Saravanan666/pypi-org huggingface dataset:
Package: slicefix-jonathandannel
A simple Python script for editing Photoshop slice generated HTML for use with e-blasts.RequirementsPython 3. Runwhich python3; If not found, install with Homebrew, apt, or whatever else you use. Once it is installed, make sure the shebang path at the start of the script (ex:#!/usr/bin/python3) matches where your Python 3 is installed.Use pip 3 to install dependencies:pip3will be installed with your Python 3 install.Runpip3 install -r requirements.txt. This will install the bs4 and datetime packages. You can also install them manually, if you like. The script will not work if you skip this step.Usagepython3 fix.py -f some-html-file-1942.html -d yourdomainhere.caThe script takes two arguments,-f(file) and-d(domain).-fThe .html file you want to fix. If you're running the script in the same directory as the HTML file, then all you have to do is type in/paste the file name. You can also specify a path (this is better)For example, if yourfix.pyis in your~/or/home/directory, and your HTML file is located in~/Downloads/eblasts, you would navigate to~/and runpython3 fix.py --file ~/Downloads/eblasts/some-html-file-1942.html --domain yourdomainhere.ca. The output file will be generated in the same directory as the HTML file input.You can also movefix.pyinto whatever directory contains the HTML file and run it from there, so you don't have to type out the path to the file.-dThe domain (withouthttp://) where the images in the HTML are hosted. For example,yourdomainhere.com.ResultAll<img>elements get the correct style tags added to them.All<img>srcattributes will be edited to use the right domain/path for the FTP (http://and/eblasts/).Center element, SEO text div, and other pre-table and post-table content is added.The original HTML file will be untouched. A new file will be generated, named the same as the original file but with an underscore and timestamp (seconds) added to it. The new file will be generated in the same directory as the original HTML file.TodoDepending on usage, I could work a bit more on customizing where the file is saved or generated.Add batch file support, more CLI args.AlsoYou'll still need to edit the SEO text and client address text manually.Feel free to contribute more features if you like. It's simple now, but it could end up being pretty useful in the future.
Package: sliceguard
sliceguardDetect problematic data slices in unstructured and structured data – fast.🚀 IntroductionSliceguard helps you to quickly discoverproblematic data segments. It supports structured data as well as unstructured data like images, text or audio. Sliceguard generates aninteractive reportwith just a few lines of code:fromsliceguardimportSliceGuardsg=SliceGuard()issues=sg.find_issues(df,features=["image"])sg.report()⏱️ QuickstartInstall sliceguard by runningpip install sliceguard[all].Go straight to our quickstart examples for your use case:🖼️Unstructured Data (Images, Audio, Text)–🕹️ Interactive Demo📈Structured Data (Numerical, Categorical Variables)–🕹️ Interactive Demo📊Mixed Data (Contains Both)–🕹️ Interactive Demo🗺️ Public RoadmapWe maintain apublic roadmapso you can follow along the development of this library.
Package: slicegui
SliceAn open-source application to create custom font design spaces from variable fontsAboutSlice is an open-source, cross-platform GUI app that generates fonts with custom design sub-spaces from variable font inputs.InstallmacOS:Slice.0.7.1.dmgWindows:Slice-0.7.1-Installer.exePlease see theInstallation docsfor additional details, including available package manager installation/upgrade approaches.User documentationUser docs are available athttps://slice-gui.netlify.app/docs/InstallationUsageAxis definitionsSlice currently supports combinations of the following axis definition types in output fonts:Fixed instance locationsLevel 3 restricted axis ranges (must include original axis default value in the new, smaller axis range)[1]Full, original variable axis rangesDefine your font axes with the syntax in the table below.Axis definitionAxis Editor SyntaxExampleFixed axis locationInteger or float value400.0Restricted axis rangeColon-delimited min:max integer or float range200:700Full axis rangeLeave editor row blankn/aIssuesPlease file issues on theproject tracker.ContributingSource contributions are welcome.  Please see theSlice application developer documentationfor instructions on how to set up a local development environment and test your source changes.  Submit a pull request with any changes that you would like to share upstream.The Slice documentation is maintained in a separate GitHub repository.  Please see theSlice documentation developer docsfor additional details about how to modify documentation content and set up a local testing environment.Contributions to this project are accepted under the licenses specified in theLicensessection below.LicensesThe Slice project is licensed under the GNU General Public License version 3. Please see theLICENSEdocument for details.Please see thethirdparty directoryfor additional details about third-party licenses.Acknowledgments❤️ Slice slices with the fantasticfonttools Python library.❤️ Slice uses the wonderfulRecursive(sliced with Slice!) andIBM Plextypefaces in the UI.⚡Slice docsare powered by Netlify (doc sources).1: Default axis locations are required to compile valid variable font format files.  The default axis value defined in the original font must be included in the restricted axis range due to the lack of compiler support for default axis location moves during the slicing process. We intend to support default axis location moves when it is possible to do so.This issue is being tracked on our GitHub tracker.
Package: sliceit
sliceitDynamically sized slice views which avoid storing their own data.The builtin list, tuple, str, etc., create copies when sliced.
This is to allow all of the unnecessary memory to be freed if it
is no longer needed. In some cases, the opposite problem occurs,
where none of the memory needs to be freed anyways, meaning slices
simply take up more space than necessary.Some data structures provide slicing views already, such as:numpypandastensorflowand many other data science packagesIf these packages already fit your needs, consider using them instead.What's different?sliceitprovides sliceable views anySequence(orMutableSequence),
meaning it works for lists, tuples, strings, etc., and can also be used
as an easy way to implement slicing for custom classes.Furthermore,sliceituses lazily evaluated slices. This means the
underlying data is free to change size as much as it wants. The catch
is that some objects may raise runtime errors if you try iterating
over them at the same time.Unlike some,sliceitis also recursively sliceable and supports mutations,
although modifying slices may in some cases be unintuitive.InstallUnix/macOS:python3 -m pip install sliceitWindows:py -m pip install sliceitExamplesfromsliceitimportsliceitprint("Create a slice view of some data.")L=list(range(10))S=sliceit(L)[::-1]print(f"L ={L}")print(f"list(S) ={list(S)}")print()print("Slices act as a view over the data.")print(f"list(S) ={list(S)}")L[0]=-10print(f"L[0] := -10")print(f"list(S) ={list(S)}")L[0]=0print(f"L[0] := 0")print(f"list(S) ={list(S)}")print()print("They can be looped over or indexed as you would expect.")print(f"[x for x in S] ={[xforxinS]}")print(f"S[0] ={S[0]}")print()print("If the data is mutable, the slice is mutable.")S[0]=0print("S[0] := 0")print(f"L[-1] ={L[-1]}")S[0]=9print("S[0] := 9")print(f"L[-1] ={L[-1]}")
Package: sliceline
Sliceline is a Python library for fast slice finding for Machine
Learning model debugging.It is an implementation ofSliceLine: Fast, Linear-Algebra-based Slice
Finding for ML Model
Debugging,
from Svetlana Sagadeeva and Matthias Boehm of Graz University of
Technology.👉 Getting startedGiven an input datasetXand a model error vectorerrors,
SliceLine finds the top slices inXthat identify where a ML model
performs significantly worse.You can use sliceline as follows:fromsliceline.slicefinderimportSlicefinderslice_finder=Slicefinder()slice_finder.fit(X,errors)print(slice_finder.top_slices_)X_trans=slice_finder.transform(X)We invite you to check thedemo
notebooksfor a more thorough tutorial:Implementing Sliceline on Titanic datasetImplementing Sliceline on California housing dataset🛠 InstallationSliceline is intended to work withPython 3.7 or above. Installation
can be done withpip:pipinstallslicelineThere arewheels
availablefor Linux,
MacOS, and Windows, which means that you most probably won’t have to
build Sliceline from source.You can install the latest development version from GitHub as so:pipinstallgit+https://github.com/DataDome/sliceline--upgradeOr, through SSH:pipinstallgit+ssh://git@github.com/datadome/sliceline.git--upgrade🔗 Useful linksDocumentationPackage releasesSliceLine paper👐 ContributingFeel free to contribute in any way you like, we’re always open to new
ideas and approaches.Open a
discussionif you have any question or enquiry whatsoever. It’s more useful to
ask your question in public rather than sending us a private email.
It’s also encouraged to open a discussion before contributing, so
that everyone is aligned and unnecessary work is avoided.Feel welcome toopen an
issueif
you think you’ve spotted a bug or a performance issue.Please check out thecontribution
guidelinesif you want to bring modifications to the code base.📝 LicenseSliceline is free and open-source software licensed under the3-clause BSD license.
Package: slicemap
Python Slice MapSlicemap is a MIT licensed library introducing a useful, dictionary-like data structure,
similar to normal Python dict, but instead of setting values key by key, you set entire slices.Features:Implemented entirely in PythonHas only one dependency:sortedcontainersIs efficient, it hasO(log(n))time complexity for insertion and queryAdding new slices might make old ones become redundantncorrespondes to the maximal number of slices present in SliceMap at a timeMakes life easier, seeapplicationsExamplefromslicemapimportSliceMapsm=SliceMap()sm[-3:3]=0.1sm[6.5:]="Hello, SliceMap"print(sm[0])print(sm[10])0.1
'Hello, SliceMap'See more examples inQuick Start.InstallationInstall easily with pip:pip install slicemapLinksRead DocumentationSee on GitHubSee on PyPI
Package: slice-match
slice-matchSimple class, that simplify usage of slices in__getitem__.Available on PyPi:https://pypi.org/project/slice-match/InstallationInstall with pip:pipinstall-Uslice-matchRequirementsPython 3.10 and newerDescriptionIt's just a little trick, that allows you to do:classcustom_indexed:def__getitem__(self,index):matchindex:caseint(s):print('this is "me[0]"-like expression')caseSlice(int(s)):# note, this also matches "me[0:<Any>:<Any>]"-likeprint('this is "me[0:]"-like expression')caseSlice(int(start),int(stop)):# note, this also matches "me[0:5:<Any>]"-likeprint('this is "me[0:5]"-like expression')caseSlice(int(start),int(stop),int(stride)):print('this is "me[0:5:2]"-like expression')caseSlice(start,None,stride):print('this is "me[<Any>::<Any>]"-like expression')caseSlice(start=12):print('this is "me[12:<Any>:<Any>]"-like expression')Performance dropUsingSlicecause ~2x performance drop, compared with usingslice.Simple benchmark notebook can be found here:https://github.com/SaelKimberly/slice-match/blob/main/slice-match.ipynbSo, readability improved (over 9000% ;) ), but performance slightly drops.
Package: slicenet
Slicenetmininet-like simulation for Network SlicesWhat is SlicenetA mininet like Simulator for simulating large macro network topologies along with UEs, Application nodes, Access networks, Transport networks, Core network & Data network.Network Slicing policies & optimization logics can be experimented in various topologies and performance of each experiment can be measured in predictable & reproducible manner.Unlike mininet, Slicenet only “simulates” the network. Hence without any real compute & power resources, lot of resource optimization, scheduling, prioritization & capacity models can be experimented in consistent way.By abstracting topology out of the traffic pattern, same topology can be experiments with different traffic pattern. Mobility scenarios can also be easily experimentedWhy Slicenet ?Operators & Researchers have a simple & efficient way to try their experiments without the need to emulate entire physical / virtual topologyBorrows the topology, simulation & experiments concepts on all the previous tools and provides a consistent way to experiment & report the findingsBased on python and thereby extending itself to popular ML frameworks like TensorFlow / PyTorch to native use ML/DL/NN models as part of the experimentsSince Slicenet is just simulation, it can be run in Jupyter notebook setup as well (unlike mininet which is based on linux namespaces). This makes Slicenet extremely useful for researchers to quickly export the findings of the experiments and generates charts / visualizations and share it with wider research communityIf you findSlicenetto be useful in your research work, please cite the following publication:[1]V. Kumar Skand Priya, A. Dandoushand . gladys . diaz, “Slicenet: A Simple and Scalable Flow-Level Simulator for Network Slice Provisioning and Management”. TechRxiv, 18-Oct-2023, doi: 10.36227/techrxiv.24311254.v1.@article{KumarSkandPriya2023,author="Viswanath Kumar Skand Priya and Abdulhalim Dandoush and gladys diaz",title="{Slicenet: A Simple and Scalable Flow-Level Simulator for Network Slice Provisioning and Management}",year="2023",month="10",url="https://www.techrxiv.org/articles/preprint/Slicenet_A_Simple_and_Scalable_Flow-Level_Simulator_for_Network_Slice_Provisioning_and_Management/24311254",doi="10.36227/techrxiv.24311254.v1"Other Publications@misc{kumarskandpriya2023slicenet,title={Slicenet:aSimpleandScalableFlow-LevelSimulatorforNetworkSliceProvisioningandManagement},author={ViswanathKumarSkandPriyaandAbdulhalimDandoushandGladysDiaz},year={2023},eprint={2310.11033},archivePrefix={arXiv},primaryClass={cs.NI}}
Package: sliceparser
sliceparserIntroductionAs perthis question, creating from string slice object, or even advanced indexing tuple, is a common requirement.
However, there exists few robust and safe solution, if at all, to solve the problem.
Therefore I attempt to solve it and expose programmatic interface via PyPI.
I also put myanswerto the question above.This repo is adapted frommy Gist.Installpipinstallsliceparser# or pip3 install sliceparserUsageimportsliceparsera=[1,2,3,4]asserta[sliceparser.parse_slice('2:')]==a[2:]asserta[sliceparser.parse_slice('::2')]==a[::2]asserta[sliceparser.parse_slice('1')]==a[1]importnumpyasnpA=np.eye(3)assertnp.array_equal(A[sliceparser.parse_slice('0, 1:')],A[0,1:])assertnp.array_equal(A[sliceparser.parse_slice('..., 2')],A[...,2])etc.
Package: sliceplots
Slice PlotsThin wrapper on top ofmatplotlib’s.imshow()for 2D plotting, with attached slice plotsFeaturesonly depends onmatplotlibuses its pure OO (look Ma, nopyplot!) interfacesupport for 1D and 2D plots with various customization optionsbroken-axis 1D plotssmall codebasedesigned for non-interactive use, scripting and publication-quality plotsHistory0.3.3 (2023-10-11)Bring dependencies up to date0.3.2 (2019-10-28)Implement vmin, vmax and alpha for colored line plot0.3.1 (2019-08-06)Minor bugfixes and docs update.0.3.0 (2019-08-03)Add colored line plot with colorbar.0.2.1 (2019-08-02)Fix bumpversion problem0.2.0 (2019-08-02)Simplify documentation and tests.Allow passing an existingAxesinstance to all methods/classes.0.1.2 (2019-06-19)Fixed label positions and colors.0.1.0 (2019-06-17)Added regression tests, usage and docstrings.0.0.1 (2019-06-16)First release on PyPI.
Package: slicer
slicer [alpha](Equal Contribution) Samuel Jenkins & Harsha Nori & Scott Lundbergslicerwraps tensor-like objects and provides a uniform slicing interface via__getitem__.It supports many data types including:numpy|pandas|scipy|pytorch|list|tuple|dictAnd enables upgraded slicing functionality on its objects:# Handles non-integer indexes for slicing.S(df)[:,["Age","Income"]]# Handles nested slicing in one call.S(nested_list)[...,:5]It can also simultaneously slice many objects at once:# Gets first elements of both objects.S(first=df,second=ar)[0,:]This package has0dependencies. Not even one.InstallationPython 3.6+ | Linux, Mac, WindowspipinstallslicerGetting StartedBasic anonymous slicing:fromslicerimportSlicerasSli=[[1,2,3],[4,5,6]]S(li)[:,0:2].o# [[1, 2], [4, 5]]di={'x':[1,2,3],'y':[4,5,6]}S(di)[:,0:2].o# {'x': [1, 2], 'y': [4, 5]}Basic named slicing:importpandasaspdimportnumpyasnpdf=pd.DataFrame({'A':[1,3],'B':[2,4]})ar=np.array([[5,6],[7,8]])sliced=S(first=df,second=ar)[0,:]sliced.first# A    1# B    2# Name: 0, dtype: int64sliced.second# array([5, 6])Real example:fromslicerimportSlicerasSfromslicerimportAliasasAdata=[[1,2],[3,4]]values=[[5,6],[7,8]]identifiers=["id1","id1"]instance_names=["r1","r2"]feature_names=["f1","f2"]full_name="A"slicer=S(data=data,values=values,# Aliases are objects that also function as slicing keys.# A(obj, dim) where dim informs what dimension it can be sliced on.identifiers=A(identifiers,0),instance_names=A(instance_names,0),feature_names=A(feature_names,1),full_name=full_name,)sliced=slicer[:,1]# Tensor-like parallel slicing on all objectsassertsliced.data==[2,4]assertsliced.instance_names==["r1","r2"]assertsliced.feature_names=="f2"assertsliced.values==[6,8]sliced=slicer["r1","f2"]# Example use of aliasingassertsliced.data==2assertsliced.feature_names=="f2"assertsliced.instance_names=="r1"assertsliced.values==6Contact usRaise an issue on GitHub, or contact us atinterpret@microsoft.com
Package: slicerator
Sliceratora lazy-loading, fancy-slicable iterableThink of it like a generator that is "reusable" and has a length.Please see the documentationfor examples and an API reference.InstallationOn any platform, use pip or conda.pip install sliceratororconda install -c conda-forge sliceratorExamplefromsliceratorimportSlicerator@Slicerator.from_classclassMyLazyLoader:def__getitem__(self,i):# this method will be wrapped by Slicerator, so that it accepts slices,# lists of integers, or boolean masks. Code below will only be executed# when an integer is used.# load thing number ireturnthingdef__len__(self):# do stuffreturnnumber_of_things# Demo:>>>a=MyLazyLoader()>>>s1=a[::2]# no data is loaded yet>>>s2=s1[1:]# no data is loaded yet>>>some_data=s2[0]
Package: slice-ref
Python Slicing ReferencePython's builtinlisttype allows one to pass in slices
to get, set or delete a range of elements.>>>my_list=['a','b','c']>>>my_list[0:2]['a','b']>>>my_list[0:3:2]['a','b']>>>my_list[1:3]=[1,2]>>>my_list['a',1,2]>>>my_list[::-1]=['z','y','x']>>>my_list['x','y','z']The slice notation using colons is infact aslicebuiltin,
wherestart:stop:stepis equivalent toslice(start, stop, step).
This looks an awful lot like therange(start, stop, step)builtin,
but 1-to-1 translating slices to ranges is not always appropiate.I have created this package as a reference implementation oflist,
specifically to educate on how it deals with slices.
I useHypothesisto test my custom classlistyagainst Python's very ownlist,
hopefully ensuring that all situations where slicing is involved
is perfectly emulated.
Package: slicerfiducials
SlicerFiducialsA project to manage code for manipulating slicer ficucialsFree software: GNU General Public License v3Documentation:https://slicerfiducials.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-01-20)First release on PyPI.
Package: sliceri18n
sliceri18nTo use this tool, it is necessary to import the Extractor module as follows:from sliceri18n import ExtractorTo make the extraction you have to call the extract function of the Extractor module by giving it in parameter either the .py file containing marked strings or a directory containing .py filesExtractor.extract("DataProbe.py") #fileExtractor.extract("Scripted") #folderThen a .ts file will be generated
Package: slicer-img
DescriptionThis script takes images and uses transparent pixel grids in order to seperate each object into smaller files. A test image is included in order to see how this script works.RequirementsThis package needs Pillow which can be done through:pip install PillowInstallationTo install:pip install slicer-imgUsagecd {main folder}
slice {path to image file} {format}ExamplesUses test.png and outputs in default png formatslice test.pngTo specify a different format, type the format like belowslice test.png jpgThis format works tooslice test.png .jpg
Package: slicer-package-manager
TheSlicer Package Managerincludes a REST API service and CLI built onGirderfor downloading, uploading
and organizing application and extension packages for both3D Slicerand3D Slicer-basedapplications.Documentation is available athttps://slicer-package-manager.readthedocs.ioThis software is licensed under the terms of theApache Licence Version 2.0.
Package: slicer-package-manager-client
Python client for managing Slicer application and extension packages
organized on a server with the corresponding Girder plugin installed.The documentation is accessible athttps://slicer-package-manager.readthedocs.io/en/latest/commands_shell.html#slicer-package-manager-client.InstallationInstall with:$ pip install slicer-package-manager-clientor:$ git clone https://github.com/girder/slicer_package_manager.git
$ cd slicer_package_manager/python_client
$ pip install -e .for development.ResourcesTo learn more about the Slicer package manager server and associated client, check out the following resources.https://slicer-package-manager.readthedocs.io/en/latest/commands_shell.html#slicer-package-manager-clienthttps://slicer-package-manager.readthedocs.ioLicenseThis software is licensed under the terms of theApache Licence Version 2.0.
Package: slicesampling
slicesamplerSet of Markov chain Monte Carlo (MCMC) sampling methods based on slice samplingAvailable methodsThe package includes the following methods:Univariate slice sampler, as described in [1]Multivariate slice sampler based on univariate updates along eigenvectors, as described in [2]Multivariate slice sampler based on combination of hit-and-run and univariate slice sampler, named hybrid slice sampler in [3]ExamplesExamples are included in the git repo athttps://code.ornl.gov/2kv/slicesamplingexample1_univariate.py illustrates how to use the package for univariate slice samplingexample2_bivariate.py illustrates how to use the package for multivariate slice samplingReferences[1] Neal, Radford M. (2003). Slice sampling. The Annals of Statistics, 31(3), 705 - 767. URL:https://doi.org/10.1214/aos/1056562461[2] Thompson, Madeleine (2011). Slice Sampling with Multivariate Steps. PhD Thesis. URL:https://hdl.handle.net/1807/31955[3] Rudolf, Daniel; Ullrich, Mario (2018). Comparison of hit-and-run, slice_sampler sampler and random walk metropolis. Journal of Applied Probability, 55(4), 1186-1202. URL:https://doi.org/10.1017/jpr.2018.78