Saravanan666/pypi-org huggingface dataset:
Package: sampledb
SampleDBSampleDB is a web-based sample and measurement metadata database.DocumentationYou can find the documentation for the current release athttps://scientific-it-systems.iffgit.fz-juelich.de/SampleDB/.Getting StartedWe recommend using our pre-built Docker images for setting upSampleDB. You will need two containers, one for a PostgreSQL database and another for SampleDB itself, and a directory to store all files in.If you would like to set up a development version of SampleDB instead, please see thecontribution guide.If you do not have Docker installed yet, pleaseinstall Docker.Using docker-composeFirst, get thedocker-compose.ymlconfiguration file. You can git clone this repo or just get the file:curlhttps://raw.githubusercontent.com/sciapp/sampledb/develop/docker-compose.yml.dist--outputdocker-compose.ymlThen simply bring everything up with:docker-composeup-dUsing docker commandsFirst, start your database container:dockerrun\-d\-ePOSTGRES_PASSWORD=password\-ePGDATA=/var/lib/postgresql/data/pgdata\-v`pwd`/pgdata:/var/lib/postgresql/data/pgdata:rw\--restart=always\--namesampledb-postgres\postgres:12Next, start the SampleDB container:dockerrun\-d\--linksampledb-postgres\-eSAMPLEDB_CONTACT_EMAIL=sampledb@example.com\-eSAMPLEDB_MAIL_SERVER=mail.example.com\-eSAMPLEDB_MAIL_SENDER=sampledb@example.com\-eSAMPLEDB_ADMIN_PASSWORD=password\-eSAMPLEDB_SQLALCHEMY_DATABASE_URI=postgresql+psycopg2://postgres:password@sampledb-postgres:5432/postgres\--restart=always\--namesampledb\-p8000:8000\sciapp/sampledb:0.26.0Once it's startedThis will start a minimal SampleDB installation athttp://localhost:8000and allow you to sign in with the usernameadminand the passwordpassword(which you should change immediately after signing in).To learn how to further set up SampleDB, please follow the rest of theGetting Started guide.ContributingIf you want to improve SampleDB, please read thecontribution guidefor a few notes on how to report issues or submit changes.SupportIf you run into any issues setting up or running SampleDB, pleaseopen an issue on GitHub.You can also subscribe to theSampleDB mailing listto learn about new features and to discuss any questions regarding SampleDB.
Package: sampledbapi
SampleDB API WrapperWhat it doesThis package is a simple Python wrapper for theHTTP APIofSampleDB, a web-based sample and measurement metadata database developed at PGI and JCNS.This Python wrapper may also be used e.g. in Matlab and Julia.InstallationUser installation using pip:pip install --upgrade --user sampledbapiSystem installation using pip:pip install --upgrade sampledbapiExample usagePythonfromsampledbapiimport*server_address=...api_key=...# Authenticationauthenticate(server_address,api_key)# Simple queriesprint(actions.get_list())print(objects.get(123))print(instruments.get_list())# Advanced searchprint(objects.get_list("material ==\"Sb\""))More examples for usage in Python can be foundhere.MatlabYou need a working installation of Python andsampledbapiinstalled for this to work.
Some type conversions are needed (e.g. to pass integers).% Authenticationpy.sampledbapi.authenticate("https://...","your_api_key")% Simple queriesprint(instruments.get_list())py.sampledbapi.objects.get(py.int(123))py.sampledbapi.instruments.get_list())% Advanced searchl=py.sampledbapi.objects.get_list('material == "Sb"')obj=l{1}obj.dataIn an analogous way, the Python examples shownherecan be used in Matlab.DocumentationThe current API documentation can be foundhere.
Further details on the input and output of each function (usually JSON) can be found in the documentation of theHTTP API.What worksThe full HTTP API of SampleDB is supported. This includesAuthenticationObjectsReading a list of all objectsGetting the current object versionReading an object versionCreating a new objectUpdating an object / Creating a new object versionGetting related objectsObject permissionsReading whether an object is publicSetting whether an object is publicReading all users' permissionsReading a user's permissionsSetting a user's permissionsReading all groups' permissionsReading a group's permissionsSetting a group's permissionsReading all project groups' permissionsReading a project group's permissionsSetting a project group's permissionsInstrumentsReading a list of all instrumentsReading an instrumentInstrument log entriesReading a list of all log entries for an instrumentReading an instrument log entryReading a list of all log categories for an instrumentReading an instrument log categoryReading a list of all file attachments for a log entryReading a file attachment for a log entryReading a list of all object attachments for a log entryReading an object attachment for a log entryCreating an instrument log entryActionsReading a list of all actionsReading an actionAction typesReading a list of all action typesReading an action typeUsersReading a list of all usersReading a userReading the current userLocationsReading a list of all locationsReading a locationReading a list of an object's locationsReading an object's locationLocation typesReading a list of all location typesReading a location typeFilesReading a list of an object's filesReading information for a fileUploading a filePosting a linkCommentsReading a list of an object’s commentsReading information for a commentPosting a comment
Package: samplefit
samplefitsamplefitis a Python library to assess sample fit, as opposed to model fit, via theSample Fit Reliabilityalgorithm as developed by Okasa & Younge (2022).samplefitis linked to thestatsmodelslibrary (Seabold & Perktold, 2010) and follows the same command workflow.Copyright (c) 2022 Gabriel Okasa & Kenneth A. Younge.AUTHOR:  Gabriel Okasa & Kenneth A. Younge
SOURCE:  https://github.com/okasag/samplefit
LICENSE: Access to this code is provided under an MIT License.Repo maintainer: Gabriel Okasa (okasa.gabriel@gmail.com)Introductionsamplefitis a Python library for the assessment of sample fit in
econometric models. In particular,samplefitimplements the Sample Fit
Reliability (SFR) algorithm, a re-sampling procedure to estimate the
reliability of data and check the sensitivity of results. To that end,
SFR is a computational approach with three aspects:Scoring, to estimate a
point-wise reliability score for every observation in a sample based on the
expected estimation loss over sub-samples;Annealing, to test the sensitivity
of results to the sequential removal of unreliable data points; andFitting,
to estimate a weighted regression that adjusts for the reliability of the data.Detailed documentation of thesamplefitlibrary is availablehere.InstallationTo install thesamplefitlibrary fromPyPirun:pip install samplefitor alternatively, to clone the repo run:git clone https://github.com/okasag/samplefit.gitThe required modules can be installed by navigating to the root of
the cloned project and executing the following command:pip install -r requirements.txt.ExampleThe example below demonstrates the workflow of using thesamplefitlibrary in conjunction with the well-knownstatsmodelslibrary.Import libraries:importsamplefitassfimportstatsmodels.apiassmGet data:boston=sm.datasets.get_rdataset("Boston","MASS")Y=boston.data['crim']X=boston.data['lstat']X=sm.add_constant(X)Assess model fit:model=sm.OLS(endog=Y,exog=X)model_fit=model.fit()model_fit.summary()Assess sample fit:sample=sf.SFR(linear_model=model)sample_fit=sample.fit()sample_fit.summary()Assess sample reliability:sample_scores=sample.score()sample_scores.plot()Assess sample sensitivity:sample_annealing=sample.anneal()sample_annealing.plot()ReferencesOkasa, Gabriel, and Kenneth A. Younge. “Sample Fit.” Working Paper. 2022.Seabold, Skipper, and Josef Perktold. “statsmodels: Econometric and statistical modeling with python.” Proceedings of the 9th Python in Science Conference. 2010.
Package: sample-git-diffs
sample-git-diffsSample git diffs uniformly wrt. number of changes per file. The output is formatted as a .diff file.

optional arguments:
  -h, --help            show this help message and exit
  --n N                 Total number of diffs to be sampled
  --diffstat DIFFSTAT   Custom git diff command for the sampling probabilities
  --diffcommand DIFFCOMMAND
                        Custom git diff command for the actual diffFor example, if you want to draw a sample of 25 diffs from the folder data/, you runsample-git-diffs --diffstat "git diff --stat data/" --n 25To save this to changes.diff, you runsample-git-diffs --diffstat "git diff --stat data/" --n 25 > changes.diffdiff2markdownThere's also a script that converts the generated .diff / .patch files into markdown.usage: diff2markdown [-h] --path PATH [--username USERNAME] [--reponame REPONAME] [--branch BRANCH]

optional arguments:
  -h, --help           show this help message and exit
  --path PATH
  --username USERNAME
  --reponame REPONAME
  --branch BRANCHFor example, if you want to convert the changes.diff file into markdown, assuming that the repo is called 'sample-git-diffs', you're on branch 'main' and the github username is 'testuser', you rundiff2markdown --path changes.diff --username testuser --reponame sample-git-diffs --branch main
Package: sample-id
Sample IDAcoustic fingerprinting for Sample IdentificationFeaturesWhat it do?UsageTODOInstallpip install sample-idDocumentationSeehttps://sample-id.readthedocs.org/en/latest/Developmentpip install poetrycd sample-idpoetry installRunTo run cli entrypoint:poetry run sample_id --helpTestspoetry run toxDockerTo run with dockerdocker build -t sample_id .docker run sample_id:latest sample_id --help
Package: sample-jojo
All rights reserved.Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.Description: Sample Module Repository========================This simple project is an example repo for Python projects.`Learn more <http://www.kennethreitz.org/essays/repository-structure-and-python>`_.---------------If you want to learn more about ``setup.py`` files, check out `this repository <https://github.com/kennethreitz/setup.py>`_.✨🍰✨Platform: UNKNOWN
Package: sample-klein-app
A sample application in Python, using theKleinweb framework.Klein is a lightweight web framework, similar toFlaskorBottle.
The primary differentiator for Klein is that it is built on theTwistedframework, which enables one to writeasynchronousapplications.This sample application attempts to demonstrate a few things:Basic usage of Klein.
Seehello.py.Using URL path components as arguments.
Seemath.py.Use ofhandle_errorsto catch exceptions and respond with an
appropriate error.
Seemath.py.Composition of Klein applications.
Seecomposite.py.Using Twisted to write asynchronous code usingasync/await.
Seedns.py.
Package: sample-lines
Sample lines from a file that has already been written.InstallInstall like so.pip install sample-linesHow toSee the help for documentation.sample-lines -h
usage: Randomly select lines from a file. [-h] [--sample-size N]
                                          [--method {simple-random,systematic}]
                                          [--repeat REPEAT]
                                          file

positional arguments:
  file

optional arguments:
  -h, --help            show this help message and exit
  --sample-size N, -n N
                        Number of lines to emit
  --method {simple-random,systematic}, -m {simple-random,systematic}
                        Sampling method
  --repeat REPEAT, -r REPEAT
                        Number of repetitions for systematic samplingSamples are with replacement and weighted by line length. The probability
of selecting a line is proportional the length of the previous line.
This allows us to
sample very quickly, but it makes this approach appropriate only if your
file has reasonably consistent line lengths or at least if there is no
periodic variation in line length.How fastConsider this 1-gigabyte CSV file.$ wc big-file.csv
 2388430 27673790 1071895374 big-file.csvRunningwctook three seconds.time wc big-file.csv
 2388430 27673790 1071895374 big-file.csv

real    0m3.789s
user    0m3.560s
sys     0m0.190sHere’s how long it takes to parse the whole file.$ time python3 -c 'for line in open("big-file.csv"): pass'

real    0m2.892s
user    0m2.641s
sys     0m0.245ssample-linesis much faster. Here’s a simple random sample of 40 lines,$ time sample-lines -n 40 -m simple-random big-file.csv > /dev/null

real    0m0.136s
user    0m0.113s
sys     0m0.018sa systematic sample of 40 lines,$ time sample-lines -n 40 -m systematic -r 4 big-file.csv > /dev/null

real    0m0.148s
user    0m0.122s
sys     0m0.019sand repeated systematic sample, with 4 repeats and 10 lines each, for
a total of 40 lines.$ time sample-lines -n 10 -m systematic -r 4 big-file.csv > /dev/null

real    0m0.175s
user    0m0.140s
sys     0m0.025sMost of the time in the above examples was spent loading Python and the
various modules; printing the help takes almost as long as running the sample.$ time sample-lines -h > /dev/null

real    0m0.157s
user    0m0.129s
sys     0m0.021sSo even a pretty big sample is still fast to run.$ time sample-lines -n 2000 -m systematic -r 50 big-file.csv > /dev/null

real    0m2.695s
user    0m2.435s
sys     0m0.231sAlternativesUsesampleif you want to sample from a stream.
Package: sample-package-chanshing
Sample PyPI package + GitHub Actions + VersioneerThis template aims to automate the tedious and error-prone steps of tagging/versioning, building and publishing new package versions. This is achieved by syncing git tags and versions with Versioneer, and automating the build and release with GitHub Actions, so that publishing a new version is as painless as:$gittagvX.Y.Z&&gitpush--tagsThe following guide assumes familiarity withsetuptoolsand PyPI. For an introduction to Python packaging, see the references at the bottom.How to use this templateClick on theUse this templatebutton to get a copy of this repository.Renamesrc/sample_packagefolder to your package name —src/is where your package must reside.Go through each of the following files and rename all instances ofsample-packageorsample_packageto your package name. Also update the package information such as author names, URLs, etc.setup.pypyproject.toml__init__.pyInstallversioneerandtomli, and runversioneer:$pipinstalltomli$pipinstallversioneer$versioneerinstallThencommitthe changes produced byversioneer. Seehereto learn more.Setup your PyPI credentials. See the sectionSaving credentials on Githubofthis guide. You should use the variable namesTEST_PYPI_API_TOKENandPYPI_API_TOKENfor the TestPyPI and PyPI tokens, respectively. See.github/workflows/release.yaml.You are all set! It should now be possible to rungit tag vX.Y.Z && git push --tagsto automatically version, build and publish a new release to PyPI.Finally, it is a good idea toconfigure tag protection rulesin your repository.ReferencesPython packaging guide:https://packaging.python.org/en/latest/tutorials/packaging-projects/...and how things are changing:https://snarky.ca/what-the-heck-is-pyproject-toml/— in particular, note that whilepyproject.tomlseems to be the future, currently Versioneer still depends onsetup.py.Versioneer:https://github.com/python-versioneer/python-versioneerGitHub Actions:https://docs.github.com/en/actions
Package: sample-pool
Sample Pool Aliquot Size CalculatorThis package can be used to quickly calculate the ratio of 1 unit volume one may need to use so that all aliquots contain the same amount of proteomics contentDependenciespandas="^1.4.3"Usageimportpandasaspdfromsample_pool.experimentimportExperiment# Read tabulated text file containing the datapath=r".\RN_220625_Hippo-TiO2_15TMT_Minipool_PSMs.txt"df=pd.read_csv(path,sep="\t")# Create a variable with list of columns containing sample datasamples=["Abundance: 126","Abundance: 127N","Abundance: 127C","Abundance: 128N","Abundance: 128C","Abundance: 129N","Abundance: 129C","Abundance: 130N","Abundance: 130C","Abundance: 131N","Abundance: 131C","Abundance: 132N","Abundance: 132C","Abundance: 133N","Abundance: 133C"]# Create Experiment object with the dataframe and sample list as parametersexp=Experiment(df,samples)# Get aliquot size ratio as a dictionary with key being sample name and value being volume ratiosize=exp.get_aliquot_size(minimum_good_samples=10)# By default get_aliquot_size would use the sample with the lowest normalized sum intensity as the base for ratio calculation. To specify the sample, you can use based_on_sample parameter.size=exp.get_aliquot_size(based_on_sample="Abundance: 127C",minimum_good_samples=10)print(size)
Package: sampleproject
A sample Python projectA sample project that exists as an aid to thePython Packaging User
Guide'sTutorial on Packaging and Distributing
Projects.This project does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.The source for this project is available here.The metadata for a Python project is defined in thepyproject.tomlfile,
an example of which is included in this project. You should edit this file
accordingly to adapt this sample project to your needs.This is the README file for the project.The file should use UTF-8 encoding and can be written usingreStructuredTextormarkdownwith the appropriatekey set. It will be used to generate the project webpage on PyPI and will be
displayed as the project homepage on common code-hosting services, and should be
written for that purpose.Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not a
good idea, although a simple “What's New” section for the most recent version
may be appropriate.
Package: sampleproject-123456789
A sample Python projectA sample project that exists as an aid to thePython Packaging User
Guide'sTutorial on Packaging and Distributing
Projects.This project does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.The source for this project is available here.Most of the configuration for a Python project is done in thesetup.pyfile,
an example of which is included in this project. You should edit this file
accordingly to adapt this sample project to your needs.This is the README file for the project.The file should use UTF-8 encoding and can be written usingreStructuredTextormarkdownwith the appropriatekey set. It will be used to generate the project webpage on PyPI and will be
displayed as the project homepage on common code-hosting services, and should be
written for that purpose.Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not a
good idea, although a simple “What's New” section for the most recent version
may be appropriate.
Package: sampleproject4cxhjet
A sample project that exists as an aid to the [Python Packaging UserGuide][packaging guide]'s [Tutorial on Packaging and DistributingProjects][distribution tutorial].This project does not aim to cover best practices for Python projectdevelopment as a whole. For example, it does not provide guidance or toolrecommendations for version control, documentation, or testing.[The source for this project is available here][src].Most of the configuration for a Python project is done in the `setup.py` file,an example of which is included in this project. You should edit this fileaccordingly to adapt this sample project to your needs.----This is the README file for the project.The file should use UTF-8 encoding and can be written using[reStructuredText][rst] or [markdown][md use] with the appropriate [key set][mduse]. It will be used to generate the project webpage on PyPI and will bedisplayed as the project homepage on common code-hosting services, and should bewritten for that purpose.Typical contents for this file would include an overview of the project, basicusage examples, etc. Generally, including the project changelog in here is not agood idea, although a simple “What's New” section for the most recent versionmay be appropriate.[packaging guide]: https://packaging.python.org[distribution tutorial]: https://packaging.python.org/en/latest/distributing.html[src]: https://github.com/pypa/sampleproject[rst]: http://docutils.sourceforge.net/rst.html[md]: https://tools.ietf.org/html/rfc7764#section-3.5 "CommonMark variant"[md use]: https://packaging.python.org/specifications/core-metadata/#description-content-type-optionalKeywords: sample setuptools developmentPlatform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Intended Audience :: DevelopersClassifier: Topic :: Software Development :: Build ToolsClassifier: License :: OSI Approved :: MIT LicenseClassifier: Programming Language :: Python :: 2Classifier: Programming Language :: Python :: 2.7Classifier: Programming Language :: Python :: 3Classifier: Programming Language :: Python :: 3.4Classifier: Programming Language :: Python :: 3.5Classifier: Programming Language :: Python :: 3.6Description-Content-Type: text/markdownProvides-Extra: devProvides-Extra: test
Package: sampleproject-doubleyoung18
A sample Python projectA sample project that exists as an aid to thePython Packaging User
Guide'sTutorial on Packaging and Distributing
Projects.This project does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.The source for this project is available here.Most of the configuration for a Python project is done in thesetup.pyfile,
an example of which is included in this project. You should edit this file
accordingly to adapt this sample project to your needs.This is the README file for the project.The file should use UTF-8 encoding and can be written usingreStructuredTextormarkdownwith the appropriatekey set. It will be used to generate the project webpage on PyPI and will be
displayed as the project homepage on common code-hosting services, and should be
written for that purpose.Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not a
good idea, although a simple “What's New” section for the most recent version
may be appropriate.