Saravanan666/pypi-org huggingface dataset:
Package: topa
topatopa - Top Output Python AnalyzerA command line app to analyze linux top command output.It will shows you below information for each and every pid in the log file or the pids you specified by adding-pparameter:Total record countMax CpuMin CpuAverage CpuMax MemMin MemAverage MemInstallpipinstalltopaUsagetopa-h(--help)Usage: topa [OPTIONS] FILENAME

  TOPA - Top Output Python Analyzer

  A python cli application to analyze standard linux top output

Options:
  -p, --pid INTEGER       The pid list to be analyzed
  -o, --out [STD|MD|PDF]  The analyze report file format  [default: STD]
  -h, --help              Show this message and exit.PDFare not supported yet.Sample outputtopatop.log-p2476_               _ __
  | |_     ___    | '_ \  __ _
  |  _|   / _ \   | .__/ / _` |
  _\__|   \___/   |_|__  \__,_|
_|"""""|_|"""""|_|"""""|_|"""""|
"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'  1.0.1, by https://github.com/jwenjian/topa# ReadingReading top.log  [####################################]  100%# ReportReport of`1`process(es) ready in below## Pid = 2476Total record count = 17261
Max CPU = 47.4%
Min CPU = 9.4%
Avg CPU = 15.69%
Max MEM = 11.1%
Min MEM = 7.4%
Avg MEM = 10.34%Note:The progress bar when readingReading top.log  [####################################]  100%may not displayed if your output files are too small and topa process it too fast, this is the limitation ofclick
Package: topacedo
# TopACeDo
#### Topology Assisted Cell DownsamplingTopacedo works with Scarf to perform memory efficient downsampling of single-cell genomics data.
Using a pre-built neighbourhood graph of cells, Topacedo aims to sample cells from the graph such
that the manifold is preserved. Topecedo’s algorithm can be diveded into two phases:assigning prizes to cells and penalties to edgesrunning a fast approximate prize-collecting steiner tree
Package: to-paragraphs
to_paragraphsNote, the code is currently ~slow and messy. It's a work in progress.Extracts paragraphs from a string, using the semantic similarity between sentences to determine paragraph boundaries.
This tends to work better than the naive approach of splitting on newlines.Installationpipinstallto_paragraphsExamplefromto_paragraphsimportto_paragraphstext="""The biosphere includes everything living on Earth it is also known as ecosphere. Currently the biosphere has a biomass (or amount of living things) at around 1900 gigatonnes of carbon. It is not certain exactly how thick the biosphere is, though scientists predict that it is around 12,500 meters. The biosphere extends to the upper areas of the atmosphere, including birds and insects.Pizza is an Italian food that was created in Italy (The Naples area). It is made with different toppings. Some of the most common toppings are cheese, sausages, pepperoni, vegetables, tomatoes, spices and herbs and basil. These toppings are added over a piece of bread covered with sauce. The sauce is most often tomato-based, but butter-based sauces are used, too. The piece of bread is usually called a "pizza crust". Almost any kind of topping can be put over a pizza. The toppings used are different in different parts of the world. Pizza comes from Italy from Neapolitan cuisine. However, it has become popular in many parts of the world."""defembed_fn(content):# ... some function that returns an embedding for a stringpassparagraphs=to_paragraphs(text,embed_fn=embed_fn)forparagraphinparagraphs:print(paragraph)# prints the paragraph about the biosphere, then the paragraph about pizzaExample embedding functionimporttorchimporttorch.nn.functionalasFfromtransformersimportAutoTokenizer,AutoModelCACHE_PATH='/tmp/transformers'TOKENIZER=AutoTokenizer.from_pretrained('sentence-transformers/all-MiniLM-L6-v2',cache_dir=CACHE_PATH)MODEL=AutoModel.from_pretrained('sentence-transformers/all-MiniLM-L6-v2',cache_dir=CACHE_PATH)defmean_pooling(model_output,attention_mask):token_embeddings=model_output[0]# First element of model_output contains all token embeddingsinput_mask_expanded=attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()returntorch.sum(token_embeddings*input_mask_expanded,1)/torch.clamp(input_mask_expanded.sum(1),min=1e-9)defembed(sentences):encoded_input=TOKENIZER(sentences,padding=True,truncation=True,return_tensors='pt')withtorch.no_grad():model_output=MODEL(**encoded_input)sentence_embeddings=mean_pooling(model_output,encoded_input['attention_mask'])returnF.normalize(sentence_embeddings,p=2,dim=1)
Package: toparu-arushigupta
This is a simple package to use topsis (Technique for Order of preference by Similarity to Ideal Solution) approach to select best among many things based on different attributes, such as selecting the best Machine Learning algorithms based on correlation,R-square,root mean square error and accuracy. You can use this simple package to get ranks on basis of topsis approach, ypu simply need to pass  NumPy array after pre-processing your data along with weights between 0 and 1 and all weights should sum to 1 to get correct results and you need to pass impacts as well in form of '+' or '-' where '+' indicates that you need to maximise value of that particular column and '-' indicates that you need to minimise value of that particular column. After passing all these parameters you will get your rank row.
Package: topas2numpy
topas2numpyReadingTOPASresults intoNumPyarrays.FeaturesTOPASis a Monte Carlo tool for particle simulation, designed for medical physics research. It can output two data types:binned: a quantity (e.g. dose) is accumulated within a binned geometry componentntuple: multiple data columns are recorded per particle historyThis package is able to read both data types, enabling analysis within Python.Basic Usagefromtopas2numpyimportBinnedResultx=BinnedResult('Dose.csv')fromtopas2numpyimportread_ntupley=read_ntuple('Beam.phsp')History0.1.2 (2016-02-23)Support upcoming binary ntuple headersSupport additional integer columns in old-style binary phasespaces0.1.0 (2016-02-19)First release on PyPI
Package: topasdosecalc
TopasDoseCalcA GUI to merge and scale split-up TOPAS simulations to absolute doses and calculate DVHsThis GUI allows the merging of multiple TOPAS DICOM simulations. This can be useful when a patient plan has been split up into individual simulations of the control points. The merged simulation can then be scaled using a reference calibration simulation and data from the RTPLAN. Finally, DVHs can be automatically created when supplying a RTSTRUCT file.InstallationInstall using pip:$pipinstalltopasdosecalcThen, start the GUI by running:$python-mtopasdosecalcOr, if your Python is added to $PATH, simply run:$topasdosecalcManualTo use TopasDoseCalc, you need to supply at least five things:A directory containing your TOPAS DICOM simulation results, named after the control point (order is relevant!)A TOPAS dose profile reference simulation. The mean of the values close to the center axis is used as the scaleA directory containing at least the relevant RTPLAN file. For DVH calculation, a RTDOSE and RTSTRUCT file is requiredThe histories used for the simulation of each control point (individual, not total)A new series description for the merged DICOMIf you supplied a RTDOSE and RTSTRUCT file, you can select the structures for which to calculate a DVH. This can be useful as an initial validation of the simulation results.Note:The program assumes 1 MU to be equivalent to 1cGy. If this doesn't apply to your case, scale the histories per simulation by the relevant amount.ScreenshotsDependenciesBuilt using the beautifulAzure-ttk themeby@rdbende. Requires python3, numpy, matplotlib, pydicom and dicompyler-core.Contact me!Thank you for using TopasDoseCalc! Please let me know about any issues you encounter, or suggestions/wishes you might have!
Package: topasgraphsim
TopasGraphSimA GUI to simplify and streamline the plotting and analysis of medical physics simulationsThis GUI can visualize and analyze percentage depth dose (pdd) and dose profiles (dp) simulations fromTOPAS. Depth dose measurements are assumed to be in the z-direction, dose profiles in the x- or y-directions. Data read-in is handled bytopas2numpy.InstallationInstall using pip:$pipinstalltopasgraphsimThen, start the GUI by running:$python-mtopasgraphsimOr, if your Python is added to $PATH, simply run:$topasgraphsimOpen compatible files from the command line:$topasgraphsim"path_to_your_file"Since all my testing in done on Windows 11, I cannot guarantee ToapsGrapSim will work on any other plattform. I'm open to suggestions or PRs making the software work better cross-plattfrom!FeaturesVisit thewikifor detailed information!Highlights include:Reproducible graphing and analysis of 1D TOPAS simulation for medical physicsSimultaneous plotting and parameter calculation for all data setsCalculation of the Gamma Index with adjustable parametersGraph adjustment optionsNormalization (On/Off)Error bars (On/Off)Graph order and colorsMarker size and styleLine widthDrag and drop of filesCenter axis deviation correctionImport of EGS and RadCalc simulation results *Import of custom measurements (as numpy .txt files)Import of PTW tbaScan (MEPHYSTO mc2) measurementsGerman and english language supportDark mode(*) Not yet implementedScreenshotsParametersDepending on the imported measurement, the following parameters can be calculated:Measurement typeParametersDepth doseQ-FactorzmaxDose profileFWHMCAXdevFLATKriegerFLATstddevPenumbra (L&R)Integral (L&R)Q-Factor : Radiation Quality Factorzmax: Depth at MaximumFWHM : Full-Width at Half-MaximumCAXdev: Centre Axis DeviationFLATKrieger: Flatness of Dose Plateau (Definition by Krieger)FLATstddev: Flatness of Dose Plateau (Standard Deviation)Penumbra (L&R) : Width of Left and Right PenumbraIntegral (L&R) : Integral below Left and Right PenumbraDependenciesThe UI is based on thecustomtkinterlibrary.Requires python3, numpy, scipy, matplotlib, Pillow, python-opencv, pynput, requests, topas2numpy, and python-tkdnd.Contact me!Thank you for using TopasGraphSim! Please let me know about any issues you encounter, or suggestions/wishes you might have!
Package: topaztrainmetrics
topaztrainmetricsPlot metrics from aTopaztraining run.Installation$ pip install topaztrainmetricsUsage$  topaztrainmetrics --help
Usage: topaztrainmetrics [OPTIONS] <file>

  Plot validation metrics from a Topaz training run.

  <file> is the results.txt file from standalone Topaz or the
  model_plot.star file from Topaz run within RELION.

Options:
  -l, --loss                Plot loss.
  -g, --gepenalty           Plot GE penalty.
  -p, --precision           Plot precision.
  -t, --tpr                 Plot true/false positive rates.
  -c, --auprc               Plot area under precision/recall curve (default).
  -x, --xaxis [iter|epoch]  X axis (iter or epoch; default: iter).
  -o, --output TEXT         File name to save the plot (optional: with no file
                            name, simply display plot on screen without saving
                            it; recommended file formats: .png, .pdf, .svg or
                            any format supported by matplotlib).

  -h, --help                Show this message and exit.
Package: topbid
topbidHelper library to fetch and store current orderbook top bid/ask price and volume from crypto exchanges APIs.
Currently supports Binance, Bybit, Gateio, Kraken, Kucoin and OKX.Requires Python 3.8+Installationpip install topbidUsage>>>fromtopbid.orderbookimportOrderBook# Instanciate OrderBook.>>>orderbook=OrderBook()# Add one or more market pairs to be fetched from an exchange REST API.>>>orderbook.add("binance","BTC/USDT")>>>orderbook.add("kucoin",["BTC/USDT","ETH/USDT"])# Start the background thread fetching prices and volume (here, every 2 seconds).>>>orderbook.start(update_every=2)# Retrieve the highest bid on the orderbook.>>>orderbook.get_orderbook_top_bid("binance","BTC/USDT")(23130.41,0.0584)# Retrieve the lowest ask on the orderbook.>>>orderbook.get_orderbook_top_ask("binance","BTC/USDT")(23130.43,0.0214)# Removes a pair from being fetched.>>>orderbook.delete("binance","BTC/USDT")# Stop the background thread and removes all watched pairs.# It must be called before exiting your own application.>>>orderbook.stop()
Package: topcoder-dl
Downloads Topcoder data-science tutorials and save as PDFInstallationBuild from sourcegitclone"https://github.com/tushar-rishav/topcoder-dl.git"cdtopcoder-dlpythonsetup.pyinstallUsing pippipinstalltopcoder-dlDefault config:target  : TopcoderPdfUsageFetch single postTo fetch single tutorial, say Binary Search, run this in your shelltopcoderdl-phttps://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/Note: the above command will save the pdf in default directoryFetch all tutorial in your custom directorytopcoderdl-tmy_directory_abs_pathNote: If the directory do not exists then topcoder-dl will create a new
one else the PDFs will be saved in the exsting directoryGet helptopcoderdl-hExampletopcoderdl-phttps://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/-tBSearch_TopCoderThe above command will fetch binary-search tutorial from TopCoder and
save its PDF in Bsearch_TopCoder directoryContributionsHave an idea to make it better? Go ahead! I will be happy to see a pull
request from you! :blush:License
Package: topdesk
topdeskAn API client forTOPdeskin Python, usingrequests.Installationtopdeskcan be obtained through pip:pip install topdeskUsageAll requests are encapsulated in aTopdeskobject. To construct this object, you
need to supply it with a URL and username/token pair:fromtopdeskimportTopdesktopdesk=Topdesk("<topdesk url>"app_creds=("<username>","<token>"))Then you can start requesting. Let’s get the API version!print(topdesk.version())This will return a dictionary representing the JSON body of the response. If it
fails it will throw an exception that inherits fromtopdesk.HttpException, for
instancetopdesk.NotFoundfor404 Not Founderrors.If you don’t have a token, you can also login as a person or operator. I
wholeheartedly recommend tokens, though.topdesk.login_person("<username>","<password>")# or alternativelytopdesk.login_operator("<username>","<password>")Then we can try and request some information! Let’s get a list of incidents that
are not resolved, and order them by their target date!print(topdesk.incidents({'order_by':"target_date+ASC",'resolved':False}))The API is somewhat well documented. You can explore it from your REPL through
thehelpfunction or look at theautogenerated documentation.CaveatsThe Knowledge Base API is currently not supported, because it uses GraphQL
whereas the rest of the API uses REST. If you have experience with and/or
interest in GraphQL, I invite you to submit a patch!The Supporting Files API is not yet supported. It’s a large swath of useful
API functions that we do not wrap until now. If you need to use any of the
endpoints, you’ll have to fall back to the lower-levelget,put,patch,post, anddeletemethods.Have fun!
Package: top-drawer
Top DrawerEver had trouble finding a valid name for that new package ?top-draweris command line tool to help with that by searching for synonyms
of a word and validate if they are available on pypi or npm.InstallPython >= 3.6:$ pip install top-drawerUsage$ top-drawer --help
usage: top-drawer [-h] [-v] [--log-file LOG_FILE] [--quiet] [-c CONFIG_FILE]
                  [--api-key API_KEY]
                  ...

    Thesaurus search and availability validators to find new package names.
    

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         - (default: False)
  --log-file LOG_FILE
  --quiet
  -c CONFIG_FILE, --config-file CONFIG_FILE
                        Config file path (default: None)
  --api-key API_KEY     Your bighugelabs.com api key (default: None)

Commands:
  
    search              Search for valid words from the thesaurus definition.
    validate            Validate a word is available.
    thesaurus           Get the thesaurus definition from Big Huge Thesaurus.
    clear-cache         Clear the validations cache.$ top-drawer search --help                                                                                                                                      ✔  17:37 
usage: top-drawer search [-h] [-c {snakecase,spinalcase}] [--pypi] [--npm] [-f]
                         [-w {noun,verb,adjective} [{noun,verb,adjective} ...]]
                         [-m {syn,ant,usr,sim,rel} [{syn,ant,usr,sim,rel} ...]]
                         word

Search for valid words from the thesaurus definition.

positional arguments:
  word                  The word to search.

optional arguments:
  -h, --help            show this help message and exit
  -c {snakecase,spinalcase}, --casing {snakecase,spinalcase}
                        The casing to apply to synonyms. (default: spinalcase)
  --pypi                Disable validation on pypi. (default: True)
  --npm                 Disable validation on npm. (default: True)
  -f, --full            Include the invalids in the output. (default: False)
  -w {noun,verb,adjective} [{noun,verb,adjective} ...], --word-type {noun,verb,adjective} [{noun,verb,adjective} ...]
                        Type of words to use. (default: None)
  -m {syn,ant,usr,sim,rel} [{syn,ant,usr,sim,rel} ...], --mode {syn,ant,usr,sim,rel} [{syn,ant,usr,sim,rel} ...]LinksBig Huge Thesaurusprecept
Package: topdrawersoccer-sdk
TopDrawerSoccer SDKThis package contains modules and packages providing access to TopDrawerSoccer data.SetupCreate your virtual environment of choiceInstall Poetry globallyInstall dependencies$pipinstall-e.Update dependencies$invokeupdateClean up transient files$invokecleanAnalyze syntax$invokelintRun tests$invoketestGenerate Coverage Report$invokecoverBuild the project$invokebuild
Package: topenai
topenaitopenai (terminal openai) — a simple command line interface tool to interact with OpenAI.Installationpip install topenaiHow to get an OpenAI API keyOpenAPI modelsTo install the latest testing version (may contain more bugs), run:pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ topenaiFeaturesMultiple chat threadsChat historyRename, delete and switch sessionsUsageRuntopenaiin your terminalEnter/newto start a new chat (/n)/switch <chat_id>to change chat (/s)/listto list all chats (/l)/rename <old_id> <new_id>to rename a chat (/r)/delete <chat_id>to delete a chat (/d)/apikeyto change API key/modelto change model/helpto display this help message (/h)/exitto exit (/e)Known issuesUUIDs of sessions instead of readable namesRename is not workingDeveloping SetupIf you want to set this package up for directly editing it's source code (for contributing):Clone the packagegit clone https://github.com/vladzima/topenaiCreate a dynamic linkThis will make the package dynamically update with your local changes:pip install -e .TODOMake chat history more accesibleAllow OpenAI API fune-tuning parametersMigrate to official OpenAI python API client
Package: topeology
[![Build Status](https://travis-ci.org/hammerlab/topeology.svg?branch=master)](https://travis-ci.org/hammerlab/topeology) [![Coverage Status](https://coveralls.io/repos/hammerlab/topeology/badge.svg?branch=master&service=github)](https://coveralls.io/github/hammerlab/topeology?branch=master)# TopeologyTopeology compares neoepitope sequences with epitopes from [IEDB](http://www.iedb.org/).## ExampleFrom the command line:```shtopeology --input epitopes.csv --epitope-lengths 8 9 10 11 > scores.csv```In Python:```pythonfrom topeology import compareoutput_dataframe = compare('epitopes.csv')```Input looks like:| sample      | epitope| ------      | -------| 001         | AAALPGKCGVOutput looks like:| sample      | epitope        | iedb_epitope    | score| ------      | -------        | ------------    | -----| 001         | AAALPGKCGV     | EFKEFAAGRR      | 2.38## InstallationYou can install topeology using [pip]:```shpip install topeology```Currently, topeology use [seq-align] to quickly compare sequences, wrapped in a C extension. It will beinstalled if [seq-align] is installed; otherwise, topeology reverts to using another scorer.To install topeology with this extension:- Follow [seq-align]'s installation instructions, and then set `SEQ_ALIGN_PATH` to the installationdirectory.- Install topeology via [pip]. If topeology is already installed, run `pip install topeology --upgrade --no-deps --force-reinstall`.## MethodologyTopeology uses Smith-Waterman alignment to align each neoepitope with each IEDB epitope of thesame length, and returns the resultant epitope-epitope scores. Only position 3 to the penultimateamino acid are considered.This software uses the following libraries for Smith-Waterman alignment:- [seq-align]- [Complete-Striped-Smith-Waterman-Library](https://github.com/mengyao/Complete-Striped-Smith-Waterman-Library)[seq-align]: https://github.com/noporpoise/seq-align[pip]: https://pip.pypa.io/en/latest/quickstart.html
Package: top-framework
Top Framework is a Python library for writing UNIX top like Text User Interface applications.It comes withweb-top,
atoplike monitoring tool for HTTP requests and responses on any web server.Use casesThe goal of Top Framework is to make is easy to roll out
custom live monitoring tools with text user interface quickly.
Sometimes you just need to log in to your server and see what's going on.
Top tools are is ideal for observing and catching issues when they happen.
These tools are supplement for Application Performance Management (APM),
metrics like statsd and Prometheus and logging.Monitoring use cases you might have include:HTTP request/response trackers for web serversBackground job trackers for Cron, Celery and other background job managersDocumentationBrowse documentationCommunityJoin Discord for any questionsSocial mediaFollow on TwitterFollow on TelegramFollow on LinkedInLicenseMIT.Developed and maintained by Trading Strategy.
Package: topftp
topftpa package on top of ftplib to use FTP easilyinstallationpipinstalltopftpusagefromtopftp.ftpimportFTPhost="127.0.0.1"user="username"password="password"port=21timeout=5ftp=FTP(host,user,password,port=port,timeout=timeout)# set verbose to True to print exceptions# set silent to True to not raise exceptions# ftp.silent = True# ftp.verbose = Trueftp.connect()# list files in current directoryfiles,folders=ftp.listdir()# download fileftp.download("/file.txt","local_file.txt")# download file content to listlines=ftp.download_to_list("/file.txt")# upload fileftp.upload("local_file.txt","/remote_file.txt")# upload from stringftp.upload_from_string("Hello, topftp!","/remote_file.txt")# delete fileftp.delete("/remote_file.txt")# for missing methods on ftplib.FTP, you can use them directly# ftp.some_method(*args, **kwargs)# is same to# ftp.ftp.some_method(*args, **kwargs)# close connectionftp.close()