Saravanan666/pypi-org huggingface dataset:
Package: combilog-handler
CombiLog-PythonHandlerPython package containing custom log handler to integrate with CombiLogInstallation$ pip install combilog-handlerUsage GuideExample usageimport logging
import combilog_handler

# Points to the Websocket Server Url hosted in the Combilog Aggregator.
url = "ws://AGG_DOMAIN:AGG_SOCKET_PORT"

# Secret of the service registered in the Combilog Dashboard
secret = "MY-SPECIAL-SECRET"

logger = logging.Logger("NamedService")
handler = combilog_handler.loghandler.CombilogHandler(aggregator_url=url, service_secret=secret)
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
handler.setFormatter(formatter)
logger.addHandler(handler)
Package: combinadics
combinadicsCombinatorial system of degree k ranking and unranking is a standalone simple (not necessarily the most efficient) module to compute the combinadics of a natural number (a.k.a unranking) and the inverse operation (a.k.a ranking)Code is a commented python implementation ofJames McCaffrey' conceptsofGenerating combinations through generating combination successors.Calculating an arbitrary mathematical combination from a given lexicographical index (unranking) and, not explicit in McCaffrey' article,Given a combination, calculate its lexicographical index (ranking).Note that in the original article the author claims that the combinations he
presents are in lexicographic order, which is not true. However, both his
discussion and code are correct.InstallationpipinstallcombinadicsUsefromcombinadicsimportChoose,Combinationcombinations=Choose(5,3)print("Choose(5,3) results in{}combinations".format(combinations))combination=Combination(5,3)print("Combination(5, 3) is initially{}".format(Combination(5,3)))print("The lexicographic successor of combination{}is{}".format(combination,combination.Successor()))print("Now we set the combination data to be {0 3 4}")combination.data=[0,3,4]print("The lexicographic successor of combination{}is{}".format(combination,combination.Successor()))combination=Combination(5,3,[2,3,4])print("The rank of combination{}is{}".format(combination,combination.Rank()))combination=Combination(5,3)position=3print("In position{}we find combination{}".format(position,combination.Element(position)))outputsChoose(5,3) results in 10 combinations
Combination(5, 3) is initially {0 1 2}
The lexicographic successor of combination {0 1 2} is {0 1 3}
Now we set the combination data to be {0 3 4}
The lexicographic successor of combination {0 3 4} is {1 2 3}
The rank of combination {2 3 4} is 9
In position 3 we find combination {0 2 3}
Package: combination-py
combination_pyPython package for combination calculationInstallationUse the package managerpipto install combination_py.pipinstallcombination-pyUsageimportcombination# combination.Combination(n_max, mod=10**9+7)comb=combination.Combination(10**6)# comb.nCr(n, r)comb.nCr(10,5)# return 252# comb.nPr(n, r)comb.nPr(10,5)# return 30240# comb.nHr(n, r)comb.nHr(10,5)# return 2002# 上昇階乗冪 n * (n + 1) * ... * (n + r - 1)# comb.rising_factorial(n, r)comb.rising_factorial(10,5)# return 240240# 第1種スターリング数# n要素をk個の巡回列に分割する場合の数# comb.stirling_first(n, k)comb.stirling_first(10,5)# return 269325# 第2種スターリング数# n要素を区別のないkグループに分割する場合の数# comb.stirling_second(n, k)comb.stirling_second(10,5)# return 42525# n要素を区別のあるkグループに分割する場合の数# comb.balls_and_boxes_3(n, k)comb.balls_and_boxes_3(10,5)# return 5103000# ベルヌーイ数# comb.bernoulli(n)comb.bernoulli(10)# return 348484851# n要素をk個の空でない順序付き集合に分割する場合の数# comb.lah(n, k)comb.lah(10,5)# return 3810240# n要素をkグループ以下に分割する場合の数# comb.bell(n, k)comb.bell(10,5)# return 86472ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseApache License 2.0
Package: combinatorial-tests-agragland
Combinatorial Testing PackageThis package allows a user to input a list ofnfactors andklevels with a coverage strength valuetto
create an optimal suite of tests that can be run.Test Suite GenerationTo import the package once installed, use:import comb_testingThis package contains two types of algorithms designed to generate test suites. One uses a greedy method, while the other uses a weighted method.Greedy AlgorithmOnce imported, the greedy algorithm function is called using:comb_testing.greedy_algorithm(<list>, <strength>, <flag>)Where<list>is theNxklist of factors and levels and<strength>is thetvalueThe<flag>value allows the user to select between two different algorithms for suite generation.The first, whereflag == 1is an algorithm which is optimized for a larger covering array (one that exceeds more than 5 levels and/or 5 factors).The second, whereflag == 2is an algorithm optimized for speed but is only fast with a smaller sized covering array.The first algorithm is designed to be more traditionally greedy, but due to usage of random generation, final test suites can vary in size.The second algorithm takes a more "back-to-front" approach by first generating all possible candidate rows and generating a suite based on
how many tuples the top-most row can generate over time.Biased AlgorithmA secondary algorithm which will generate a test suite through usage of a "benefit list" is available as well and can be called ascomb_testing.biased_algorithm(<main_list>, <benefit_list>, <exclusions>)One note about this algorithm is that it can only support pairwise (2-way) coverage.The structure<main_list>is similar to that of<list>as described above. It is anNxklist of factors and levels.The<benefit_list>structure is alsoNxksize, but instead of unique values, the values are replaced with weights
or "benefit" values associated with the corresponding element in the<main_list>.NOTE: If user intends to use<benefit_list>with covering array generation as dicussed below, a matching array with benefit values must be coded in place.
Creating a function which will do this process automatically with a range of benefit values will be added in the futureFinally,<exclusions>allows the user to enter a list of pairwise tuples to exclude from the final test suite. For example, if a
user wants to exclude the pair (2, 4) from the final suite, then the<exclusions>list would be[(2,4)]and so on for more than one pair.Covering Array GenerationIf there is no predetermined list, this package features a function to generate a covering array based on a regex stringThe function can be called using:comb_testing.generate_covering_array("<regex>")The value of<regex>will be a string with the following format:"<N>^<k> <N>^<k> ..."An example of this function to generate a covering array with 4 factors and 3 levels would be:covering_arr = comb_testing.generate_covering_array("3^4")In this example, the result is stored incovering_arrand can be iterated over like any other list
Package: combine
CombineBuild a straightforward marketing or documentation website with the power ofJinja.
No fancy JavaScript here — this is just like the good old days.Put your site into the "content" directory and Combine will:Render files using JinjaCreate pretty URLs ("file-system routing")Inject variablesRun custom build steps (like building Tailwind)Most sites follow a simple pattern.Create abase.template.html:<!DOCTYPE html><htmllang="en"><head><metacharset="UTF-8"><metaname="viewport"content="width=device-width, initial-scale=1.0"><title>My site</title></head><body>{%blockcontent%}{%endblock%}</body></html>And use it (ex.pricing.html):{%extends"base.template.html"%}{%blockcontent%}<divclass="pricing"><divclass="flex">...</div></div>{%endblock%}In the end, you get a static HTML site that can be deployed almost anywhere.
Package: combineArrays
combineArraysThis package provides Python CFFI bindings to combine NumPy arrays in C++. Functions are:replicate_arrayscalc_distancecentroid_auxDocumentationUser ManualInstallationTo install type:$pipinstallcombineArraysUsage of replicate_arrays( a, y, length_a, n)fromcombineArraysimportreplicate_arraysParametersInput parameters:a: array to be replicated, floatn:  num replications, int64Output parameters:y: replicated array of length n_times * length_array, floatUsage of calc_distance( a_x_u, a_y_u, b_x, b_y, dist, num_u, num_b)fromcombineArraysimportcalc_distanceParametersInput parameters:a_x_u, a_y_u: arrays of length num_u, floatb_x, b_y: arrays of length num_b, floatOutput parameters:dist: array of size U*B of pairwise distances arranged as [d_u1b1, d_u1b2, d_u2b1, d_u2b2, d_u3b1, d_u3b2], floatUsage of centroid_aux( a_demand, ov_allocation_u_b, a_coordinate_u, coo_b)fromcombineArraysimportcentroid_auxParametersInput parameters:demand: array of length num_u, floatallocation: array of length num_u * num_b, floatcoordinate: array of length num_u, floatOutput parameters:coo_b : array of length num_b, floatTestTo unit test type:$test/test.py
Package: combined-config
combined_configA Python library for stitching multiple configuration sources together in order or priority.The intention of this library is to provide a type,CombinedConfig, that represents all of the
configuration options for a Python project in a format conversant with Python'sconfigparserandargparsemodules. ACombinedConfiginstance
represents an ordering in which ingested configuration values should be searched, and optional
default values for configuration values that have not been provided. ACombinedConfigis
instantiated with one or moreConfigVarinstances, which present fields corresponding to those
provided toargparse.ArgumentParser.add_argument.CombinedConfigimportconfigparserfromcombined_configimportCombinedConfig,ConfigVarmy_config=CombinedConfig(ConfigVar(name="arg_with_default",shortname="a",default="my default"),ConfigVar(name="switch",action="store_true",default=False,help="Turns on the frobnicator"),ConfigVar(name="no_default",type=int),)# You can create a `ArgumentParser` from the `CombinedConfig`.parser=my_config.make_parser()parsed=parser.parse_args(["-a","other value","--no-default","10","--switch"])# Appending a config gives it lower priority than those already added.my_config.append(parsed)print(my_config.values.arg_with_default)# => other valueprint(my_config.values.no_default)# => 10print(my_config.values.switch)# => Trueconfig_parser=ConfigParser()config_parser.read({"my_section":{"no_default":35}})# Example contents of "some-other-conf.ini"# [my_section]# no_default = 35# Prepending a config gives it higher priority than those already added.my_config.prepend(config_parser["my_section"])print(my_config.values.no_default)# => 35# We can also add dictionaries.my_config.prepend({"arg_with_default":"another other value"})print(my_config.values.arg_with_default)# => another other valueFileBackedConfigMixinCommonly, you'll want to be able to easily read and write the configuration from/to file. This can
be done with a subclass ofCombinedConfigthat also subclassesFileBackedConfigMixin.fromcombined_configimportCombinedConfig,ConfigVar,FileBackedConfigMixinclassMyBackedConfig(CombinedConfig,FileBackedConfigMixin):# Should be a mapping of ini section names to the `ConfigVar` names that will be stored there.# Special value `"__ALL__"` means all keys.ini_section_names={"my_section":"__ALL__"}filename="/tmp/my-config.ini"my_config=MyBackedConfig(ConfigVar(name="arg_with_default",shortname="a",default="my default"),ConfigVar(name="switch",action="store_true",default=False,help="Turns on the frobnicator"),ConfigVar(name="no_default",type=int),)# Load the config from file.my_config.read()my_config.prepend({"switch":True})# Write the config back to file. Only configuration values that differ from their defaults will be# written.my_config.write()
Package: combined-energy-api
Python: Asynchronous client for Combined Energy APIProvides an async Python 3.8+ interface for thehttp://combined.energy/monitoring platform API.Note this API client is reverse engineered from observing requests being madein the web-application. Please report any failures to read data, this is likely
to occur for readings as I am only able to create entries for devices that I
have.InstallationInstall from PyPIpython3-mpipinstallcombined-energy-apiUsageimportasynciofromcombined_energyimportCombinedEnergyfromcombined_energy.helpersimportReadingsIteratorasyncdefmain():"""Example using Combined Energy API client."""asyncwithCombinedEnergy(mobile_or_email="user@example.com",password="YOUR_COMBINED_ENERGY_PASSWORD",installation_id=9999,)ascombined_energy:status=awaitcombined_energy.communication_status()print(status)# To generate a stream of readings use the iterator, this example fetches# data in 5 minute incrementsasyncforreadingsinReadingsIterator(combined_energy,increment=300):print(readings)awaitasyncio.sleep(300)asyncio.run(main())Development EnvironmentYou will need:Python 3.8+poetrypre-commitEnsure pre-commit is installed into your git repository withpre-commit install.
Package: combined-gene-caller
OverviewCombined gene caller for MGnify pipeline, to combine predictions of Prodigal and FragGeneScan.Free software: Apache Software License 2.0Installationpipinstallhttps://github.com/ebi-metagenomics/combined-gene-caller/archive/main.zipUsageTo use the project:combined_gene_caller--help
usage:MGnifygenecallercombiner.Thisscriptwillmergethegenecalledbyprodigalandfraggenescan(inanyorder)[-h]-nNAME[-kMASK][-aPRODIGAL_OUT][-bPRODIGAL_FFN][-cPRODIGAL_FAA][-dFGS_OUT][-eFGS_FFN][-fFGS_FAA][-p{prodigal_fgs,fgs_prodigal}][-v][--version]optionalarguments:-h,--helpshowthishelpmessageandexit-nNAME,--nameNAMEbasename-kMASK,--maskMASKSequencemaskfile-aPRODIGAL_OUT,--prodigal-outPRODIGAL_OUTStatsoutprodigal-bPRODIGAL_FFN,--prodigal-ffnPRODIGAL_FFNStatsffnprodigal-cPRODIGAL_FAA,--prodigal-faaPRODIGAL_FAAStatsfaaprodigal-dFGS_OUT,--fgs-outFGS_OUTStatsoutFGS-eFGS_FFN,--fgs-ffnFGS_FFNStatsffnFGS-fFGS_FAA,--fgs-faaFGS_FAAStatsfaaFGS-p{prodigal_fgs,fgs_prodigal},--caller-priority{prodigal_fgs,fgs_prodigal}Callerpriority.-v,--verboseverboseoutput--versionshowprogram'sversionnumberandexitDevelopmentTo run all the tests run:pytest
Package: combine-harvester
Combine HarvesterCLI tool to logHarvesttimesheets with FZFRequirementsAt least python 3.6 (sorry, I just like f-strings a bit too much)fzfInstallationpip install combine-harvesterEnvironment VariablesTwo variables need to be in your environment to authenticate yourself to Harvest's API.HARVEST_ACCOUNT_IDHARVEST_ACCOUNT_TOKENCreating these tokens can be done throughHarvest's Developer Toolspage.UsageThiswiki pagelists all commands and their usage.> harvest

Usage: harvest [OPTIONS] COMMAND [ARGS]...

  Combine Harvester is a Harvest CLI Tool

Options:
  --help  Show this message and exit.

Commands:
  daily  Get notes from previous work day, to be used during daily standup.
  list   Get time entries from today, or optionally another day.
  log    Log time entry for today, using FZF.DisclaimerThis tool is not an officialHarvesttool, nor am I affiliated to them.
Package: combine-notebooks
combine-notebooks - COMBINE jupyter notebooks in pythonProject OverviewThis repository contains Jupyter notebooks that showcaseCOMBINEstandards and their libraries around one common theme; the repressilator model.The following standards are demonstratedSystems Biology Graphical Notation (SBGN): Used to describe visually biological knowledge.Systems Biology Markup Language (SBML): Used for representing models of biological processes.Simulation Experiment Description Markup Language (SED-ML): Used for encoding experiments. SED-ML allows defining the models to use, the experimental tasks to run, and which results to produce. It is a computer-readable format for representing the models of biological processes.CellML: Used to store and exchange computer-based mathematical models.Synthetic Biology Open Language (SBOL): Used for description and the exchange of synthetic biological parts, devices, and systems.NeuroML: Used for XML based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models.Setup/InstallationTo work with the notebooks create a virtual environment and install the dependencies:mkvirtualenv combine_notebooks --python=python3.10
(combine_notebooks) pip install -e .[development] --upgradeAfter changes ensure code formatting via:./fcode.shTests can be run via pytest and tox. To run all tests use:tox -pTo run individual tests use the following targetsflake8,mypy,py38,py39,py310:tox -e flake8NotebooksTo run the notebooks install a notebook environment:pip install jupyterlabRegister the created virtual environmentcombine_notebooksas jupyter kernel:ipython kernel install --user --name=combine_notebooksOr alternatively install the package in an existing virtual environment to get all the dependencies. I.e.:pip install combine-notebooksStart the notebooks:cd ./notebooks
jupyter lab© 2022 Matthias König & Aditya Singhal
Package: combine-pvalues-discrete
A Python module for combiningpvalues of discrete tests.Install with:pip installcombine-pvalues-discretepip3 installgit+git://github.com/BPSB/combine-p-values-discreteor similar.Install requirements for testing withpip install “.[test]”(or similar). Run the test withpytest(or similar) in the source directory. Runpytest -m “not slow”to exclude some particularly time-consuming tests.DocumentationIssue Tracker– Please use this if you need any help with this module, in particular if you are facing any bugs or require features (in particular support for tests).Contributions are welcome. Feel free to discuss them on the issue tracker or just file a pull request.DOI for citing:10.5281/zenodo.8338798
Package: combine-re-compile
任意组合 re.compile兼容环境Windows/Linux/MacOs1 安装pip 安装$ pip install combine_re_compile源码安装$ git clone https://github.com/landybird/combine_re_compile.git
 $ cd combine_re_compile
 $ python setup.py install2 使用DIGIT_PATTERN=re.compile(r"""(?P<my_digit_pattern>        # start named group\d+                        # 1 or more integers)                            # close named group""",re.VERBOSE)CHAR_PATTERN=re.compile(r"""(?P<my_char_pattern>         # start named group[a-z]                      # a character)                            # close named group""",re.VERBOSE)CHARS_PATTERN=re.compile(r"""(?P<my_char_pattern>         # start named group[a-z]+                     # a character)                            # close named group""",re.VERBOSE)r=CombinationPattern(DIGIT_PATTERN,CHAR_PATTERN,new_pattren_name="my_new_pattern").get_new_patterns="213213as2312"print(r.search(s).group('my_new_pattern'))# 分组名称>>213213aLicenseMIT©landybird
Package: combine-signatures
# combine-signaturesCombine signatures of functions.COPY FROM [jsbueno/terminedia](https://github.com/jsbueno/terminedia/blob/62b1c307e5f276e7eb5d56dacc35a326fb424481/terminedia/utils/__init__.py#L83).[HOW TO USE?](https://stackoverflow.com/questions/34402773/signature-changing-decorator-properly-documenting-additional-argument)
Package: comb-model
comb-model:  A package to simulate Fractional Brownian walks on a comb-like structure.This package simulate trajectories of the comb model via Langevin equations driven by fractional Gaussian noises (long-range correlated).If you have usedcomb-modelin a scientific publication, we would appreciate citations to the following reference[1]:Haroldo V. Ribeiro, Angel A. Tateishi, Luiz G. A. Alves, Rafael S. Zola, Ervin K Lenzi (2014).Investigating the interplay between mechanisms of anomalous diffusion via fractional Brownian walks on a comb-like structure.  New Journal of Physics 16, 093050For more detailed information about the methods functions incomb-model, please
consult itsdocumentation.InstallationThecomb-modelpackage is available on pypi and can be installed using pippipinstallcomb-modelDependenciesnumpystochastictdqmProcessesThis package offers functions to simulate Fractional Brownian walks on a plane or Comb-like structures via via Langevin equations.# Fractional Brownian walks on a planeimportmatplotlib.pyplotaspltfromcombmodelimportlangevin_fbnx,y=langevin_fbn(x0=0,y0=0,betax=1,betay=1,hurstx=0.5,hursty=0.5,tmax=1000,disable_tqdm=True)f,ax=plt.subplots(nrows=1,ncols=1,figsize=(9.1,7))ax.plot(x,y,color='#D62728',markersize=0,linewidth=2)ax.set_xlabel(r'Position, $x(t)$')ax.set_ylabel(r'Position, $y(t)$')# Fractional Brownian walks on a Comb-like structureimportmatplotlib.pyplotaspltfromcombmodelimportcomb_modelx,y=comb_model(x0=0,y0=0,betax=1,betay=1,hurstx=0.5,hursty=0.5,tmax=5000,eps=1,disable_tqdm=True)f,ax=plt.subplots(nrows=1,ncols=1,figsize=(9.1,7))ax.plot(x,y,color='#D62728',markersize=0,linewidth=2)ax.set_xlabel(r'Position, $x(t)$')ax.set_ylabel(r'Position, $y(t)$')References[1]Haroldo V. Ribeiro, Angel A. Tateishi, Luiz G. A. Alves, Rafael S. Zola, Ervin K Lenzi (2014).Investigating the interplay between mechanisms of anomalous diffusion via fractional Brownian walks on a comb-like structure. New Journal of Physics 16, 093050
Package: combocurve-api-helper
combocurve-api-helperA utility library mapped to ComboCurve's API.InstallationInstall from Python package repository:python-mpipinstallcombocurve-api-helperor install directly from GitHub:python-mpipinstallgit+https://github.com/petbox-dev/combocurve-api-helper.git@mainSetupTwo files are required in~/.combocurve:cc-api.config.jsoncombocurve.jsonThese are given by ComboCurve when configuring API access. Example files are provided
in./config-examples/assetsto demonstrate the expected file structures.cc-api.config.example.json:{"apikey":"<apikey>"}combocurve.example.json:{"type":"service_account","project_id":"beta-combocurve","private_key_id":"<private_key_id>","private_key":"<private_key>","client_email":"<client_email>","client_id":"<client_id>","auth_uri":"https://accounts.google.com/o/oauth2/auth","token_uri":"https://oauth2.googleapis.com/token","auth_provider_x509_cert_url":"https://www.googleapis.com/oauth2/v1/certs","client_x509_cert_url":"<client_x509_cert_url>"}AuthorsDavid FulfordLicenseMIT LicenseCopyright (c) 2023 Petroleum Engineering ToolboxPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.