Saravanan666/pypi-org huggingface dataset:
Package: smacc
Sleep Manipulation And Communication ClickythingA clickable interface for running sleep-related experiments.Trigger audio cuesCollect dream reportsTrigger EEG portcodesSave a detailed event logand more!InstallationGet PythonDownload eitherAnacondaorMiniconda. I prefer Miniconda, which is a much smaller install. If you're only using Python for SMACC, just get Miniconda.Get SMACCOpen thePowershellapp on your PCwith Admin privileges(Right-click to open and selectRun as administrator).Create a new conda environment, so that our installation is isolated from the rest of your system. Also we need to make sure we use Python 3.8. Typeconda create -n smacc python=3.8and hitEnter.Activate the environment you just created. Typeconda activate smaccand hitEnter.Install SMACC! Typepip install 'smacc[port_triggers]'and hitEnter. If you donotplan to use port triggers, use onlypip install smaccinstead.Generate some sound files to use for cueing. You can add your own, but this is just to get started and make sure everything works. Typepython -m smacc generate_cuesand hitEnter. That creates a simple beep cue. Now to make a pink-noise file for masking cues, Typepython -m smacc generate_noiseand hitEnter.If planning to use parallel port, downloadInpOut32. Typepython -m smacc download_inpoutand hitEnter.UsageOptional setupThese steps must be donebeforerunning SMACC.SMACC will create a folder in your home directory, and then 3 folders in within that. It will look like this.Users/<username>/smacc_data/cues  # <-- Any .wav file in here is made available as a cue to play with SMACC
Users/<username>/smacc_data/logs  # <-- Data .log files are saved here.
Users/<username>/smacc_data/noise # <-- The pink noise file is saved here.If you don't want to use the default~/smacc_datafolder, you can change this by setting a new environment variable calledSMACC_DATA_DIRECTORYequal to whatever directory you want to use. SMACC will create it and all the subfolders (if not already present).Place any sound files in the~/smacc_data/cuesfolder (must be.wavfiles!).There is aRecord Dream Reportbutton that will start to record from whatever external recording device is selected from the SMACC menubar. There is also an option to have it pop open a website URL. I use this to open up a dream report survey I have set up on Qualtrics. If you want it to open something, update theSURVEY_URLvariable inconfig.py.Run SMACC# Make sure the conda environment is active.condaactivatesmacc# Run SMACC.python-msmaccTest the setup by trying to play some cues.If planning to record dreams, choose sound device for recording audio from the menubar (Audio > Input device > [choose device]).
Package: smacom
[![Build Status](https://travis-ci.com/Sama-Business-Services/smacom.svg?branch=master)](https://travis-ci.com/Sama-Business-Services/smacom)
[![Say Thanks!](https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg)](https://saythanks.io/to/master@samabusiness.sa)## SmaCOMPythonCLI
Package: smahat
Smahat Time Series EncodingSmahat allows to encode a sequence of integer values using a fixed (for all values) number of bits but minimal with regards to the data range. For example: for a series of boolean values only one bit is needed, for a series of integer percentages 7 bits are needed, etc.Smahat is useful when:Time series is integer-valued. (It doesn't work with floats :))The range of the data is known in advance (if not streaming, this is not necessary).The data range is relatively small.The data does not have properties that would make other compression algorithms useful, or these other algorithms have an unacceptable cost for the use case.Smahat can also be used as a baseline to calculate the true compression ratio of a compression algorithm on data of a certain nature.InstallationTo install the latest release:$ pip install smahatYou can also build a local package and install it:$ make build
$ pip install dist/*.whlUsageImportsmahatmodule.>>>importsmahatData to encode.>>>values=[12,0,17,15,78,10]EncodingYou can useencode_nextto encode one value by one:>>>encoder=smahat.Encoder(min_value=0,max_value=100,strategy='saturate')>>>forvinvalues:...encoder.encode_next(v)>>>content=encoder.get_encoded()>>>content{'encoded':b'\x18\x00\x88\xf9\xc2\x80','shift':0,'n_bits_per_value':7,'n_padding_bits':6}Or you can useEncoder.encode_allto encode all values (range min and max will be inferred from values if not provided):>>>content=smahat.Encoder.encode_all(values,min_value=0,max_value=100,strategy='saturate')>>>content{'encoded':b'\x18\x00\x88\xf9\xc2\x80','shift':0,'n_bits_per_value':7,'n_padding_bits':6}DecodingTo decode useDecoder.decode_all.>>>smahat.Decoder.decode_all(content)[12,0,17,15,78,10]Encoding resultThe result of the encoding of a sequence of values using Smahat is aSmahatContentdictionary containing theencodeddata, plus three fields :shiftis used to bring the data range to start from zero (values are shifted and encoded in pure binary),n_bits_per_valueindicates the number of bits used to encode each value,n_padding_bits(between 0 and 7) indicates the number of unused padding bits within the last byte.classSmahatContent(TypedDict):encoded:bytesshift:intn_bits_per_value:intn_padding_bits:intIf you want to use this library for message exchanges, you can serialize the result of the encoding as you like (JSON, protobuf, etc.)Contribute$ git clone https://github.com/ghilesmeddour/smahat-time-series-encoding.git
$ cd smahat-time-series-compressionmake format
make dead-code-check
make test
make type-check
make coverage
make buildTODOsAdd unit tests.Improve doc.
Package: smaht-submitr
THIS IS A PRE-RELEASE VERSION.This was recently forked from SubmitCGAP and is not yet ready for normal use.Watch for version 1.0.submitrA file submission tool for SMAHTDescriptionThis is a tool for uploading certain kinds of files to SMaHT.The “R” is for Remote file submission. You can think of this tool as putting the “R” in “SMaHT”. :)BackgroundThis tool was forked from SubmitCGAP and will probably remain compatible, but by forking it, the original repository will remain stable and this new repository can experiment safely.Because SubmitCGAP supported submission of new cases, family histories, and gene lists, that’s what this begins with. But that doesn’t imply that those things are present in SMaHT. The protocol is designed to require both ends to agree on the availability of a particular kind of upload for it to happen.InstallationInstalling this system involves these steps:Create, install, and activate a virtual environment.Only if you are a developer, install poetry and select the source repository.
Others will not have a source repository to select,
so should skip this step.If you are an end user, do “pip install submitr”.
Otherwise, do “make build”.Set up a~/.smaht-keys.jsoncredentials file.See detailed information about these installation steps atInstalling submitr.TestingTo run unit tests, do:$ make testAdditional notes on testing these scripts for release can be found inTesting submitr.Getting StartedOnce you have finished installing this library into your virtual environment,
you should have access to thesubmit-metadata-bundleand thesubmit-genelistcommands. For more information about how to format files for submission and how to
use these commands, seeGetting Started.
Package: smak
SMAK3.0MicroAnalysis Toolkit v3If you haven't recently used conda, it is a good idea to update your installation before beginning.conda update condaInstallation with CondaCreate a new environment from Anaconda prompt/navigator. Choose 'y' when prompted.conda create -n smakenv python==3.10Activate the new environmentconda activate smakenvInstall package via pippip install smakNavigate to the folder within your anaconda environment where smak has been installed. This can be tricky to find.To start, type inPATH(windows) or$PATH(mac). This will provide a list of Anaconda directories. Yours may look something like this: "C:\Users\yourUsername\AppData\Local\anaconda3\envs\smakenv" (windows)Copy the first of the paths from the previous step and navigate to that folder on your computer in finder/file explorer. This is the folder for your smak specific virtual environment.From the virtual environment folder, navigate to "Lib\site-packages\smak" (windows) or "Lib\python 3.10\site-packages\smak"(mac)In this folder, you will see the code for smak, including "smak.py". Bookmark this folder, you will need to access it frequently.Optional: Segmentation and image registrationTo use the full functionality of SMAK, you will need to follow a few additional steps. This is not necessary unless you plan to use segmentation and image registration.Download the files from the following links. They are quite large and may take a while to download.sam_vit_b_01ec64.pthsam_vit_h_4b8939.pthsam_vit_l_0b3195.pthvgg16partial.npyMove the files into the main smak folder. This is the folder you found and bookmarked in step 4 of "Installation with Conda".From Anacoda prompt, with your smakenv virtual environment active, run the following commands to install packages. Please follow this exact order of package installation.pip install pycocotoolsconda install gitpip install git+https://github.com/facebookresearch/segment-anything.gitpip install torchpip install torchvisionconda install lap -c conda-forgepip install numpy==1.24To check this functionality, open SMAK and navigate to the Analyze/Segmentation. An expanded menu including "Initialize SAM" will be available to you.Running SMAKOpen Anaconda prompt/navigator.Activate the environment you use to run smakconda activate smakenvNavigate to the folder within your anaconda environment where smak has been installed. This is the folder you found and bookmarked in step 4 of "Installation with Conda". Using quotes aroung the path may be helpful.Run smakpython smak.pyImprovements on this installation process and guide are underway! In the meantime, don't hesitate to reach out to Joy (joy.a.wood@dartmouth.edu) or Sam (samwebb@slac.stanford.edu) for assistance.
Package: smake
smakeSmake is a simple and convenient build-and-run system for C and C++ projects.Why make another build system?CMake and GNU Make are great build systems. However, as the project gets larger, and as there are increasingly many types of builds (e.g. a builds for debugging), it becomes tedious to add duplicate code.Smake solves this problem with its target-mode-build hierarchy. In this system,
every project has a set of targets, and each target has a set of build modes. When
smake is run on a target with a specific build mode, it will run the build
corresponding to that mode.Each mode also has a post-build script that can be run. For most builds, this will
simply be executing the target object file, but in some cases, the user may want
to run a different command (i.e.gdborvalgrind) with the object file.InstallSmake can be installed easily withpip install smake.One can also simply clone the source and link thesmakeexecutable.How does it work?Smake searches for asmake.yamlfile in the current directory and creates configurations for each target, including all modes and their
corresponding builds and post-build scripts, etc.The structure of ansmakeconfiguration file is as follows (in no strict
order):# Variables that can be referenced in buildsdefinitions:-gsourceA:fileA.c, fileB.c# List of builds that will be used by the targetsbuilds:-buildA:-sources:gsourceA# Reference a group of sources defined# in the sources section-buildB:-sources:main.c# Sources can be specified in the build as well-flags:-Wall, -Wextra# Flags are specified here, can be comma# separated or specified as a list-buildC:-sources:main.c-flags:-Wall, -Wextra, -g# List of all targetstargets:-targetA:-modes:default# Specifiy modes here (default mode does# not really need to be specified)-builds:-default:buildA# Must specify builds as a pair of `mode: build`# Note that post-build scripts do not need to be specified:#   if nothing is specified, then there is no post-build script-targetB:-modes:default, debug# Comma separated modes-builds:# Modes are selected using the -m option of smake-default:buildB#   for example: smake targetB -m debug-debug:buildC# the default mode is used if no mode is specified-postbuild:# Post-build scripts, specified per mode (optional)-debug:'gdb{}'# The {} is replaced by the target object fileThis configuration allows for the following commands:$smaketargetA
$smaketargetB
$smaketargetB-mdebugAs one can imagine, this build system is quite simple, yet powerful.Another example ofsmakefile can be found inside theexampledirectory.
Clone this repository and runsmaketo get started (available targets aresmake basicandsmake multisource).Future featuresPre-build scripts, for cases where source code needs to be auto-generatedAdd options for parallelizing buildsEasier way to define macro arguments for the compilersDetect changes in included headers, and the config in general
Package: smaktest1
SMAK3.0MicroAnalysis Toolkit v3If you haven't recently used conda, it is a good idea to update your installation before beginning.conda update condaInstallation with CondaCreate a new environment from Anaconda prompt/navigator. Choose 'y' when prompted.conda create -n smakenv python==3.10Activate the new environmentconda activate smakenvInstall package via pippip install smakNavigate to the folder within your anaconda environment where smak has been installed. This can be tricky to find.To start, type inPATH(windows) or$PATH(mac). This will provide a list of Anaconda directories. Yours may look something like this: "C:\Users\yourUsername\AppData\Local\anaconda3\envs\smakenv" (windows)Copy the first of the paths from the previous step and navigate to that folder on your computer in finder/file explorer. This is the folder for your smak specific virtual environment.From the virtual environment folder, navigate to "Lib\site-packages\smak" (windows) or "Lib\python 3.10\site-packages\smak"(mac)In this folder, you will see the code for smak, including "smak.py". Bookmark this folder, you will need to access it frequently.Optional: Segmentation and image registrationTo use the full functionality of SMAK, you will need to follow a few additional steps. This is not necessary unless you plan to use segmentation and image registration.Download the files from the following links. They are quite large and may take a while to download.sam_vit_b_01ec64.pthsam_vit_h_4b8939.pthsam_vit_l_0b3195.pthvgg16partial.npyMove the files into the main smak folder. This is the folder you found and bookmarked in step 4 of "Installation with Conda".From Anacoda prompt, with your smakenv virtual environment active, run the following commands to install packages. Please follow this exact order of package installation.pip install pycocotoolspip install git+https://github.com/facebookresearch/segment-anything.gitpip install pytorchpip install torchvisionconda install lap -c conda-forgepip install numpy==1.24To check this functionality, open SMAK and navigate to the Analyze/Segmentation. An expanded menu including "Initialize SAM" will be available to you.Running SMAKOpen Anaconda prompt/navigator.Activate the environment you use to run smakconda activate smakenvNavigate to the folder within your anaconda environment where smak has been installed. This is the folder you found and bookmarked in step 4 of "Installation with Conda". Using quotes aroung the path may be helpful.Run smakpython smak.pyImprovements on this installation process and guide are underway! In the meantime, don't hesitate to reach out to Joy (joy.a.wood@dartmouth.edu) or Sam (samwebb@slac.stanford.edu) for assistance.
Package: smaland
Smaland - Avanza API python wrapperThis is an unofficial python wrapper for the Avanza API. I am in no way affiliated with Avanza, using Smaland may violate the Avanzaterms of service.InstallationInstall viapip$pipinstallsmalandTOTP SecretTo log in through Smaland to Avanza, you need the TOTP Secret and log in with 2FA. To get the secret:Go to Mina Sidor > Profil > SajtinstÃ¤llningar > TvÃ¥faktorsinloggning and click "Ã…teraktivera". (Only do this step if you have already set up two-factor auth.)Click "Aktivera" on the next screen.Select "Annan app fÃ¶r tvÃ¥faktorsinloggning".Click "Kan du inte scanna QR-koden?" to reveal your TOTP Secret.Save the 2FA secret in a safe place, preferably a password manager.Temporarly save you avanza username, password, and secrit to a .env file (and add the .env file to your .gitignore)username_av=my_username
password_av=my_password
secret_av=my_secretWhen logging into Avanza through Smaland, enter the credentials as:fromsmalandimportSmalandimportdotenvimportos#Load environment variablesdotenv.load_dotenv()credentials={"username":os.getenv("username_av"),"password":os.getenv("password_av"),"secret":os.getenv("secret_av")}sl=Smaland()sl.authenticate(credentials)LICENSEMIT license. See the LICENSE file for details.RESPONSIBILITIESThe author of this software is not responsible for any indirect damages (foreseeable or unforeseeable), such as, if necessary, loss or alteration of or fraudulent access to data, accidental transmission of viruses or of any other harmful element, loss of profits or opportunities, the cost of replacement goods and services or the attitude and behavior of a third party.AcknowledgmentThis wrapper was inspired by the nodeAvanza-api, where the author did a great job in finding all the endpoints etc. Thank you!
Package: small-ai
Simple-AIA brief description of what this project does and who it's forFeaturesWIPDocumentationDocumentationInstallationInstall simple-ai withpippipinstallsimple-aiRun LocallyClone the projectgitclonehttps://github.com/deadpyxel/simple-aiGo to the project directorycdsimple-aiInstall dependencies withpipenvpipenvinstall--devStart the dev serverpipenvrunpytestRunning TestsTo run tests, run the following commandpipenvrunpytestOr, if you are using a non-pipenv managed env, first activate the virtual env, then just runpytestWith this you should have the tests always running, monitoring for file changes and reporting coverage as terminal, XML and HTML reports.Usage/ExamplesimportComponentfrom'my-project'functionApp(){return<Component/>}OptimizationsWhat optimizations did you make in your code? E.g. refactors, performance improvements, accessibilityLessons LearnedWhat did you learn while building this project? What challenges did you face and how did you overcome them?AcknowledgementsClass lecturesPipenvArchitecture Patterns with PythonHow to write a Good readmeLicenseMITAlso onLICENSEfile.ContributingContributions are always welcome!Seecontributing.mdfor ways to get started.Please adhere to this project'scode of conduct.Authors@deadpyxel
Package: smallbrowser
Grace to you and peace from God our Father and the Lord Jesus Christ.I give thanks to my God always for you because of the grace of God that was given you in Christ Jesus, that in every way you were enriched in him in all speech and all knowledgeâ€” even as the testimony about Christ was confirmed among youâ€” so that you are not lacking in any gift, as you wait for the revealing of our Lord Jesus Christ, who will sustain you to the end, guiltless in the day of our Lord Jesus Christ. God is faithful, by whom you were called into the fellowship of his Son, Jesus Christ our Lord.smallbrowserpipinstallsmallbrowserA small HTTP browser library in Python based on therequestslibrary.DependencyAll due credits torequestsandpyqueryPython libraries.ConceptThis library is only composed of five (5) methods.Browser#type(String url)Browser#enter()Browser#fillup(dict form)Browser#submit()Browser#responseSimilar to what you do with a browser, youtypethe URL and pressenterto load the URL.
Then, you will get aresponseback.
When there is a form, youfill upthe form and clicksubmit.UsageThe code below will print out the raw HTML ofhttps://www.google.comwebsite.fromsmallbrowserimportBrowserbrowser=Browser("browser.storage")response=browser.type("https://www.google.com").enter().responseprint(response.text)TheBrowser#responseis the return object fromrequestslibrary.
When initializing theBrowserobject, you need to pass a path to a directory, which is namedbrowser.storage. This directory is automatically created by the library. This will contain session information so that your session may be saved.For debugging purposes, you may open thebrowser.storage/contentsandbrowser.storage/responsesdirectory that contains information about all your visited websites.GLORY BE TO OUR LORD JESUS CHRIST. JESUS LOVES YOU.
Package: smallconfig
smallconfigFor Python 3.8+.A small utility for managing script-specific settings and multiple
configurations. Configuration files are stored inAppdata/Roamingas
.json files. Uses only the standard library.QuickstartThis utility contains a template classSmallConfigwhich handles
multiple configuration files for the same script.Create a child class ofSmallConfigthat implements themanager_nameanddefault_configproperties.fromsmallconfigimportSmallConfigasSmallConfigTemplateclassSmallConfig(SmallConfigTemplate):@propertydefmanager_name(self):return'ExampleManagerName'@propertydefdefault_config(self):return{'key':'value','is_example':True,}Then create an instance of the class. Set a default configuration to
clean up function calls.config=SmallConfig('configuration.json')config.get('key')# returns 'value'config.set('key','othervalue')config.get('key')# returns 'othervalue'config.set_active_config('otherconfiguration.json')config.get('key')# returns 'value'config.get('key','configuration.json')# returns 'othervalue'Other useful functions, mostly for juggling multiple configurations:# returns a list of full file paths to configs with given manager nameconfig.get_configs()# gets the config dictionary of a given config nameconfig.get_config('config.json')# reloads the cache of a config directly from a fileconfig.reload()# creates a new configuration file (with default settings)config.create_config('newconfig.json')# sets the default configurationconfig.set_active_config('otherconfig.json')
Package: smalldata
UNIX pipe fittings for statisticsIn the quest forcommand line data science,
this kit contains three command line utilities intended to be used in UNIX pipes.All three process STDIN to STDOUT output their docstrings if run without parameters.Python 3 is required.sd_c  (smalldata count)Is a regular expression counter filter, contained insmalldata/counter.py. Please see docstring for further help.sd_g  (smalldata groupby)Concatenates lines from stdin that match a regular expression, contained insmalldata/groupby.py. Please see docstring.sd_e (smalldata extract)In the spirit ofRegExSerDe, this
tool uses regular expressions to generate a CSV file from a free-form text file. It is contained insmalldata/extract.pyand has a docstring.Other Useful ToolsIf you've got CSV files, you should definitively check outq.To DoA cookbook would be nice. Showing how to analyze log files etc.HistoryUsed to live in a gist:https://gist.github.com/martinvirtel/94cf47f64bf304e1c66598e93cd565c4
Package: smalldocpy
Smalldoc is a small lib which allow to extract your Python documentation in an easy way.The following documentation of Smalldoc had been generate executing scriptdoc.pysmalldocSmall module which allow you to extract your docstring documentation in the format of your choice.parsedefparse(working_path:str,module_name:str,show_private=False)->dictParse your code and  docstring then generate a dict with it.ArgumentsNameTypeDescriptionmodule_namestrThe name of the module you want to generate dict of your documentationshow_privateIf True, parser will navigate through your private methode. At False by default.working_pathstrThe working directory to fetch your moduleReturndict: Dictionnary which contain metadata and doc.writedefwrite(module:dict)->strNow, allow to generate a single page documentation in markdown using the only on Jinja template available.
The dictionary should be generated by parser.ArgumentsNameTypeDescriptionmoduledictThe dict of your module generated by parser.Returnstr: A single page markdown representation of your documentation