Saravanan666/pypi-org huggingface dataset:
Package: pylicenser
Pylicenser提供了2种加密的方式：基于sourcedefender的原理自己加以实现的，更好的兼容了目录级别的代码加密。使用Cython进行代码封装，也支持了目录级别的文件加密。此外，Pylicenser还支持运行时的过期校验——即设置ttl，服务启动后，Pylicenser会在其运行过程中时检测失效时间。安装pipinstallpylicenser加密usage: pylicenser encrypt [-h] [--ttl TTL] [--dist DIST] str [str ...]

positional arguments:
  str          待加密的文件或文件夹

optional arguments:
  -h, --help   帮助信息
  --ttl TTL    有效日期，默认：0，单位：seconds。示例： 1s、2d、3m、4h (default: 0)
  --dist DIST  输出目录，默认当前dist目录 (default: ./dist)运行加密代码usage: pylicenser run [-h] script ...

positional arguments:
  script      py脚本文件
  args        脚本需要的参数

optional arguments:
  -h, --help  帮助信息使用Cython方式加密采用该方式需要预先安装Cython，安装方式如下：pipinstallCython--install-option="--no-cython-compile"使用方式如下：usage: pylicenser cython [--dist DIST] [-h] str [str ...]

positional arguments:
  str          待编译的代码文件或文件夹

optional arguments:
  --dist DIST  输出目录，默认当前dist目录 (default: ./dist)
  -h, --help   帮助信息Cython加密后，不影响代码原有使用方式，即原来脚本怎么运行，加密后还是怎么运行。相较于第一种加密，Cython加密具有平台依赖性，即在darwin上加密的代码在win或者linux下不一定能运行。
Package: pylicensing
pylicensingPylicensing is a leightweight tool designed to make key authentication and creation on your distributed python programs easier.
It connects to a mongodb database. Click this link to learn more aboutmongodb, a nosql easy-to-use database with a free tier.How to installPylicensing can be installed via pypipipinstallpylicensingWarningI do not recommend to connect to the database on the client directly. If your program was to be cracked, you would expose a database connection string to a possibly malicious person. Be precautious and introduce an API between your client and the database. Pylicensing provides the methods your API client needs.You can still use pylicensing on your user client, as you could for example check that theKeyyour user entered conforms theKeyFormatyou used for your application, this would prevent people from spamming meaningless keys.FeaturesCustomize the Format of aKey, i.e allow sets of characters, customize amount of sections...Keymetadata (creation date, expiration date, owner, hwids..)HWID limitations and registrations (max hwids, registered hwids...)Key format validations, to avoid requesting a database query.Easy database management and queriesExampleYou can also check theexamples folderin the repository for more detailed examples.Creating aKeyobjectmy_key_format=KeyFormat(sections=5,chars_per_section=5,seperator="-",numeric_characters=True)new_user_key=Key.create(my_key_format,user="Freddie Faulig",hwid_limit=1,valid_for=timedelta(days=30))Establishing your database connectionclient:MongoClient=MongoClient(os.environ.get("DATABASE_CONNECTION"))key_manager=KeyManager(client.test.example)Adding a key to the databasenew_user_key=Key.create(my_key_format,user="Freddie Faulig",hwid_limit=1,valid_for=timedelta(days=30))key_manager=KeyManager(client.test.example)key_manager.add_to_collection(new_user_key)
Package: pylick
pyLickis a Python tool designed to measure spectral features, such as Lick indices and D4000, in galaxy spectra. It currently supports over 80 features spanning the near-UV to the near-IR. New ones can be easily introduced. The uncertainties are evaluated using the signal-to-noise method proposed byCardiel et al. (1998). The code interpolates over bad pixels when a bad pixels mask is provided, allowing users to discard measurements above a specified Bad Pixel Fraction threshold. Additionally, the code includes convenient plotting routines.InstallationThe code can be quikly installed fromPypi:pip install pylickFor more flexibility, clone the source repository into your working folder and install it locally:git clone https://gitlab.com/mmoresco/pylick.git
cd pylick/
pip install -e .To test the installation, run the following command:python -c "import pylick; print(pylick.__version__)"DocumentationRead the docs atpylick.readthedocs.ioCitationPlease cite the following paper if you find this code useful in your research (ADS,arXiv,INSPIRE):@ARTICLE{Borghi2022a,
    author = {{Borghi}, Nicola and {Moresco}, Michele and {Cimatti}, Andrea and et al.},
     title = "{Toward a Better Understanding of Cosmic Chronometers: Stellar Population Properties of Passive Galaxies at Intermediate Redshift}",
   journal = {ApJ},
      year = 2022,
     month = mar,
    volume = {927},
     pages = {164},
       doi = {10.3847/1538-4357/ac3240},
    eprint = {2106.14894},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2022ApJ...927..164B},
}The teamMain developers:Michele Moresco (michele.moresco@unibo.it)Nicola Borghi (nicola.borghi6@unibo.it)Salvatore Quai (squai@uvic.ca)Contributors:Alexandre HuchetLucia PozzettiAndrea Cimatti
Package: pyLICORS
pyLICORS: readme================``pylicors`` is a Python module for predictive state estimation fromcontinuous valued spatio-temporal data... warning::This package is in a **Planning status**. That means it has only very limitedfunctionality, and function names, arguments, output, etc. **WILL** change inthe future.  Do not use this yet for any more involved analysis or automatedanalysis of any kind.  The code you write now **will break** with the next releases.``pylicors`` has two *cousins* in `R<www.r-project.org>`_:- `LICORS<cran.r-project.org/web/packages/LICORS>`_- `LSC<cran.r-project.org/web/packages/LSC>`_Support and Documentation-------------------------See  `pylicors website <http://pypi.python.org/pypi/pylicors>`_on `PyPI <http://pypi.python.org/pypi/>`_  to viewdocumentation, report bugs, and obtain support.License-------``pylicors`` is offered under the `GPL3 license<http://opensource.org/licenses/gpl-3.0.html>`_.Authors-------``pylicors`` is developed and maintained by `Georg M. Goerg<http://www.stat.cmu.edu/~gmg>`_.Credits-------- `numpy`_- `pyopencv`_- `OpenCV`_.. _numpy: numpy.scipy.org/.. _pyopencv: http://code.google.com/p/pyopencv/.. _`OpenCV`: http://opencv.willowgarage.com/wiki/
Package: pylicup
PythonLicenseUpdaterSimple tool that updates your python files license headers for the given directories. By default it will skipinit.py.How to use it?Installation.With pip:pipinstallpylicupWith latest version from GitHub:pipinstallgit+https://github.com/Carsopre/PythonLicenseUpdater.gitWith custom version from GitHub:pipinstallgit+https://github.com/Deltares/PythonLicenseUpdater.git@v0.0.1UsageThe following command should be used.pythonpylicup-l<path_to_your_license_file>-d<path_to_directory_with_python_files><path_to_your_licenses_file> List of licenses, the first one will replace the ones that follow (in case present) or simply added at the top.<path_to_directory_with_python_files> List of arguments representing paths to the directories containing python files.ExamplesGiven the following directory hierarchy:license_manager.py
|-src\
    |-__init__.py
    |-main.py
    |-utils.py
|-test\
    |-__init__.py
    |-test_main.py
    |-test_utils.py
|-setup.py
|-my_license.txt
|-my_newer_license.txtThe following command will update the license for src\main.py and src\utils.py:pythonlicense_manager.py-lmy_license.txt-dsrcWhereas executing the following command will result in updating the license header for src\main.py, src\utils.py, test\test_main.py and test\test_utils.py:pythonlicense_manager.py-lmy_license.txt-dsrctestLast, if we want to replace an existing license header with a new one, we would do the following command:pythonlicense_manager.py-lmy_license.txtmy_newer_license.txt-dsrc
Package: pylicy
PylicyAn customizable and extensible policy creation and enforcement framework.Installation$ pip install pylicyA Simple ExampleExamples can be found in theexamples/directory.importasyncioimportpylicy@pylicy.policy_checker('token_age_policy')asyncdefmy_policy(resource:pylicy.Resource,rule:pylicy.Rule)->pylicy.PolicyDecision:ifresource.data['token_age']>30:returnpylicy.PolicyDecision(action=pylicy.PolicyDecisionAction.DENY,reason="expired",detail={'age':resource.data['token_age']})elifresource.data['token_age']>20:returnpylicy.PolicyDecision(action=pylicy.PolicyDecisionAction.WARN)else:returnpylicy.PolicyDecision(action=pylicy.PolicyDecisionAction.ALLOW)policies=pylicy.Pylicy.from_rules([pylicy.UserRule(name='token_age',resources=['*_token*'],policies=['token_*'],)])results=asyncio.run(policies.apply_all([pylicy.Resource(id='my_ok_token',data={'token_age':10}),pylicy.Resource(id='my_old_token',data={'token_age':21}),pylicy.Resource(id='my_expired_token',data={'token_age':90})]))print(results)LicenseThis project is licensed under the terms of the MIT license.
Package: pylidator
pylidatorpylidator is a validation framework for Python projects.Many business systems have complex validation rules.  This library provides a method of organizing those rules for
convenience and testability.  Avalidatormethod is written for each rule (or group of rules), which simply returns a
list of errors if any are found.ValidatorsA validator method checks the validity of one or a closely-related group of
assertions about a piece of data.  They all look basically like this:importpylidator@pylidator.validator(of="child")defchild_is_valid(child):messages=[]ifchild['age']>=18:messages.append({"age":"Child is too old."}ifchild['type']!='human':messages.append({"type":"Only humans allowed."}returnmessages(Alternately, you can return just a dict of{field: message}items.)Validating SomethingOnce you have authored some@pylidator.validatormethods as above, you can use them!  Try this:importpylidatorobjs={'name':"Mrs. Teacher's Class",'children':[{'name':"Joe",'age':15,'type':'human'},{'name':"Sarah",'age':19,'type':'human'},]}# Define a providerdef_provide_child(obj):fori,cinenumerate(obj['children']):yieldc,{"description":"Child{}".format(i)}providers={"child":_provide_something}# "child" matches the `of` argument of the `@pylidator.validator`.ret=pylidator.validate(objs,{pylidator.ERROR:[some_values_are_valid]},providers=providers)child_is_validwill be invoked once per child, and any that return something truthy will show as an ERROR.Function Reference@pylidator.validatordecorates any method that will be passed topylidator.validate, and takes several optional parameters:@pylidator.validator(of, requires=None, affects=None)

`of` specifies what provider the validator should use.   The `validate` call needs an item in `providers`
     that matches `of`.
`requires` (optional) can add additional context items, such as the current time or other services that can supply
     data or settings to the validator.  The requirement is fulfilled by passing `extra_context` to the `validate`
     call, containing any items that are used in a `requires`.
`affects` (optional) is simply passed through to results.  It can be used as guidance for UI/error reporting for
     helping to resolve any resultant errors.pylidator.validate(
    obj, validators=None, providers=None, extra_context=None, field_name_mapper=None, 
    validation_type=None)

`obj` is the top-level object requiring validation.
`validators` is a dict of {level: list of `@pylidator.validator` objects}
`providers` is a dict of {of: func that takes obj and returns an iterable of some subobjects}
`extra_context` is a dict of other data that can be injected into `@pylidator.validator` with `requires`.
`field_name_mapper` is a string->string func that converts field names given in returned errors into verbose names.
`validation_type` is added as documentation into the error object.
`logging` If set to False, disables logging of validation results.
`why` String added to logging to identify the logpoint.
Package: pylife
pyLife – a general library for fatigue and reliabilitypyLife is an Open Source Python library for state of the art algorithms used in
lifetime assessment of mechanical components subject to fatigue load.Purpose of the projectThis library was originally compiled atBosch
Researchto collect algorithms needed by
different in house software projects, that deal with lifetime prediction and
material fatigue on a component level. In order to further extent and
scrutinize it we decided to release it as Open Source.  Readthis
articleabout pyLife's origin.So we are welcoming collaboration not only from science and education but also
from other commercial companies dealing with the topic. We commend this library
to university teachers to use it for education purposes.The companyViktorhas set up aweb application for Wöhler
test analysisbased on pyLife code.StatuspyLife-2.0.3 has been released.  That means that for the time being we hope
that we will not introducebreakingchanges.  That does not mean that the
release is stable finished and perfect.  We will do small improvements,
especially with respect to documentation in the upcoming months and release
them as 2.0.x releases.  Once we have noticeable feature additions we will come
up with a 2.x.0 release.  No ETA about that.ContentsThere are/will be the following subpackages:stresseverything related to stress calculationequivalent stressstress gradient calculationrainflow counting...strengtheverything related to strength calculationfailure probability estimationS-N-calculations...meshFEM mesh related stuffstress gradientsFEM-mappinghotspot detectionutilall the more general utilities...materialdataanalysis of material testing dataWöhler (SN-curve) data analysismateriallawsmodeling material behaviorRamberg OsgoodWöhler curvesvmapa interface toVMAPLicensepyLife is open-sourced under the Apache-2.0 license. See theLICENSEfile for details.For a list of other open source components included in pyLife, see the
file3rd-party-licenses.txt.
Package: pylife-odbclient
pylife-odbclientA Python 3 client for odbAccess using pylife-odbserverPurposeUnfortunately Abaqus still comes with a python-2.x engine. So you can't access
an Abaqus odb file from within modern python code. This python package is the
client part of a client server setup to make odb files accessible from within
python-3.x code in a transparent way.SolutionThe sibling packagepylife-odbserverprovides a slim server that as
python-2.7 software, that can be run inside the Abaqus python engine. It
accepts command viasys.stdinand according to the command is querying data
from theodbAccessinterface and returning them in a pickle object.This package comes with a python classOdbClientthat spawns the server in
the background when an instance ofOdbClientis instantiated. Then the client
object can be used to transparently access data from the odb file via the
server. Once the client object goes out of scope i.e. is deleted, the server
process is stopped automatically.InstallationInstall the odbclient usingpipwith the commandpip install pylife-odbclientSee theinstructions inpylife-odbserveron how
to install the server.UsageUsually you only will see theOdbClientclass interface when you access an
odb file. The only point you care about the server is when you instantiate anOdbClientobject. You need to know the following thingsThe path to the Abaqus executableThe path to the python environmentpylife-serveris installed into.Then you can instantiate aOdbClientobject usingimportodbclientasCLclient=CL.OdbClient("yourodb.odb")See theAPI docs ofOdbClientfor details.LimitationsLimited functionalityOnly a subset of Abaqus variable locations are supported. These are: nodal,
element nodal, whole element and centroid. Integration point variables are
extrapolated to element nodal.You can only extract data from an odb file, not write to it.String literalsSo far only names made ofasciistrings are supported.  That means that
instance names, node that names and the like containing non-ascii characters
like German umlauts will not work.
Package: pylife-odbserver
pylife-odbserverA server for odbAccess to be accessed by pylife-odbclientPurposeUnfortunately Abaqus still comes with a python-2.x engine. So you can't access
an Abaqus odb file from within modern python code. This python package is the
client part of a client server setup to make odb files accessible from within
python-3.x code in a transparent way.SolutionThis package provides a slim server that as python-2.7 software, that can be
run inside the Abaqus python engine. It accepts command viasys.stdinand
according to the command is querying data from theodbAccessinterface and
returning them in a pickle object.The sibling packagepylife-odbclientcomes with a python classOdbClientthat spawns the server in the background when an instance ofOdbClientis
instantiated. Then the client object can be used to transparently access data
from the odb file via the server. Once the client object goes out of scope
i.e. is deleted, the server process is stopped automatically.InstallationCreate and activate a plain python-2.7 environment without additional
packages.  For example byconda create -n odbserver python=2.7 pipRunpip install pylife-odbserverSee theinstructions inpylife-odbclienton how
to install the client.
Package: pylift
pyliftRead our documentation!pyliftis an uplift library that provides, primarily, (1) fast uplift modeling implementations and (2) evaluation tools (UpliftEvalclass). While other packages and more exact methods exist to model uplift,pyliftis designed to be quick, flexible, and effective.pyliftheavily leverages the optimizations of other packages -- namely,xgboost,sklearn,pandas,matplotlib,numpy, andscipy. The primary method currently implemented is the Transformed Outcome proxy method (Athey 2015).This branch is a fork fromgithub.com/wayfair/pylift, and is actively being maintained.InstallationThis version of pylift can be installed through pypi:pip install pyliftLicenseLicensed under the BSD-2-Clause by the authors.ReferenceAthey, S., & Imbens, G. W. (2015). Machine learning methods for estimating heterogeneous causal effects. stat, 1050(5).Gutierrez, P., & Gérardy, J. Y. (2017). Causal Inference and Uplift Modelling: A Review of the Literature. In International Conference on Predictive Applications and APIs (pp. 1-13).Hitsch, G., & Misra, S. (2018). Heterogeneous Treatment Effects and Optimal Targeting Policy Evaluation. Preprint
Package: pyliftover
PyLiftover is a library for quick and easy conversion of genomic (point) coordinates between different assemblies.It uses the same logic and coordinate conversion mappings as the UCSCliftOver tool.As of current version (0.2), PyLiftover only does conversion of point coordinates, that is,
unlikeliftOver, it does not convert ranges, nor does it provide any special facilities to work with BED files.
For single-point coordinates it produces exactly the same output asliftOver(verified with at least thehg17ToHg18.over.chain.gzfile for now).InstallationThe simplest way to install the package is viaeasy_installorpip:$ easy_install pyliftoverUsageThe primary usage example, supported by the library is the following:from pyliftover import LiftOver
lo = LiftOver('hg17', 'hg18')
lo.convert_coordinate('chr1', 1000000)The first line will automatically download the hg17-to-hg18 coordinate conversionchain filefrom UCSC,
unless it is already cached or available in the current directory. Alternatively, you may provide your own chain file:lo = LiftOver('hg17ToHg18.over.chain.gz')
lo.convert_coordinate('chr1', 1000000, '-')The result oflo.convert_coordinatecall is eitherNone(if the source chromosome name is unrecognized) or a list of target positions in the
new assembly. The list may be empty (locus is deleted in the new assembly), have a single element (locus matched uniquely), or, in principle,
have multiple elements (although this is probably a rare occasion for most default intra-species genomic conversions).
Note that coordinates in the tool are 0-based. That is, a position that you would refer to in the genome browser bychr1:10corresponds to coordinate9in PyLiftover’s terms.Although you may try to apply the tool with arbitrary chain files, like the originalliftOvertool, it makes most sense for conversion of
coordinates between different assemblies of the same species.See alsoBlog post:http://fouryears.eu/2013/02/25/the-curse-of-genomic-coordinates/Report issues and submit fixes at Github:https://github.com/konstantint/pyliftover
Package: pylifx
A Python library to control and monitor LIFX bulbs. Also provides a workaround
for users having issues with controlling LIFX bulbs on their network.GitHub:https://github.com/derkarnold/pylifxPyPi:https://pypi.python.org/pypi/pylifxOriginally written to allow the LIFX bulb to work in non-standard networks, but
it is growing to be much more.Contributors: Deryck Arnold, Michael Farrell (micolous)Huge thanks to Kevin Bowman(magicmonkey) and others for the lifxjs project on GitHub:https://github.com/magicmonkey/lifxjs/Without their work on the lifxjs project, this one would not have been possible.Current features:Allows the LIFX bulb smartphone app to work by “faking” a bulb and relaying
commands to the real one (see examples/bridge.py).Gives the ability to display the contents of LIFX messages coming through.
** Huge thanks to magicmonkey and the lifxjs project for their hard work on
working out the LIFX protocol.The ability to run “scenes” - provide a dictionary of times and colours and
the library will do the rest (see examples/sunrise.py).Upcoming features:Auto-discovery of bulbs (yes, should have been there already).Support for more than one bulb per bridge (waiting on another bulb to arrive).How to install:Get Python (tested with 2.7, others may work). I use the Python(x, y) distribution.Ensure you have the Python setuptools.Run “easy_install pylifx” from a command prompt or terminal.You’re done.Two common issues with installing:Linux users - ensure you have python-dev installed (for the netifaces package).Windows users - install the pre-built binaries for your python distribution
using the links in the following URL:http://alastairs-place.net/projects/netifaces/(The section is just above the start of the Changelog section).
Package: pylifxtiles
PYLIFXTILESREAD THIS FIRSTThis library is currently in alpha state and should not be used for production installations.
Support is not offered at this time, but GITHUB issues are welcome if bugs or potential feature
enhancements are found.##DescriptionThis is a sample python language binding for the LIFX Tiles products.InstallationProduct should be on pip. Can also be installed directly using the typical ways.pip install -r requirements.txt
Package: pylighthouse
pylighthouseHelps workloads find safe harbor.Free software: Apache Software License 2.0Documentation:https://pylighthouse.readthedocs.io.FeaturesScheduling-as-a-library, in pure pythonSchedule workloads onto nodesFlexible definition of requirements needed by workloads and resources offered
by nodesTag nodes simply by adding a zero-quantity resource“Taints and Tolerations”-like behavior supported through the use of
Wards and ImmunititesAnti-affinity-group-like behavior supported through the use of
Aversion GroupsCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.ChangelogAll notable changes to this project will be documented here.The format is based onKeep a Changelogand this project adheres toSemantic Versioning.UnreleasedAddedChangedFixedv0.1.0AddedNode classWorkload classDistributor base classPrioritizedDistributor classRoundRobinDistributor classBinPackDistributor classdistributor classes have a method calledattempt_attach_workloads,
the primary use case of this libraryChangedFixed