters, and their descriptions, check outthe\ndocumentation.Here\u2019s a brief example on how to use filters withuaconnect:>>> import uaconnect\n>>> consumer = uaconnect.EventConsumer(\n... app_key='application_key',\n... access_token='access_token',\n... recorder=uaconnect.FileRecorder('.offset')\n... )\n>>> f = uaconnect.Filter()\n>>> f.types(\"PUSH_BODY\", \"SEND\") # only receive PUSH_BODY and SEND events.\n>>> consumer.add_filter(f)\n>>> consumer.connect()"} +{"package": "uacs", "pacakge-description": "Ultimate_Auto_Check_ServicesThis script allows to check services under Linux and sends mails in case of crash of one of them.#--------------* UNDER DEVELOPMENT *--------------#"} +{"package": "uacs1", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "uactor", "pacakge-description": "uActor: Process Actor ModeluActor is a process actor library for Python with a simple yet powerful API,\nimplementing theactor modelatopmultiprocessing,\nwith no dependencies other than thePython Standard Library.Simple: Minimalistic API, no boilerplate required.Flexible: Trivial to integrate, meant to be extended.Concurrent: Share workload over CPU cores, and across the network.Documentation:uactor.readthedocs.ioUsage:importosimportuactorclassActor(uactor.Actor):defhello(self):returnf'Hello from subprocess{os.getpid()}!'print(f'Hello from process{os.getpid()}!')# Hello from process 22682!print(Actor().hello())# Hello from subprocess 22683!QuickstartInstallationYou can install it usingpip.pipinstalluactorOr alternatively by including our singleuactor.pyfile into your project.Your first actorWith uActor, actors are defined as classes inheriting fromuactor.Actor,\nwith some special attributes we'll cover later.importuactorclassMyActor(uactor.Actor):defmy_method(self):returnTrueDuring instantiation, every actor is initialized on its own dedicated\nprocess, returning a proxy.my_actor_proxy=MyActor()my_actor_proxy.my_method()Once you're done with your actor, it is always a good idea to finalize its\nprocess withuactor.Actor.shutdownmethod.my_actor_proxy.shutdown()Alternatively,uactor.Actorinstances can be used as context managers, so\nthe actor process will be finalized once we're done with it.withMyActor()asmy_actor_proxy:my_actor_proxy.my_method()Actor processes will be also finished when every proxy gets garbage-collected\non its parent process.Returning result proxiesActor methods can return proxies instead of actual objects, keeping them\nsound and safe on our actor process.To specify which proxy will be returned from an specific method, we can add\nboth method name and proxy typeid touactor.Actor._method_to_typeid_special\nclass attribute.importuactorclassMyActor(uactor.Actor):_method_to_typeid_={'my_method':'dict'}def__init__(self):self.my_data={}defmy_method(self):returnself.my_dataOr, alternatively, we can explicitly create a proxy for our object, usinguactor.proxyutility function.importuactorclassMyActor(uactor.Actor):def__init__(self):self.my_data={}defmy_method(self):returnuactor.proxy(self.my_data,'dict')There is a limitation with proxies, applying two different proxies to\nthe same object will raise an exception, this is likely to change in\nthe future.Becoming asynchronous (and concurrent)Actor methods are fully synchronous by default, which is usually not very\nuseful on distributed software, the following example will show you how\nto return asynchronous results from the actor.importtimeimportmultiprocessing.poolimportuactorclassMyActor(uactor.Actor):_method_to_typeid_={'my_method':'AsyncResult'}def__init__(self):self.threadpool=multiprocessing.pool.ThreadPool()defmy_method(self):returnself.threadpool.apply_async(time.sleep,[10])# wait 10swithMyActor()asmy_actor:# will return immediatelyresult=my_actor.my_method()# will take 10 secondsresult.wait()Based on this, we can now run code concurrently running on the same actor.withMyActor()asmy_actor:# these will return immediatelyresult_a=my_actor.my_method()result_b=my_actor.my_method()# these all will take 10 seconds in totalresult_a.wait()result_b.wait()And now we can to parallelize workloads across different actor processes.actor_a=MyActor()actor_b=MyActor()withactor_a,actor_b:# these both will return immediatelyresult_a=actor_a.my_method()result_b=actor_b.my_method()result_a.wait()# this will take ~10s to completeresult_b.wait()# this will be immediate (we already waited 10s)Next stepsYou can dive into ourdocumentationor\ntake a look at our code examples.The basics:Actor inheritance.Actor lifetime.Result proxies.Method callbacks.Advanced patterns:Sticky processes.Actor pool.Networking.uActor designWith the constant rise in CPU core count, highly threaded python applications\nare still pretty rare (except for distributed processing frameworks likecelery), this is due a few reasons:threadingcannot use multiple cores becausePython Global Interpreter Lockforces the interpreter to run on a\nsingle core.multiprocessing, meant to overcome threading limitations\nby using processes, exposes a pretty convoluted API as processes\nare way more complex, exposing many quirks and limitations.uActor allows implementing distributed software as easy as just declaring\nand instancing classes, following theactor model, by thinly\nwrapping the standardSyncManagerto circumvent most omultiprocessingcomplexity and some of its flaws.uActor API is designed to be both minimalistic and intuitive, but still few\ncompromises had to be taken to leverage onSyncManageras much as possible, as it is both somewhat actively maintained and\nalready available as part of thePython Standard Library.ActorsJust like the actor programming model revolves around the actor entity,\nuActor features theuactor.Actorbase class.When an actor class is declared, by inheriting fromuactor.Actor, itsActor.proxy_classgets also inherited and updated to mirror the actor\ninterface, either following the explicit list of properties defined atActor._exposed_or implicitly by actor public methods.Actor.manager_classis also inherited registering actor specific proxies\ndefined inActor._proxies_mapping (key used as a typeid) along with'actor'and'auto'special proxies.Keep in mind the defaultActor.manager_class,uactor.ActorManager, already\nincludes every proxy fromSyncManager(including the internalAsyncResultandIterator) which are all available to the actor and ready\nuse (you can callActor.manager_class.typeids()to list them all).As a reference, these are all the availableuactor.Actorconfiguration\nclass attributes:manager_class: manager base class (defaults to parent's one, up touactor.ActorManager).proxy_class: actor proxy class (defaults to parent's one, up touactor.ActorProxy)._options_: option mapping will be passed tomanager_class._exposed_: list of explicitly exposed methods will be made available byproxy_class, ifNoneor undefined then all public methods will be\nexposed._proxies_: mapping (typeid, proxy class) of additional proxies will be\nregistered in themanager_classand, thus, will be available to\nbe returned by the actor._method_to_typeid_: mapping (method name, typeid) defining which method\nreturn values will be wrapped into proxies when invoked fromproxy_class.When anuactor.Actorclass is instantiated, a new process is spawned and auactor.Actor.proxy_classinstance is returned (as the real actor will be\nkept safe in said process), transparently exposing a message-based interface.importosimportuactorclassActor(uactor.Actor):defgetpid(self):returnos.getpid()actor=Actor()print('My process id is',os.getpid())# My process id is 153333print('Actor process id is ',actor.getpid())# Actor process id is 153344ProxiesProxies are objects communicating with the actor process, exposing\na similar interface, in the most transparent way possible.It is implied most calls made to a proxy will result on inter-process\ncommunication and serialization overhead.To alleviate the serialization cost, actor methods can also return proxies,\nso the real data is kept well inside the actor process boundaries, which can\nbe efficiently shared between processes with very little serialization cost.Actors can define which proxy will be used to expose the result of certain\nmethods by defining that in theirActor._method_to_typeid_property.importuactorclassActor(uactor.Actor):_method_to_typeid_={'get_mapping':'dict'}...defget_data(self):returnself.my_data_dictOr, alternatively, using theuactor.proxyfunction, receiving both value\nand a proxytypeid(as inSyncManagersemantics).importuactorclassActor(uactor.Actor):...defget_data(self):returnuactor.proxy(self.my_data_dict,'dict')Keep in minduactor.proxycan only be called from inside the actor process\n(it will raiseuactor.ProxyErrorotherwise), as proxies can only be created\nfrom there.You can define your own proxy classes (followingBaseProxysemantics), and they will be made available in an actor by including it on\ntheActor._proxies_mapping (along its typeid).importuactorclassMyDataProxy(uactor.BaseProxy):defmy_method(self):returnself._callmethod('my_method')my_other_method=uactor.ProxyMethod('my_other_method')classActor(uactor.Actor):_proxies_={'MyDataProxy':MyDataProxy}_method_to_typeid_={'get_data':'MyDataProxy'}...In addition to all proxies imported from bothSyncManager(including internal ones asIteratorandAsyncResult) andActor._proxies_, we always register these ones:actor: proxy to the current process actor.auto: dynamic proxy based based on the wrapped object.You can list all available proxies (which can vary between python versions)\nby callingActorManager.typeids():importuactorprint(uactor.Actor.manager_class.typeids())# ('Queue', 'JoinableQueue', 'Event', ..., 'auto', 'actor')print(uactor.ActorManager.typeids())# ('Queue', 'JoinableQueue', 'Event', ..., 'auto')ContributinguActor is deliberately very small in scope, while still aiming to be easily\nextended, so extra functionality might be implemented via external means.If you find any bug or a possible improvement to existing functionality it\nwill likely be accepted so feel free to contribute.If, in the other hand, you feel a feature is missing, you can either create\nanother library using uActor as dependency or fork this project.LicenseCopyright (c) 2020, Felipe A Hernandez.MIT License (seeLICENSE)."} +{"package": "ua-currency-exporter", "pacakge-description": "\\n# ua-currency-exporter"} +{"package": "uadatasdk", "pacakge-description": "\u8c03\u7528\u65b9\u6cd5\u5b89\u88c5\u65b9\u6cd5# \u9996\u6b21\u5b89\u88c5pipinstalluadatasdk\u4f7f\u7528\u65b9\u6cd5importuadatasdk# \u767b\u5f55\u8ba4\u8bc1uadatasdk.auth(username,password)# \u83b7\u53d6\u6570\u636euadatasdk.get_price(\"AG2301.XSHE\",start_date=\"2022-11-01\",end_date=\"2023-01-01\")#\u83b7\u53d6\u6240\u6709\u4ea4\u6613\u65e5\nuadatasdk.get_all_trade_days()\n\n#\u83b7\u53d6\u6307\u5b9a\u65e5\u671f\u8303\u56f4\u5185\u7684\u6240\u6709\u4ea4\u6613\u65e5\n#statr_date\u548ccount\u4e0d\u80fd\u90fd\u4e3a\u7a7a,\u4e8c\u9009\u4e00\nuadatasdk.get_trade_days(start_date=None, end_date=None, count=None)\n\n#\u83b7\u53d6\u67d0\u671f\u8d27\u54c1\u79cd\u5728\u7b56\u7565\u5f53\u524d\u65e5\u671f\u7684\u53ef\u4ea4\u6613\u5408\u7ea6\u6807\u7684\u5217\u8868\nuadatasdk.get_future_contracts(underlying_symbol, date=None)\n\n#\u83b7\u53d6\u4e3b\u529b\u5408\u7ea6\u5bf9\u5e94\u7684\u6807\u7684\nuadatasdk.get_dominant_future(underlying_symbol, date=None)\n\n#\u8865\u5168\u5408\u7ea6\nuadatasdk.normalize_code(code)\n\n#\u83b7\u53d6\u5408\u7ea6\u7684futures_sett_price\u548c open_interest\nuadatasdk.get_extras(fields, security, start_date=None, end_date=None, count=None)\n\n#\u83b7\u53d6\u5408\u7ea6\u7684\u8d77\u59cb\u7ed3\u675f\u65f6\u95f4,name\u548cdisplay_name\nuadatasdk.get_security_info(code, date=None)###\u4f8b\u5b50auth('name','password')\ndata = uadatasdk.get_all_securities('2023-01-21')\n\ndata = uadatasdk.get_price(['AG2301.XSGE','AG2302.XSGE'],count=5,end_date='2023-01-31',fields=[\"open\",\"close\"])\n\ndata = uadatasdk.get_all_trade_days()\n\n\ndata = uadatasdk.get_trade_days(count='5',end_date='2022-12-30')\n\n\ndata =uadatasdk.get_future_contracts('ag',)\n\n\ndata = uadatasdk.get_dominant_future('ag','2022-12-21')\n\n\ndata = uadatasdk.normalize_code('a2303')\n\n\ndata = uadatasdk.get_extras('futures_sett_price',['AG2301.XSGE','AG2302.XSGE'],count=5,end_date='2022-12-30')\n\ndata = uadatasdk.get_security_info('AG2301.XSGE')"} +{"package": "ua-datasets", "pacakge-description": "ua_datasetsUA-datasetsis a collection of Ukrainian language datasets. Our aim is to build a benchmark for research related to\nnatural language processing in Ukrainian.This library is provided by FIdo.ai (machine learning research division of the non-profit student's organizationFIdo, National University of Kyiv-Mohyla Academy) for research purposes.InstallationThe library can be installed from PyPi in your virtual environment (e.g. venv, conda env)pipinstallua_datasetsLatest Updates05.07.22 - Added HuggingFace API for Q&A (UA-SQuAD) and Text Classification (UA-News) datasetsAvailable DatasetsQuestion Answering (UA-SQuAD)Text Classification (UA-News)Token Classification (Mova Institute Part of Speech)ContributionIn case you are willing to contribute (update any part of the library, add your dataset) do not hesitate to connect throughGitHub Issue. Thanks in advance for your contribution!\nLet's make the Ukrainian language even greater!Citation@software{ua_datasets_2021,author={Ivanyuk-Skulskiy, Bogdan and Zaliznyi, Anton and Reshetar, Oleksand and Protsyk, Oleksiy and Romanchuk, Bohdan and Shpihanovych, Vladyslav},month=oct,title={ua_datasets: a collection of Ukrainian language datasets},url={https://github.com/fido-ai/ua-datasets},version={0.0.1},year={2021}}"} +{"package": "uaddress", "pacakge-description": "\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\u0420\u0430\u0437\u0431\u043e\u0440\u043a\u0430 \u0430\u0434\u0440\u0435\u0441\u0430 \u043d\u0430 \u0442\u0438\u043f\u044b. \u0410\u0434\u0430\u043f\u0442\u0430\u0446\u0438\u044f \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438usaddress\u043f\u043e\u0434 \u0443\u043a\u0440\u0430\u0438\u043d\u0441\u043a\u0438\u0435 \u0430\u0434\u0440\u0435\u0441\u0430Read this in other language:English,\u0420\u0443\u0441\u0441\u043a\u0438\u0439,\u0423\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0438\u0439\u0422\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u0438\u044fpython3jackmartin.parserator\u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430pip3installuaddress\u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u043epython3setup.pyinstall--user\u041e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u043c\u043e\u0434\u0435\u043b\u0438parseratortraintraining/data.xmluaddress\u041a\u043e\u0433\u0434\u0430 \u0434\u0440\u0443\u0433\u043e\u0435 \u0440\u0430\u0441\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u043c\u043e\u0434\u0435\u043b\u0438parseratortraintraining/data.xmluaddress--modelfileanotherpath/uaddr.crfsuite\u0422\u0435\u0441\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043c\u043e\u0434\u0435\u043b\u0438parseratorlabeltraining/raw.csvtraining/data.xmluaddress\u041a\u043e\u0433\u0434\u0430 \u0434\u0440\u0443\u0433\u043e\u0435 \u0440\u0430\u0441\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u043c\u043e\u0434\u0435\u043b\u0438parseratorlabeltrainig/raw.csvtraining/data.xmluaddress--modelfileanotherpath/uaddr.crfsuite\u0421\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0430\u0424\u0430\u0439\u043b\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435training/data.xml\u041d\u0430\u0431\u043e\u0440 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0438training/raw.csv\u0421\u043f\u0438\u0441\u043e\u043a \u0430\u0434\u0440\u0435\u0441\u043e\u0432 \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0438\u043b\u0438 \u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438uaddress/uaddr.crfsuiteNLP \u043c\u043e\u0434\u0435\u043b\u044c\u041f\u0440\u0438\u043c\u0435\u0440\u044b\u041f\u0440\u0438\u043c\u0435\u0440 \u0441\u043a\u0440\u0438\u043f\u0442\u0430python3example.py\u0422\u0438\u043f\u044b\u041d\u0430\u0437\u0432\u0430\u043d\u0438\u0435\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435Country\u0421\u0442\u0440\u0430\u043d\u0430RegionType\u0422\u0438\u043f \u043e\u0431\u043b\u0430\u0441\u0442\u0438Region\u041e\u0431\u043b\u0430\u0441\u0442\u044cCountyType\u0422\u0438\u043f \u0440\u0430\u0439\u043e\u043d\u0430County\u0420\u0430\u0439\u043e\u043dSubLocalityType\u0422\u0438\u043f \u043f\u043e\u0434\u0440\u0430\u0439\u043e\u043d\u0430SubLocality\u041f\u043e\u0434\u0440\u0430\u0439\u043e\u043dLocalityType\u0422\u0438\u043f \u043d\u0430\u0441\u0435\u043b\u0451\u043d\u043d\u043e\u0433\u043e \u043f\u0443\u043d\u043a\u0442\u0430Locality\u041d\u0430\u0441\u0435\u043b\u0451\u043d\u043d\u044b\u0439 \u043f\u0443\u043d\u043a\u0442StreetType\u0422\u0438\u043f \u0443\u043b\u0438\u0446\u044bStreet\u0423\u043b\u0438\u0446\u0430HousingType\u0422\u0438\u043f \u043a\u043e\u0440\u043f\u0443\u0441\u0430Housing\u041a\u043e\u0440\u043f\u0443\u0441HostelType\u0422\u0438\u043f \u043e\u0431\u0449\u0435\u0436\u0438\u0442\u0438\u044fHostel\u041e\u0431\u0449\u0435\u0436\u0438\u0442\u0438\u0435HouseNumberType\u0422\u0438\u043f \u043d\u043e\u043c\u0435\u0440\u0430 \u0434\u043e\u043c\u0430HouseNumber\u041d\u043e\u043c\u0435\u0440 \u0434\u043e\u043c\u0430HouseNumberAdditionally\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0439 \u043d\u043e\u043c\u0435\u0440 \u0434\u043e\u043c\u0430SectionType\u0422\u0438\u043f \u0441\u0435\u043a\u0446\u0438\u0438Section\u0421\u0435\u043a\u0446\u0438\u044fApartmentType\u0422\u0438\u043f \u043a\u0432\u0430\u0440\u0442\u0438\u0440\u044bApartment\u041a\u0432\u0430\u0440\u0442\u0438\u0440\u0430RoomType\u0422\u0438\u043f \u043a\u043e\u043c\u043d\u0430\u0442\u044bRoom\u041a\u043e\u043c\u043d\u0430\u0442\u0430Sector\u0421\u0435\u043a\u0442\u043e\u0440EntranceType\u0422\u0438\u043f \u043f\u043e\u0434\u044a\u0435\u0437\u0434\u0430Entrance\u041d\u043e\u043c\u0435\u0440 \u043f\u043e\u0434\u044a\u0435\u0437\u0434\u0430FloorType\u0422\u0438\u043f \u044d\u0442\u0430\u0436\u0430Floor\u042d\u0442\u0430\u0436PostCode\u0418\u043d\u0434\u0435\u043a\u0441Manually\u041d\u0430\u0431\u043e\u0440 \u0442\u0438\u043f\u043e\u0432 \u0434\u043b\u044f \u0434\u0430\u043b\u044c\u043d\u0435\u0439\u0448\u0435\u0439 \u0440\u0430\u0437\u0431\u043e\u0440\u043a\u0438 \u0430\u0434\u0440\u0435\u0441\u0430NotAddress\u041d\u0435 \u0430\u0434\u0440\u0435\u0441Comment\u041a\u043e\u043c\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439AdditionalData\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0434\u0430\u043d\u043d\u044b\u0435"} +{"package": "uaddressformat", "pacakge-description": "UAddressFormat\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\u0418\u0441\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0442\u0438\u043f\u043e\u0432 \u0430\u0434\u0440\u0435\u0441\u0430 \u043d\u0430 \u044d\u0442\u0430\u043b\u043e\u043d\u043d\u044b\u0435. \u041c\u043e\u0434\u0443\u043b\u044c \u0434\u043b\u044f \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438uaddress.Read this in other language:English,\u0420\u0443\u0441\u0441\u043a\u0438\u0439,\u0423\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0438\u0439\u0422\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u0438\u044fpython3uaddress\u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430pip3installuaddressformat\u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430 \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u043epython3setup.pyinstall--user\u041f\u0440\u0438\u043c\u0435\u0440python3example.py\u041c\u0435\u0442\u043e\u0434\u044bclearTrashstr: StringRegionTypestr: Stringregion: StringLocalitytype: Stringname: StringStreetstr: Stringtype: BooleanStreetTypestr: StringHousingstr: Stringtype: BooleanEntranceTypestr: Stringtype: BooleanHouseNumberTypestr: Stringhouse: StringHouseNumberstr: Stringadditionally: StringHouseNumberAdditionallynumber: Stringsub: StringApartmentTypestr: Stringtype: Boolean"} +{"package": "uaddresspacy", "pacakge-description": "\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\u0420\u0430\u0437\u0431\u043e\u0440\u043a\u0430 \u0443\u043a\u0440\u0430\u0438\u043d\u0441\u043a\u043e\u0433\u043e \u0430\u0434\u0440\u0435\u0441\u0430 \u043d\u0430 \u0442\u0438\u043f\u044bRead this in other language:English,\u0420\u0443\u0441\u0441\u043a\u0438\u0439,\u0423\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0438\u0439\u0422\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u0438\u044fpython3spacyrepandasxlrdcsvossignalthreading\u0421\u043e\u0437\u0434\u0430\u043d\u0438\u0435 \u043c\u043e\u0434\u0435\u043b\u0438python3train.py\u041e\u0431\u0443\u0447\u0438\u0442\u044c \u043c\u043e\u0434\u0435\u043b\u044cpython3-mspacytrainconfig/config.cfg--paths.traintraining/train.spacy--paths.devtraining/test.spacy--outputmodels\u041e\u0431\u0443\u0447\u0438\u0442\u044c \u0431\u043e\u043b\u0435\u0435 \u0442\u043e\u0447\u043d\u0435\u0435 \u043c\u043e\u0434\u0435\u043b\u044cpython3-mspacytrainconfig/config_acc.cfg--paths.traintraining/train.spacy--paths.devtraining/test.spacy--outputmodels\u041f\u0440\u043e\u0432\u0435\u0440\u043a\u0430 \u043c\u043e\u0434\u0435\u043b\u0438python3example.py\u0421\u043e\u0437\u0434\u0430\u0442\u044c \u0444\u0430\u0439\u043b \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0438python3-mspacyinitfill-configconfig/base_config.cfgconfig/config.cfg\u0421\u043e\u0437\u0434\u0430\u0442\u044c \u0444\u0430\u0439\u043b \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u044f \u0431\u043e\u043b\u0435\u0435 \u0442\u043e\u0447\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438python3-mspacyinitfill-configconfig/base_config_acc.cfgconfig/config_acc.cfg\u041f\u0440\u0438\u043c\u0435\u0440\u044bimportuaddresspacyprint(uaddresspacy.parse(\", - \u043f\u043e\u043b\u0442\u0430\u0432\u0441\u044c\u043a\u0430 \u0447\u0443\u0442\u0456\u0432\u0441\u044c\u043a\u0438\u0439 \u0436\u043e\u0432\u0442\u043d\u0435\u0432\u0435 \u0432\u0443\u043b. -, \u0431\u0443\u0434. -, \u043a\u0432.,\"))# [('\u043f\u043e\u043b\u0442\u0430\u0432\u0441\u044c\u043a\u0430', 'Locality'), ('\u0447\u0443\u0442\u0456\u0432\u0441\u044c\u043a\u0438\u0439', 'CountyType'), ('\u0436\u043e\u0432\u0442\u043d\u0435\u0432\u0435', 'Locality'), ('\u0432\u0443\u043b.', 'StreetType'), ('\u0431\u0443\u0434.', 'HouseNumberType'), ('\u043a\u0432.', 'ApartmentType')]print(uaddresspacy.parse(\", 01000 \u043a\u0438\u0457\u0432, \u043c\u0456\u0441\u0442\u043e \u043a\u0438\u0457\u0432, \u043c\u0456\u0441\u0442\u043e \u043a\u0438\u0457\u0432 \u0432\u043e\u0440\u043e\u0432\u0441\u044c\u043a\u043e\u0433\u043e, \u0431\u0443\u0434. 43-\u0431, \u043a\u0432. 14,\"))# [('01000', 'PostCode'), ('\u043a\u0438\u0457\u0432', 'Region'), ('\u043c\u0456\u0441\u0442\u043e', 'LocalityType'), ('\u043a\u0438\u0457\u0432', 'Locality'), ('\u0432\u043e\u0440\u043e\u0432\u0441\u044c\u043a\u043e\u0433\u043e', 'Street'), ('\u0431\u0443\u0434.', 'HouseNumberType'), ('43-\u0431', 'HouseNumber'), ('\u043a\u0432.', 'ApartmentType'), ('14', 'Apartment')]\u0421\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0430\u0424\u0430\u0439\u043b\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435pretrain.py\u041f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0438train.py\u041f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0430 \u043c\u043e\u0434\u0435\u043b\u0438example.py\u041f\u043e\u043b\u0443\u0447\u0438\u0442\u044c \u043f\u0440\u0438\u043c\u0435\u0440 \u0440\u0430\u0437\u0431\u043e\u0440\u043a\u0438 \u0430\u0434\u0440\u0435\u0441\u0430 \u043d\u0430 \u0442\u0438\u043f\u044braw.csv\u0414\u0430\u043d\u043d\u044b\u0435 \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044freport.csv\u041f\u0440\u0438\u043c\u0435\u0440 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u043d\u0430 \u0442\u0438\u043f\u044baddresses.csv\u0421\u043f\u0438\u0441\u043e\u043a \u0430\u0434\u0440\u0435\u0441\u043e\u0432 \u0434\u043b\u044f \u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438training/pretrain.csv\u0414\u0430\u043d\u043d\u044b\u0435 \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0438\u0422\u0438\u043f\u044b\u041d\u0430\u0437\u0432\u0430\u043d\u0438\u0435\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435Country\u0421\u0442\u0440\u0430\u043d\u0430RegionType\u0422\u0438\u043f \u043e\u0431\u043b\u0430\u0441\u0442\u0438Region\u041e\u0431\u043b\u0430\u0441\u0442\u044cCountyType\u0422\u0438\u043f \u0440\u0430\u0439\u043e\u043d\u0430County\u0420\u0430\u0439\u043e\u043dIncluded\u0412\u0445\u043e\u0434\u0438\u0442 \u0432 \u0441\u043e\u0441\u0442\u0430\u0432LocalityType\u0422\u0438\u043f \u043d\u0430\u0441\u0435\u043b\u0451\u043d\u043d\u043e\u0433\u043e \u043f\u0443\u043d\u043a\u0442\u0430Locality\u041d\u0430\u0441\u0435\u043b\u0451\u043d\u043d\u044b\u0439 \u043f\u0443\u043d\u043a\u0442StreetType\u0422\u0438\u043f \u0443\u043b\u0438\u0446\u044bStreet\u0423\u043b\u0438\u0446\u0430HousingType\u0422\u0438\u043f \u043a\u043e\u0440\u043f\u0443\u0441\u0430Housing\u041a\u043e\u0440\u043f\u0443\u0441HostelType\u0422\u0438\u043f \u043e\u0431\u0449\u0435\u0436\u0438\u0442\u0438\u044fHostel\u041e\u0431\u0449\u0435\u0436\u0438\u0442\u0438\u0435HouseNumberType\u0422\u0438\u043f \u043d\u043e\u043c\u0435\u0440\u0430 \u0434\u043e\u043c\u0430HouseNumber\u041d\u043e\u043c\u0435\u0440 \u0434\u043e\u043c\u0430HouseNumberAdditionally\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0439 \u043d\u043e\u043c\u0435\u0440 \u0434\u043e\u043c\u0430SectionType\u0422\u0438\u043f \u0441\u0435\u043a\u0446\u0438\u0438Section\u0421\u0435\u043a\u0446\u0438\u044fApartmentType\u0422\u0438\u043f \u043a\u0432\u0430\u0440\u0442\u0438\u0440\u044bApartment\u041a\u0432\u0430\u0440\u0442\u0438\u0440\u0430RoomType\u0422\u0438\u043f \u043a\u043e\u043c\u043d\u0430\u0442\u044bRoom\u041a\u043e\u043c\u043d\u0430\u0442\u0430Sector\u0421\u0435\u043a\u0442\u043e\u0440FloorType\u0422\u0438\u043f \u044d\u0442\u0430\u0436\u0430Floor\u042d\u0442\u0430\u0436PostCode\u0418\u043d\u0434\u0435\u043a\u0441Manually\u041d\u0430\u0431\u043e\u0440 \u0442\u0438\u043f\u043e\u0432 \u0434\u043b\u044f \u0434\u0430\u043b\u044c\u043d\u0435\u0439\u0448\u0435\u0439 \u0440\u0430\u0437\u0431\u043e\u0440\u043a\u0438 \u0430\u0434\u0440\u0435\u0441\u0430NotAddress\u041d\u0435 \u0430\u0434\u0440\u0435\u0441Comment\u041a\u043e\u043c\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439AdditionalData\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0434\u0430\u043d\u043d\u044b\u0435"} +{"package": "uadetector", "pacakge-description": "WSGI Middleware and web framework extensions for handling User-Agent. Thanks towoothee, UADetector supports various User-Agents. This library respects tok0kubun/rack-user_agent.Installation$ pip install uadetectorUsageWSGI middlewareThis middleware provides auadetector.useragent.UserAgentobject to handling User-agents.fromwsgiref.simple_serverimportmake_server# import middlewarefromuadetectorimportUADetectordefapp(environ,start_response):start_response('200 OK',[('Content-Type','text/plain')])# get 'UserAgent' object from environ dict.ua=environ.get('uadetector.useragent')ua.user_agent#=> \"Mozilla/5.0 (Macintosh; ...\"ua.device_type#=> \"pc\"ua.os#=> \"Mac OSX\"ua.browser#=> \"Chrome\"ua.from_pc#=> Trueua.from_smartphone#=> Falsereturn[ua.os.encode('utf-8')]# Apply middlewareapplication=UADetector(app)if__name__==\"__main__\":withmake_server('127.0.0.1',8000,application)asserver:print(\"Serving on port 8000...\")server.serve_forever()You can also replace the key ofenvironor theUserAgentclass.fromuadetector.useragentimportUserAgentclassMyUserAgent(UserAgent):# Write your custom codes.# Apply middlewareapplication=UADetector(app,envorion_key='your.favorite.key'useragent_class='path.to.MyUserAgent')See alsoWSGI example.Web framework extensionsSome web frameworks provide a way to extend in a different way from WSGI Middleware. This library provide shortcuts according to that way.Caution: I do not actively support individual frameworks. If you are worried, you should use WSGIMiddleware.DjangoYou can use Django\u2019sMIDDLEWARE.# settings.pyMIDDLEWARE=[# Add UADetecorMiddleware'uadetector.django.middleware.UADetectorMiddleware',# ... omit ...]# views.pydefindex_view(request):print(request.ua.from_smartphone)# => True or False# ... omit ...Customize property name of request object and replace UserAgent class.# settings.pyUADETECTOR_REQUEST_PROPERTY_NAME='agent'# => You can use \"request.agent\"UADETECTOR_USERAGENT_CLASS='path.to.MyUserAgent'See alsoDajngo example.Tips:Switch templates based on User-Agent(usingdjango-variantmpl).PyramidYou can useconfig.add_request_method.fromuadetector.pyramidimportua_propdefindex(request):print(request.ua.from_smartphone)# => True or False# ... omit ...withConfigurator()asconfig:config.add_route('index','/')config.add_view(index,route_name='index')config.add_request_method(ua_prop(),name='ua',reify=True)# ... omit ...Customize property name of request object and replace UserAgent class.config.add_request_method(ua_prop('path.to.MyUserAgent'),name='agent',# => You can use \"request.agent\"reify=True)See alsoPyramid example.FlaskYou can useFlask Extension.fromflaskimportFlask,requestfromuadetector.flaskimportUADetectorapp=Flask(__name__)UADetector(app)@app.route('/')defindex():print(request.ua.from_smartphone)# => True or False# ... omit ...Customize property name of request object and replace UserAgent class.app=Flask(__name__)app.config['UADETECTOR_USERAGENT_CLASS']='path.to.MyUserAgent'app.config['UADETECTOR_REQUEST_PROPERTY_NAME']='agent'# => You can use \"request.agent\"UADetector(app)See alsoFlask example.TornadoYou can use customRequestHandler.fromuadetector.tornado.webimportRequestHandlerclassIndexHandler(RequestHandler):defget(self):print(self.request.ua.from_smartphone)# => True or False# ... omit ...Customize property name of request object and replace UserAgent class.fromtornado.optionsimportdefinefromuadetector.tornado.webimportRequestHandlerdefine('uadetector_request_property_name',default='agent',# => You can use \"self.request.agent\")define('uadetector_useragent_class',default='path.to.MyUserAgent')classIndexHandler(RequestHandler):See alsoTornado example.UserAgentList of properties ofuadetector.useragent.UserAgentobject.attrsUserAgent.device_variantUserAgent.device_typeUserAgent.osUserAgent.os_versionUserAgent.browserUserAgent.browser_versionUserAgent.browser_vendorhelpersUserAgent.from_pcUserAgent.from_smartphoneUserAgent.from_mobilephoneUserAgent.from_applianceUserAgent.from_crawlerdetectorsUserAgent.smartphone_versionUserAgent.from_iphoneUserAgent.from_ipadUserAgent.from_ipodUserAgent.from_androidUserAgent.from_android_tabletUserAgent.from_windows_phoneUserAgent.from_iosUserAgent.from_android_osTipsIf you want aUserAgentobject simply from the User-Agent string, Please useget_useruseragent.fromuadetectorimportget_useragentua_string=\"Mozilla/5.0 (iPhone; CPU iPhone OS ...\"ua=get_useragent(ua_string)us.from_smartphone# => True# Use custom useragent classua=get_useragent(ua_string,useragent_class='path.to.MyUserAgent')SupportSupport latest 3 minor versions.Python 3.4, 3.5, 3.6Django 1.10, 1.11, 2.0Pyramid 1.7, 1.8, 1.9Flask 0.10, 0.11, 0.12Tornado 4.5, 4.6, 4.7LicenseMIT LicenseAuthorstell-k History0.1.3(Feb 20, 2018)Lazy parsing User-Agent string.0.1.2(Feb 19, 2018)First release"} +{"package": "uaDevice", "pacakge-description": "ua-device\u89e3\u6790user-agent\u7684python\u5305\uff0c\u53ef\u4ee5\u83b7\u53d6\u5230\u7cfb\u7edf\u3001\u6d4f\u89c8\u5668\u5185\u6838\u3001\u6d4f\u89c8\u5668\u3001\u8bbe\u5907\u4fe1\u606f\uff0c\u5176\u7279\u70b9\uff1a\u76f8\u6bd4\u56fd\u5185\u5916\u7684\u6d41\u884c\u7684python\u5305\uff0c\u8be5\u6a21\u5757\u89e3\u6790\u56fd\u5185\u590d\u6742\u7684ua\u4fe1\u606f\u66f4\u52a0\u7cbe\u786e\uff0c\u6709\u51e0\u5343\u884c\u4ee3\u7801\u4e13\u95e8\u6765\u5339\u914d\u5177\u4f53\u7684\u7279\u5b9a\u7684uaWhy\u7531\u4e8e\u5728\u56fd\u5185\u751f\u4ea7PC\u7684\u5382\u5bb6\u6709\u9650\uff0c\u5927\u4f17\u7528\u6237\u4f7f\u7528\u7684\u6d4f\u89c8\u5668\u4e5f\u4e3b\u8981\u662f\u5f53\u524d\u7684\u4e00\u4e9b\u4e3b\u6d41\u6d4f\u89c8\u5668\u3002\u56e0\u6b64\u76ee\u524d\u7684UA\u89e3\u6790\u5e93\u5728\u5bf9OS\u3001\u6d4f\u89c8\u5668\u5916\u58f3\u3001\u6d4f\u89c8\u5668\u5185\u6838\u7b49\u7684\u8bc6\u522b\u7387\u90fd\u76f8\u5f53\u9ad8\u3002\u4f46\u662f\u7531\u4e8e\u56fd\u5185\u7684\u79fb\u52a8\u8bbe\u5907\u7684\u4e94\u82b1\u516b\u95e8\uff0c\u5bf9\u4e8e\u79fb\u52a8\u8bbe\u5907\u7684\u786c\u4ef6\u4fe1\u606f\u662f\u5f88\u96be\u7528\u4e00\u5957\u901a\u7528\u7684\u65b9\u6cd5\u8fdb\u884c\u8bc6\u522b\uff0c\u56e0\u6b64 ua-device \u8bde\u751f\u901a\u8fc7\u673a\u578b\u8bc6\u522b\u54c1\u724c: \u4f8b\u5982 [-\\s](Galaxy[\\s-]nexus|Galaxy[\\s-]\\w*[\\s-]\\w*|Galaxy[\\s-]\\w*|SM-\\w*|GT-\\w*|s[cgp]h-\\w*|shw-\\w* \u8fd9\u6837\u7684\u5339\u914d\u89c4\u5219\u4ee5\u53ca\u4e00\u4e9b\u4ece\u4e2d\u5173\u6751\u5728\u7ebf\u722c\u53d6\u5230\u7684\u673a\u578b\u540d\u79f0\u5982G3508\u3001G3508J\u3001G3508i \u7b49\u8bc6\u522b\u51fa\u6765\u8be5\u673a\u578b\u7684\u54c1\u724c\u4e3aSamsung \u56e0\u4e3a\u5355\u7eaf\u4eceUA\u4fe1\u606f\u786e\u5b9e\u65e0\u6cd5\u5f97\u5230\u54c1\u724c\u6570\u636e\uff0c\u8fd9\u4e5f\u662f\u4e3a\u4f55\u5f88\u591a\u9ad8Star\u7684UA\u89e3\u6790\u5e93\u8bc6\u522b\u624b\u673a\u54c1\u724c\u6210\u529f\u7387\u53ea\u670930%-40%\u7684\u539f\u56e0(ua-device\u8bc6\u522b\u7387\u53ef\u89c1\u4e0b\u9762\u6d4b\u8bd5\u7528\u4f8b)\u3002\u89e3\u51b3\u56fd\u5185UA\u4fe1\u606f\u4e0d\u89c4\u8303: \u7531\u4e8e\u56fd\u5185\u5f88\u591a\u624b\u673a\u751f\u4ea7\u5382\u5bb6\u7684\u8bbe\u8ba1\u95ee\u9898\uff0c\u4f8b\u5982\u5c0f\u7c73\u53ef\u4f9b\u8bc6\u522b\u7684UA\u6570\u636e\u53ef\u80fd\u4e3a mi 2 \u3001mi2\u3001m2\u3001mi-2LTE\u3001MI-20150XX\u3001minote\u7b49\u7b49\uff0c\u5982\u679c\u5339\u914d\u89c4\u5219\u9650\u5236\u592a\u7d27\u5c31\u4f1a\u5bfc\u81f4\u6570\u636e\u65e0\u6cd5\u547d\u4e2d\uff0c\u5982\u679c\u5339\u914d\u89c4\u5219\u592a\u677e\u53c8\u4f1a\u8ba9\u5176\u5b83\u5c71\u5be8\u673a\u578b\u6ee5\u7afd\u5145\u6570\uff0c\u6240\u4ee5\u9700\u8981\u4e00\u5957\u6bd4\u8f83\u7279\u6b8a\u7684\u5904\u7406\u6d41\u7a0b\u3002\u89e3\u51b3\u56fd\u5185\u56e0\u4e0d\u540c\u53d1\u7248\u800c\u9020\u6210\u7684UA\u6570\u636e\u4e0d\u4e00\u81f4: \u4f8b\u5982\u5f88\u591a\u673a\u578b\u4f1a\u56e0\u540c\u7535\u4fe1\u3001\u79fb\u52a8\u3001\u8054\u901a\u800cUA\u4fe1\u606f\u4e0d\u540c\uff0c\u4f46\u5b9e\u9645\u5e94\u8be5\u628a\u4ed6\u4eec\u7b97\u6210\u540c\u4e00\u6b3e\u624b\u673a\u89e3\u51b3\u673a\u578b\u7684\u91cd\u547d\u540d\u4e0e\u5408\u5e76: \u5f88\u591a\u624b\u673a\u5728\u4e0d\u540c\u65f6\u95f4\u751f\u4ea7\u5176UA\u4fe1\u606f\u53ef\u80fd\u4e0d\u540c\uff0c\u6240\u4ee5\u9700\u8981\u5bf9\u4ed6\u4eec\u8fdb\u884c\u5408\u5e76\uff0c\u9632\u6b62\u5728\u5c55\u793atop\u6570\u636e\u65f6\u56e0\u6570\u636e\u5206\u6563\u800c\u6392\u4e0d\u4e0a\u53f7\u3002\u89e3\u6790\u6210\u529f\u7387\u4f9b\u53c2\u8003\uff08\u4ee530000\u4e2a\u7ebf\u4e0aua\u6d4b\u8bd5\uff09:\u6d4f\u89c8\u5668\uff1a98.5%\u7cfb\u7edf\uff1a 99.8%\u5185\u6838\uff1a 99.92%\u8bbe\u5907\u7c7b\u578b\uff1a 100%\u8bbe\u5907\u578b\u53f7\uff1a98.9%\u5382\u5546\u4fe1\u606f\uff1a95.5%javascript\u7248\u672cua-device\u5b89\u88c5pipinstall-UuaDevice\u4f7f\u7528importuaDeviceua='Mozilla/5.0 (iPhone; CPU iPhone OS 12_0_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/12.0 MQQBrowser/8.9.1 Mobile/15E148 Safari/604.1 MttCustomUA/2 QBWebViewType/1 WKType/1'info=uaDevice.parseUA(ua)output='\\t'.join([info['os']['name'],info['os']['version']['original'],info['browser']['name'],info['browser']['version']['original'],info['engine']['name'],info['engine']['version']['original'],info['device']['type'],info['device']['model'],info['device']['manufacturer']])print(output)\u8d21\u732e\u968f\u7740\u65b0\u8bbe\u5907\u65b0app\u7b49\u7b49\u7684\u4e0a\u5e02\uff0cua\u4fe1\u606f\u4f1a\u8d8a\u6765\u8d8a\u590d\u6742\uff0c\u56e0\u4e3a\u8be5\u9879\u76ee\u9700\u8981\u4e0d\u65ad\u8fed\u4ee3\uff0c\u5e0c\u671b\u5927\u5bb6\u4e00\u8d77\u6765\u8d21\u732e\u4e0d\u652f\u6301\u7684ua\uff0c\u4f7f\u5f97ua\u89e3\u6790\u8d8a\u6765\u8d8a\u51c6\u786e\u611f\u8c22\u8be5\u9879\u76ee\u662f\u57fa\u4e8efex\u56e2\u961f\u7ef4\u62a4\u7684js\u7248\u672c\u7684ua\u89e3\u6790\u5e93ua-device\uff0c \u5728\u6b64\u8868\u793a\u611f\u8c22"} +{"package": "ua-djangolibrary", "pacakge-description": "For use within Django.There are two Python modulesguardedsettings.py\nprojectbuilder.pyguardedsettingsFor use within a Django settings.py file.\nIt allows a Django project to ship and\nnot incorporate secret information in the\nsettings.py file, such as the SECRET_KEY\nand DATABASE:PASSWORD.When the guardedsettings program starts, it\nreads the guardedsettings.json file and creates\na Python dictionary from guardedsettings.json content.\nThe JSON is referenced by using the method,\nSettingsDictionary['Key In The JSON'].guardedsettings.jsonIn the Django Project Root, where the manage.py\nfile resides, you create a JSON file named\nguardedsettings.JSON as such.{\n\"SecretKey\": \"Secret\",\n\"DatabasePassword\" : \"MoreSecret\"\n}Consider the line containing\"SecretKey\": \"Secret\",The term \"SecretKey\" is a key and the term\n\"Secret\" is the value. Together they are called\na pair, hence the term 'key/value pair'.Add as many key/value pairs as necessary, each\nseparated by a comma.settings.pyUse guardedsettings within the Django settings.py\nfile as shown below. Place the two lines of code close\nto or at the top of the settings.py file.--- At Or Near The Top of settings.pyfrom UA_GuardedSettings import guardedsettings\ngs = guardedsettings.guardedsettings()---An instance of guardedsettings is now instantiated\nas the variable named 'gs'. You are welcome to name\nthe variable as you choose.Later in the settings.py, use guardedsettings as\nshown.The generic form of usage isSomeDjangoSetting = gs.SettingsDictionary['SomeKey']For example-- in the settings.py fileSECRET_KEY\t= gs.SettingsDictionary['SecretKey']and like so for a database password.-- in the settings.py file DATABASE section.'PASSWORD' : gs.SettingsDictionary['databasePassword'],projectbuilder.pyThe goal of projectbuilder is to package an existing\nDjango Project (not the apps), and create a package under\na new name - for use as a Site in a deployment.This alleviates the need to create a new Django Project\nin each deployment phase; testing, staging and production,\namong others your organization may employ.projectbuilder must run in the 'Project Root', where the\nDjango manage.py folder resides.The program requires two inputs.\n(1) The name of the existing Django project to package.\n(2) The name of the new Django Project to create.The new package will be completely referenced to the\nnew name you provide. The manage.py will be re-referenced,\nas is the asgi.py, settings.py and, the wsgi.py files, all\nreferencing the new project.It will build a zip file in the RootFolder\\dist\\projects\nfolder and is named with '_Project.zip' preceding the\nproject name you input as the new name.Transport this zip file to a new deployment site and\nunzip it."} +{"package": "uaedata", "pacakge-description": "Aiml UAE Python libreryChange Log0.0.1 (05/07/2022)First Release"} +{"package": "ua-eds-api", "pacakge-description": "UA-EDS-APIProvides easy interface for making REST requests to University of Arizona EDS registry.MotivationTo make a python API that could generically interact with the REST architecture of EDS.Code Examplefromua_eds_apiimportua_eds_apieds_api=ua_eds_api.EdsApi(\"host\",\"username\",\"password\",\"grouper url\")users=eds_api.get_grouper_users(\"grouper endpoint\")Installationpip install --user ua-eds-apiCreditsRyanJohannesBlandEtienneThompsonLicenseMIT"} +{"package": "ua-email-client", "pacakge-description": "UA-Email-ClientProvides easy interface for sending emails through Amazons Simple Email Service.MotivationTo make a python API that could obfuscate the details of sending emails using AWS SES service.Code Examplefromua_email_clientimportua_email_clientclient=ua_email_client.EmailClient(email)# The template name given should be relative name to a file.client.add_template(\"success.html\")# Destinationsclient.send_email(destinations,\"success.html\",subject,body)# No Templateclient.send_email(destinations,None,subject,body,use_template=False)Installationpip install --user ua-email-clientTestsNOTE:Running this test suiteWILLsend emails. Please specify an email which can receive emails. The emails can all be ignored once received.To run the tests you will need to create a json configuration with some user-specific values. This file will be ua_email_client/tests/email_creds.json. It will be populated with:{\"email\":\"...\",\"default_recipient\":\"...\",\"secondary_recipient\":\"...\"}Where\"email\"is the sending email,\"default_recipient\"is the main email you want to receive emails, and\"secondary_recipient\"is a second email to test sending emails to multiple recipients at once.Once this file is created, just run:cdua_email_client/tests\nnoseteststest_ua_email_client.pyCreditsRyanJohannesBlandEtienneThompsonLicenseMIT"} +{"package": "ua-framer", "pacakge-description": "UA-framerOverviewDraw the frame of the Ukrainian flag on the image.InstallPython 3 or higher is required.# Linux/OS X\n$ python -m pip install -U ua-framer\n\n# Windows\n> py -3 -m pip install -U ua-framerExampleDraw the frame.importframerfromPILimportImageframer(\"example.png\",10).save(\"example.png\")"} +{"package": "ua-gec", "pacakge-description": "\u0423\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u043e\u044eUA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian LanguageThis repository contains UA-GEC data and an accompanying Python library.What's newNovember 2022: Version 2.0 released, featuring more data and detailed annotations.January 2021: Initial release.SeeCHANGELOG.mdfor detailed updates.DataAll corpus data and metadata stay under the./data. It has two subfolders\nforgec-fluency and gec-only corpus versionsBoth corpus versions contain two subfolderstrain and test splitswith different data\nrepresentations:./data/{gec-fluency,gec-only}/{train,test}/annotatedstores documents in theannotated format./data/{gec-fluency,gec-only}/{train,test}/sourceand./data/{gec-fluency,gec-only}/{train,test}/targetstore the\noriginal and the corrected versions of documents. Text files in these\ndirectories are plain text with no annotation markup. These files were\nproduced from the annotated data and are, in some way, redundant. We keep them\nbecause this format is convenient in some use cases.Metadata./data/metadata.csvstores per-document metadata. It's a CSV file with\nthe following fields:id(str): document identifier;author_id(str): document author identifier;is_native(int): 1 if the author is native-speaker, 0 otherwise;region(str): the author's region of birth. A special value \"\u0406\u043d\u0448\u0435\"\nis used both for authors who were born outside Ukraine and authors\nwho preferred not to specify their region.gender(str): could be \"\u0416\u0456\u043d\u043e\u0447\u0430\" (female), \"\u0427\u043e\u043b\u043e\u0432\u0456\u0447\u0430\" (male), or \"\u0406\u043d\u0448\u0430\" (other);occupation(str): one of \"\u0422\u0435\u0445\u043d\u0456\u0447\u043d\u0430\", \"\u0413\u0443\u043c\u0430\u043d\u0456\u0442\u0430\u0440\u043d\u0430\", \"\u041f\u0440\u0438\u0440\u043e\u0434\u043d\u0438\u0447\u0430\", \"\u0406\u043d\u0448\u0430\";submission_type(str): one of \"essay\", \"translation\", or \"text_donation\";source_language(str): for submissions of the \"translation\" type, this field\nindicates the source language of the translated text. Possible values are\n\"de\", \"en\", \"fr\", \"ru\", and \"pl\";annotator_id(int): ID of the annotator who corrected the document;partition(str): one of \"test\" or \"train\";is_sensitive(int): 1 if the document contains profanity or offensive language.Annotation formatAnnotated files are text files that use the following in-text annotation format:{error=>edit:::error_type=Tag}, whereerrorandeditstand for a text item before\nand after correction respectively, andTagdenotes an error category and an error subcategory in case of Grammar- and Fluency-related errors.Example of an annotated sentence:I {likes=>like:::error_type=G/Number} turtles.Below you can see a list of error types presented in the corpus:Spelling: spelling errors;Punctuation: punctuation errors.Grammar-related errors:G/Case: incorrect usage of case of any notional part of speech;G/Gender: incorrect usage of gender of any notional part of speech;G/Number: incorrect usage of number of any notional part of speech;G/Aspect: incorrect usage of verb aspect;G/Tense: incorrect usage of verb tense;G/VerbVoice: incorrect usage of verb voice;G/PartVoice: incorrect usage of participle voice;G/VerbAForm: incorrect usage of an analytical verb form;G/Prep: incorrect preposition usage;G/Participle: incorrect usage of participles;G/UngrammaticalStructure: digression from syntactic norms;G/Comparison: incorrect formation of comparison degrees of adjectives and adverbs;G/Conjunction: incorrect usage of conjunctions;G/Other: other grammatical errors.Fluency-related errors:F/Style: style errors;F/Calque: word-for-word translation from other languages;F/Collocation: unnatural collocations;F/PoorFlow: unnatural sentence flow;F/Repetition: repetition of words;F/Other: other fluency errors.An accompanying Python package,ua_gec, provides many tools for working with\nannotated texts. See its documentation for details.Train-test splitWe expect users of the corpus to train and tune their models on thetrainsplit\nonly. Feel free to further split it into train-dev (or use cross-validation).Please use thetestsplit only for reporting scores of your final model.\nIn particular, never optimize on the test set. Do not tune hyperparameters on\nit. Do not use it for model selection in any way.Next section lists the per-split statistics.StatisticsUA-GEC contains:GEC+FluencySplitDocumentsSentencesTokensAuthorsErrorstrain1,70631,038457,01775238,213test1662,69743,601767,858TOTAL1,87233,735500,61882846,071Seestats.gec-fluency.txtfor detailed statistics.GEC-onlySplitDocumentsSentencesTokensAuthorsErrorstrain1,70631,046457,00475230,049test1662,70443,605766,169TOTAL1,87233,750500,60982836,218Seestats.gec-only.txtfor detailed statistics.Python libraryAlternatively to operating on data files directly, you may use a Python package\ncalledua_gec. This package includes the data and has classes to iterate over\ndocuments, read metadata, work with annotations, etc.Getting startedThe package can be easily installed bypip:$ pip install ua_gecAlternatively, you can install it from the source code:$ cd python\n $ python setup.py developIterating through corpusOnce installed, you may get annotated documents from the Python code:>>>fromua_gecimportCorpus>>>corpus=Corpus(partition=\"train\",annotation_layer=\"gec-only\")>>>fordocincorpus:...print(doc.source)# \"I likes it.\"...print(doc.target)# \"I like it.\"...print(doc.annotated)# like} it.\")...print(doc.meta.region)# \"\u041a\u0438\u0457\u0432\u0441\u044c\u043a\u0430\"Note that thedoc.annotatedproperty is of typeAnnotatedText. This\nclass is described in thenext sectionWorking with annotationsua_gec.AnnotatedTextis a class that provides tools for processing\nannotated texts. It can iterate over annotations, get annotation error\ntype, remove some of the annotations, and more.Here is an example to get you started. It will remove all F/Style annotations from a text:>>>fromua_gecimportAnnotatedText>>>text=AnnotatedText(\"I {likes=>like:::error_type=G/Number} it.\")>>>forannintext.iter_annotations():...print(ann.source_text)# likes...print(ann.top_suggestion)# like...print(ann.meta)# {'error_type': 'Grammar'}...ifann.meta[\"error_type\"]==\"F/Style\":...text.remove(ann)# or `text.apply(ann)`Multiple annotatorsSome documents are annotated with multiple annotators. Such documents\nsharedoc_idbut differ indoc.meta.annotator_id.Currently, test sets for gec-fluency and gec-only are annotated by two annotators.\nThe train sets contain 45 double-annotated docs.ContributingData and code improvements are welcomed. Please submit a pull request.CitationTheaccompanying paperis:@misc{syvokon2021uagec,\n title={UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language},\n author={Oleksiy Syvokon and Olena Nahorna},\n year={2021},\n eprint={2103.16997},\n archivePrefix={arXiv},\n primaryClass={cs.CL}}Contactsnastasiya.osidach@grammarly.comolena.nahorna@grammarly.comoleksiy.syvokon@gmail.compavlo.kuchmiichuk@gmail.com"} +{"package": "uagen", "pacakge-description": "\u7b80\u5355 UA \u751f\u6210\u5668\u987b\u77e5\uff1a\u6839\u636e\u7248\u672c\u89c4\u5219\u751f\u6210\u5f88\u591a\u5f88\u591a\u4e2a\u4e0d\u540c\u7684 ua \uff08\u6211\u4e5f\u6ca1\u6570\u8fc7\uff0c\u603b\u4e4b\u5f88\u591a\uff09\u6709 chrome \u548c firefox \u548c opera \u7684\u6709\u4e9b\u53ef\u80fd\u6ca1\u6709\u7528\u53ef\u4ee5\u5728\u4ee3\u7801\u4e2d import\uff0c\u4e5f\u53ef\u4ee5\u5728\u7ec8\u7aef\u6d4b\u8bd5UA\u7528\u4e0d\u4e86\u522b\u602a\u6211\u5b89\u88c5\uff1a# \u6ce8\u610f\u662f uagen, \u4e0d\u662f uagent, \u90a3\u662f\u53e6\u5916\u4e00\u4e2a\u8001\u5144\u7684\n$ pip3 install uagen\u4ee3\u7801\u5bfc\u5165\uff1aimport uagen\n\nrandom_user_agent = uagen.random_ua() # \u968f\u673a ua\nfirefox_user_agent = uagen.firefox_ua() # firefox ua\nchrome_user_agent = uagen.chrome_ua() # chrome ua\nopera_user_agent = uagen.opera_ua() # opera ua\u7ec8\u7aef\uff1a# \u751f\u6210\u4e00\u4e2a ua\uff0c\u5728\u7ec8\u7aef\u6253\u5370\u51fa\u6765\n$ uagen [-m --mode random/firefox/chrome/opera]"} +{"package": "ua-generator", "pacakge-description": "ua-generatorA random user-agent generator for Python >= 3.6FeaturesNo external user-agent list. No downloads.Templates are hardcoded into the code.Platform and browser versions are based on real releases.Client hints (Sec-CH-UA fields).Installingpip3install-Uua-generatorBasic usageimportua_generatorua=ua_generator.generate()print(ua)# Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_3) AppleWebKit/604.1.38 (KHTML, like Gecko) Version/15.2 Safari/604.1.38CustomizationThere are three different parameters to the generate user-agent by the certain conditions.device=('desktop','mobile')platform=('windows','macos','ios','linux','android')browser=('chrome','edge','firefox','safari')All of the parameters are optional, and the types can be choose multiple.importua_generatorua=ua_generator.generate(device='desktop',browser='firefox')print(ua.text)# Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:85.0) Gecko/20100101 Firefox/85.0print(ua.platform)# linuxprint(ua.browser)# firefoxprint(ua.ch.brands)# \" Not A;Brand\";v=\"99\"print(ua.ch.mobile)# ?0ua=ua_generator.generate(platform=('ios','macos'),browser='chrome')print(ua.text)# Mozilla/5.0 (iPhone; CPU iPhone OS 15_4 like Mac OS X) AppleWebKit/537.36 (KHTML, like Gecko) CriOS/80.0.3987.44 Mobile/15E148 Safari/537.36print(ua.platform)# iosprint(ua.browser)# chromeprint(ua.ch.brands)# \" Not A;Brand\";v=\"99\", \"Chromium\";v=\"80\", \"Google Chrome\";v=\"80\"print(ua.ch.mobile)# ?1AuthorEkin Karadeniz (iamdual@icloud.com)"} +{"package": "ua-generic-rest-api", "pacakge-description": "UA-Generic-Rest-ApiProvides basic REST API Implementation for GET, PUT, and POST, and DELETE.MotivationWas designed to remove similarities among REST API implementations by creating a generic REST API that classes can be extended and override for specific needs.FeaturesGET - Implementation of GET which can single GET, batch GET, single GET with query, and GET every page on a paginated endpoint.Batch gets with queries are unavailable as there is no way to give each get a unique query. Because of this the feature was not included.PUT - Basic implementation of PUT which puts the payload to the given endpoint.POST - Basic implementation of POST which posts the payload to the given endpoint.DELETE - Basic implementation of DELETE which deletes the given endpoint.Code Examplefromua_generic_rest_apiimportGenericRestApiclassSpecificRestApi(GenericRestApi):# Replace '...' with any other initialization arguments.def__init__(self,...):# host, header_info, page_query, and page_tag are site specific.# Set them to your own values.super().__init__(host,header_info,page_query,page_tag=page_tag)# Can override GET, PUT, POST, or DELETE here.host - The base url for the endpoint that is to be gotten.header_info - Any information to be added to a request header such as Authorization or Content-Type.Should be in the form of a dictionary, such as {\"Authorization\": None, \"Content-Type\": \"text/xml\"}.page_query - The tag to use when querying for specific pages.For example, for sites queried with the tag \"?page=\", page_query should be \"page\".page_tag - The tag name of paginated endpoints to search for when getting data.For sites paginated with the tag \"page\", page_tag should be \"page\".Installationpipinstallua-generic-rest-api\npipinstall-rrequirements.txtTestsTests are only necessary when wanting to make changes to the module.pipinstall--updatenodecd./ua_generic_rest_apicd./tests\nnoseteststest_generic_rest_api.pyCreditssterns1EtienneThompsonLicenseMIT"} +{"package": "uagent", "pacakge-description": "UNKNOWN"} +{"package": "uagents", "pacakge-description": "Installation (Python)Install \u03bcAgents for Python 3.8 to 3.12:poetryinstall\npoetryshellDocumentationBuild and run the docs locally with:mkdocsserveOr go to the official docs site:https://docs.fetch.ai/uAgents.ExamplesTheexamplesfolder contains several examples of how to create and run various types of agents."} +{"package": "uagents-ai-engine", "pacakge-description": "AI-Engine Integration\ud83d\udcccOverviewThis integration adds types required by AI-Engine to UAgents.UAgentResponse digest:model:66841ea279697fd62a029c37b7297e4097966361407a2cc49cd1e7defb924685"} +{"package": "uagents-twilio", "pacakge-description": "Thisuagentsutlity was generated withCookiecutter.Featuresuagents protocols to send SMS or Whatsapp messages using twiliosupports on_message and on_query methods to receive and send messagesInstallationYou can install \u201cuagents-twilio\u201d viapipfromPyPI:$ pip install uagents-twilioYou can install \u201cuagents_twilio\u201d via poetry:$ poetry add uagents-twilioUsageCreate .env file in root folder of project:AGENT_ADDRESS=\"\"\nACCOUNT_SID=\"\"\nAUTH_TOKEN=\"\"\nFROM_NUMBER=\"\"\nWP_FROM_NUMBER=\"\"\nTO_NUMBER=\"\"Create a uagents in your projectImport uagents_twilio protocol:$ from uagents_twilio.protocols.messages import service_protocolInclude protocol in uagent:$ service_agent.include(service_protocol)Use functions:from uagents_twilio.models import Message, MessageType\n\n@service_agent.on_interval(period=2.0)\nasync def send_message(ctx: Context):\n await ctx.send(\n AGENT_ADDRESS,\n Message(receiver=\"\", msg=\"hello there bob\", type=MessageType.sms),\n )"} +{"package": "uagents-twilio-beta", "pacakge-description": "Thisuagentsutlity was generated withCookiecutter.Featuresuagents protocols to send SMS or Whatsapp messages using twiliosupports on_message and on_query methods to receive and send messagesInstallationYou can install \u201cuagents-twilio\u201d viapipfromPyPI:$ pip install uagents-twilioYou can install \u201cuagents_twilio\u201d via poetry:$ poetry add uagents-twilioUsageCreate .env file in root folder of project:AGENT_ADDRESS=\"\"\nACCOUNT_SID=\"\"\nAUTH_TOKEN=\"\"\nFROM_NUMBER=\"\"\nWP_FROM_NUMBER=\"\"\nTO_NUMBER=\"\"Create a uagents in your projectImport uagents_twilio protocol:$ from uagents_twilio.protocols.messages import service_protocolInclude protocol in uagent:$ service_agent.include(service_protocol)Use functions:from uagents_twilio.models import Message, MessageType\n\n@service_agent.on_interval(period=2.0)\nasync def send_message(ctx: Context):\n await ctx.send(\n AGENT_ADDRESS,\n Message(receiver=\"\", msg=\"hello there bob\", type=MessageType.sms),\n )"} +{"package": "uagents-twilio-test-01", "pacakge-description": "Thisuagentsutlity was generated withCookiecutter.FeaturesTODORequirementsTODOInstallationYou can install \u201cuagents-twilio\u201d viapipfromPyPI:$ poetry add uagents-twilioUsageTODO"} +{"package": "uagents-twilio-test-dummy", "pacakge-description": "Thisuagentsutlity was generated withCookiecutter.Featuresuagents protocols to send SMS or Whatsapp messages using twiliosupports on_message and on_query methods to receive and send messagesInstallationYou can install \u201cuagents-twilio\u201d viapipfromPyPI:$ pip install uagents-twilioYou can install \u201cuagents_twilio\u201d via poetry:$ poetry add uagents-twilioUsageCreate .env file in root folder of project:AGENT_ADDRESS=\"\"\nACCOUNT_SID=\"\"\nAUTH_TOKEN=\"\"\nFROM_NUMBER=\"\"\nWP_FROM_NUMBER=\"\"\nTO_NUMBER=\"\"Create a uagents in your projectImport uagents_twilio protocol:$ from uagents_twilio.protocols.messages import service_protocolInclude protocol in uagent:$ service_agent.include(service_protocol)Use functions:from uagents_twilio.models import Message, MessageType\n\n@service_agent.on_interval(period=2.0)\nasync def send_message(ctx: Context):\n await ctx.send(\n AGENT_ADDRESS,\n Message(receiver=\"\", msg=\"hello there bob\", type=MessageType.sms),\n )"} +{"package": "ua-headers", "pacakge-description": "Fake HeadersAn ideal tool for generating random user agentsUser Agents:\n\nElementaryos # elementary OS\nBlackberry # blackberry\nOpenbsd # openbsd\nWindows # windows\nConsole # nintendo/ps/xbox\nAndroid # android\nSumbian # sumbian OS\nSunos # Sun OS\nLinux # fedora/ubuntu/debian & other\nIos # iosfromheadersimportuaua.elementaryos()#Generate elementary OS user agentua.blackberry()#Generate Blackberry user agentua.windows()#Generate Windows user agentua.console()#Generate Nintendo/PS/Xbox user agentua.openbsd()#Generate OpenBSD user agentua.sumbian()#Generate Sumbian user agentua.android()#Generate Android user agentua.sunos()#Generate sun OS user agentua.linux()#Generate Linux user agentua.ios()#Generate IOS user agent"} +{"package": "uaibot", "pacakge-description": "UAIBotIntroductionUAIBot is aweb-based Python robotic simulatordeveloped byVinicius Mariano Gon\u00e7alves(Electrical Engineering Department, Federal University of Minas Gerais, Brazil) and his students.While teaching robotics, I used many different desktop-based simulators with my students (such as CoppeliaSim and Matlab Toolboxes). However, I realized that students nowadays are much more used to web-based applications. This is why I, together with my students, came up with the idea of creating a simulator with the following goals:It can be used in a web browser if the student desires.Programming should be done in a language that most students already know or have some interest in learning, i.e., they should not be forced to learn a very specific language to use this simulator. Nowadays, the language that better fits these requirements isPython.It should be easy to set up and simple to use.For didactic purposes, it should be alow-levelsimulator. This means that is up to the user to simulate everything, with the help of the functions/interfaces from the simulator. Since everything is under the user's control, if something goes awry it is easier to pinpoint what is wrong.Guided by these goals, me and my studentJohnata Brayancame, in January 2022, with the idea of creatingUAIBot.\nIt is focused, so far, onopen-chain serial robotic manipulators, although there is some limited support already for other kind of robots.How it worksA Python library is used to code everything. First, it is used toset up the scenario(robots and other objects). Then, it is up to the user to explicitly compute each object's movement using the provided interfaces, creatinganimation framesfor each one of them. Then the usercreates the interactive animationas a HTML file, that can be shared and even embedded in a Web Page for didactic purposes.So, in UAIBot, all the simulation is first created (the computations take place) and the animation is displayed!Examples of HTML simulations made using UAIBot can be seenhere,hereandhere.The animations are displayed usingThree.js, in JavaScript. So the Python code automatically generates the JavaScript code to set up the animation that was coded using Python. In fact, UAIBot wraps in Python many of Three.js' functions, allowing us to use many of Three.js' features to visually customize the simulation.Getting startedIt is easier to start using UAIBot in a web browser. We will useGoogleColabsince it allows us to run Python code in a web browser.Open a new notebook. Now, we need to install UAIBot in the GoogleColab servers. This can be done by simply running the following commands:!pipinstalluaibotAfter it is done, we test if it is working by running the following commandimportuaibotasubsim=ub.Demo.control_demo_1()This will generate a simulation that was already pre-coded into UAIbot. It will return the simulation variable (sim) and automatically run the animation for you!If you want to run the simulation again, you don't need to compute it again. Just runsim.run().Note that you will need to reinstall UAIBot every time you open GoogleColab since the virtual machine created for you will be deleted.Using in desktop-based IDE'sYou can install the UAIBot package in a desktop-based IDE such as Pycharm. Install using the terminal>>pipinstalluaibotThesim.run()may not work in some IDEs. In that case, you need to save the simulation as a HTML file:importuaibotasubsim=ub.Demo.control_demo_1()sim.save('C:\\\\','test_uaibot')This will save the filetest_uaibot.htmlin your C: directory. You can then just open and visualize it. You can share just this file with your friends as well, it usually will be a small file. Since much of the information (as 3D models) is stored in a web server,in order to visualize the file an internet connection is required.How to use the simulatorPlease see theUAIBot documentation.If you know Portuguese, you can also see myRobotic Manipulator course, which uses UAIBot.Why \"UAIBot\"?\"Uai\" is an interjection commonly used by mineiros, that is, people who were born in the state of Minas Gerais, Brazil. It is one of the regional symbols of Minas Gerais. It is pronounced like the English \"why\" and has roughly the same meaning, used when mineiros are confused or in doubt. Indeed, some linguistic researchers think that the origin of this interjection is exactly the English word \"why\".What is exactly the logo of \"UAIBot\"???It is supposed to be a robotic manipulator in front of a mountain. Mountains, along with the aforementioned \"Uai\", are one of the symbols of the state of Minas Gerais, Brazil.CollaboratorsJohnata Brayan(Electrical Engineering student, UFMG)"} +{"package": "ua-ilab-tools", "pacakge-description": "UA-Ilab-ToolsA set of tools that interact with Ilab's REST database.MotivationWas designed to implement a simple way to interact with Ilab's REST architecture.Featuresilab_api.py contains a class to use simple REST functions such as GET, PUT, POST, and DELETE.ua_ilab_tools.py contains a class to interact with the REST architecture outside of the simple REST verbs, such as:get_service requests which returns the service requests with a given status.get_service_cost which returns the cost associated with a given service_id.get_request_charges which returns all of the charges of the request id.get_milestones which returns all of the milestones associated with a service request.get_custom_forms which returns all of the custom forms associated with the request id.extract_project_info which gets the relevant project info from a request.extract_custom_form_info which gets all of the fields of a form.Code Examplefromua_ilab_toolsimportilab_api,ua_ilab_toolsapi=ilab_api.IlabApi(core_id,auth_creds)# \"token\" contains the Authorization information for headers.tools=ua_ilab_tools.IlabTools(core_id,token)prj_info=ua_ilab_tools.extract_project_info(soup)form_info=ua_ilab_tools.extract_custom_form_info(req_id,form_id,form_soup)Installationpipinstallua-ilab-toolsTestsYou will have to create a file named \"ilab_creds.json\" in the format of:{\"token\":\"Bearer {your token}\",\"core_id\":\"{your core_id}\"}```bashpipinstall--updatenosecd./ua_ilab_toolscd./testsnoseteststest_ilab_tools.pyHow to UseGet general endpointsGet information associated with specific service requests.Get data associated with specific projects and custom_forms.Creditssterns1EtienneThompsonLicenseMIT"} +{"package": "uai-openlabel", "pacakge-description": "uai_openlabelThis repository is an implementation of theASAM OpenLABELv1.0.0 standard.\nOpenLABEL defines a JSON schema for saving annotations in the context of data labeling.How to useThe entry point to the uai_openlabel data structure isOpenLabel, importable viafrom uai_openlabel import OpenLabel.\nTo export an example OpenLABEL file and save it to disk, doimportjsonfrompathlibimportPathfromuai_openlabelimportOpenLabelexample=OpenLabel.example()withPath(\"where/to/save/example.json\").open(\"w\")asf:json.dump(example.to_dict(exclude_none=True),f)Useto_dict(exlude_none=True)to remove any none-valued fields from the dataclass.\nThis makes the export much more compact and is also the way the official ASAM examples are serialized.DevelopmentPoetryThis package uses Poetry, a tool for dependency management and packaging.\nPlease install it via the official installer fromhere.Working with this repositoryThis repository employs several tools to ensure a constant and good code quality.BlackBlackis a code formatter that we use to assure consistent code style across our projects.\nUse it in-between, or after your code changes, viapoetry run black .in the root directory of this repository.MyPyMypyis a static type checker for Python.\nMypy can be run withpoetry run mypy .in the root directory of this repository.RuffRuffis a Python linter and code formatter.\nIt can be run withpoetry run ruff .in the root directory of this repository.Things left to be implementedNot implemented because they aren't needed yet.Section7.10.2 Semantic segmentation: imageSection7.10.4 MeshSection7.10.5 Mat and binarySection7.10.6 Point2d and Point3dPlease choose a test-driven-development: Find an example JSON in the OpenLABEL spec and create a de- & re-serialization\ntest for it. Then implement the features required to pass the test.Debugging apischemaDebugging problems in (de)serialization with apischema is tricky because apischema is in a compiled state when\ninstalling it from PyPI.\nTo have a better debugging experience, it is advisable to clone theapischema repositorylocally alongside this repository.\nThen, set the apischema dependency asapischema = { path=\"../apischema\", develop=true }inpyproject.toml.\nFollow up withpoetry lock; poetry install --sync.\nNow you can more easily get the keys and values where apischema is throwing exceptions.MyPy specialties in this libraryMapping instead of dictThroughout this repository, you'll find the usage ofMappingtype decorators instead ofdict.\nThe typeMappingiscovariant, whiledictisinvariant(read about ithere).This is important if you want to extend the base OpenLABEL spec with a customer-specific spec that overrides fields\nand narrows down the type, like such:fromdataclassesimportdataclass,fieldfromtypingimportMappingclassLowerCaseStr(str):def__init__(self,val:str):ifnotval.islower():raiseValueError(f\"{val}isn't lower-case\")@dataclassclassAction:name:str=field()@dataclassclassCustomAction(Action):name:LowerCaseStr=field()@dataclassclassOpenLabel:# Setting the type to dict will cause a MyPy erroractions:Mapping[str,Action]=field()@dataclassclassCustomOpenLabel(OpenLabel):actions:dict[str,CustomAction]=field()Why all these_no_defaultdefault values?When creating dataclasses that inherit from each other, an issue that can occur is that a subclass has a field without\na default, while the parent class contains fields with defaults.\nWhen this occurs, you'll seeTypeErrorswhen trying to execute it, and PyCharm will complain too.To fix this, there are several possibilities, the best of them are discussedhere.\nOther possibilities involve using metaclass magic and a deep forest of complicated code that would make the code harder to\nunderstand.The cleanest solution that a) doesn't double the class count, b) is understood by PyCharm, and c) sticks with plain dataclasses,\nis the following:\nOn fields that may not be left empty according to the official OpenLABEL spec, we set adefault_factorythat raises an exception.In order for apischema to work, we have to add theapischema.metadata.requiredin the field's metadata,\notherwise apischema will call the default factory before checking if there even is a value to be deserialized."} +{"package": "uai-pre-import-transform-interface", "pacakge-description": "GeneralThis package provides an Interface that can be implemented to then be turned into a job.\nThe used URI interface (from uai_pre_transform_interface import URI) is basically apathlib.Pathwith some missing functionality.WARNING: URI is not a local fileBeware: Inside understand.ai we will hand cloud paths as URIs. So using the string of a path to open it will fail in these cases!\nE.g. Donotdo things like this:fromuai_pre_import_transform_interfaceimportPreImportTransformInterface,URIfromPILimportImageclassPreImportTransformer(PreImportTransformInterface):deftransform(self,input_path:URI,output_path:URI):path_to_image=input_path/\"images\"/\"00001.png\"withImage.open(str(path_to_image))asim:# This will fail if input path is \"gs://dataset/clip1/\"im.show()instead you could dofromuai_pre_import_transform_interfaceimportPreImportTransformInterface,URIfromPILimportImagefromtempfileimportNamedTemporaryFileclassPreImportTransformer(PreImportTransformInterface):deftransform(self,input_path:URI,output_path:URI):path_to_image=input_path/\"images\"/\"00001.png\"# example for when your method takes readable byteswithImage.open(path_to_image.open(\"rb\"))asim:im.show()# example for when your method needs just a path to the filewithNamedTemporaryFile()astmp:tmp.write(path_to_image.open(\"rb\").read())Image.open(tmp.name)Unit tests do not catch this, unfortunately. One idea to be more save against this could be to not use pathlib.Path directly for debugging but to instead extend path with an implementation that raises an error on usage of__str__.frompathlibimportPathclassDebuPath(Path):def__str__(self):raiseException(\"it is not a good idea to use strings for paths for anything but logging as these paths could point to remote resources.\")ImplementationEvery implementation should provide a python package named by you. Let's usepackage_nameas an example. From this package the following import has to work:frompackage_nameimportPreImportTransformerThis should give your implementation of the interface. To achieve this the__init__.pyoyour package should contain something like this (depending on how you name things):from.my_interface_implementationimportPreImportTransformer__all__:Sequence[str]=[\"PreImportTransformer\"]This is how we will automatically bind your library into our system."} +{"package": "uai-uri-interface", "pacakge-description": "URI IntefaceThis package provides an interface for file access that is basically a subset of pathlib.Path. It is needed because we internally use a path abstraction that allows for exactly this subset of operations. So for debugging methods that take an URI as input you can put in a pathlib.Path while we internally will input our path abstraction."} +{"package": "ualfred", "pacakge-description": "ualfredModernAlfredworkflow library for Python3.NoteThis project is based ondeanishe/alfred-workflow, and make it compatible with Python3.For full usage documentation, see the origin projectdocs.And don't forget to replace import statements fromworkflowtoualfred:# replace this:# from workflow import *# tofromualfredimport*"} +{"package": "uam", "pacakge-description": "# uamUniversal application manager.## Development### Create a docker environment```docker run -dt -v `pwd`:/app --workdir /app --entrypoint bash --name uam -v /var/run/docker.sock:/var/run/docker.sock -v `pwd`/uamlib/:/usr/local/uam python:2docker exec -ti uam bash```### Run Locally1. Run without installation:```python -m uam```2. Install locally and run:```pip install --editable .uam```"} +{"package": "uamconfig-cli", "pacakge-description": "UNKNOWN"} +{"package": "uamc-qed", "pacakge-description": "QED packageQEDstands for quantitative estimation of drug-likeness and the concept has been introduced by Richard Bickerton and coworkersBickerton, G.R.; Paolini, G.V.; Besnard, J.; Muresan, S.; Hopkins, A.L. (2012) \u2018Quantifying the chemical beauty of drugs\u2019, Nature Chemistry, 4, 90-98. This module relies onRDKitas a chem-informatics toolkit.IntroductionThis section is about installing and usingQEDwithin your own Python scripts or as a standalone Python tool.The empirical rationale of theQEDmeasure reflects the underlying distribution of molecular properties including molecular weight, logP, topological polar surface area, number of hydrogen bond donors and acceptors, the number of aromatic rings and rotatable bonds, and the presence of unwanted chemical functionalities.TheQEDresults as generated by this module are not completely identical to those from theoriginal publication. These differences are a consequence of differences within the underlying calculated property calculators used in both methods. For example, discrepancies can be noted in the results from the logP calculations, nevertheless despite the fact that both approaches (Pipeline Pilot in the original publication and RDKit in this implementation) mention to use theWildmann and Crippenmethodology for the calculation of their logP-values. In this respect, Gregory Gerebtzoff has been so kind to perform a refitting of theQEDparameters with logP values generated by RDKit (see rdkit-discuss). These refitted values have been implemented inQEDas the default values; however, the original publication values can still be used if desired.\nThis section assumes you have installed RDKit correctly and that you are familiar with the basic functions of it. It is also recommended to have read the originalQED publication.InstallationThere are two ways to installQED. The first one is by download from theGitHubrepository and installing, and the second way is using Python's standardpipapproach. Both methods are explained below.1. Installing withpipThis is probably the easiest way to installQED. First make sure you havepipinstalled:> pip -Vpip 20.0.2 from /Users/hans/anaconda3/envs/rdkit/lib/python3.7/site-packages/pip (python 3.7)Ifpipis not installed, then install it first by following thesepip installation notes.Now you are ready to installQED:> pip install uamc-qedDepending on yourpythonlocation, it might be that you need admin rights. In that case, type:> sudo pip install uamc-qed2. Alternative manner: download from Github and runsetup.py installDownloadQEDfromGitHub. In this section we assume you have downloaded the file into your~/Downloadsdirectory) and untar this file into this directory:> cd ~/Downloads> sudo tar -xvf uamc-qed-1.0.2.tar.gz> cd uamc-qed-1.0.2You should now have a number of files in your~/Downloads/uamc-qed-1.0.2directory:> ls -lqed-1.0.2/qed-1.0.2/LICENSEqed-1.0.2/README.mdqed-1.0.2/dist/qed-1.0.2/how_to_make_distribution.txtqed-1.0.2/qed/qed-1.0.2/setup.pyMove into thedistdirectory anduntaragain:> cd dist\n> tar -xvf qed-1.0.2.tar.gz\n> cd qed-1.0.2Now install with Python:> python setup.py installThis process creates aqedfolder with all theqedfiles into your default Python site-package install directory. It might be that you need to get root permissions:> sudo python setup.py installCheck your installation by launchingPython:>>>fromqedimportqed>>>fromrdkitimportChem>>>m=Chem.MolFromSmiles('c1ccccc1')>>>qed.default(m)0.44619898311523704Using QEDTheqed()function takes as argument a RDKit molecule and returns the corresponding QED value calculated from it.\nTheqed()function comes in three flavors, each differing in the relative weight that is imposed on the underlyingmolecular descriptors. These three flavors correspond to the three differentQEDmeasures that were described in the original publication:QEDw,maxusing the set of weights that give maximal information content.QEDw,mousing the mean weights of the optimal 1,000 weight combinations that give the highest information content.QEDw,uwith all weights as unity, hence unweighted.Specifying the required QED weighting scheme inQEDis done using the corresponding function:qed.weights_mean()uses the mean weighting scheme and corresponds to QEDw,mo. Another name for this function isqed.default().qed.weights_max()specifies the max weighting scheme and corresponds to QEDw,max.qed.weights_none()specifies unit weights and corresponds to QEDw,u.and exemplified below:>>>fromqedimportqed>>>fromrdkitimportChem>>>m=Chem.MolFromSmiles('c1ccccc1')>>>qed.default(m)0.44619898311523704>>>qed.weights_mean(m)0.44619898311523704>>>qed.weights_max(m)0.4733526950948539>>>qed.weights_none(m)0.3047153431243204As already mentioned above, the current implementation ofQEDuses the refitted logP parameters from Gregory Gerebtzoff. However, the original values can still be used by specifyingFalseas second argument to the appropriate function call:>>>qed.default(m,False)0.4426283718993647>>>qed.weights_mean(m,False)0.4426283718993647>>>qed.weights_max(m,False)0.4706596045646091>>>qed.weights_none(m,False)0.3021185764176498TheQEDmodule also provides its own test set:>>>test=qed.test_data()>>>fornameintest:print(test[name],name)...Nc1nc(NC2CC2)c2ncn([C@@H]3C[C@H](CO)C=C3)c2n1AbacavirCC(=O)NCCCS(O)(=O)=OAcamprosateCCCC(=O)Nc1ccc(OCC(O)CNC(C)C)c(c1)C(C)=OAcebutololCC(=O)Nc1ccc(O)cc1AcetaminophenCC(=O)Nc1nnc(s1)S(N)(=O)=OAcetazolamideCC(=O)c1ccc(cc1)S(=O)(=O)NC(=O)NC1CCCCC1AcetohexamideCC(=O)c1ccc2Sc3ccccc3N(CCCN3CCN(CCO)CC3)c2c1AcetophenazineFc4ccc(C1CCNCC1COc3ccc2OCOc2c3)cc4ParoxetineCc1oncc1C(=O)Nc2ccc(C(F)(F)F)cc2LeflunomideCN1C4CCCC1CC(NC(=O)c2nn(C)c3ccccc23)C4GranisetronCCCN2CC(CSC)CC1c3cccc4[nH]cc(CC12)c34PergolideCCc3c(C)[nH]c2CCC(CN1CCOCC1)C(=O)c23MolindoneCCCCCCCCCCCCCCCC(=O)OCC(NC(=O)C(Cl)Cl)C(O)c1ccc([N+]([O-])=O)cc1ChloramphenicalPalmitateCCCCCCCCCCCCCCCOC(=O)C2C(O)C(O)C(C(NC(=O)C1CC(CCC)CN1C)C(C)Cl)OC2SCClindamycinPalmitateCCOc3nc2cccc(C(=O)OC(C)OC(=O)OC1CCCCC1)c2n3Cc6ccc(c4ccccc4c5nn[nH]n5)cc6CandesartanCilexetilCN(C)CCC=c2c1ccccc1sc3ccc(Cl)cc23ChlorprothixeneO=c3c(O)c(C2CCC(c1ccc(Cl)cc1)CC2)c(=O)c4ccccc34AtovaquoneCN(C)CCCN3c1ccccc1CCc2ccc(Cl)cc23ClomipramineCN4CCCC(CC3c1ccccc1Sc2ccccc23)C4MethixeneCCN(CC)C(C)Cn3c1ccccc1sc2ccccc23EthopropazineN=C(CCSCc1csc(N=C(N)N)n1)NS(N)(=O)=OFamotidineCNC(=NCCSCc1nc[nH]c1C)NC#N CimetidineCCCCCNC(=N)NN=Cc1c[nH]c2ccc(CO)cc12TegaserodC=CC3=C(C(=O)O)N2C(=O)C(NC(=O)C(=NO)c1csc(N)n1)C2SC3CefdinirCC5(C)SC4C(NC(=O)C(C(=O)Oc2ccc1CCCc1c2)c3ccccc3)C(=O)N4C5C(=O)OCarbenicillinIndanylOne can inspect the individual properties that are used to calculate the Qed value by calling theproperties()function:>>>fornameintest:...mol=Chem.MolFromSmiles(test[name])...p=qed.properties(mol)...print(\"%6.2f\\t%6.3f\\t%6d\\t%6d\\t%6.2f\\t%6d\\t%6d\\t%6d\\t%6.3f\\t%-s\"%(p[0],p[1],p[2],p[3],p[4],p[5],p[6],p[7],qed.default(mol),name))...286.341.09263101.884210.737Abacavir181.21-0.6004283.474020.467Acamprosate336.432.3655387.6610110.571Acebutolol151.161.3512249.331110.602Acetaminophen222.25-0.85652115.042110.662Acetazolamide324.402.2104292.344110.833Acetohexamide411.573.4926147.027210.688Acetophenazine329.373.3274139.724200.917Paroxetine270.213.2543155.132200.896Leflunomide312.422.3183150.162200.927Granisetron314.504.2712119.034200.871Pergolide276.381.9633145.333100.923Molindone561.556.94162118.7721150.056ChloramphenicalPalmitate663.416.27983108.3322030.071ClindamycinPalmitate610.676.319101143.3410520.141CandesartanCilexetil315.875.188203.243300.629Chlorprothixene366.845.5053154.372200.741Atovaquone314.864.528206.484200.782Clomipramine309.485.015203.242200.735Methixene312.485.020306.485200.734Ethopropazine337.46-0.55865173.337130.263Famotidine252.350.5975388.895150.239Cimetidine301.392.2983596.297240.235Tegaserod395.42-0.17284158.215140.239Cefdinir494.572.49672113.016240.274CarbenicillinIndanyl>>>print(\" MW\\tALOGP\\tHBA\\tHBD\\tPSA\\tROTB\\tAROM\\tALERTS\\tQED\\tNAME\")MWALOGPHBAHBDPSAROTBAROMALERTSQEDNAMERevision historyVersion 1.0.2Added to the PyPi repository to enable installation usingpip.Version 1.0.1Incorporation of the refitted logP parameters of Gregory Gerebtzoff and making these values default (rdkit-discuss).Modification of theqed()function to enable the selection of the original parameters, if desired.DOI identifierDOI:10.5281/zenodo.4293730"} +{"package": "uamc-spectrophore", "pacakge-description": "SpectrophoresThis module contains python code to calculatespectrophoresfrom molecules. It is using theRDKitandnumbatoolkits.The technology and its applications have been described inJournal of Cheminformatics(2018)10, 9. The paper is also included in this distribution.Thespectrophorecode can be used in two ways:As a standalone program to convert the molecules in a sd-file into their correspondingspectrophores;As apythonmodule to import in your ownpythoncode.In the following sections, both usages will be documented.Installation1. Installation of RDKit and NumbaWe recommend to install bothRDKitandNumbausingAnaconda. Ifcondais not yet available on your system, you should install this first following the instructions on theAnaconda website.Numbais an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code.RDKitis open source cheminformatics software that provides the code to work with molecules.The easiest way to have everything installed is usingconda. First create a suitable environment in which you will install thespectrophoretechnology:> conda create --name spectrophore python=3This will install a newcondaenvironment with Python 3.9 installed in it. Now activate this environment:> conda activate spectrophoreNumbaandrdkitcan now be installed as follows (make sure you first activated thespectrophoreenvironment):> conda install numba> conda install cudatoolkit> conda install -c conda-forge rdkitYou can test therdkitinstallation by opening apythonsession from your command-line (assuming you are still in the activatedspectrophoreenvironment) and typing the following:>>>fromrdkitimportChem>>>mol=Chem.MolFromSmiles(\"C1CCCC1\")>>>print(mol.GetNumAtoms())5Similarly, you can test thenumbainstallation with this smallpythonsnippet:>>>importnumba>>>numba.__version__'0.51.2'Withnumba -scommand you can also check whether you have a CUDA device installed (check for the section__CUDA Information__).2. Installing the spectrophore codeWith thespectrophoreenvironment still active, you can now easily install thespectrophoremodule using:> pip install uamc-spectrophoreCheck the installation by opening apythonsession and entering:>>>fromspectrophoreimportspectrophore>>>spectrophore.__version__'1.2.0'1. Usage as a standalone programAfter installation, one should be able to use thespectrophore.pycode as a standalone program to calculatedspectrophoresfrom a sd-file with molecules. You can find out wherespectrophore.pyis located by starting apythonshell and typing:>>>fromspectrophoreimportspectrophore>>>spectrophore.__file__'/Users/hans/anaconda3/envs/spectrophore/lib/python3.8/site-packages/spectrophore/spectrophore.py'Either you can use this full path to call thespectrophore.pycode, or you can add it to your $PATH environment variable.To usespectrophore.py, type the following on the command-line:> spectrophore.py -hThis will provide you with all details on how to calculatespectrophoresfrom a sd-file:usage: spectrophore.py [-h] [-n {none,mean,all,std}] [-s {none,unique,mirror,all}] [-a {1,2,3,4,5,6,9,10,12,15,18,20,30,36,45,60,90,180}][-r RESOLUTION] [-p MAX_WORKERS] -i INFILE -o OUTFILECalculate spectrophoresoptional arguments:-h, --help show this help message and exit-n {none,mean,all,std}, --norm {none,mean,all,std}normalization setting (default: all)-s {none,unique,mirror,all}, --stereo {none,unique,mirror,all}stereo setting (default: none)-a {1,2,3,4,5,6,9,10,12,15,18,20,30,36,45,60,90,180}, --accuracy {1,2,3,4,5,6,9,10,12,15,18,20,30,36,45,60,90,180}accuracy setting (default: 20)-r RESOLUTION, --resolution RESOLUTIONresolution setting (>0) (default: 3)-p MAX_WORKERS, --np MAX_WORKERSnumber of processors to use; -1 is all processors (default: -1)required arguments:-i INFILE, --in INFILEinput sdf file (default: None)-o OUTFILE, --out OUTFILEoutput spectrophore file (default: None)2. Usage as apythonmodule2.1. IntroductionOnce you have installed all required tools and theuamc-spectrophorepackage, you are ready to use the tool. In its most simple form,spectrophorescan be calculated as follows:>>>fromspectrophoreimportspectrophore>>>fromrdkitimportChem>>>fromrdkit.ChemimportAllChem>>>mol=Chem.MolFromSmiles(\"c1ncncc1\")>>>mol=Chem.AddHs(mol)>>>AllChem.EmbedMolecule(mol,randomSeed=1)0>>>calculator=spectrophore.SpectrophoreCalculator(normalization='none')Probesinitialised:48numberofprobesintotal12probesareusedduetotheimposedstereoflag>>>calculator.calculate(mol)array([1.409246,2.021652,1.6011626,3.034698,2.4150815,5.0872273,2.285813,1.7250485,3.436644,4.0012817,5.092206,2.9844987,0.6417792,0.8024898,4.8707156,4.870761,2.8789856,4.104702,1.9413302,3.5960448,4.9019723,4.151822,4.5394773,5.766127,44.79124,71.551796,106.82244,106.82059,49.73703,61.662792,23.50798,81.88448,77.47026,67.52185,57.44229,112.96884,0.6794604,1.1607243,2.470075,2.470103,1.0203087,1.1483352,0.51142335,1.7433033,1.8094715,1.3015395,1.2431506,2.5163455],dtype=float32)In the example shown, the first three lines import the required modules: modulespectrophorefor the calculation of spectrophores, moduleChemto generate a RDKit molecule from a smiles string, and moduleAllChemto generate a 3D-conformation from the molecule. Next, a molecule is created from a smiles string (line 4), and a conformation is then generated at the 6'th line after adding hydrogen atoms on the 5'th line. Finally, on lines 7 and 8, aSpectrophoreCalculatorobject is generated and this object is then used to calculate aspectrophoredescriptor (line 8), which consists in its default form of 4 * 12 numbers.Note: a few words on the shape of aspectrophore:Eachspectrophoreconsists of a set of floating point numbers, and this set is always a multiple of 4. The actual number count depends on how stereochemistry is treated in the calculation of spectrophores; this is controlled by thestereo()method:stereo(\"none\"): the total number of numbers in aspectrophoreis 48 (4 * 12; default),stereo(\"unique\"): the total number of numbers in aspectrophoreis 72 (4 * 18),stereo(\"mirror\"): the total number of numbers in aspectrophoreis 72 (4 * 18),stereo(\"all\"): the total number of numbers in aspectrophoreis 144 (4 * 36).Whatever the actual number ofspectrophorepoints, these are always calculated according the same atomic properties. For example, consider aspectrophoreof 4npoints, then these points represent the following:Points 1 ton: representing the interaction energies between theatomic partial chargesand each of thenboxes;Pointsn+1 to 2n: representing the interaction energies between theatomic lipophilicitiesand each of thenboxes;Points 2n+1 to 3n: representing the interaction energies between theatomic shape deviationsand each of thenboxes;Points 3n+1 to 4n: representing the interaction energies between theatomic electrophilicitiesand each of thenboxes.Please have a look at the original publication form more information about the way these interaction energies are calculated, and what thestereo()method actually means.If a molecule contains more than one 3D-conformation, then one may specify which conformation should be used for the calculation ofspectrophores. As an example, consider the following code:>>>calculator=spectrophore.SpectrophoreCalculator(normalization='none')Probesinitialised:48numberofprobesintotal12probesareusedduetotheimposedstereoflag>>>aspirin=Chem.MolFromSmiles(\"CC(Oc1ccccc1C(O)=O)=O\")>>>mol=Chem.AddHs(mol)>>>cids=AllChem.EmbedMultipleConfs(aspirin,numConfs=3,randomSeed=1)>>>print(len(cids))3>>>foriinrange(len(cids)):calculator.calculate(aspirin,i)...array([2.964628,3.1078947,2.927014,4.7348037,7.507005,6.7752705,4.694607,4.9843326,6.566493,8.246073,10.165346,6.63523,4.858508,8.002102,6.8100824,8.816333,15.715073,19.571812,10.928973,14.395827,17.003227,18.447824,25.714355,15.146796,72.9549,98.34449,169.34996,182.39804,131.36954,131.15866,65.37012,130.0362,162.26236,149.89626,179.36638,198.5693,2.2463505,3.1564593,5.1663566,5.612588,4.058919,4.409714,2.2037854,4.4034805,4.9583206,5.239315,5.461795,6.264689],dtype=float32)array([2.863708,3.1190798,2.9663007,4.770968,7.393107,7.3158054,4.9012723,5.10262,6.548969,8.572092,10.425214,6.4823613,4.787042,8.08808,6.631177,8.741646,16.067795,19.49238,10.819519,14.260894,16.789541,18.33067,25.610632,14.279321,69.21315,96.67396,170.67822,184.54782,119.22876,135.03757,59.888947,119.49558,173.35124,145.16624,180.47777,187.60854,2.1962543,3.108443,5.2100787,5.6747303,3.8506951,4.435027,2.1061015,4.0988173,5.171605,5.103154,5.384299,5.955127],dtype=float32)array([3.0309825,3.435472,2.8768196,4.706544,7.5557814,6.4479575,4.55689,4.953575,6.4871607,8.706506,8.518427,6.3662963,4.9284625,9.355401,6.6179686,8.523829,15.459739,19.284777,10.792515,13.991817,16.795666,18.597605,24.084375,13.117221,77.639145,120.10927,169.49625,166.18648,131.14139,144.46242,72.4695,149.30933,140.35475,155.59204,130.84991,174.86932,2.4413445,3.8801153,5.1489463,4.834638,4.0795846,4.013626,2.4914305,4.5840054,4.270138,5.335861,4.6315002,5.6371183],dtype=float32)One can easily visualisespectrophoresby plotting the actual values. For example, consider the following snippet:>>>importmatplotlib.pyplotasplt>>>mol=Chem.MolFromSmiles(\"CC(CCC1=CC=CC=C1Cl)N1CCOCC1\")>>>mol=Chem.AddHs(mol)>>>cids=AllChem.EmbedMultipleConfs(mol,numConfs=10,randomSeed=1)>>>spectrophores=[]>>>forcidincids:spectrophores.append(calculator.calculate(mol,cid))...>>>foriinrange(len(spectrophores)):plt.plot(range(1,49),spectrophores[i],label='Conf%d'%(i+1))...[][][][][][][][][][]>>>plt.legend(loc='upper left')>>>plt.grid()>>>plt.savefig(\"spectrophore/images/exampleplot1.png\")which generates the following plot:Similarly, one can easily compare thespectrophoresfrom two different molecules, and quantify the difference:>>>plt.close()>>>spectrophores=[]>>>mols=[Chem.MolFromSmiles(\"ClC(Br)(I)F\"),Chem.MolFromSmiles(\"CC(CCC1=CC=CC=C1Cl)N1CCOCC1\")]>>>foriinrange(2):...mols[i]=Chem.AddHs(mols[i])...AllChem.EmbedMolecule(mols[i],randomSeed=1)...spectrophores.append(calculator.calculate(mols[i]))...00>>>foriinrange(2):plt.plot(range(1,49),spectrophores[i],label='Molecule%d'%(i+1))...[][]>>>plt.grid()>>>plt.savefig(\"spectrophore/images/exampleplot2.png\")>>>fromscipy.spatialimportdistance>>>distance.euclidean(spectrophores[0],spectrophores[1])2060.65478515625From the last example, it is clear that the actualspectrophorevalues may differ a lot depending on the type of molecule. Also, the absolute values are depending on the property type, with some properties leading to large values (e.g. shape deviation) and others very small. For this reason, a number of normalisation methods are provided as shown below.2.2. Module methodsresolution()Theresolution()method controls the smallest distance between the molecule and the surrounding box. By default this value is set to 3.0 A. Theresolution()can be specified at the moment of class creation, or later on using theresolution()method:>>>mol=Chem.MolFromSmiles(\"ClC(Br)(I)F\")>>>AllChem.EmbedMolecule(mol,randomSeed=1)0>>>calculator=spectrophore.SpectrophoreCalculator(normalization='none')# Default of 3.0Probesinitialised:48numberofprobesintotal12probesareusedduetotheimposedstereoflag>>>print(calculator.calculate(mol)[0])2.9869986>>>calculator=spectrophore.SpectrophoreCalculator(normalization='none',resolution=3.0)Probesinitialised:48numberofprobesintotal12probesareusedduetotheimposedstereoflag>>>print(calculator.calculate(mol)[0])2.9869986>>>calculator=spectrophore.SpectrophoreCalculator(normalization='none',resolution=5.0)Probesinitialised:48numberofprobesintotal12probesareusedduetotheimposedstereoflag>>>print(calculator.calculate(mol)[0])1.341883>>>calculator.resolution(10.0)>>>print(calculator.calculate(mol)[0])0.3347178The larger the resolution value (e.g. 10.0versus3.0 A), the smaller the interaction energies and correspondingspectrophorevalues.Calling theresolution()method without an argument returns the current resolution value:>>>calculator.resolution()10.0accuracy()Theaccuracy()method controls the angular stepsize by which the molecule is rotated within the cages. By default this value is set to 20\u00b0. This parameter can be modified either at class creation, or using theaccuracy()method later on. The accuracy should be an integer fraction of 180, hence 180 modulusaccuracyshould be equal to 0. The smaller the accuracy value (meaning smaller angular stepsizes), the longer the computation time:>>>calculator=spectrophore.SpectrophoreCalculator(accuracy=20.0,normalization='none')# DefaultProbesinitialised:48numberofprobesintotal12probesareusedduetotheimposedstereoflag>>>print(calculator.calculate(mol)[0])2.9869986>>>calculator=spectrophore.SpectrophoreCalculator(normalization='none')Probesinitialised:48numberofprobesintotal12probesareusedduetotheimposedstereoflag>>>print(calculator.calculate(mol)[0])2.9869986>>>calculator=spectrophore.SpectrophoreCalculator(accuracy=2.0,normalization='none')Probesinitialised:48numberofprobesintotalOnlyusing12probes>>>print(calculator.calculate(mol)[0])# Takes some time3.0315504>>>100.0*(3.0315504-2.9869986)/3.03155041.469604463775361Calling theaccuracy()method without an argument returns the current accuracy value:>>>calculator.accuracy()2normalization()With thenormalization()method, one can specify the type ofspectrophorenormalization. There are four possibilities:normalization(\"none\"): no normalization is applied and thespectrophorevalues are the raw calculated interaction energies (multiplied by -100),normalization(\"mean\"): for each property, the average value is calculated and each of the individualspectrophoreproperty value are reduced by these mean values. This centers the calculated values around 0,normalization(\"std\"): for each property, the standard deviation is calculated and each of the individualspectrophoreproperty value is divided by these standard deviations,normalization(\"all\"): each spectrophore value is normalized by mean and standard deviation. This is the fefault option.The default value is \"all\".>>>calculator.accuracy(20)>>>calculator.normalization(\"none\")>>>spec=calculator.calculate(mol)>>>print(spec[:12])[2.98699862.70232151.80297094.4689097.37554457.25227454.11233474.05599365.90845978.56496059.3282566.22969]>>>sum(spec[:12])64.78871297836304>>>calculator.normalization(\"mean\")>>>spec=calculator.calculate(mol)>>>print(spec[:12])[-2.4120607-2.6967378-3.5960884-0.93015051.97648531.8532152-1.2867246-1.34306570.509400373.16590123.92919640.8306308]>>>sum(spec[:12])1.430511474609375e-06>>>calculator.normalization(\"std\")>>>spec=calculator.calculate(mol)>>>print(spec[:12])[1.29241111.16923740.78010741.93360233.19124223.13790581.77932021.75494272.55646563.70587734.0361392.695455]>>>sum(spec[:12])28.032706141471863>>>calculator.normalization(\"all\")>>>spec=calculator.calculate(mol)>>>print(spec[:12])[-1.0436476-1.1668214-1.5559514-0.402456460.855183360.80184704-0.5567385-0.581116140.220406771.36981841.70008020.35939637]>>>sum(spec[:12])6.854534149169922e-07Using a normalization over 'all' makes it more easier to comparespectrophoresbetween molecules:>>>plt.close()>>>mols=[Chem.MolFromSmiles(\"ClC(Br)(I)F\"),Chem.MolFromSmiles(\"CC(CCC1=CC=CC=C1Cl)N1CCOCC1\")]>>>spectrophores=[]>>>foriinrange(2):...mols[i]=Chem.AddHs(mols[i])...AllChem.EmbedMolecule(mols[i],randomSeed=1)...spectrophores.append(calculator.calculate(mols[i]))...00>>>foriinrange(2):plt.plot(range(1,49),spectrophores[i],label='Molecule%d'%(i+1))...[][]>>>plt.legend()>>>plt.grid()>>>plt.savefig(\"spectrophore/images/exampleplot3.png\")>>>fromscipy.spatialimportdistance>>>distance.euclidean(spectrophores[0],spectrophores[1])8.374645233154297The same holds true when comparingspectrophoresfrom different conformations:>>>plt.close()>>>spectrophores=[]>>>mol=Chem.MolFromSmiles(\"CC(CCC1=CC=CC=C1Cl)N1CCOCC1\")>>>mol=Chem.AddHs(mol)>>>cids=AllChem.EmbedMultipleConfs(mol,numConfs=10,randomSeed=1)>>>calculator.normalization(\"all\")>>>forcidincids:spectrophores.append(calculator.calculate(mol,cid))...>>>foriinrange(len(spectrophores)):plt.plot(range(1,49),spectrophores[i],label='Conf%d'%(i+1))...[][][][][][][][][][]>>>plt.legend(loc='upper left')>>>plt.savefig(\"spectrophore/images/exampleplot4.png\")>>>fromscipy.spatialimportdistance>>>distance.euclidean(spectrophores[0],spectrophores[1])5.974719524383545>>>distance.euclidean(spectrophores[0],spectrophores[2])6.081935882568359>>>distance.euclidean(spectrophores[1],spectrophores[2])3.7508902549743652stereo()Thestereo()method specifies the kind of cages to be used. The reason for this is that some of the cages that are used to calculatespectrophoreshave a stereospecific distribution of the interaction points:There are four possibilities:stereo(\"none\"): no stereospecificity (default).Spectrophoresare generated using cages that are not stereospecific. For most applications, thesespectrophoreswill suffice,stereo(\"unique\"): unique stereospecificity.Spectrophoresare generated using unique stereospecific cages,stereo(\"mirror\"): mirror stereospecificity. Mirror stereospecificspectrophoresarespectrophoresresulting from the mirror enantiomeric form of the input molecules,stereo(\"all\"): all cages are used. This results in the longestspectrophoresand should only in specific cases be used.The differences between the corresponding data points of unique and mirror stereospecificspectrophoresare very small and require very long calculation times to obtain a sufficiently high quality level. This increased quality level is triggered by theaccuracysetting and will result in calculation times being increased by at least a factor 100. As a consequence, it is recommended to apply this increased accuracy only in combination with a limited number of molecules, and when the small differences between the stereospecificspectrophoresare really critical. However, for the vast majority of virtual screening applications, this increased accuracy is not required as long as it is not the intention to draw conclusions about differences in the underlying molecular stereoselectivity. Non-stereospecificspectrophoreswill therefore suffice for most applications.3. InterpretingspectrophoresAspectrophoreis a vector of real number and has a certain length. The length depends on the usedstereomethod and the number of properties. The standard setting uses a set of non-stereospecific probes in combination with four properties:property 1: atomic partial chargesproperty 2: atomic lipophilicitiesproperty 3: atomic shape deviationsproperty 4: atomic electrophilictiesThe combination of four properties and the set of non-stereospecific probes leads to aspectrophorevector length of 48. The use of other probes leads to other vector lengths, as summarised in this table:StereospecificityNumber of probesNumber of propertiesLengthnone12448unique18472mirror18472all364144The general layout of aspectrophore, irrespective of its length, is always:Property 1Property 2Property 3Property 4probe 1..probenprobe 1..probenprobe 1..probenprobe 1..probenmeaning that the firstnvalues (withnbeing the number of probes) are calculated using property 1 (partial charges), then anothernvalues (n+1 up to 2n) calculated using property 2 (lipophilicities), and so forth.4. Release updates1.2.0:Switched to numpy.float32 type to achieve major speedup1.1.0:Updated and optimised the NumPy codeBug fixesIntroduced NumbaMade the 'all' normalization method the default oneAdded a test suite1.0.1: First official release on PyPi5. Reference and citationIf you use thespectrophoretechnology in your own research work, please cite as follows:Gladysz, R.; Mendes Dos Santos, F.; Langenaeker, W.; Thijs, G.; Augustyns, K.; De Winter, H. (2018) 'Spectrophores as one-dimensional descriptors calculated from three-dimensional atomic properties: applications ranging from scaffold hopping to multi-target virtual screening',J. Cheminformatics10, 9."} +{"package": "uamd", "pacakge-description": "uamd(User Agent Mobile Detect) is for detecting japanese mobile phone\nfrom HTTP_USER_AGENT and return device information include UID from HTTP Header\nand spoof check by CIDR of each carrierInstallsudo pip install uamdor:sudo pip install git+git://github.com/lambdalisue/uamd.git#egg=uamdRequired (Automatically installed)IPyBeautifulSoupHow to use>>> META = {\n>>> 'HTTP_USER_AGENT': u\"J-PHONE/2.0/J-SH02\",\n>>> 'HTTP_X_JPHONE_UID': u\"XXXXXXX\",\n>>> 'REMOTE_ADDR': u\"123.108.237.0\", # Valid IP for Softbank (2011/03/22)\n>>> }\n>>> deice = uamd.detect(META)\n>>> device.name\nu'J-SH02'\n>>> device.type\nu'J-Phone'\n>>> device.uid\nu'XXXXXXX'\n>>> device.spoof\nFalse"} +{"package": "uamf", "pacakge-description": "uArray Meta File"} +{"package": "uaml", "pacakge-description": "Uncertainty-aware machine learningPython package for uncertainty-aware classification built on top of Scikit-learn.Descriptionuamlis a Python package for uncertainty-aware machine learning based on probabilistic ensembles and the Jensen\u2013Shannon divergence. Currently, it is built on top of Scikit-learn and supports all probabilistic base classifiers.InstallationClone this repositorytfmortie/uamland runpip install . -r requirements.txtor install by means ofpip install uaml.ExampleThe uncertainty-aware classifier is provided throughuaml.multiclass.UAClassifier. Below we show a minimal working and more elaborate example.Basic usageWe start by importing some packages that we will need throughout the example:fromsklearn.datasetsimportmake_moonsfromsklearn.linear_modelimportLogisticRegressionfromsklearn.model_selectionimporttrain_test_split# some example dataX,y=make_moons(n_samples=100,noise=0.1,random_state=0)X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=.4,random_state=42)Creating an uncertainty-aware classifier, withLogisticRegressionas underlying probabilistic model, is done as follows:fromuaml.multiclassimportUAClassifier# use LogisticRegression as base (probabilistic) estimatorest=LogisticRegression(solver=\"liblinear\")# construct and fit an uncertainty-aware classifier with 500 estimators and parallelize over 5 coresclf=UAClassifier(est,ensemble_size=500,train_ratio=0.5,n_jobs=5)UAClassifierfollows the Scikit-learn API, as illustrated below:# fit our classifierclf.fit(X_train,y_train)# obtain predictions by means of majority votingpreds=clf.predict(X_test,avg=True)# obtain probabilitiesprobs=clf.predict_proba(X_test,avg=True)Finally, let's calculate aleatoric and epistemic uncertainty:ua,ue=clf.get_uncertainty(X_test)VisualisationIn a next example, let's see how aleatoric and epistemic uncertainty evaluate in the feature space of the \"two moons\" dataset for different classifiers:importnumpyasnpimportmatplotlibmatplotlib.use('Agg')importmatplotlib.pyplotaspltfromuaml.multiclassimportUAClassifierfromsklearn.model_selectionimporttrain_test_splitfromsklearn.preprocessingimportStandardScalerfromsklearn.datasetsimportmake_moonsfromsklearn.neural_networkimportMLPClassifierfromsklearn.neighborsimportKNeighborsClassifierfromsklearn.svmimportSVCfromsklearn.treeimportDecisionTreeClassifierfromsklearn.discriminant_analysisimportQuadraticDiscriminantAnalysisfromsklearn.datasetsimportmake_moonsfromsklearn.treeimportDecisionTreeClassifier# different estimators for UAClassifierclassifiers={\"5-NN\":KNeighborsClassifier(5),\"Linear SVM\":SVC(kernel=\"linear\",C=0.025,probability=True),\"RBF SVM\":SVC(gamma=1,C=1,probability=True),\"Decision Tree\":DecisionTreeClassifier(max_depth=5),\"Simple Neural Network\":MLPClassifier(alpha=1,max_iter=1000),\"QDA\":QuadraticDiscriminantAnalysis()}# create datasetX,y=make_moons(n_samples=100,noise=0.1,random_state=0)X=StandardScaler().fit_transform(X)X_train,X_test,y_train,y_test=\\train_test_split(X,y,test_size=.4,random_state=42)x_min,x_max=X[:,0].min()-1,X[:,0].max()+1y_min,y_max=X[:,1].min()-1,X[:,1].max()+1xx,yy=np.meshgrid(np.arange(x_min,x_max,0.02),np.arange(y_min,y_max,0.02))# create plotcm=plt.cm.viridisfig,ax=plt.subplots(len(classifiers),3,figsize=(10,10))fori,clfinenumerate(classifiers.keys()):# fit classifiers and obtain predictions and uncertainty estimatesmodel=classifiers[clf]clf=UAClassifier(model,500,0.8,n_jobs=5,verbose=1)clf.fit(X_train,y_train)Zp=clf.predict(np.c_[xx.ravel(),yy.ravel()],avg=True)Za,Ze=clf.get_uncertainty(np.c_[xx.ravel(),yy.ravel()])# construct contour plotZp=Zp.reshape(xx.shape)Za=Za.reshape(xx.shape)Ze=Ze.reshape(xx.shape)ax[i,0].contourf(xx,yy,Zp,cmap=cm,alpha=.8)ifi==0:ax[i,0].set_title(\"Prediction\")# prediction plot# plot the training pointsax[i,0].scatter(X_train[:,0],X_train[:,1],c=y_train,cmap=cm)# plot the testing pointsax[i,0].scatter(X_test[:,0],X_test[:,1],c=y_test,cmap=cm,alpha=0.6)ax[i,0].set_xlim(xx.min(),xx.max())ax[i,0].set_ylim(yy.min(),yy.max())# aleatoric uncertainty plotax[i,1].contourf(xx,yy,Za,cmap=cm,alpha=.8)ifi==0:ax[i,1].set_title(\"Aleatoric uncertainty\")# plot the training pointsax[i,1].scatter(X_train[:,0],X_train[:,1],c=y_train,cmap=cm)# plot the testing pointsax[i,1].scatter(X_test[:,0],X_test[:,1],c=y_test,cmap=cm,alpha=0.6)ax[i,1].set_xlim(xx.min(),xx.max())ax[i,1].set_ylim(yy.min(),yy.max())# epistemic uncertainty plotax[i,2].contourf(xx,yy,Ze,cmap=cm,alpha=.8)ifi==0:ax[i,2].set_title(\"Epistemic uncertainty\")# plot the training pointsax[i,2].scatter(X_train[:,0],X_train[:,1],c=y_train,cmap=cm)# plot the testing pointsax[i,2].scatter(X_test[:,0],X_test[:,1],c=y_test,cmap=cm,alpha=0.6)ax[i,2].set_xlim(xx.min(),xx.max())ax[i,2].set_ylim(yy.min(),yy.max())ReferencesAleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods, H\u00fcllermeier et al., Machine learning (2021)"} +{"package": "uamobile", "pacakge-description": "WSGIUserAgentMobile is HTTP mobile user agent string parser. It\u2019ll be useful in parsing HTTP_USER_AGENT strings of (mainly Japanese) mobile devices.This library is ported from similar libraries in Perl and PHP and owes a lot to them.HTTP-MobileAgent?http://search.cpan.org/~kurihara/HTTP-MobileAgent-0.26/lib/HTTP/MobileAgent.pmPEAR::Net_UserAgent_Mobile? http://pear.php.net/package/Net_UserAgent_Mobile"} +{"package": "uamqp", "pacakge-description": "uAMQP for PythonAn AMQP 1.0 client library for Python.DisclaimeruAMQP for Python requires Python 3.6+ starting from v1.5, and Python 2.7 is no longer supported. If Python 2.7 is required, please install uAMQP v1.4.3:$pipinstalluamqp==1.4.3InstallationWheels are provided for most major operating systems, so you can install directly with pip:$pipinstalluamqpIf you are running a Linux distro that does not supportManyLinux1or you need to customize the build based on your system settings and packages, you can install from source:$apt-getupdate$apt-getinstall-ybuild-essentiallibssl-devuuid-devcmakelibcurl4-openssl-devpkg-configpython3-devpython3-pip$pip3installuamqp--no-binary:all:If you are running Alpine, you can install from source:$apkadd--updatepython3py-pippython3-devcmakegccg++openssl-devbuild-base$pip3installuamqp--no-binary:all:If you are running Red Hat, you can install from source:$yuminstallcmakegccgcc-c++makeopenssl-develpython3-devel$pip3installuamqp--no-binary:all:DocumentationReference documentation can be found here:docs.microsoft.com/python/api/uamqp/uamqp.Developer SetupIn order to run the code directly, the Cython extension will need to be build first.Pre-requisitesWindows: Setup abuild environment.Linux: Install dependencies as descriped above in the installation instructions.MacOS: Install cmake using Homebrew:$brewinstallcmakeBuilding the extensionThis project has two C library dependencies. They are vendored in this repository in these versions:Azure uAMQP for C@2021-11-16Azure C Shared Utility@2021-11-15To build, start by creating a virtual environment and installing the required Python packages:$python-mvenvenv$env/Scripts/activate(env)$pipinstall-rdev_requirements.txtNext, run the build command:$pythonsetup.pybuild_ext--inplaceTestsThe tests can be run from within the virtual environment. The extension must be built first using the instructions above.(env)$pytestProvide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.ContributingThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visithttps://cla.microsoft.com.When you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.This project has adopted theMicrosoft Open Source Code of Conduct.\nFor more information see theCode of Conduct FAQor\ncontactopencode@microsoft.comwith any additional questions or comments.Release History1.6.8 (2024-01-29)Incorporate fixes fromPR1.6.7 (2024-01-17)Fixes for CVE-2024-216461.6.6 (2023-11-16)Added support for python 3.111.6.5 (2023-07-12)Few more updates to submodules to support OpenSSL 3.0 compilation1.6.4 (2023-02-09)Updated OpenSSL dependency to 1.1.1tUpdated submodules to support OpenSSL 3.0 compilationRemoved dependency on sixFixed a bug that caused the wrong port to selected for websockets when a port was not passed in1.6.3 (2022-10-27)Publish 3.11 wheels1.6.2 (2022-10-27)Added support for python 3.11Updated OpenSSL dependency to 1.1.1qUpdated cython dependency to 0.29.32Dropped support for manylinux2010Using cibuildwheel to generate wheels1.6.1 (2022-10-11)Added support for handling of duplicate certificates inazure-c-shared-utilitydependency by usingCERT_STORE_ADD_REPLACE_EXISTINGparameter in theCertAddEncodedCertificateToStorefunction call. (azure-sdk-for-python issue #26034)1.6.0 (2022-08-18)This version and all future versions will require Python 3.7+, Python 3.6 is no longer supported.Addeddata,value,sequenceproperties touamqp.Message, which return the body if the body type corresponds.Addedmessage_annotationsproperty touamqp.Message, which is an alias for theannotationsinstance variable.Addeddataproperty touamqp.BatchMessage, which returns the iterable body of the batch.Addedttlproperty touamqp.MessageHeader, which is an alias for thetime_to_liveinstance variable.1.5.3 (2022-03-23)Updated OpenSSL dependency to 1.1.1n for wheels of manylinux and macOS.1.5.2 (2022-03-15)Fixed bug that resulted in an error when deepcopying BatchMessage objects (azure-sdk-for-python issue #22529).1.5.1 (2022-01-12)Added back the support for Python 3.6.1.5.0 (2022-01-05)This version and all future versions will require Python 3.7+, Python 2.7 and Python 3.6 are no longer supported.SASTokenAuth,JWTTokenAuth,SASTokenAsync, andJWTTokenAsyncnow takes keyword argumentrefresh_windowto override default token refresh timing in constructors.Fixed bug thatSendClientAsyncmight run into infinite loop while sending when it is shutdown unexpectedly.Updated dependencies Azure uAMQP C @2021-11-16and Azure C Shared Utility @2021-11-15.Fixed bug that thekeep_alive_threadofAMQPClientshould not keep program from exiting in the case ofAMQPClientnot being closed properly.1.4.3 (2021-10-06)Added support for Python 3.10.1.4.2 (2021-09-21)Fixed memory leak in win32 socketio and tlsio (azure-sdk-for-python issue #19777).Fixed memory leak in the process of converting AMQPValue into string (azure-sdk-for-python issue #19777).1.4.1 (2021-06-28)Fixed bug that JWTTokenAuth and JWTTokenAsync do not initialize token for token types other than b\u2019jwt\u2019.Fixed bug that attibutescreation_time,absolute_expiry_timeandgroup_sequenceonMessagePropertiesshould be compatible with integer types on Python 2.7.1.4.0 (2021-05-03)This version and all future versions will require Python 2.7 or Python 3.6+, Python 3.5 is no longer supported.Fixed memory leaks in the process of link attach where source and target cython objects are not properly deallocated (azure-sdk-for-python issue #15747).Improved management operation callback not to parse description value of non AMQP_TYPE_STRING type as string (azure-sdk-for-python issue #18361).1.3.0 (2021-04-05)This version will be the last version to officially support Python 3.5, future versions will require Python 2.7 or Python 3.6+.Added support for AMQP Sequence as the body type of an amqp message.Added new classuamqp.MessageBodyTypeto represent the body type of an amqp message, including:Data: The body consists of one or more data sections and each section contains opaque binary data.Sequence: The body consists of one or more sequence sections and each section contains an arbitrary number of structured data elements.Value: The body consists of one amqp-value section and the section contains a single AMQP value.Added new parameters to the constructor ofuamqp.Message:body_typewhich takesuamqp.MessageBodyTypeto specify the body type of an amqp message.footerwhich takes a dict to set the footer of an amqp message.delivery_annotationswhich takes a dict to set the delivery annotations of an amqp message.Added support for picklinguamqp.Message.Fixed bug that sending message of large size triggering segmentation fault when the underlying socket connection is lost.Fixed bug in link flow control where link credit and delivery count should be calculated based on per message instead of per transfer frame.1.2.15 (2021-03-02)Added desired-capabilities forSendClient(Async)andMessageSender(Async)as part of the AMQP protocol.Added types for AMQPShort and AMQPuShort for explicit handling of short and unsigned short encoding.1.2.14 (2021-02-01)Updated Azure uAMQP C and Azure C Shared Utility dependencies.Fixed memory leak with SAS Token creation.1.2.13 (2021-01-06)Fixed bug in accessingMessageProperties.user_idtriggering segmentation fault when the underlying C bytes are NULL.Fixed bug inMessageProperties.user_idbeing limited to 8 bytes.Fixed bug where connection establishment on macOS with Clang 12 triggering unrecognized selector exception.Fixed bug that macOS was unable to detect network error.Fixed bug thatReceiveClientandReceiveClientAsyncreceive messages during connection establishment.1.2.12 (2020-10-09)Updated cython dependency to 0.29.21.Added support for Python 3.9.1.2.11 (2020-10-01)Updated tlsio_openssl module to send SNI when establishing tls connection (Thanks to milope).Fixed bug whereMessage.footerandMessage.delivery_annotationwere not encoded into the outgoing payload.Fixed bug where message sending timeout error didn\u2019t get raised out.1.2.10 (2020-08-05)Added parametershutdown_after_timeouttoReceiveClientandReceiveClientAsyncwhich gives control over whether to shutdown receiver after timeout.1.2.9 (2020-07-06)Added methodMessageReceiver.reset_link_creditwhich is responsible for resetting current available link credit on the receiver link and send update to the sender.1.2.8 (2020-05-19)Fix to initialize delivery_count header at 0 instead of None (azure-sdk-for-python issue #9708)Added info fields to rejected delivery disposition.1.2.7 (2020-05-04)Fixed bug in setting certificate of tlsio on MacOS (azure-sdk-for-python issue #7201).Fixed seg fault in logging network tracing on MacOS (PR#147, Thanks to malthe).Fixed typos in log messages (PR#146, Thanks to bluca).Improved reproducibility of the generated c_uamqp.c file (PR#144, Thanks to bluca).1.2.6 (2020-02-13)Fixed seg fault in tearing down a failed link with unsent pending messages.1.2.5 (2019-12-10)Fixed garbage collection of C objects to prevent crashing on uncontrolled shutdown.Fixed missing event loop references passed into asyncio functions.Fixed bug in noneffective flow control when large messages are received.Demote link redirect logging from warning to info.1.2.4 (2019-12-02)Fixed bug in calculating send timeout.RemovedThreadPoolExecutorinConnectionAsync.Added support for Python 3.81.2.3 (2019-10-07)Fixed bug in dropping received messages at the moment when the connection just started working.Fixed bug where underlying io type wasn\u2019t set to WebSocket when http_proxy was applied (PR#92, Thanks to skoop22).Fixed bug in noneffective timeout when sending messages.Added desired-capabilities forReceiveClient(Async)andMessageReceiver(Async)as part of the AMQP protocol.Added delivery-tag toMessage(azure-sdk-for-python issue #7336).Added methodworktoMessageReceiverandwork_asynctoMessageReceiverAsyncresponsible for updating link status.1.2.2 (2019-07-02)Made bug fix in asyncio.get_event_loop backwards-compatible for now by just printing a warning rather than raising an error. In the next major version bump we can disable entirely.1.2.1 (2019-06-20)Updated the implementation ofupdate_token()inJWTTokenAuthandJWTTokenAsync(issue #80).1.2.0 (2019-04-16)Fixed bug in batched messages missing application_properties (azure-event-hubs-python issue #97).Fixed bug in datetime object parsing (issue #63).Fixed bug in unexposed send/receive settle modes.Fixed bug where retried messages were not added back to the send queue.Fixed bug in using asyncio.get_event_loop.Added type objects for AMQP Byte and uBytes types.Added async locking around pending messages queue (PR#54, Thanks to zach-b)Added WebSocket(AMQP over WebSocket) support (azure-sdk-for-python issue #5318).Added new token classJWTTokenAuthandJWTTokenAsyncto support OAuth.1.1.0 (2018-11-12)Support for Python 2.7 (>_<)/Where ever aTimeoutErroris raised in Python 3.x, this will be replaced with a new ~uamqp.errors.ClientTimeout exception in Python 2.7.A Python 2strobject will be treated asbytesin Python 3 and a Python 2unicodeobject will be treated like a Python 3str.Added uamqp.compat module for handling Py 2 vs 3 imports and types (PR#46, Thanks to maxkrivich).AMQP encoding of an integer type will now automatically failover into a Long type or a double type if the value is too large.Improved support for promptly detecting invalid ATTACH handles and raising the appropriate error.Added types for AMQPDescribed, AMQPInt and AMQPuInt for explicit handling of int and unsigned int encoding.Added new errorerrors.AMQPClientShutdownas a wrapper forKeyboardInterruptto better handle interrupt handling.Added better handling of keyboard interrupts during C callbacks to better facilitate clean client shutdown.Added additional handling of keyboard interrupt at the C level to clean up annoying warnings.Added classmethodMessage.decode_from_bytesto create a message from AMQP wire-encoded data.AddedMessage.encode_messagemethod to retrieve the AMQP wire-encoded byte representation of the current message.Fixed behaviour ofMessage.get_message_encoded_size()to return accurate size.Added new optionalcallbackargument toclient.mgmt_requestto allow for custom handling of different status codes.Added new client methodsauth_complete()andclient_ready()to allow for more fine-tuned monitoring or the client opening stages.Client message handler is now a public attributeclient.message_handler(SendClient._message_senderandReceiveClient._message_receiverare now deprecated).Added automatic encoding ofdatetime.datetimeobjects into AMQP timestamp.Better support for Source filters with optionaldescriptorargument inSource.set_filter()and newSource.get_filter()method.Fixed Session settings not being passed to CBS session.Added support for a callback on receipt on a Link ATTACH frame. Can be supplied to a client through theon_attachkeyword argument.Removed unsued message.SequenceBody class.Exposed BatchMessage.size_offset property for batch size customization.1.0.3 (2018-09-14)Reduced CPU load during idle receive.Updated Azure uAMQP C and Azure C Shared Utility dependencies.1.0.2 (2018-09-05)Fixed additional bugs in setting MessageProperties as string or bytes.Removed auth locking to prevent locking issues on keyboard interrupt.1.0.1 (2018-08-29)Added some more checks in place to prevent lock hanging on a keybaord interrupt.Fixed bug in setting MessageProperties.subject as string or bytes.uamqp.send_messagenow returns a list ofuamqp.constants.MessageStateto indicate the success of each message sent.1.0.0 (2018-08-20)API settled.Behaviour changeWhen a SendClient or SendClientAsync is shutdown, any remaining pending messages (that is messages\nin the statesWaitingToBeSentandWaitingForSendAck) will no longer be cleared, but can be retrieved from a new\nattributeSendClient.pending_messagesin order to be re-processed as needed.Behaviour changeThe functionSendClient.queue_messagenow allows for queueing multiple messages at once by simply\npassing in additional message instances:send_client.queue_message(my_message)send_client.queue_message(message_1, message_2, message_3)send_client.queue_message(*my_message_list)An authentication object will now raise aValueErrorif one attempts to use it for more than one connection.Renamed internal_asyncmodule to non-privateasync_opsto allow for docs generation.Reformatted logging for better performance.Added additional logging.0.2.1 (2018-08-06)Fixed potential crashing in bindings for amqpvalue.Fixed bindings fault in cbs PUT token complete callback.Updated uAMQP-C.Added additional auth and connection locking for thread/async safety.Increased INFO level logging.Removed platform deinitialization until it can be improved.Added handling for a connection reaching a client-caused error state.0.2.0 (2018-07-25)Breaking changeMessageSender.send_asynchas been renamed toMessageSender.send, andMessageSenderAsync.send_asyncis now a coroutine.Breaking changeRemoveddetach_receivedcallback argument from MessageSender, MessageReceiver,\nMessageSenderAsync, and MessageReceiverAsync in favour of newerror_policyargument.Added ErrorPolicy class to determine how the client should respond to both generic AMQP errors\nand custom or vendor-specific errors. A default policy will be used, but a custom policy can\nbe added to any client by using a newerror_policyargument. Value must be either an instance\nor subclass of ErrorPolicy.Theerror_policyargument has also been added to MessageSender, MessageReceiver, Connection, and their\nasync counterparts to allow for handling of link DETACH and connection CLOSE events.The error policy passed to a SendClient determines the number of message send retry\nattempts. This replaces the previousconstants.MESSAGE_SEND_RETRIESvalue which is now\ndeprecated.Added new ErrorAction object to determine how a client should respond to an error. It has\nthree properties:retry(a boolean to determine whether the error is retryable),backoff(an integer to determine how long the client should wait before retrying, default is 0) andincrement_retries(a boolean to determine whether the error should count against the maximum\nretry attempts, default isTrue). Currentlybackoffandincrement_retriesare only\nconsidered for message send failures.AddedVendorConnectionCloseandVendorLinkDetachexceptions for non-standard (unrecognized)\nconnection/link errors.Added support for HTTP proxy configuration.Added support for running async clients synchronously.Added keep-alive support for connection - this is a background thread for a synchronous\nclient, and a background async function for an async client. The keep-alive feature is\ndisabled by default, to enable, set thekeep_alive_intervalargument on the client to\nan integer representing the number of seconds between connection pings.Added support for catching a Connection CLOSE event.Added support forConnection.sleepandConnectionAsync.sleep_asyncto pause the connection.Added support for surfacing message disposition delivery-state (with error information).Addedconstants.ErrorCodesenum to map standard AMQP error conditions. This replaces the previousconstants.ERROR_CONNECTION_REDIRECTandconstants.ERROR_LINK_REDIRECTwhich are now both\ndeprecated.Added new super errorAMQPErrorfrom which all exceptions inherit.Added newMessageHandlerErrorexception, a subclass ofAMQPConnectionError, for\nSenders/Receivers that enter an indeterminate error state.MessageExceptionis now a subclass ofMessageResponse.AddedClientMessageErrorexception, a subclass ofMessageExceptionfor send errors raised client-side.Catching Link DETACH event will now work regardless of whether service returns delivery-state.Fixed bug where received messages attempting to settle on a detached link crashed the client.Fixed bug in amqp C DescribedValue.Fixed bug where client crashed on deallocating failed management operation.0.1.1 (2018-07-14)Removed circular dependency in Python 3.4 with types.py/utils.pyWhen a header properties is not set, returnsNonerather than raising ValueError.Fixed bug in receiving messages with application properties.0.1.0 (2018-07-05)Fixed bug in error handling for CBS auth to invalid hostname.Changed C error logging to debug level.Bumped uAMQP C version to 1.2.7Fixed memory leaks and deallocation bugs with Properties and Annotations.0.1.0rc2 (2018-07-02)Breaking changeSubmoduleasynchas been renamed to the internal_async.\nAll asynchronous classes in the submodule can now be accessed from uamqp or uamqp.authentication directly.Breaking changeAnything returned by a callback supplied to receive messages will now be ignored.Breaking changeChanged message state enum values:Complete -> SendCompleteFailed -> SendFailedWaitingForAck -> WaitingForSendAckAdded new message state enum values:ReceivedUnsettledReceivedSettledBreaking changeChanges to message settlement exceptions:Combined theAbandonMessageandDeferMessageexceptions asMessageModifiedto be in keeping with the AMQP specification.RenamedAcceptMessagetoMessageAccepted.RenamedRejectMessagetoMessageRejectedwhich now takesconditionanddescriptionarguments rather thanmessage.Addederrors.LinkDetachexception as new subclass ofAMQPConnectionErroras a wrapped for data in a Link DETACH dispostition.Addederrors.LinkRedirectas a specific subclass ofLinkDetachto decode the specific redirect fields of a Link Redirect response.Addederrors.MessageAlreadySettledexception for operations performed on a received message that has already returned a receipt dispostition.Addederrors.MessageReleasedexception.Addederrors.ErrorResponseexception.A received Message can now be explicitly settled through a set of new functions on the message:Message.accept()Message.reject(condition:str, description:str)Message.release()Message.modify(failed:bool, deliverable:bool, annotations:dict)Added explicitauto_completeargument toReceiveClientandReceiveClientAsync. Ifauto_completeis set toFalsethen all messages must be\nexplicitly \u201caccepted\u201d or \u201crejected\u201d by the user otherwise they will timeout and be released. The default isTrue, which is the exiting behaviour for each receive mechanism:Received messages processed by callback (ReceiveClient.receive_messages()) will be automatically \u201caccepted\u201d if no explicit response has been set on completion of the callback.Received messages processed by batch (ReceiveClient.receive_message_batch()) will by automatically \u201caccepted\u201d before being returned to the user.Received messages processed by iterator (ReceiveClient.receive_message_iter()) will by automatically \u201caccepted\u201d if no explicit response has been set once the generator is incremented.Added new methods to clients and connections to allow to redirect to an alternative endpoint when a LinkRedirect exception is raised.\nThe client redirect helper cannot be used for clients that use a shared connection - the clients must be closed before the connection can be redirected.\nNew credentials must be supplied for the new endpoint. The new methods are:uamqp.Connection.redirect(redirect_info, auth)uamqp.async.ConnectionAsync.redirect_async(redirect_info, auth)uamqp.SendClient.redirect(redirect_info, auth)uamqp.ReceiveClient.redirect(redirect_info, auth)uamqp.async.SendClientAsync.redirect_async(redirect_info, auth)uamqp.async.ReceiveClientAsync.redirect_async(redirect_info, auth)Addedon_detach_receivedargument toSenderandReceiverclasses to pass in callback to run on Link DETACH.Removed automatic char encoding for strings of length 1, and addedtypes.AMQPCharfor explicit encoding.Bumped uAMQP C version to 1.2.5Bumped Azure C Shared Utility to 1.1.5Fixed memory leaks in MessageProperties, MessageHeader and message annotations.0.1.0rc1 (2018-05-29)Fixed import error in async receiver.Exposed sender/receiver destroy function.Moved receiver.open on_message_received argument to constructor.Removed sasl module and moved internal classes into authentication module.Added encoding parameter everywhere where strings are encoded.Started documentation.Updated uAMQP-C to 1.2.4 and C Shared Utility to 1.1.4 (includes fix for issue #12).Fixed return type of MgmtOperation.execute - now returns ~uamqp.message.Message.Made AMQP connection/session/sender/receiver types in a client overridable.Added debug trace to management operations.Fixed error in management callback on failed operation.Default AMQP encoding of bytes is now a String type and a bytearray is a Binary type.Added AMQP Array type and fixed Long type range validation.Addedheaderargument to Message and BatchMessage for setting a MessageHeader.Fixed MessageHeader attribute setters.0.1.0b5 (2018-04-27)Added Certifi as a depedency to make OpenSSL certs dynamic.Addedverifyoption to authentication classes to allow setting custom certificate path (for Linux and OSX).0.1.0b4 (2018-04-19)Fixed memory leak in async receive.Removed close_on_done argument from client receive functions.Added receive iterator to synchronous client.Made async iter receive compatible with Python 3.5.0.1.0b3 (2018-04-14)Fixed SSL errors in manylinux wheels.Fixed message annoations attribute.Fixed bugs in batched messages and sending batched messages.Fixed conflicting receiver link ID.Fixed hanging receiver by removing queue max size in sync clients.Added support for sending messages with None and empty bodies.0.1.0b2 (2018-04-06)Added message send retry.Added timeouts and better error handling for management requests.Improved connection and auth error handling and error messages.Fixed message annotations type.SendClient.send_all_messages() now returns a list of message send statuses.Fixed OpenSSL platform being initialized multiple times.Fixed auto-refresh of SAS tokens.Alteredreceive_batchbehaviour to return messages as soon as they\u2019re available.Parameterbatch_sizeinreceive_batchrenamed tomax_batch_size.Fixed messageapplication_propertiesdecode error.Removed MacOS dependency on OpenSSL and libuuid.0.1.0b1 (2018-03-24)Added management request support.Fixed message-less C operation ValueError.Store message metadata in Python rather than C.Refactored Send and Receive clients to create a generic parent AMQPClient.Fixed None receive timestamp bug.Removed async iterator queue due to instabilities - all callbacks are now synchronous.0.1.0a3 (2018-03-19)Added support for asynchronous message receive by iterator or batch.Removed synchronous receive iterator, and replaced with synchronous batch receive.Added sync and async context managers for Send and Receive Clients.Fixed token instability and added put token retry policy.Exposed Link ATTACH properties.A connection now has a single $cbs session that can be reused between clients.Added C debug trace logging to the Python logger (\u2018uamqp.c_uamqp\u2019)0.1.0a2 (2018-03-12)Exposed OPEN performative properties for connection telemetry.Exposed setters for message.message_annotations and message.application_properties.Made adjustments to connection open and close to facilitate sharing a connection object between send/receive clients.Support for username/password embedded in connection URI.Clients can now optionally leave connection/session/link open for re-use.Updated build process and installation instructions.Various bug fixes to increase stability.0.1.0a1 (2018-03-04)Initial release"} +{"package": "uamutils", "pacakge-description": "Overviewuamutilspackage provides a Python interface toUpper Atmosphere Model(UAM) binary data format as well as utilities for processing & analysing UAM data.DocumentationThisJupyter notebook demonstrates essential functionality of the package.CautionThis project is a work in progress. Some features are still lacking, while existing features need more rigorous testing. Also, huge refactoring is due \u2014 API-breaking changeswillbe made."} +{"package": "ua-node-avail", "pacakge-description": "ua-node-availA simple script to host on pip to allow the user to analyze the queues for available nodes.Installation:pip install ua-node-availUsage:node_availOutput:CPU CORES MEMORY GB\n NODE VENDOR FREE ALLOC TOTAL FREE ALLOC TOTAL\n\n chpc-compute-12-2 AMD 32 32 64 123 128 251\n chpc-compute-12-8 AMD 32 32 64 123 128 251\n chpc-compute-12-17 AMD 32 32 64 123 128 251\n chpc-compute-12-22 AMD 32 32 64 123 128 251\n chpc-compute-12-24 AMD 32 32 64 133 118 251\n chpc-compute-12-0 AMD 16 48 64 67 184 251\n chpc-compute-12-1 AMD 16 48 64 64 187 251\n chpc-compute-12-3 AMD 16 48 64 64 187 251\n chpc-compute-12-4 AMD 16 48 64 64 187 251\n chpc-compute-12-6 AMD 16 48 64 64 187 251\n chpc-compute-12-7 AMD 16 48 64 67 184 251\n chpc-compute-12-9 AMD 16 48 64 73 178 251\n chpc-compute-12-15 AMD 16 48 64 64 187 251\n chpc-compute-12-16 AMD 16 48 64 64 187 251\n chpc-compute-12-18 AMD 16 48 64 64 187 251\n chpc-compute-12-12 AMD 10 54 64 50 201 251\n chpc-compute-12-10 AMD 0 64 64 14 237 251\n chpc-compute-12-11 AMD 0 64 64 14 237 251\n chpc-compute-12-13 AMD 0 64 64 14 237 251\n chpc-compute-12-14 AMD 0 64 64 10 241 251\n chpc-compute-12-19 AMD 0 64 64 14 237 251\n chpc-compute-12-20 AMD 0 64 64 14 237 251\n chpc-compute-12-21 AMD 0 64 64 10 241 251\n chpc-compute-12-23 AMD 0 64 64 14 237 251\n chpc-gpu-12-1 AMD 64 0 64 251 0 251\n chpc-gpu-10-0 AMD 0 64 64 14 237 251\n chpc-gpu-10-2 AMD 0 64 64 14 237 251\n chpc-gpu-12-0 AMD 0 64 64 14 237 251\n chpc-highmem-12-0 AMD 40 8 48 1906 109 2015\n chpc-highmem-10-0 AMD 0 48 48 15 2000 2015\n chpc-highmem-10-1 AMD 0 48 48 926 1089 2015\n chpc-highmem-12-1 AMD 0 48 48 1411 604 2015"} +{"package": "uao", "pacakge-description": "Big5-UAO table in pure Python.\u7d14 Python \u7684 UAO (Unicode-At-On) encoder/decoder\u3002Installationpip install uaoUsagefromuaoimportregister_uaoregister_uao()# register big5-uao as a builtin codecsprint(\"\u65e0\u6cd5\u88abBig5\u7de8\u78bc\u306e\u5b57\u4e32\u2665\".encode(\"big5-uao\").decode(\"big5-uao\"))Or use the standaloneBig5UAOCodecclass:fromuaoimportBig5UAOCodecuao=Big5UAOCodec()print(uao.decode(uao.encode(\"\u65e0\u6cd5\u88abBig5\u7de8\u78bc\u306e\u5b57\u4e32\u2665\")))Changelog0.2.0 (Feb 22, 2021)Add: support python 3.7~3.9.0.1.1 (Jun 11, 2018)Fix: remove a print statement.0.1.0 (Jun 11, 2018)First release."} +{"package": "ua-parse", "pacakge-description": "ua-parseUser-agent parsing library inspired by thehttps://faisalman.github.io/ua-parser-js/project.It is essentially an adaptation ofua-parser-jsin python.\nUnlike other UA-parsing libraries, this library detect MacOS asMac OS, notMac OS X, and thebrowser,engine, andosversions are already joined into a one string, which is convenient for use.Installationpipinstallua-parseGet startedThe library exports just one function that returns all the parameters at once.Parse user-agent:fromua_parseimportparse_uasafari_user_agent='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/15.2 Safari/605.1.15'result=parse_ua(safari_user_agent)assertresult=={'browser':{'name':'Safari','version':'15.2'},'cpu':{'architecture':None},'device':{'model':None,'type':None,'vendor':None},'engine':{'name':'WebKit','version':'605.1.15'},'os':{'name':'Mac OS','version':'10.15.7'},}ie_user_agent='Mozilla/5.0 (Windows NT 6.3; Trident/7.0; rv 11.0) like Gecko'result_2=parse_ua(ie_user_agent)assertresult_2=={'browser':{'name':'IE','version':'11.0'},'cpu':{'architecture':None},'device':{'model':None,'type':None,'vendor':None},'engine':{'name':'Trident','version':'7.0'},'os':{'name':'Windows','version':'8.1'},}empty_user_agent=''result_3=parse_ua(empty_user_agent)assertresult_3=={'browser':{'name':None,'version':None},'cpu':{'architecture':None},'device':{'model':None,'type':None,'vendor':None},'engine':{'name':None,'version':None},'os':{'name':None,'version':None},}Supported OS:AIX, Amiga OS, Android[-x86], Arch, Bada, BeOS, BlackBerry, CentOS, Chromium OS,\nContiki, Fedora, Firefox OS, FreeBSD, Debian, Deepin, DragonFly, elementary OS,\nFuchsia, Gentoo, GhostBSD, GNU, Haiku, HP-UX, Hurd, iOS, Joli, KaiOS, Linpus, Linspire,\nLinux, Mac OS, Maemo, Mageia, Mandriva, Manjaro, MeeGo, Minix, Mint, Morph OS, NetBSD,\nNintendo, OpenBSD, OpenVMS, OS/2, Palm, PC-BSD, PCLinuxOS, Plan9, PlayStation, QNX,\nRaspbian, RedHat, RIM Tablet OS, RISC OS, Sabayon, Sailfish, Series40, Slackware, Solaris,\nSUSE, Symbian, Tizen, Ubuntu, Unix, VectorLinux, WebOS, Windows [Phone/Mobile], Zenwalk, ...Supported browsers:2345Explorer, 360 Browser, Amaya, Android Browser, Arora, Avant, Avast, AVG,\nBIDUBrowser, Baidu, Basilisk, Blazer, Bolt, Brave, Bowser, Camino, Chimera,\nChrome Headless, Chrome WebView, Chrome, Chromium, Comodo Dragon, Dillo,\nDolphin, Doris, Edge, Electron, Epiphany, Facebook, Falkon, Fennec, Firebird,\nFirefox [Reality], Flock, Flow, GSA, GoBrowser, ICE Browser, IE, IEMobile, IceApe,\nIceCat, IceDragon, Iceweasel, Instagram, Iridium, Iron, Jasmine, K-Meleon,\nKindle, Klar, Konqueror, LBBROWSER, Line, Links, Lunascape, Lynx, MIUI Browser,\nMaemo Browser, Maemo, Maxthon, MetaSr Midori, Minimo, Mobile Safari, Mosaic,\nMozilla, NetFront, NetSurf, Netfront, Netscape, NokiaBrowser, Obigo, Oculus Browser,\nOmniWeb, Opera Coast, Opera [Mini/Mobi/Tablet], PaleMoon, PhantomJS, Phoenix,\nPolaris, Puffin, QQ, QQBrowser, QQBrowserLite, Quark, QupZilla, RockMelt, Safari,\nSailfish Browser, Samsung Browser, SeaMonkey, Silk, Skyfire, Sleipnir, Slim,\nSlimBrowser, Swiftfox, Tesla, Tizen Browser, UCBrowser, UP.Browser, Vivaldi,\nWaterfox, WeChat, Weibo, Yandex, baidu, iCab, w3m, Whale Browser...Supported device types and vendors:console, mobile, tablet, smarttv, wearable, embeddedAcer, Alcatel, Amazon, Apple, Archos, ASUS, AT&T, BenQ, BlackBerry, Dell,\nEssential, Fairphone, GeeksPhone, Google, HP, HTC, Huawei, Jolla, Lenovo, LG,\nMeizu, Microsoft, Motorola, Nexian, Nintendo, Nokia, Nvidia, OnePlus, OPPO, Ouya,\nPalm, Panasonic, Pebble, Polytron, Realme, RIM, Roku, Samsung, Sharp, Siemens,\nSony[Ericsson], Sprint, Tesla, Vivo, Vodafone, Xbox, Xiaomi, Zebra, ZTE, ...Supported engines:Amaya, Blink, EdgeHTML, Flow, Gecko, Goanna, iCab, KHTML, Links, Lynx, NetFront,\nNetSurf, Presto, Tasman, Trident, w3m, WebKitSupported cpus:68k, amd64, arm[64/hf], avr, ia[32/64], irix[64], mips[64], pa-risc, ppc, sparc[64]"} +{"package": "uaparser", "pacakge-description": "This library parses browser user-agent strings with data from [user-agent-string.info](http://user-agent-string.info/).This library is loosely based on the work by Hicro Kee (hicrokee AT gmail DOT com) and Michal Molhanec (http://molhanec.net).Usage:from uaparser import UA, UAParser\nparser = UAParser()\nparser.update_data()\nua = UA(parser, user_agent_string)\nprint ua.is_robot() # returns empty dictionary if robot is not detected\nprint ua.get_browser_details() # returns empty dictionary, or browser details\nprint ua.get_device_type() # returns dict containing device type fields\nprint ua.get_os_details()\n# Or alternatively,\nprint ua.parse() # returns all parsed fields for the UA stringDjango integrationAs running a large number of regexes takes a long time, Django integration uses caching.Usage:from uaparser.django.caching_ua_parser import parse_user_agent\nparsed = parse_user_agent(request.META.get(\"HTTP_USER_AGENT\"))parse_user_agentfetches all user-agent fields (i.e it callsua.parse()).Settings:UA_CACHE_DIRECTORY: directory for data file (\u201ccache.pickle\u201d). Mandatory.UA_CACHE_NAME: defaults to \u201cdefault\u201d. Defines custom Django cache name.UA_CACHE_PREFIX: defaults to \u201cparse_ua\u201d. Key prefix for cache.UA_CACHE_TIMEOUT: defaults to 48 hours. Cache key timeout in seconds.Middleware: adduaparser.django.middleware.UAParserMiddlewaretoMIDDLEWARE_CLASSES.Context processor: to addparsed_uavariable to context, adduaparser.django.context_processor.add_parsed_uatoCONTEXT_PROCESSORS. This does nothing ifUAParserMiddlewareis not enabled.LicenseLicensed under the MIT license.Copyright (c) 2014 Olli Jarva Permission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \u201cSoftware\u201d), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in\nall copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \u201cAS IS\u201d, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\nTHE SOFTWARE."} +{"package": "ua-parser", "pacakge-description": "No description available on PyPI."} +{"package": "ua-parser-next", "pacakge-description": "No description available on PyPI."} +{"package": "ua-parser-py", "pacakge-description": "UAParser.pyfork ofUAParser.jsPython library to detect Browser, Engine, OS, CPU, and Device type/model from User-Agent data.DocumentationConstructorUAParser([uastring])returns new instanceUAParser.parse([uastring])returns result object{ 'ua': '', 'browser': {}, 'cpu': {}, 'device': {}, 'engine': {}, 'os': {} }Propertiesbrowserreturns{ 'name': '', 'version': '' }# Possible 'browser.name':2345Explorer,360Browser,Amaya,AndroidBrowser,Arora,Avant,Avast,AVG,\nBIDUBrowser,Baidu,Basilisk,Blazer,Bolt,Brave,Bowser,Camino,Chimera,\nChromeHeadless,ChromeWebView,Chrome,Chromium,ComodoDragon,Dillo,\nDolphin,Doris,Edge,Electron,Epiphany,Facebook,Falkon,Fennec,Firebird,\nFirefox[Reality],Flock,Flow,GSA,GoBrowser,ICEBrowser,IE,IEMobile,IceApe,IceCat,IceDragon,Iceweasel,Instagram,Iridium,Iron,Jasmine,K-Meleon,\nKindle,Klar,Konqueror,LBBROWSER,Line,Links,Lunascape,Lynx,MIUIBrowser,\nMaemoBrowser,Maemo,Maxthon,MetaSrMidori,Minimo,MobileSafari,Mosaic,\nMozilla,NetFront,NetSurf,Netfront,Netscape,NokiaBrowser,Obigo,OculusBrowser,\nOmniWeb,OperaCoast,Opera[Mini/Mobi/Tablet],PaleMoon,PhantomJS,Phoenix,Polaris,Puffin,QQ,QQBrowser,QQBrowserLite,Quark,QupZilla,RockMelt,Safari,SailfishBrowser,SamsungBrowser,SeaMonkey,Silk,Skyfire,Sleipnir,Slim,SlimBrowser,Swiftfox,Tesla,TizenBrowser,UCBrowser,UP.Browser,Vivaldi,Waterfox,WeChat,Weibo,Yandex,baidu,iCab,w3m,WhaleBrowser...# 'browser.version' determined dynamicallydevicereturns{ 'model': '', 'type': '', 'vendor': '' }# Possible 'device.type':console,mobile,tablet,smarttv,wearable,embedded# Possible 'device.vendor':Acer,Alcatel,Amazon,Apple,Archos,ASUS,AT&T,BenQ,BlackBerry,Dell,\nEssential,Fairphone,GeeksPhone,Google,HP,HTC,Huawei,Jolla,Lenovo,LG,Meizu,Microsoft,Motorola,Nexian,Nintendo,Nokia,Nvidia,OnePlus,OPPO,Ouya,\nPalm,Panasonic,Pebble,Polytron,Realme,RIM,Roku,Samsung,Sharp,Siemens,\nSony[Ericsson],Sprint,Tesla,Vivo,Vodafone,Xbox,Xiaomi,Zebra,ZTE,...# 'device.model' determined dynamicallyenginereturns{ 'name': '', 'version': '' }# Possible 'engine.name'Amaya,Blink,EdgeHTML,Flow,Gecko,Goanna,iCab,KHTML,Links,Lynx,NetFront,\nNetSurf,Presto,Tasman,Trident,w3m,WebKit# 'engine.version' determined dynamicallyosreturns{ 'name': '', 'version': '' }# Possible 'os.name'AIX,AmigaOS,Android[-x86],Arch,Bada,BeOS,BlackBerry,CentOS,ChromiumOS,\nContiki,Fedora,FirefoxOS,FreeBSD,Debian,Deepin,DragonFly,elementaryOS,Fuchsia,Gentoo,GhostBSD,GNU,Haiku,HP-UX,Hurd,iOS,Joli,KaiOS,Linpus,Linspire,\nLinux,MacOS,Maemo,Mageia,Mandriva,Manjaro,MeeGo,Minix,Mint,MorphOS,NetBSD,\nNintendo,OpenBSD,OpenVMS,OS/2,Palm,PC-BSD,PCLinuxOS,Plan9,PlayStation,QNX,Raspbian,RedHat,RIMTabletOS,RISCOS,Sabayon,Sailfish,Series40,Slackware,Solaris,SUSE,Symbian,Tizen,Ubuntu,Unix,VectorLinux,WebOS,Windows[Phone/Mobile],Zenwalk,...# 'os.version' determined dynamicallycpureturns{ 'architecture': '' }# Possible 'cpu.architecture'68k,amd64,arm[64/hf],avr,ia[32/64],irix[64],mips[64],pa-risc,ppc,sparc[64]uareturns UA string of current instanceUsageimportjsonfromuaparserimportUAParseruastring1='Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.2 (KHTML, like Gecko) Ubuntu/11.10 Chromium/15.0.874.106 Chrome/15.0.874.106 Safari/535.2'result=UAParser(uastring1)print(result.browser)# 'browser': {'name': 'Chromium', 'version': '15.0.874.106', 'major': '15'}print(result.device)# {'vendor': None, 'model': None, 'type': None}print(result.os)# {'name': 'Ubuntu', 'version': '11.10'}print(result.os.version)# '11.10'print(result.engine.name)# 'WebKit'print(result.cpu.architecture)# 'amd64'uastring2='Mozilla/5.0 (compatible; Konqueror/4.1; OpenBSD) KHTML/4.1.4 (like Gecko)'result=UAParser.parse(uastring2)print(result['browser']['name'])# 'Konquerorprint(result['os'])# {'name': 'OpenBSD', 'version': None}print(result['engine'])# {'name': 'KHTML', 'version': '4.1.4'}uastring3='Mozilla/5.0 (PlayBook; U; RIM Tablet OS 1.0.0; en-US) AppleWebKit/534.11 (KHTML, like Gecko) Version/7.1.0.7 Safari/534.11'result=UAParser.parse(uastring3)print(json.dumps(result,indent=4))# {# \"ua\": \"Mozilla/5.0 (PlayBook; U; RIM Tablet OS 1.0.0; en-US) AppleWebKit/534.11 (KHTML, like Gecko) Version/7.1.0.7 Safari/534.11\",# \"browser\": {# \"name\": \"Safari\",# \"version\": \"7.1.0.7\",# \"major\": \"7\" // @deprecated# },# \"cpu\": {# \"architecture\": null# },# \"device\": {# \"vendor\": \"RIM\",# \"model\": \"PlayBook\",# \"type\": \"tablet\"# },# \"engine\": {# \"name\": \"WebKit\",# \"version\": \"534.11\"# },# \"os\": {# \"name\": \"RIM Tablet OS\",# \"version\": \"1.0.0\"# }# }"} +{"package": "ua-parser-up2date", "pacakge-description": "Anup to datepython implementation of the UA Parser (https://github.com/ua-parser,\nformerlyhttps://github.com/tobie/ua-parser)Build StatusInstallingInstall via pipJust run:$pipinstallua-parser-up2dateManual installIn the top-level directory run:$pythonsetup.pyinstallChange LogBecause this repo is mostly a python wrapper for the User Agent String Parser repo (https://github.com/ua-parser/uap-core), the changes made to this repo are best described by the update diffs in that project. Please see the diffs for this submodule (https://github.com/ua-parser/uap-core/releases) for a list of what has changed between versions of this package.Getting StartedRetrieve data on a user-agent string>>>fromua_parserimportuser_agent_parser>>>importpprint>>>pp=pprint.PrettyPrinter(indent=4)>>>ua_string='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2272.104 Safari/537.36'>>>parsed_string=user_agent_parser.Parse(ua_string)>>>pp.pprint(parsed_string){'device':{'brand':'Apple','family':'Mac','model':'Mac'},'os':{'family':'Mac OS X','major':'10','minor':'9','patch':'4','patch_minor':None},'string':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) ''AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2272.104 ''Safari/537.36','user_agent':{'family':'Chrome','major':'41','minor':'0','patch':'2272'}}Extract browser data from user-agent string>>>fromua_parserimportuser_agent_parser>>>importpprint>>>pp=pprint.PrettyPrinter(indent=4)>>>ua_string='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2272.104 Safari/537.36'>>>parsed_string=user_agent_parser.ParseUserAgent(ua_string)>>>pp.pprint(parsed_string){'family':'Chrome','major':'41','minor':'0','patch':'2272'}\u26a0\ufe0fBefore 0.15, the convenience parsers (ParseUserAgent,ParseOs, andParseDevice) were not cached, which could\nresult in degraded performances when parsing large amounts of\nidentical user-agents (which might occur for real-world datasets).For these versions (up to 0.10 included), prefer usingParseand extracting the sub-component you need from the resulting\ndictionary.Extract OS information from user-agent string>>>fromua_parserimportuser_agent_parser>>>importpprint>>>pp=pprint.PrettyPrinter(indent=4)>>>ua_string='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2272.104 Safari/537.36'>>>parsed_string=user_agent_parser.ParseOS(ua_string)>>>pp.pprint(parsed_string){'family':'Mac OS X','major':'10','minor':'9','patch':'4','patch_minor':None}Extract Device information from user-agent string>>>fromua_parserimportuser_agent_parser>>>importpprint>>>pp=pprint.PrettyPrinter(indent=4)>>>ua_string='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2272.104 Safari/537.36'>>>parsed_string=user_agent_parser.ParseDevice(ua_string)>>>pp.pprint(parsed_string){'brand':'Apple','family':'Mac','model':'Mac'}CopyrightCopyright 2008 Google Inc. See ua_parser/LICENSE for more information"} +{"package": "uapi", "pacakge-description": "uapiuapiis an elegant, high-level, extremely low-overhead Python microframework for writing HTTP APIs, either synchronously or asynchronously.uapiuses a lower-level HTTP framework to run. Currently supported frameworks are aiohttp, Django, Flask, Quart, and Starlette.\nAnuapiapp can be easily integrated into an existing project based on one of these frameworks, and a pureuapiproject can be easily switched between them when needed.Usinguapienables you to:writeeither async or syncstyles of handlers, depending on the underlying framework used.use and customize afunction composition(dependency injection) system, based onincant.automaticallyserialize and deserializedata throughattrsandcattrs.generate and useOpenAPIdescriptions of your endpoints.optionallytype-checkyour handlers withMypy.write and use reusable andpowerful middleware, which integrates into the OpenAPI schema.integratewith existing apps based onDjango,Starlette,Flask,Quartoraiohttp.Here's a simple taste (install Flask and gunicorn first):fromuapi.flaskimportAppapp=App()@app.get(\"/\")defindex()->str:return\"Index\"app.serve_openapi()app.serve_elements()app.run(__name__)# Now open http://localhost:8000/elementsProject InformationPyPISource CodeDocumentationChangelogLicenseuapiis written byTin Tvrtkovi\u0107and distributed under the terms of theApache-2.0license."} +{"package": "uapp", "pacakge-description": "UAPPThis program tries to update all installed packages through pip.INSTALL(git clone):git clonehttps://github.com/accessmaker/UAPP.gitpython setup.py installINSTALL(PIP):pip install uappUSAGE:$ uappOPTIONSUAPP(Update All Python Packages):is an unofficial package manager, which makes it easy to update packages installed with piphelp, --help or -h = show uapp help options;version, --version = show uapp version;check-update = Search and show available updates;update, upgrade = Update all packages;update package = Update the selected package."} +{"package": "ua-project-transfer", "pacakge-description": "UA-Project-TransferTransfers service requests from Agilent's iLab software to Illumina's Clarity LIMS software.MotivationTo transfer service requests from iLab to Clarity LIMS programmatically.FeaturesCreates projects in Clarity LIMS based on corresponding iLab service requests.Route samples to the correct workflow in Clarity LIMS.Validates service request prices.If the transfer fails at any point in sample creation, there will not be side effects of project transfer.Installationgitclonehttps://github.com/UACoreFacilitiesIT/UA-Project-Transfer.gitCode ExamplecdUA-Project-Transfer/ua_project_transfer\npythonproject_transfer.py--ilab{iLabenvironment}--lims{LIMSenvironment}TestscdUA-Project-Transfer/ua_project_transfer/tests\nnoseteststest_project_lims_tools.pyHow to UseTo use project_transfer with default settings in your environment, you will need to make a few changes:Environment changesAdd a file named \"lims_token.json\" in the form of:{\n\"host\": \"{api_endpoint(https://.*v2/)}\",\n\"username\" : \"{api_creds_username)\",\n\"password\" : \"{api_creds_password}\"\n}Add a file named \"ilab_token.json\" in the form of:{\n\"token\": \"{ilab_api_token}\",\n\"core_id\": \"{ilab_core_id}\"\n}- If you want to customize logging, run monitoring, or credential harvesting, create a \"core_specifics.py\" file with that code. Otherwise, save the \"core_specifics_template.py\" file as \"core_specifics.py\".To customize logging:\nEither save the \"log_config_template.py\" as \"log_config.py\" OR create a custom log_config file, including at least what is in the template file.To customize run monitoring:\nAdd the setup for whichever software monitoring you decide to use. Can be left blank if no monitoring is desired.To customize credential harvesting:\nEither use what is written in the template, utilizing the two token files you just created. OR delete those two token files and implement your own credential harvesting method.The wf_locations dictionary must also be updated to map the iLab\nForm names to their respective next_steps functions.The unroutable_forms list must be updated to contain any iLab Form names\nyou want to skip.Clarity changesThe UDF's in either the custom form's grid or fields with _each_sample in their identifiers must be exactly the name of the target Clarity UDF.A sample's container type's name must map exactly to a container type's name in Clarity.Workflows can only have samples routed to them if they are active.WF_STEPS in wf_steps.py must hold the mappings of conditions to a tuple containing (the workflow, the step name).iLab changesThe code that interprets service requests (ua_ilab_tools) has a few requirements with you iLab setup:Sample specific changes (sample grid):The information for samples must be stored in a \"grid\" custom form data type.The first column of that grid will be interpreted as the sample names.Any text added to this grid will have it's input scrubbed so that it matches r\"[^a-zA-Z0-9:,.+]\", where '+' is replaced with \"plus\", and is encoded as ascii -- special characters are converted usingunicodedata.normalize(\"NFKD\", text).encode(\"ascii\", \"ignore\").decode(\"ascii\")If a form is set up with 96-well plate(s) as the form's container type (see below how to set a form's container type), the it must have the column name of \"Well Location\".The formats that are allowed in the \"Well Location\" column are A:1, H12, B09, or C:09 (of course including A-H and 1-12).If a UDF is of the \"numeric\" type in Clarity, add that UDF identifier (the column name in the grid or the .*_each_sample form field identifier) to extract_custom_forms.py's ONLY_INT_FIELDS.Similarly, anything that is set as a \"Toggle Switch\" UDF in CLarity should be added to extract_custom_forms.py's BOOL_FIELDS.Price Check specific changes:You will need to define the quantity of each unit of a charge in price_check.py's unit_definitions (e.g. {\"each\": 1, \"prep\":11}).Form specific changes:Custom forms with names that match the pattern in ua_ilab_tools' SKIP_FORM_PATTERNS will not be evaluated.Youcanhave a service request with a skipped form and a not skipped form, and the request will transfer.Each service request can only have one form that has sample information.Any custom form fields that end with \"_each_sample\" will be applied to every sample in the form.For example, if your Clarity environment had the UDF \"Concentration\", and you wanted a single concentration value to be added to every sample within a form's sample grid, the identifier for that field in the custom form's iLab setup should say \"Concentration_each_sample\".These identifiers must be exactly the name of the UDF in Clarity, before the \"_each_sample\" portion.The container type of the form is determined by whether:There's a grid column named \"Container Name\" (multiple 96-well plates)There's a custom form field with the identifier of container_name (single 96-well plate)Else, the container type is a TubeIf you need to add more container types or change these rules, you can do so by editing the .*_bind functions, and updating the con_strategy dict() in bind_container_info() in extract_custom_forms.py.Each form must have only 1 container type.Duplicate location values are handled based on the container type of the form. The rules for what is allowed are:Container TypeDuplicate Names AllowedDuplicate Wells AllowedTube:x:Always 1:196 Well Plate:heavy_check_mark::x:Creditssterns1raflopjrRyanJohannesBlandEtienneThompsonLicenseMIT"} +{"package": "uapy", "pacakge-description": "uapyPython wrapper for Linux UAPI ioctlOverviewThis project provides a Python wrapper for Linux Media Infrastructure userspace API ioctl requests.SupportCurrent milestone is Linux 5.8.0APIv4l - Video for Linux version 2dvb - Digital TVrc - Remote Controllermediactl - Media Controllercec - Consumer Electronics ControlExamplefromuapy.v4l2.videodevimport*cap=V4l2_Capability()res=fcntl.ioctl(vd1,Vidioc.QUERYCAP,cap)format=V4l2_Format()format.type=V4l2_Buf_Type.VIDEO_OUTPUTInstalluser@machine:~$pip3installuapy"} +{"package": "uapycon", "pacakge-description": "Python package to work with UAPycon site APIFree software: BSD licenseDocumentation:https://uapycon.readthedocs.org.FeaturesTODOHistory0.1.0 (2015-04-15)First release on PyPI."} +{"package": "uarango", "pacakge-description": "UNKNOWN"} +{"package": "uareach", "pacakge-description": "AboutThe Airshipuareach(Wallet) library is a Python library for\nusing theAirshipWallet REST API.Version 0.1.0 is a beta release. Please visitAirship Supportwith feature requests, questions,\nbug reports, or comments.RequirementsAs of version 0.1.0, Python 2.7 is required.For tests,uareachalso needsMock.Running TestsTo run tests, run:$ nosetestsUsageTo get started, simply import the library and set up a client:importuareachasuaclient=ua.Reach('email','wallet_key')# Example: getting a passmy_pass=ua.get_pass(client,pass_id=12345)For more details on using this library, please see thefull documentation, as well as theAirship Wallet API Documentation."} +{"package": "uarizona-ece275-outputfileTester", "pacakge-description": "UArizona ECE 275 Output File TesterThis package is used to compare output files for ECE 275 at The University of Arizona.\nThe package really should not be used by anyone else as functionality is not very general and there is no documentation.\nPackage placed on PyPI for easy student (and Docker container) install only!"} +{"package": "uarm", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "uarm4py", "pacakge-description": "UNKNOWN"} +{"package": "uarmserial", "pacakge-description": "uarmserial packageRequirementsuARM Python SDKOpenMV (IDE) - if using OpenMV camera"} +{"package": "uarm-serial", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "uaromanizer", "pacakge-description": "UaromanizerProvides means for romanization of Ukrainian writing(barely)Installation:pip install uaromanizerUsage:from uaromanizer import RomanizerRomanizer().romanize()-> str"} +{"package": "uarray", "pacakge-description": "uarray- A back-end mechanism geared towards array computingDocumentationRoad MapFuture MeetingsMeeting NotesReferencesPapersContributingSeeCONTRIBUTING.mdfor more information on how to contribute touarray."} +{"package": "uart", "pacakge-description": "Utility for simply creating and modifying VHDL bus slave modules"} +{"package": "uart-debugger", "pacakge-description": "No description available on PyPI."} +{"package": "uartis", "pacakge-description": "UNKNOWN"} +{"package": "uart-wifi", "pacakge-description": "AboutThis is a library to provide support for Mono X Printers.uart-wifitheuart-wifilibrary can be downloaded from PyPI. It contains required python tools for communicating with MonoX Printers. To install, simply install Python, then typepip install uart-wifi. After which, you can create fake printers and communicate with them.monox.pyA command line script to gather information from the Mono X printer. This is tested working on the Anycubic Mono X 6k and should work on any Mono X or Mono SE printer.Usage: monox.py -i -c \nargs:\n -i [--ipaddress=] - The IP address which your Anycubic Mono X can be reached\n\n -c [--command=] - The command to send.\n\nCommands may be used one-at-a-time. Only one command may be sent and it is expected to be in the format below.\n\nCommand: getstatus - Returns a list of printer statuses.\n\nCommand: getfile - returns a list of files in format : . When referring to the file via command, use the .\n\nCommand: sysinfo - returns Model, Firmware version, Serial Number, and wifi network.\n\nCommand: getwifi - displays the current wifi network name.\n\nCommand: gopause - pauses the current print.\n\nCommand: goresume - ends the current print.\n\nCommand: gostop,end - stops the current print.\n\nCommand: delfile,,end - deletes a file.\n\nCommand: gethistory,end - gets the history and print settings\nof previous prints.\n\nCommand: delhistory,end - deletes printing history.\n\nCommand: goprint,,end - Starts a print of the\nrequested file\n\nCommand: getPreview1,,end - returns a list of dimensions used for the print.fake_printer.pyA command line script to simulate a MonoX 3D printer for testing purposes. You can simulate a fleet of Mono X 3D printers!Usage: fake_printer.py -i -c \nargs:\n [-i, [--ipaddress=]] - The IP address which to acknowledge requests. This defaults to any or 0.0.0.0.\n\n [-p [--port=]] - The port to listen on. This defaults to 6000."} +{"package": "uas", "pacakge-description": "uasDescriptionThis fake user agent generator does not use any external data. Instead it\nrandomizes browser versions for Firefox, Chrome and OS versions for MacOS,\nWindows.uasalso contains some static user agents for bots from Facebook,\nGoogle and Bing.Installationpip install uasUsageimport requests\nfrom uas import chrome, firefox, bot, GOOGLE\n\n\nr = requests.get(\"https://example.com/chrome\", headers={\"User-Agent\": chrome()})\nr = requests.get(\"https://example.com/firefox\", headers={\"User-Agent\": firefox()})\nr = requests.get(\"https://example.com/bot\", headers={\"User-Agent\": bot()})\nr = requests.get(\"https://example.com/google\", headers={\"User-Agent\": GOOGLE[0]})"} +{"package": "uasiren", "pacakge-description": "\ud83c\uddfa\ud83c\udde6 UA Siren \ud83d\udea8UK\u0406\u043c\u043f\u043b\u0435\u043c\u0435\u043d\u0442\u0443\u0454 siren.pp.ua API - \u043f\u0443\u0431\u043b\u0456\u0447\u043d\u0443 \u043e\u0431\u0433\u043e\u0440\u0442\u043a\u0443 \u043d\u0430\u0432\u043a\u043e\u043b\u043eapi.ukrainealarm.com, \u044f\u043a\u0438\u0439 \u043f\u043e\u0432\u0435\u0440\u0442\u0430\u0454 \u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u044e \u043f\u0440\u043e \u043f\u043e\u0432\u0456\u0442\u0440\u044f\u043d\u0456 \u0442\u0440\u0438\u0432\u043e\u0433\u0438 \u0432 \u0423\u043a\u0440\u0430\u0457\u043d\u0456.\u041e\u0431\u043c\u0435\u0436\u0435\u043d\u043d\u044f200 \u0437\u0430\u043f\u0438\u0442\u0456\u0432 \u043d\u0430 \u043f\u0440\u043e\u0442\u044f\u0437\u0456 5 \u0445\u0432\u0438\u043b\u0438\u043d \u0437 \u043e\u0434\u043d\u043e\u0433\u043e IP.ENImplements siren.pp.ua API - public wrapper forapi.ukrainealarm.comAPI that returns info about Ukraine air raid alarms.LimitationsThere is a limit of 200 requests per 5 minutes from a single IP address."} +{"package": "uasparser2", "pacakge-description": "Fast and reliable User Agent parser.Easy to usefrom uasparser2 import UASparser\n\nuas_parser = UASparser('/path/to/your/cache/folder', mem_cache_size=1000)\n\nresult = uas_parser.parse('YOUR_USERAGENT_STRING')\n\n# If input data is not avaible in cache folde, UASparser will download and prepare it on init.\n# Force data update by calling:\n\nuas_parser.updateData()FastParsing 100,000 real user agents (10,000 unique):\n\noriginal uasparser: 7264.2 sec\nuasparser2 without cache: 171.7 sec\nuasparser2 with cache(size 1000): 34.6 secLinksGitHub HomeUser Agent Database"} +{"package": "ua-spoofer", "pacakge-description": "ua_spooferA Python module which collects, lists, and returns up to date and commonly used\nUser Agent strings. This can be helpful for avoiding fingerprinting, and\nbypassing anti-bot/scraping measures. It also provides aRequestssession wrapper which automatically\nuses a random user agent on every connection.User AgentsAuser agentstring is sent as a\nheader in HTTP requests to identify which browser and operating system the\nclient is using. It can be used by websites to tailor the content to the device\nand software a visitor is using. It can also be used to block or restrict\ncertain programs' access, such as bots, web crawlers and scrapers. Another\nconsequence of these strings is they can help build a profile of a user, using\nthe unique compination of browser and operating system versions, a technique\ncalledfingerprinting.User agent spoofing replaces the user agent string with a random one from a\nlist of common strings, disguising the type of client from the server and\nmaking it harder to track the user between requests. This is one of the ways to\nbypass restrictions and mitigate against fingerprinting.DetailsA problem with similar modules and programs is they either use a static\ndataset, or scrape user agents from sources which are either badly outdated or\ncompletely broken. ua_spoofer attempts to solve this by fetching data which is\nup to date, based on the latest browser versions, and also amalgamates data\nfrom several sources. This provides redundancy and a good mix of current user\nagents, without depending on an API or downloading a static dataset which\nquickly goes out of date. More sources can be added over time without breaking\ncompatibility.Installingua_spoofer requires Python 3, plusRequestsandBeautifulSoup, commonly\nused modules for scraping purposes.pip install ua_spooferUsingGetting User Agentsfrom ua_spoofer import UserAgent\n\nua = UserAgent()\n\n# Random user agents from a specified browser \nua.chrome\nua.firefox\nua.ie\n\n# Any random user agent\nua.random\n\n# Get a list of supported browsers\nua.BROWSERS\n\n# Get the list of all user agent strings\nua.all\n\n# Update the list\nua.update()Using the Requests Session wrapperfrom ua_spoofer import SpoofSession\n\ns = SpoofSession()\n\n# Each request will use a different user agent string\n# A few other headers are randomised too\n# To demonstrate:\ns.get(\"https://icanhazheaders.com/\").json()\ns.get(\"https://icanhazheaders.com/\").json()\ns.get(\"https://icanhazheaders.com/\").json()\n\n# To get the UserAgent instance of the session\ns.ua\n\n# Updating the user agent list is done as you would expect\ns.ua.update()Other projectsAs mentioned earlier, there are other Python modules which attempt to do\nsimilar things:fake-useragentrequests-random-user-agentrandom_user_agentUser agent spoofing isn't the only technique to bypass restrictions, with more\nsites being Javascript based and using more aggressive techniques to protect\nagainst crawlers, bots and DDoS attacks, sometimes other methods are necessary,\nincluding headless browser automation.cloudflare-scrapeis a module\nto bypass Cloudflare's anti-bot systemPhantomJSis a scriptable headless browserSeleniumis a full browser automation frameworkScrapyis a Python framework for building crawlersSpynneris another scriptable Python\nbrowser moduleIn some cases, Tor or a VPN can be used to hide the client's IP address for\nproper anonymity.Licenseua_spoofer is released under the terms of the Apache 2.0 license."} +{"package": "uas-project", "pacakge-description": "No description available on PyPI."} +{"package": "uasset-dump", "pacakge-description": "Unreal Engine Assets DumpCommand-line Interface (CLI) responsible for returning the list of the assets of an Unreal Engine project into a JSON structure.DevelopmentPoetryUnreal Engine Assets Dumpproject used Poetry to declare all its dependencies.Poetryis a python dependency management tool to manage dependencies, packages, and libraries in your python project.We need to create the Python virtual environment using Poetry:poetryenvuse/Users/Shared/Epic\\Games/UE_5.2/Engine/Binaries/ThirdParty/Python3/Mac/bin/python3We can enter this virtual environment and install all the required dependencies:poetryshell\npoetryupdatePublicationTo publish a new version of theUnreal Engine Assets Dumplibrary toPypi, we need to execute the following command:poetrypublish--build--username$PYPI_USERNAME--password$PYPI_PASSWORDWhere the environment variables:$PYPI_USERNAME: The value__token__$PYPI_PASSWORD: TheAPI tokenused to authenticate when uploading packages to PyPI (e.g.,pypi-...)We generally defined a.envfile and add these environment variables:# Copyright (C) 2023 Bootloader. All rights reserved.\n#\n# This software is the confidential and proprietary information of\n# Bootloader or one of its subsidiaries. You shall not disclose this\n# confidential information and shall use it only in accordance with the\n# terms of the license agreement or other applicable agreement you\n# entered into with Bootloader.\n#\n# BOOTLOADER MAKES NO REPRESENTATIONS OR WARRANTIES ABOUT THE\n# SUITABILITY OF THE SOFTWARE, EITHER EXPRESS OR IMPLIED, INCLUDING BUT\n# NOT LIMITED TO THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR\n# A PARTICULAR PURPOSE, OR NON-INFRINGEMENT. BOOTLOADER SHALL NOT BE\n# LIABLE FOR ANY LOSSES OR DAMAGES SUFFERED BY LICENSEE AS A RESULT OF\n# USING, MODIFYING OR DISTRIBUTING THIS SOFTWARE OR ITS DERIVATIVES.\n\n# The Python Package Index (PyPI) API token to authenticate when\n# uploading this package to PyPI.\nPYPI_USERNAME=__token__\nPYPI_PASSWORD=pypi-(...)InstallationTo installUnreal Engine Assets Dumplibrary to Unreal Engine, execute the following command./Users/Shared/Epic\\Games/UE_5.1/Engine/Binaries/ThirdParty/Python3/Mac/bin/python3-mpipinstall--upgradeuasset-dump\n/Users/Shared/Epic\\Games/UE_5.2/Engine/Binaries/ThirdParty/Python3/Mac/bin/python3-mpipinstall--upgradeuasset-dump/Users/admin/Library/JenkinsAgent/workspace/client-app/scooby-app-build/main/Scooby/ContentExecutionThen we can load our Unreal Engine project in Unreal Engine Editor and execute the following Python instructions in the Output Log drawer:frombootloader.ue.utilsimportuasset_dump\nuasset_dump.dump_assets('/Users/dcaune/Devel/Bootloader/bootloader-human-trainer-ar5/Content')This prints long JSON data. For instance:[{\"asset_name\":\"A_d2_ChangeOutfit_01\",\"asset_class_path\":\"/Script/Engine/AnimSequence\",\"package_name\":\"/Game/ArtAssets/Pets/QuadrupedDog/Animations/A_d2_ChangeOutfit_01\",\"dependencies\":[\"/Game/ArtAssets/Pets/QuadrupedDog/Mesh/S_d2\"]},{\"asset_name\":\"A_d2_ChangeOutfit_02\",\"asset_class_path\":\"/Script/Engine/AnimSequence\",\"package_name\":\"/Game/ArtAssets/Pets/QuadrupedDog/Animations/A_d2_ChangeOutfit_02\",\"dependencies\":[\"/Game/ArtAssets/Pets/QuadrupedDog/Mesh/S_d2\"]},(...)]exportUNREAL_ENGINE_PROJECT_PATH=/Users/admin/Library/JenkinsAgent/workspace/client-app/scooby-app-build/main/Scooby/Scooby.uprojectexportUNREAL_ENGINE_ASSET_DUMP_FILE_PATH=/Users/admin/bootloader-scooby-uassets.dump.json\"`find \"/Users/Shared/EpicGames/UE_5.2\" -name UnrealEditor-Cmd`\"\\\"$UNREAL_ENGINE_PROJECT_PATH\"\\-run=pythonscript\\-stdout\\-Unattended\\-script=\"/Users/admin/Downloads/run.py\"echo$?;Command Line Execution"} +{"package": "uassist", "pacakge-description": "uassist**UASsist: Assistant for Unmanned Aircraft System photogrammetry for surveying and mapping applications. **Free software: GNU General Public License v3Documentation:https://nathanmckinney.github.io/UASsist/FeaturesReads image metadata and displays information important for UAS surveysDisplays photo coordinates on a map embedded in a notebookInput single image or folder containing multiple imagesFolder inputs will calculate average, min, max altitude for project and range of timestampsChange basemaps and upload geojson or shapefiles to display mapConverts image locations and attributes to files:CSV textGEOJSONKMLGEOPACKAGEESRI ShapefileTODO:Create project metadata fileSeparate images into sub project folders using breaks in timestampCreate flight pattern linesCheck EXIF altitude over DEM elevationCreditsThis package was created withCookiecutterand thegiswqs/pypackageproject template."} +{"package": "uas-standards", "pacakge-description": "uas_standardsThis library primarily provides data types and tools for working with standards related to uncrewed aircraft systems (UAS)."} +{"package": "ua-stache-api", "pacakge-description": "UA-Stache-APIAllows the caller to easily get \"secret\" information from stache entries at [https://stache.arizona.edu].MotivationTo make a python API that could generically get information from stache.Code Examplefromua_stache_apiimportua_stache_apikey,url=ua_stache_api.get_entry(file_name)ua_stache_api.auth(key,url)Where file_name is the name of file with content such as:{\"X-STACHE-READ-KEY\":\"stache_read_key\",\"endpoint\":\"stache_endpoint\"}stache secret must be a JSON-able dictionary that can be nested.Installationpip install --user ua-stache-apiTestscd ./ua_stache_api/tests\npython -m nose ./test_ua_stache_api.pyCreditssterns1raflopjrRyanJohannesBlandLicenseMIT"} +{"package": "uat-breeze-connect", "pacakge-description": "IndexUAT_Breeze_Connect_SDKSetup Virtual EnvironmentInstalling the clientWebsocket UsageAPI Usageget_customer_detailsget_demat_holdingsget_fundsset_fundsget_historical_dataadd_marginget_marginplace_orderorder_detailorder_listcancel_ordermodify_orderget_portfolio_holdingget_portfolio_positionget_quotesget_option_chain_quotessquare_offmodify_orderget_trade_listget_trade_detailUAT Breeze Connect SDKUAT Breeze ConnectThis is a package to integrate streaming of stocks or user's order-notification & call APIs through which you can fetch live/historical data, automate your trading strategies, and monitor your portfolio in real time.Setup virtual environmentSetup virtual environment in your MachineYou must install the virtualenv package via pippip install virtualenvYou should create breeze virtual environment via virtualenvvirtualenv -p python3 breeze_venvAnd then, You can activate virtual environment via sourcesource breeze_venv/bin/activateInstalling the clientInstalling the clientYou can install the latest release via pippip install --upgrade uat-breeze-connectOr, You can also install the specific release version via pippip install uat-breeze-connect==1.0.14rc35Websocket UsageWebsocket Usagefrombreeze_connectimportBreezeConnect# Initialize SDKbreeze=BreezeConnect(api_key=\"your_api_key\")# Obtain your session key from https://uatapi.icicidirect.com/apiuser/login?api_key=YOUR_API_KEY# Incase your api-key has special characters(like +,=,!) then encode the api key before using in the url as shown below.importurllibprint(\"https://uatapi.icicidirect.com/apiuser/login?api_key=\"+urllib.parse.quote_plus(\"your_api_key\"))# Generate Sessionbreeze.generate_session(api_secret=\"your_secret_key\",session_token=\"your_api_session\")# Connect to websocketbreeze.ws_connect()# Callback to receive ticks.defon_ticks(ticks):print(\"Ticks:{}\".format(ticks))# Assign the callbacks.breeze.on_ticks=on_ticks# subscribe stocks feedsbreeze.subscribe_feeds(exchange_code=\"NFO\",stock_code=\"ZEEENT\",product_type=\"options\",expiry_date=\"31-Mar-2022\",strike_price=\"350\",right=\"Call\",get_exchange_quotes=True,get_market_depth=False)# subscribe stocks feeds by stock-tokenbreeze.subscribe_feeds(stock_token=\"1.1!500780\")# unsubscribe stocks feedsbreeze.unsubscribe_feeds(exchange_code=\"NFO\",stock_code=\"ZEEENT\",product_type=\"options\",expiry_date=\"31-Mar-2022\",strike_price=\"350\",right=\"Call\",get_exchange_quotes=True,get_market_depth=False)# unsubscribe stocks feeds by stock-tokenbreeze.unsubscribe_feeds(stock_token=\"1.1!500780\")# subscribe order notification feedsbreeze.subscribe_feeds(get_order_notification=True)NOTEExamples for stock_token are \"4.1!38071\" or \"1.1!500780\".exchange_code must be 'BSE', 'NSE', 'NDX', 'MCX' or 'NFO'.stock_code should not be an empty string. Examples for stock_code are \"WIPRO\" or \"ZEEENT\".product_type can be either 'Futures', 'Options' or an empty string. product_type can not be an empty string for exchange_code 'NDX', 'MCX' and 'NFO'.strike_date can be in DD-MMM-YYYY(Ex.: 01-Jan-2022) or an empty string. strike_date can not be an empty string for exchange_code 'NDX', 'MCX' and 'NFO'.strike_price can be float-value in string or an empty string. strike_price can not be an empty string for product_type 'Options'.right can be either 'Put', 'Call' or an empty string. right can not be an empty string for product_type 'Options'.Either get_exchange_quotes must be True or get_market_depth must be True. Both get_exchange_quotes and get_market_depth can be True, But both must not be False.API UsageAPI Usagefrombreeze_connectimportBreezeConnect# Initialize SDKbreeze=BreezeConnect(api_key=\"your_api_key\")# Obtain your session key from https://uatapi.icicidirect.com/apiuser/login?api_key=YOUR_API_KEY# Incase your api-key has special characters(like +,=,!) then encode the api key before using in the url as shown below.importurllibprint(\"https://uatapi.icicidirect.com/apiuser/login?api_key=\"+urllib.parse.quote_plus(\"your_api_key\"))# Generate Sessionbreeze.generate_session(api_secret=\"your_secret_key\",session_token=\"your_api_session\")# Generate ISO8601 Date/DateTime Stringimportdatetimeiso_date_string=datetime.datetime.strptime(\"28/02/2021\",\"%d/%m/%Y\").isoformat()[:10]+'T05:30:00.000Z'iso_date_time_string=datetime.datetime.strptime(\"28/02/2021 23:59:59\",\"%d/%m/%Y %H:%M:%S\").isoformat()[:19]+'.000Z'Following are the complete list of API method:customer_detailGet Customer details by api-session value.breeze.get_customer_details(api_session=\"your_api_session\")Back to Indexdemat_holdingGet Demat Holding details of your account.breeze.get_demat_holdings()Back to Indexget_fundsGet Funds details of your account.breeze.get_funds()Back to Indexset_fundsSet Funds of your accountbreeze.set_funds(transaction_type=\"debit\", \n amount=\"200\",\n segment=\"Equity\")# Note: Set Funds of your account by transaction-type as \"Credit\" or \"Debit\" with amount in numeric string as rupees and segment-type as \"Equity\" or \"FNO\".Back to Indexhistorical_dataGet Historical Data for Futuresbreeze.get_historical_data(interval=\"1minute\",\n from_date= \"2022-08-15T07:00:00.000Z\",\n to_date= \"2022-08-17T07:00:00.000Z\",\n stock_code=\"ICIBAN\",\n exchange_code=\"NFO\",\n product_type=\"futures\",\n expiry_date=\"2022-08-25T07:00:00.000Z\",\n right=\"others\",\n strike_price=\"0\")Get Historical Data for Equitybreeze.get_historical_data(interval=\"1minute\",\n from_date= \"2022-08-15T07:00:00.000Z\",\n to_date= \"2022-08-17T07:00:00.000Z\",\n stock_code=\"ITC\",\n exchange_code=\"NSE\",\n product_type=\"cash\")Get Historical Data for Optionsbreeze.get_historical_data(interval=\"1minute\",\n from_date= \"2022-08-15T07:00:00.000Z\",\n to_date= \"2022-08-17T07:00:00.000Z\",\n stock_code=\"CNXBAN\",\n exchange_code=\"NFO\",\n product_type=\"options\",\n expiry_date=\"2022-09-29T07:00:00.000Z\",\n right=\"call\",\n strike_price=\"38000\")# Note : Get Historical Data for specific stock-code by mentioned interval either as \"1minute\", \"5minute\", \"30minutes\" or as \"1day\"Back to Indexadd_marginAdd Margin to your account.breeze.add_margin(product_type=\"margin\", \n stock_code=\"ICIBAN\", \n exchange_code=\"BSE\", \n settlement_id=\"2021220\", \n add_amount=\"100\", \n margin_amount=\"3817.10\", \n open_quantity=\"10\", \n cover_quantity=\"0\", \n category_index_per_stock=\"\", \n expiry_date=\"\", \n right=\"\", \n contract_tag=\"\", \n strike_price=\"\", \n segment_code=\"\")Back to Indexget_marginGet Margin of your account.breeze.get_margin(exchange_code=\"NSE\")# Note: Please change exchange_code=\u201cNFO\u201d to get F&O margin detailsBack to Indexplace_orderPlacing a Futures Order from your account.breeze.place_order(stock_code=\"ICIBAN\",\n exchange_code=\"NFO\",\n product=\"futures\",\n action=\"buy\",\n order_type=\"limit\",\n stoploss=\"0\",\n quantity=\"3200\",\n price=\"200\",\n validity=\"day\",\n validity_date=\"2022-08-22T06:00:00.000Z\",\n disclosed_quantity=\"0\",\n expiry_date=\"2022-08-25T06:00:00.000Z\",\n right=\"others\",\n strike_price=\"0\",\n user_remark=\"Test\")Placing an Option Order from your account.breeze.place_order(stock_code=\"NIFTY\",\n exchange_code=\"NFO\",\n product=\"options\",\n action=\"buy\",\n order_type=\"market\",\n stoploss=\"\",\n quantity=\"50\",\n price=\"\",\n validity=\"day\",\n validity_date=\"2022-08-30T06:00:00.000Z\",\n disclosed_quantity=\"0\",\n expiry_date=\"2022-09-29T06:00:00.000Z\",\n right=\"call\",\n strike_price=\"16600\")Place a cash order from your account.breeze.place_order(stock_code=\"ITC\",\n exchange_code=\"NSE\",\n product=\"cash\",\n action=\"buy\",\n order_type=\"limit\",\n stoploss=\"\",\n quantity=\"1\",\n price=\"305\",\n validity=\"day\"\n )Back to Indexget_order_detailGet an order details by exchange-code and order-id from your account.breeze.get_order_detail(exchange_code=\"NSE\",\n order_id=\"20220819N100000001\")# Note: Please change exchange_code=\u201cNFO\u201d to get details about F&OBack to Indexget_order_listGet order list of your account.breeze.get_order_list(exchange_code=\"NSE\",\n from_date=\"2022-08-01T10:00:00.000Z\",\n to_date=\"2022-08-19T10:00:00.000Z\")# Note: Please change exchange_code=\u201cNFO\u201d to get details about F&OBack to Indexcancel_orderCancel an order from your account whose status are not Executed.breeze.cancel_order(exchange_code=\"NSE\",\n order_id=\"20220819N100000001\")Back to Indexmodify_orderModify an order from your account whose status are not Executed.breeze.modify_order(order_id=\"202208191100000001\",\n exchange_code=\"NFO\",\n order_type=\"limit\",\n stoploss=\"0\",\n quantity=\"250\",\n price=\"290100\",\n validity=\"day\",\n disclosed_quantity=\"0\",\n validity_date=\"2022-08-22T06:00:00.000Z\")Back to Indexget_portfolio_holdingGet Portfolio Holdings of your account.breeze.get_portfolio_holdings(exchange_code=\"NFO\",\n from_date=\"2022-08-01T06:00:00.000Z\",\n to_date=\"2022-08-19T06:00:00.000Z\",\n stock_code=\"\",\n portfolio_type=\"\")# Note: Please change exchange_code=\u201cNSE\u201d to get Equity Portfolio HoldingsBack to Indexget_portfolio_positionGet Portfolio Positions from your account.breeze.get_portfolio_positions()Back to Indexget_quotesGet quotes of mentioned stock-codebreeze.get_quotes(stock_code=\"ICIBAN\",\n exchange_code=\"NFO\",\n expiry_date=\"2022-08-25T06:00:00.000Z\",\n product_type=\"futures\",\n right=\"others\",\n strike_price=\"0\")Back to Indexget_option_chainGet option-chain of mentioned stock-code for product-type Futures where input of expiry-date is not compulsorybreeze.get_option_chain_quotes(stock_code=\"ICIBAN\",\n exchange_code=\"NFO\",\n product_type=\"futures\",\n expiry_date=\"2022-08-25T06:00:00.000Z\")Get option-chain of mentioned stock-code for product-type Options where atleast 2 input is required out of expiry-date, right and strike-pricebreeze.get_option_chain_quotes(stock_code=\"ICIBAN\",\n exchange_code=\"NFO\",\n product_type=\"options\",\n expiry_date=\"2022-08-25T06:00:00.000Z\",\n right=\"call\",\n strike_price=\"16850\")Back to Indexsquare_offSquare off an Equity Margin Orderbreeze.square_off(exchange_code=\"NSE\",\n product=\"margin\",\n stock_code=\"NIFTY\",\n quantity=\"10\",\n price=\"0\",\n action=\"sell\",\n order_type=\"market\",\n validity=\"day\",\n stoploss=\"0\",\n disclosed_quantity=\"0\",\n protection_percentage=\"\",\n settlement_id=\"\",\n cover_quantity=\"\",\n open_quantity=\"\",\n margin_amount=\"\")# Note: Please refer get_portfolio_positions() for settlement id and margin_amountSquare off an FNO Futures Orderbreeze.square_off(exchange_code=\"NFO\",\n product=\"futures\",\n stock_code=\"ICIBAN\",\n expiry_date=\"2022-08-25T06:00:00.000Z\",\n action=\"sell\",\n order_type=\"market\",\n validity=\"day\",\n stoploss=\"0\",\n quantity=\"50\",\n price=\"0\",\n validity_date=\"2022-08-12T06:00:00.000Z\",\n trade_password=\"\",\n disclosed_quantity=\"0\")Square off an FNO Options Orderbreeze.square_off(exchange_code=\"NFO\",\n product=\"options\",\n stock_code=\"ICIBAN\",\n expiry_date=\"2022-08-25T06:00:00.000Z\",\n right=\"Call\",\n strike_price=\"16850\",\n action=\"sell\",\n order_type=\"market\",\n validity=\"day\",\n stoploss=\"0\",\n quantity=\"50\",\n price=\"0\",\n validity_date=\"2022-08-12T06:00:00.000Z\",\n trade_password=\"\",\n disclosed_quantity=\"0\")Back to Indexget_trade_listGet trade list of your account.breeze.get_trade_list(from_date=\"2022-08-01T06:00:00.000Z\",\n to_date=\"2022-08-19T06:00:00.000Z\",\n exchange_code=\"NSE\",\n product_type=\"\",\n action=\"\",\n stock_code=\"\")# Note: Please change exchange_code=\u201cNFO\u201d to get details about F&OBack to Indexget_trade_detailGet trade detail of your account.breeze.get_trade_detail(exchange_code=\"NSE\",\n order_id=\"20220819N100000005\")# Note: Please change exchange_code=\u201cNFO\u201d to get details about F&OBack to Index"} +{"package": "uat-python-cicd", "pacakge-description": "Welcome to the kount-ris-python-sdk wiki!Kount Python RIS SDKContains the Kount Python SDK, tests, and build/package routines.What is this repository for?Kount's SDK helps integrate Kount's fraud fighting solution into your python app.http://www.kount.com/fraud-detection-softwareContains sources, tests, and resources for the Kount Python SDK\nSDK version: 3.2.0\nPython 3.5, 3.6.1How do I get set up?pip install kount_ris_sdkHow to run integration tests in root directory?First, you need to obtain configuration key from Kount.Download the source code fromhttps://github.com/Kount/kount-ris-python-sdkGo to the root directory of the project and execute:pip install .[test]Execute tests providing the configuration key on the command linepytest tests --conf-key={KEY}or set shell environmentexport CONF_KEY={KEY}\npytest testsHow to use the SDKFor more information read the official docs:https://kount.github.ioSetting up IDE projectsKomodo IDE/Edit, Scite, Visual Studio - have automatic python integrationWho do I talk to?Repo owner or admin\nOther community or team contact"} +{"package": "uatraits", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "uavcan", "pacakge-description": "Legacy UAVCAN/CAN v0 in PythonTHIS PACKAGE HAS BEEN REPUBLISHED UNDER A DIFFERENT NAME:pyuavcan_v0Please update your references to usepyuavcan_v0-- a drop-in replacement.Find context athttps://github.com/UAVCAN/pyuavcan/issues/166.Ask questions atforum.uavcan.org."} +{"package": "uaverify", "pacakge-description": "Urban Airship Verification==========================Command line tools for verifying builds with Urban Airship. Two command line toolsare installed, one for use with iOS builds, one for use with Android builds.Setup for Use-------------The script is written against the default install of Python 2.7.2 installed on OS X 10.8.3.It's been designed to have no third party dependencies. Running on a previous version ofPython has not been thoroughly tested, and my have issues. You can set the defaultPython version with the following command, see *man python* for more details::defaults write com.apple.versioner.python Version 2.7You can install the tool multiple ways. If you aren't using a virtualenv, you'llneed to sudo to install the tool::pip install uaverify (if pip is available) or easy_install uaverifySetup for Development---------------------If you want to work on the tools themselves, this is a useful install method.Run it from the root of the project repo::python setup.py developIf you want to take the tool out for a spin directly from the repository, this command will installit in your local bin::pip install -e \"git+git@github.com:urbanairship/uaverify.git#egg=uaverify\"Usage-----**Breaking changes from previous release**uaverify has now changed to uav-ios with the addition of the uav-android tool. Now both tools areinstalled at the same time.This::uaverify /path/to/appis now::uav-ios /path/to/app <--> uav-android /path/to/project/dir**Standard usage for iOS**::uav-ios /path/to/appThe path to the build output (the AppName.app) bundle is dependent on the Xcode build configuration.Please see the Xcode documentation for more details:http://developer.apple.com/library/mac/#documentation/DeveloperTools/Reference/XcodeBuildSettingRef/0-Introduction/introduction.htmlYou can use xcodebuild to locate the build output path, specifically the CODESIGNING_FOLDER_PATH parameter. This path changesaccording to your build settings, so make sure and use the proper configuration. See the xcodebuild manpage for more information**Standard usage for Android**::uav-android /path/to/project/directory**For projects with more than one AndroidManifest, you'll need to pass the path to the manifest you want to use.**::uav-android /path/to/project/directory -m /path/to/manifest**Diagnostic usage for either tool**::uav-ios /path/to/app -d or uav-android /path/to/project/dir/ -dThe `-d` command line flag will product a diagnostic file by logging to stdoutand a file at the same time with the additional step of appending the rawentitlements, API response, and AirshipConfig.plist data to the end of thefile. You can append this file to support correspondence or bug reports."} +{"package": "uav-fdm", "pacakge-description": "uav_fdm \u65e0\u4eba\u673a\u52a8\u529b\u5b66\u6a21\u578b\u6982\u8ff0\u672c\u9879\u76ee\u5c06matlab\u4ee3\u7801\u751f\u6210\u7684\u4e09\u81ea\u7531\u5ea6\u98de\u884c\u52a8\u529b\u5b66\u6a21\u578bC++\u7c7b\u901a\u8fc7SWIG\u8fdb\u884c\u5305\u88c5\uff0c\u5e76\u901a\u8fc7pip\u53d1\u5e03\u3002\u7f16\u8bd1\u5b89\u88c5\u672c\u5730\u7f16\u8bd1pythonsetup.pybuild_ext--inplace\u5b89\u88c5\u7f16\u8bd1pythonsetup.pyinstall--userpip\u5b89\u88c5pipinstalluav-fdm\u63a5\u53e3\u8bf4\u660e\u6a21\u5757\u540d\u79f0\u4e3auav_fdm;\n\u5176\u4e2d\u7684\u7c7b\u540d\u79f0\u4e3auav_fdm\u3002\u521d\u59cb\u5316\u7c7b\u7684\u521d\u59cb\u5316\u51fd\u6570\u4e3auav_fdm.uav_fdm(x0, y0, alt0, gs0, gamma0, psi0, phi0)\u53c2\u6570\u8bf4\u660e\u5355\u4f4dx0\u521d\u59cbxmy0\u521d\u59cbymalt0\u521d\u59cb\u9ad8\u5ea6mgs0\u521d\u59cb\u5730\u901fm/sgamma0\u521d\u59cb\u822a\u8ff9\u503e\u89d2radpsi0\u521d\u59cb\u771f\u822a\u5411radphi0\u521d\u59cb\u6eda\u8f6c\u89d2rad\u4eff\u771f\u6b65\u8fdb\u7c7b\u7684\u4eff\u771f\u6b65\u8fdb\u51fd\u6570\u4e3a[t, x, y, alt, v_n, v_e, hdot, phi, psi_t, gamma, gs, tas] = uav1.update(dt, tas_c, hdot_c, psi_c, w_n, w_e)\u8f93\u5165\u53c2\u6570\u8bf4\u660e\u5355\u4f4ddt\u6b65\u8fdb\u65f6\u95f4\uff08\u4e3a0.05s\u6574\u500d\u6570\uff09stas_c\u771f\u7a7a\u901f\u6307\u4ee4m/shdot_c\u5347\u964d\u901f\u7387\u6307\u4ee4m/spsi_c\u822a\u5411\u89d2\u6307\u4ee4radw_n\u5317\u98ce\u901f\u5ea6m/sw_e\u4e1c\u98ce\u901f\u5ea6m/s\u8f93\u51fa\u53d8\u91cf\u8bf4\u660e\u5355\u4f4dt\u65f6\u95f4sxxmyymalt\u9ad8\u5ea6mv_n\u5317\u5411\u901f\u5ea6m/sv_e\u4e1c\u5411\u901f\u5ea6m/shdot\u5929\u5411\u901f\u5ea6m/sphi\u6eda\u8f6c\u89d2radpsi_t\u771f\u822a\u5411\u89d2(-pi~pi)radgamma\u822a\u8ff9\u503e\u89d2radgs\u5730\u901fm/stas\u771f\u7a7a\u901fm/s\u6307\u4ee4\u9650\u5236\u98de\u884c\u771f\u7a7a\u901f\u6307\u4ee4\u9650\u523614~24m/s\u5347\u7ea7\u901f\u7387\u6307\u4ee4\u9650\u5236-3~3m/s\u504f\u822a\u89d2\u6307\u4ee4\u9650\u5236-pi~pi rad\u4f7f\u7528\u793a\u4f8bimportuav_fdmif__name__=='__main__':x0=23# \u521d\u59cbx\uff08m\uff09y0=110# \u521d\u59cby\uff08m\uff09alt0=130# \u521d\u59cb\u9ad8\u5ea6\uff08m\uff09gs0=22# \u521d\u59cb\u5730\u901f\uff08m/s\uff09gamma0=0# \u521d\u59cb\u822a\u8ff9\u503e\u89d2\uff08rad\uff09psi0=3.14# \u521d\u59cb\u771f\u822a\u5411\uff08rad\uff09phi0=0# \u521d\u59cb\u6eda\u8f6c\u89d2\uff08rad\uff09# \u521d\u59cb\u5316uav1uav1=uav_fdm.uav_fdm(x0,y0,alt0,gs0,gamma0,psi0,phi0)# \u8fdb\u884c5\u79d2\u5e73\u98de\u4eff\u771ftas_c=22# \u771f\u7a7a\u901f\u6307\u4ee4(m/s)hdot_c=0# \u5347\u964d\u901f\u7387\u6307\u4ee4(m/s)psi_c=3.14# \u822a\u5411\u89d2\u6307\u4ee4(rad)w_n=0# \u5317\u98ce\u901f\u5ea6(m/s)w_e=0# \u4e1c\u98ce\u901f\u5ea6(m/s)t=0dt=1# \u63091\u79d2\u63a8\u8fdbwhilet<5:[t,x,y,alt,v_n,v_e,hdot,phi,psi_t,gamma,gs,tas]=uav1.update(dt,tas_c,hdot_c,psi_c,w_n,w_e)print(f'{t:.0f}{x:.0f}{y:.0f}{alt:.2f}{gs:.2f}{psi_t*57.3:.2f}{phi*57.3:.2f}')# \u8fdb\u884c15\u79d2\u8f6c\u5f2f\u4eff\u771ftas_c=22# \u771f\u7a7a\u901f\u6307\u4ee4(m/s)hdot_c=0# \u5347\u964d\u901f\u7387\u6307\u4ee4(m/s)psi_c=1.57082# \u822a\u5411\u89d2\u6307\u4ee4(rad)w_n=0# \u5317\u98ce\u901f\u5ea6(m/s)w_e=0# \u4e1c\u98ce\u901f\u5ea6(m/s)t=0dt=1# \u63091\u79d2\u63a8\u8fdbwhilet<20:[t,x,y,alt,v_n,v_e,hdot,phi,psi_t,gamma,gs,tas]=uav1.update(dt,tas_c,hdot_c,psi_c,w_n,w_e)print(f'{t:.0f}{x:.0f}{y:.0f}{alt:.2f}{gs:.2f}{psi_t*57.3:.2f}{phi*57.3:.2f}')# \u8fdb\u884c5\u79d2\u722c\u5347\u4eff\u771ftas_c=22# \u771f\u7a7a\u901f\u6307\u4ee4(m/s)hdot_c=1# \u5347\u964d\u901f\u7387\u6307\u4ee4(m/s)psi_c=1.57082# \u822a\u5411\u89d2\u6307\u4ee4(rad)w_n=0# \u5317\u98ce\u901f\u5ea6(m/s)w_e=0# \u4e1c\u98ce\u901f\u5ea6(m/s)t=0dt=1# \u63091\u79d2\u63a8\u8fdbwhilet<25:[t,x,y,alt,v_n,v_e,hdot,phi,psi_t,gamma,gs,tas]=uav1.update(dt,tas_c,hdot_c,psi_c,w_n,w_e)print(f'{t:.0f}{x:.0f}{y:.0f}{alt:.2f}{gs:.2f}{psi_t*57.3:.2f}{phi*57.3:.2f}')# \u8fdb\u884c5\u79d2\u52a0\u901f\u4eff\u771ftas_c=24# \u771f\u7a7a\u901f\u6307\u4ee4(m/s)hdot_c=0# \u5347\u964d\u901f\u7387\u6307\u4ee4(m/s)psi_c=1.57082# \u822a\u5411\u89d2\u6307\u4ee4(rad)w_n=0# \u5317\u98ce\u901f\u5ea6(m/s)w_e=0# \u4e1c\u98ce\u901f\u5ea6(m/s)t=0dt=1# \u63091\u79d2\u63a8\u8fdbwhilet<30:[t,x,y,alt,v_n,v_e,hdot,phi,psi_t,gamma,gs,tas]=uav1.update(dt,tas_c,hdot_c,psi_c,w_n,w_e)print(f'{t:.0f}{x:.0f}{y:.0f}{alt:.2f}{gs:.2f}{psi_t*57.3:.2f}{phi*57.3:.2f}')"} +{"package": "uavgeo", "pacakge-description": "uavgeo \u26f0\ufe0fA UAV-specific Python image processing library built uponxarrayandgeopandas.Explore the wiki \u00bbReport Bug.Request FeatureTable Of ContentsSummaryFeaturesIndex calculationDataset chippingDEM creationDataset shadowsInstallationSummaryUAV image analysis is a powerful tool to gain valuable insights into the rural, urban and natural environment. Especially in conjunction with Deep Learning, large strides can be made. The problem however is that there is little standardization and a lot of boilerplate code to be written for image analysis. This package serves to bridge the gap in image processing and machine learning in UAV applications. It builds upon the efforts fromxarray,rasterio/rioxarrayandgeopandas.\nImporting should be done through rioxarray functions. The currently implemented functions inuavgeoexamples cover index calculation (see below) and data/rastser chipping and reconstruction.FeaturesTheuavgeopackage can be installed throughpip. Additionally, a docker container with jupyterlab can be used. See the Installation section for more information.Dataset chippingChipping is a prerequisite for geographic raster data to be processed for ML/DL models.\nThis library implements it as follows:creating a chips-geodataframe based on wanted dimensions, overlap and raster shapechipping the input raster into a list of chipsreset the coordinates from crs to image pixels (numpy assumed dimensions)export the list of images to file (or do whatever)(optional): perform the ML modelling on the chips(optional): reconstruct the images back to the original raster and crsThis whole pipeline and functions are presented in anexample notebookCreating a dem with thecalc_dem_from_dsmfunctionThecalc_dem_from_dsmfunction is a utility to create a Digital Elevation Model (DEM) from a Digital Surface Model (DSM) using specified sampling parameters. It operates on data represented as xarray DataArray and relies on the rasterio library for Geographic Information System (GIS) operations. The resulting DEM is created by sampling and extracting the minimum elevation values from the DSM at a user-defined grid, built upon the chipping presented above.An example can be found in anexample notebookInputs:dsm (xr.DataArray): The input Digital Surface Model as an xarray DataArray.pixel_size (float): The pixel size in the same unit as the DSM data.sampling_meters (float): The distance in meters that defines the sampling grid for DEM creation.importuavgeoasugimportrioxarraryasrxrdsm_data=rxr.open_rasterio(('dsm.tif')# Load DSM data from a GeoTIFF filepixel_size=1.0# Specify the pixel size in meterssampling_distance=10.0# Define the sampling distance in metersdem=ug.compute.calc_dem_from_dsm(dsm_data,pixel_size,sampling_distance)# Calculate the DEMchm=dem-dsm_data# subtract the two, and you have a Canopy Height Model tooIndex calculationsYou can use it to calculate a variety of indices from your imagery:# assuming you already loaded your data as ortho:importuavgeoasugsavi=ug.compute.calc_savi(bandstack=ortho,red_id=1,nir_id=4,l=0.51)savi.plot.imshow(cmap=\"greens\")Implemented indices:Based on the list fromFieldImageR. With some additional indices added.\nThey can be accesses through theuavgeo.computemodule. All functions expect abandstack, which is anxarray.DataArraywityh multiple bands asbandsdata. And the required bands ids, eg.:red_id=1. By default the functions rescale the output floats back to uint8 (0-255). This behaviour can be turned of with therescale = Falseparameter.Indexcalc_indexnameDescriptionFormulaRelated TraitsReferencesBIcalc_biBrightness Indexsqrt((RA^2+GA^2+B^2)/3)Vegetation coverage, water contentRichardson and Wiegand (1977)SCIcalc_sciSoil Color Index(R-G)/(R+G)Soil colorMathieu et al. (1998)GLIcalc_gliGreen Leaf Index(2 * G-R-B)/(2 * G+R+B)ChlorophyllLouhaichi et al. (2001)HIcalc_hiHue Index(2*R-G-B)/(G-B)Soil colorEscadafal et al. (1994)NGRDIcalc_ngrdiNormalized Green Red Difference Index(G-R)/(G+R)Chlorophyll, biomass, water contentTucker (1979)SIcalc_siSaturation Index(R-B)/(R+B)Soil colorEscadafal et al. (1994)VARIcalc_variVisible Atmospherically Resistant Index(G-R)/(G+R-B)Canopy, biomass, chlorophyllGitelson et al. (2002)HUEcalc_hueOverall Hue Index#atan(2*(B-G-R)/30.5*(G-R))Soil colorEscadafal et al. (1994)BGIcalc_bgiBlue Green Pigment IndexB/GChlorophyllZarco-Tejada et al. (2005)PSRIcalc_psriPlant Senescence Reflectance Index(R-G)/(RE)Chlorophyll, LAIMerzlyak et al. (1999)NDVIcalc_ndviNormalized Difference Vegetation Index(NIR-R)/(NIR+R)Chlorophyll, nitrogen, maturityRouse et al. (1974)GNDVIcalc_gndviGreen Normalized Difference Vegetation Index(NIR-G)/(NIR+G)Chlorophyll, LAI, biomass, yieldGitelson et al. (1996)RVIcalc_rviRatio Vegetation IndexNIR/RChlorophyll, LAI, nitrogen, protein content, water contentPearson and Miller (1972)NDREcalc_ndreNormalized Difference Red Edge Index(NIR-RE)/(NIR+RE)Biomass, water content, nitrogenGitelson and Merzlyak (1994)TVIcalc_tviTriangular Vegetation Index0.5 * (120 * (NIR \u2014 G)-200 * (R \u2014 G))ChlorophyllBroge and Leblanc (2000)CVIcalc_cviChlorophyll Vegetation Index(NIR * R)/(GA^2)ChlorophyllVincini et al. (2008)EVIcalc_eviEnhanced Vegetation Index2.5 *(NIR \u2014 R)/(NIR + 6 * R \u2014 7.5 * B)Nitrogen, chlorophyllHuete et al. (2002)CIGcalc_cigChlorophyll Index \u2014 Green(NIR/G) \u2014 1ChlorophyllGitelson et al. (2003)CIREcalc_cireChlorophyll Index \u2014 Red Edge(NIR/RE) \u2014 1ChlorophyllGitelson et al. (2003)DVIcalc_dviDifference Vegetation IndexNIR-RENitrogen, chlorophyllJordan (1969)RGBVIcalc_rgbviRGB Vegetation Index((G^2)-(R * B)/(G^2)+(R * B))Nitrogen, chlorophyllBendig et al. (2015)SAVIcalc_saviSoil Adjusted Vegetation Index(NIR-R)/(NIR+R+l)*(1+l)Vegetation coverage, LAIHuete (1988)-------------------------------------------------------------------------NDWIcalc_ndwiNormalized Difference Water Index(G-NIR)/(G+NIR)Water coverage, water contentMcFeeters (1996)MNDWIcalc_mndwiModified Normalized Difference Water Index(G-SWIR)/(GREEN+SWIR)Water coverage, water contentMcFeeters (1996)AWEIshcalc_aweishAutomated water extraction index (sh)B + 2.5 * G - 1.5 * (NIR-SWIR1) - 0.25 * SWIR2Water coverage, water contentFayeisha (2014)AWEInshcalc_aweinshAutomated water extraction index (nsh)4 * (G - SWIR1) - (0.25 * NIR + 2.75* SWIR1)Water coverage, water contentFayeisha (2014)Custom/other spectral index:You could also write your own index calculators, according to the following template:fromuavgeo.computeimportrescale_floatsdefcalc_custom(bandstack:xr.DataArray,band_a=1,band_b=2,rescale=True):ds_b=bandstack.astype(float)a:xr.DataArray=ds_b.sel(band=band_a)b:xr.DataArray=ds_b.sel(band=band_b)custom=a/b+1custom.name=\"custom index\"ifrescale:custom=rescale_floats(custom)returncustomShadow calculations:Calculate vineyard shadows using a method proposed by Velez et al. (2021) for vineyards and UAVs. Based on Kmeans. Velez et al. (2021). \"A New Leaf Area Index Methodology Based on Unmanned Aerial Vehicle Imagery for Vineyards.\"https://oeno-one.eu/article/view/4639fromuavgeo.computeimportcalc_vineyard_shadowsvineyard_data=xr.open_rasterio('path/to/vineyard_image.tif')shadows_mask=calc_vineyard_shadows(vineyard_data)# can also be used with a band_id to base the shadows from (NIR or Red are usally best)shadows_mask=calc_vineyard_shadows(vineyard_data,band_id=4)Installation:It is built upon the work ofrioxarray,geopandas,shapelyand a few more: see requirements.txt.\nAdditionally, when working with the object detection part, theultralyticsandtorchlibraries (torch,torchvision,torchdata) is also a prerequisite.\nYou can choose to install everything in a Python virtual environment or directly run a jupyterlab docker:Option A: Setup directly in python:Create a new environment (optional but recommended):condacreate-nuavgeo_envpython=3.10\ncondaactivateuavgeo_envInstall the required dependencies:Using conda (not recommended):condainstall-cconda-forgerioxarraygeopandasshapelyUsing pip:pipinstall-frioxarraygeopandasshapelyInstall this package (for now: pip only)pipinstalluavgeoOption B: Setup through Docker:This starts a premade jupyter environment with everything preinstalled, based around a nvidia docker image for DL support.Linux/Ubuntu:dockerrun--rm-it--runtime=nvidia-p8888:8888--gpus1--shm-size=5gb--network=host-v/path_to_local/dir:/home/jovyanjurrain/drone-ml:gpu-torch11.8-uavgeoformers--network=hostflag whether you want to run it on a different machine in the same network, and want to access the notebook. (does not run locally)-vflag makes sure that once downloaded, it stays in that folder, accessible from the PC, and when restarting, all the weights etc. remain in that folder.path_to_local/diris thew path to your working dir where you want to access the notebook from. can be.if you alreadycded into it.--runtime=nvidiacan be skipped when working on WSL2Windows requires WSL2 and NVIDIA drivers, WSL2 should also have the nvidia toolkit (for deep learning)"} +{"package": "uavnoma", "pacakge-description": "System Model of UAV-NOMA System with Two-usersA Python 3.8 implementation of the System Model of Unmanned Aerial Vehicle with Non-Orthogonal Multiple Access (UAV-NOMA) System and 2 ground users under considerations of non-ideal conditions, such as imperfect successive interference cancelation (SIC) and residual hardware impairments (RHI). We consider a downlink UAV-aided NOMA network, as illustrated in the figure below.FeaturesTheuavnomapackage allows the user to study the modeling of a UAV-NOMA network and use it as a basis for implementing other technologies. This application can be used as a study tool to understand the behavior of the achievable rate by two users and the influence of the allocation of power coefficients in a UAV-NOMA system under non-ideal conditions. The communication model presented is a base of UAV-NOMA principles and can be expanded to several other scenarios, such as cooperative systems, full-duplex communication, and others in order to improve system performance.The user can modify parameters and analyze the system's behavior. Based on this, new methods can be proposed to solve UAV trajectory problems, power allocation, user pairing, energy harvesting for UAV maintenance, decoding order and others.The package contains functions to:Calculate the position of the UAV and users;Generate the channel gain between UAV and users;Calculate of the Signal Interference Noise Ratio (SINR);Analyze system performance using as metrics the instantaneous achievable rate and outage probability.A command line script is also included, allowing for anyone to experiment with the model without knowing or using Python. The user can run a simulation with default parameters using the following command:uavnomaThe script is fully parameterizable, and the available parameters can be listed with:uavnoma --helpRequirementsThe implementation requires Python 3.8+ to run.\nThe following libraries are also required:numpymatplotlibpandastabulateargparseHow to installFrom PyPIpip install uavnomaFrom source/GitHubDirectly using pip:pip install git+https://github.com/limabrena/uavnoma.git#egg=uavnomaOr each step at a time:git clone https://github.com/limabrena/uavnoma.git\ncd uavnoma\npip install .Installing for development and/or improving the packagegit clone https://github.com/limabrena/uavnoma.git\ncd uavnoma\npip install -e .[dev]This way, the package is installed in development mode. As a result, the pytest dependencies/plugins are also installed.Documentationuavnomapackage documentationDeveloper's guideScenario DescriptionLicenseMIT License"} +{"package": "uavro", "pacakge-description": "A cythonic acceleration of Avro tabular file readingUse this library to read Avro files into Pandas dataframes, where there are\nabsolutely no nested structures in the data schema."} +{"package": "uavsar-pytools", "pacakge-description": "uavsar_pytoolsPython tools to download and convert binary Uavsar images from the Alaska Satellite Facility and Jet Propulsion Laboratory databases. Developed by Zachary Keskinen and Jack Tarricone with guidance from Dr. Hans Peter Marshall of Boise State University, Micah Johnson with m3works, and Micah Sandusky with m3works.InstallingThis package is installable with pip. In the terminal enter the following command:pip install uavsar_pytoolsAuthorizationYou will need a.netrc filein your home directory. This is a special file that stores passwords and usernames to be accessed by programs. If you are already registered at either the alaska satellite facility or jet propulsion laboratory skip step 1. Otherwise:If you need a username and password register atlink. Please ensure you have signed the end user agreement for Uavsar. You need to attempt to download a uavsar image from vertex to prompt the end user agreement.In a python terminal or notebook enter:fromuavsar_pytools.uavsar_toolsimportcreate_netrccreate_netrc()You will be asked to prompted to enter your username and password and a netrc file will be automatically generated for you. This file will be accessed during downloading and searching for Uavsar images. You will only need to generate this file once on your computer.UsageThe fundamental class of uavsar_pytools is theUavsarScene. This class is used for downloading, unzipping, and converting binary UAVSAR files into Geotiffs in WGS84. In order to use the class you will need to instantiate an instance of the class to hold your specific url and the image data. Please see the included tutorial and code snippet below. After instantiating the class you can callscene.url_to_tiffs()to fully download and convert the Uavsar images into analysis ready tiffs. The two required inputs are a url to an ASF or JPL zip file (if looking to download a single image seeUavsarImagein the included notebooks) and that has been ground referenced (must have a .grd or _grd in the name) along with a directory that you want to store the image files in.fromuavsar_pytoolsimportUavsarScene## Example url. Use vertex to find other urls: https://search.asf.alaska.edu/zip_url='https://datapool.asf.alaska.edu/INTERFEROMETRY_GRD/UA/lowman_05208_21019-019_21021-007_0006d_s01_L090_01_int_grd.zip'## Change this variable to a directory you want to download files intoimage_directory='~/directory/to/store/images/'# Instantiating an instance of the UavsarScene class and downloading all imagesscene=UavsarScene(url=zip_url,work_dir=image_directory)scene.url_to_tiffs()You will now have a folder of analysis ready tiff images in WGS84 from the provided url in your specificed work directory.If you are interested in working with each image's numpy array the class has anscene.imagesproperty that contains the type, description, and numpy array for each image in the zip file. This is available after runningscene.url_to_tiffs().print(scene.image[0]['type']# figure out the type of the first imagescene.images[0]['array']# get the first image numpy array for analysisFor quick checks to visualize the data there is also a convenience methodscene.show(i = 1)that allows you to quickly visualize the first image, or by iterating on i = 2,3,4, etc all the images in the zip file. This method is only available after converting binary images to array withscene.url_to_tiffs().Downloading whole collectionsUavsar_pytools can now take a collection name and a start and end date and find, download, and process an entire collection of uavsar images. Collection names can be found atcampaign list. Once you know your campaign name and the date range you can give the package a working directory along with the name and dates and it will do the rest. For example if you want to download all uavsar images for Grand Mesa, Colorado from November 2019 to April 2020 and wanted to save it to your documents folder you would use:fromuavsar_pytoolsimportUavsarCollection## Collection name from the campaign listcol_name='Grand Mesa, CO'## Working directory to save files intowork_d='~/Documents/collection_ex/'## Optional dates to check betweendates=('2019-11-01','2020-04-01')collection=UavsarCollection(collection=col_name,work_dir=work_d,dates=dates)# Optional keywords: to keep binary files use `clean = False`, to download incidence angles# with each image use `inc = True`, for only certain pols use `pols = ['VV','HV']`.# See docstring of class for full list.collection.collection_to_tiffs()Each image pair found will be placed in its own directory with its Alaska Satellite Facility derived name as the directory name. Unlike for UavsarScene this functionality will automatically delete the downloaded binary and zip files after converting them to tiffs to save space.Finding URLs for your imagesThe provided jupyter notebook tutorial in the notebooks folder will walk you through generating a bounding box for your area of interest and finding urls through theasf_search api. However if you want a GUI you can also use thevertex website. After drawing a box and selecting UAVSAR from the platform selection pane (circled in red below) you will get a list of search results. Click on the ground projected image you want to download and right click on the download link (circled in orange below). Selectcopy linkand you will have copied your relevant zip url.Georeferencing SLC images to Ground RangeNote that this will require the extra packages (GDAL) specified in the setup.py. If you need this functionality please pip install using:pip install uavsar_pytools[extra].Single look complex (SLC) uavsar images and other Uavsar images without a .grd extension may be inradar slant range. This means that in order to view the image in the image in it's correct location you will need to project it to a coordinate system. Thegeolocate_uavsarfunction takes an array of lat, long, and heights called a .llh file and projects a uavsar image from radar to ground range. The .llh file is provided with slant range images in both the asf and jpl websites.from uavsar_pytools.georeference import geolocate_uavsar\nin_fp = '/change/to/path/to/slc/image.slc\nann_fp = '/path/to/annotation/file.ann\nout_dir = '/directory/to/save/new/image\nllh_fp = '/path/to/scenename.llh\nout_fp = geolocate_uavsar(in_fp, ann_fp, out_dir, llh_fp):The out_fp will be the file path to the newly created .tif file in yourout_dir.Using new DEM to Generate Incidence AngleThe incidence angle file provided with the uavsar images is generated using theSRTM dem. If you want to generate incidence angles using a high resolution dem use thecalc_inc_anglefunction. This will require georeferencing the look vector file and exporting the x,y, and z components of this look vector.from uavsar_pytools.incidence_angle import calc_inc_angle\ndem = numpy array or .tif file path of dem resampled to match uavsar.\nlkv_x = numpy array or .tif file path of x component of look vector file (.lkv)\nlkv_y = numpy array or .tif file path of y component of look vector file (.lkv)\nlkv_z = numpy array or .tif file path of z component of look vector file (.lkv)\ninc_array = calc_inc_angle(dem, lkv_x, lkv_y, lkv_z)This will return an incidence angle array that you can then save out to disk or test.Polarimetric AnalysisPolarimetric analysis of SAR images quantifies the scattering properties of objects in the scene using the phase differences between the various polarizations. A common analysis is to decompose these polarization differences into the mean alpha angle, entropy, and anisotropy. A great presentation on these terms and polarimetry is available from Carleton Universityhere. Uavsar_pytools provides functionality to decompose thepolsar uavsar imagesinto the mean alpha, alpha 1 angle, entropy, and anisotropy.from uavsar.polsar import H_A_alpha_decomp\n\n# This should point to the directory with all 6 polarization\n# (VVVV, HVHV, HVVV, HHHV, HHVV, HHHH) and the correct .ann file.\nin_dir = '/path/to/directory/full/of/polsar.grd\n\n# Will output 4 files to this directory of H, A, alpha1, and mean alpha.\nout_dir = '/path/to/directory/to/output/H_A_Alpha_entropy\nH_A_alpha_decomp(in_dir, out_dir) # use parralel = True to use dask parralelization.Note that this function involves thousands of eigenvalue calculations and may be quite slow (~4 hours on a i7 @ 2.50 GHz for any image with ~74 million valid pixels). Considering putting the above into a python script instead of calling this from a jupyter notebook. This is also a memory intensive operation and has been parralelized on dask. Useparralel = Truekeyword to use dask.Need more help?The notebook folder in this repository has example notebooks for how to utilize this repository or reach out with questions, features, bugs, or anything else."} +{"package": "uavsim", "pacakge-description": "# UAVSim\nUAV simulator that sends NMEA sentences to external devices (i.e. real uav)\nIt is written in [Python](https://www.python.org/) language and uses [Autobahn](https://autobahn.readthedocs.io/en/latest/) with [AsyncIO](https://docs.python.org/3/library/asyncio.html).\nGUI applications are using [PyQt5](https://www.riverbankcomputing.com/software/pyqt/intro) / [PySide2](http://wiki.qt.io/Qt_for_Python).\nMultiple components are being tied together with [CrossbarIO](https://crossbar.io/).## Setting up an environment ##python3.7 -m venv ~/.venv37source ~/.venv37/bin/activate## Installing dependencies ##python3.7 -m pip install \u2013upgrade -r requirements.txt \u2013no-binary :all:python3.7 -m pip install \u2013upgrade -r requirements_dev.txt \u2013no-binary :all:## Building ##python3.7 setup.py build## Installing ##python3.7 -m pip install \u2013upgrade dist/uavsim-*.whl \u2013no-binary :all:## Running ##\n`\npython3.7 -m uavsim\n`"} +{"package": "ub", "pacakge-description": "ubAccessing data in a consistent mannerTo install:pip install ub"} +{"package": "uba-calqlator", "pacakge-description": "Initiate CalQlatorclient=newTechStack(**args)calqlator=CalQlator(client)Set scopeinventory_name='TestInventory'from_timepoint='2010-01-11 00:00:00'to_timepoint='2022-12-31 23:59:59'scope=calqlator.scope(inventory_name,from_timepoint,to_timepoint)Load time seriestarget_inventory_item_id1='Y5NBb7dfIe'target_inventory_item_id2='Y5NBb7vGQi'time_series1=scope.time_series(target_inventory_item_id1)time_series2=scope.time_series(target_inventory_item_id2)Calculations with time seriescalculated_time_series1=time_series1+time_series2calculated_time_series2=time_series1*0.3Write time seriestarget_inventory_item_id='YFS6yBQF7o'scope.write(target_inventory_item_id,calculated_time_series)"} +{"package": "ubackup", "pacakge-description": "UNKNOWN"} +{"package": "ubai-client", "pacakge-description": "Universal Binary Archiver Service # noqa: E501"} +{"package": "ubak", "pacakge-description": "ubakubak is a simple script to help administrators backup their database to Tencent Cloud."} +{"package": "ubami", "pacakge-description": "ubamiA module and CLI for listing and filtering the latest Ubuntu AMIs from\ncloud-images.ubuntu.com.For when you'd rather not hard-code an Ubuntu AMI ID.Installationpip install ubamiUsage# find the latest Jammy Jellyfish AMI for amd64+hvm:ebs-ssd in Londonami_id=ubami.find(region='eu-west-2',version='22.04 LTS',arch='amd64',instance_type='hvm:ebs-ssd')[0]['ami_id']# fetch a list of all the latest official Ubuntu AMIsami_list=ubami.list()# first example as a shell commandubami--region=eu-west-2--version='22.04 LTS'--arch=amd64--instance-type=hvm:ebs-ssd|jq-r'.[0].ami_id'# second example as a shell commandubami"} +{"package": "ubank", "pacakge-description": "ubankAccessubankprogramatically.This does not provide true API-like interface, but you can retrieve information\nusing browser automation.RequirementsPython 3.8+ andPlaywright.InstallationInstall from PyPI:$pipinstallubankInstall version of Firefox required by Playwright:$playwrightinstall--with-depsfirefoxGetting startedCreate an instance ofUbankClientand log in using a security code:>>>fromubankimportUbankClient>>>ubank_client=UbankClient()>>>ubank_client.log_in_with_security_code('name@domain.com','SecretPassw0rd')Entersecuritycode:123456Then you can get account information:>>>ubank_client.get_accounts(){'linkedBanks':[{'bankId':1,'shortBankName':'ubank','accounts':[{'label':'Spend account','nickname':'Spend account','type':'TRANSACTION','balance':{'currency':'AUD','current':1000,'available':1000},'status':'Active'},{'label':'Save account','nickname':'Save account','type':'SAVINGS','balance':{'currency':'AUD','current':10000,'available':10000},'status':'Active'}]}]}After logging in with a security code, you can retrieve a trusted cookie:>>>ubank_client.get_trusted_cookie(){'name':'026d9560-3c86-4680-b926-44bdd28eba94','value':'YmxhaCBibGFoIGJsYWggYmxhaCBibGFoIGJsYWggYmxhaCBibGFo','domain':'www.ubank.com.au','path':'/','expires':1706758407,'httpOnly':True,'secure':True,'sameSite':'Strict'}Use the cookie to log in without a security code:>>>ubank_client.log_in_with_trusted_cookie(...'name@domain.com',...'SecretPassw0rd',...{'name':'026d9560-3c86-4680-b926-44bdd28eba94','value':'YmxhaCBibGFoIGJsYWggYmxhaCBibGFoIGJsYWggYmxhaCBibGFo','domain':'www.ubank.com.au','path':'/','expires':1706758407,'httpOnly':True,'secure':True,'sameSite':'Strict'}...)Stop Playwright gracefully when you're done:>>>ubank_client.stop()You can also retrieve a trusted cookie by running the ubank module from the command\nline. Use an environment variable to avoid storing your banking password in shell\nhistory:$read-sPASSWORDSecretPassw0rdRunning ubank as a module will prompt for a security code and then display the trusted\ncookie object:$python-mubankname@domain.com\"$PASSWORD\"Enter security code: 123456{'name': '026d9560-3c86-4680-b926-44bdd28eba94', 'value': 'YmxhaCBibGFoIGJsYWggYmxhaCBibGFoIGJsYWggYmxhaCBibGFo', 'domain': 'www.ubank.com.au', 'path': '/', 'expires': 1706758407, 'httpOnly': True, 'secure': True, 'sameSite': 'Strict'}Secure storage of your username, password and trusted cookie isyourresponsibility.ReleaseBump project version. e.g.,$poetryversionpatchBumping version from 0.1.1 to 0.1.2Publish to PyPI:$read-sPASSWORD$poetrypublish--build-u__token__-p\"$PASSWORD\""} +{"package": "ubarec", "pacakge-description": "UbarecRussianThe utility is designed for backup and restore databases to S3 storage.\nSo far, PostgreSQL and MS SQL databases are supported.InstallUbuntuThe basic dependencies and package are easy to install:sudoaptinstall-yp7zip-fullunixodbc-devpython3.8python3-pip&&python3.8-mpipinstallubarecWhen working with MS SQL, you must install the appropriateODBC driver.WindowsThe program uses the console archiver7-Zip,\nwhich should be pre-installed in any convenient way, for example, with thechocolatey:chocoinstall7zipThe module is installed from the environment with administrator privileges:py-mpipinstallubarecWorking principleIn backup mode Ubarec performs the following actions for each of the databases specified in the command line parametersforms database dump (either by executing SQL script or using standard utilities)archives the dump using 7zip; if theUBAREC_ZIP_PASSWORDenvironment variable is set, the archive is password-protectedthe created archive is copied to the S3-storagefiles created during the previous stages are deletedThe formed database archive has a file name by mask:The current hostname>____