Saravanan666/pypi-org huggingface dataset:
Package: mibexx-gym-minesweeper
[GYM] Minesweeper EnvironmentA simple minesweeper environment for gym.GoalGoal is to reveal all fields without a mine.InstallPIPpip install mibexx-gym-minesweeperSourcepip install -e .Initializeimportgymenv=gym.make('mibexx_gym_minesweeper:mibexx-gym-minesweeper-v0')env.reset()EnvironmentStateObservation space:  (9, 9)Low: -2High: 8[[0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0]]ValuesValueDescription-2Mine-1Empty field, no mine near0Not revealed1Revealed, 1 mine near2Revealed, 2 mines near3Revealed, 3 mines near4Revealed, 4 mines near5Revealed, 5 mines near6Revealed, 6 mines near7Revealed, 7 mines near8Revealed, 8 mines nearActionsAction space:  [9 9]Action is a (y,x) tuple.Example for row 3 col 2:state,reward,done,_=env.step((3,2))Rewardswin match: 10empty field: 1already clicked field: -1a mine: -10
Package: mib-generator
MIB GeneratorA set of python scripts that create a SCOS 2000[^1] MIB database from inputted C-header files. It includes basic abilities for 1. parsing of C syntax, 2. interpreting it along the lines of expected structure of monitoring and telecommunication packet declarations and 3. creating corresponding MIB databases.The code is hosted onGithuband releases are published onPyPI.For instruction on installation/building and usage or more general information about the project see the documentation hosted onRead The Docs(in pdf).[^1]: Satellite Mission Control System developed by the European Space Agency.
Package: mibi-bin-tools
mibi-bin-toolsCI / CDPackageMetaToolbox for extracting tiff images from MIBIScope.binfiles.We suggest usingtoffyfor more in depth.binfile extraction which also provides more diagnostic tools and post-extraction processing steps.Installation:You can install the package in your own Python environment, or if you'd like we have a Conda environment set up to use.condaenvcreate-fenvironment.ymlPyPIpipinstallmibi-bin-toolsSourceOpen terminal and navigate to where you want the code stored.Then input the command:gitclonehttps://github.com/angelolab/mibi-bin-tools.gitcdmibi-bin-tools
pipinstall.DevelopmentThis project is in early development and we make may make breaking changes and improvements. If you want to update the version on your computer to have the latest changes, perform the following steps.First pull to get the latest version ofmibi-bin-tools. Then install the package in editable mode with your python environment of choice activated.gitpull
pipinstall-e.To run the testspytestQuestions?If that doesn't answer your question, you can open anissue. Before opening, please double-check and see that someone else hasn't opened an issue for your question already.
Package: mibig-taxa
taxa-pyMIBiG taxonomy handling python bindingsThis package is designed to help MIBiG-related python code to handle NCBI taxid lookups usingNCBI taxdump data.This package contains the python bindings for theMIBiG taxa-rspackage to manage a local JSON-based cache of interesting taxa, allowing bulk database imports to speed up compared to parsing directly from the taxdump files.InstallationTo install taxa-py, run the following (assuming you are in a python virtualenv):pip install mibig-taxaUsageTo create a cache file, first grab thelatest taxdump collectionand extract it. You'll also need a directory containing the MIBiG BGC entry JSON files.Then run the following:frommibig_taxaimportTaxonCachecache=TaxonCache()cache.initialise(taxdump="path/to/taxa/rankedlineage.dmp",merged_id_dump="path/to/taxa/merged.dmp",datadir="path/to/mibig-json/data")# Save the cache to a file for later usecache.save("my_cache.json")If you want to use the cache in a different process, simply load the cache like this:frommibig_taxaimportTaxonCachecache=TaxonCache("my_cache.json")# Or, if you prefer the longer formcache=TaxonCache()cache.load("my_cache.json")To get an ID mapping, usefrommibig_taxaimportTaxonCachecache=TaxonCache("my_cache.json")id_to_map=123456name=get_name_by_id(id_to_map)print(f"Taxon with ID{id_to_map}is called{name}")If you want to transparently support deprecated IDs, also set theallow_deprecatedargument toTrue:frommibig_taxaimportTaxonCachecache=TaxonCache("my_cache.json")deprecated_id_to_map=123456name=get_name_by_id(deprecated_id_to_map,allow_deprecated=True)print(f"Taxon with deprecated ID{deprecated_id_to_map}is called{name}")To get the mapping to an antiSMASH--taxonvalue, use:frommibig_taxaimportTaxonCachecache=TaxonCache("my_cache.json")tax_id=123456as_taxon=cache.get_antismash_taxon(tax_id)print(f"For antiSMASH, use --taxon{as_taxon}with tax_id{tax_id}")You can also grab individual entries directly:frommibig_taxaimportTaxonCachecache=TaxonCache("my_cache.json")tax_id=123456entry=cache.get(tax_id)# "class" is a reserved keyword in python, can't use it directlyentry_class=getattr(entry,"class")print(f"{entry.superkingdom}>{entry.kingdom}>{entry.phylum}>{entry_class}>{entry.order}>{entry.family}>{entry.name}")LicenseLicensed under the Apache License, Version 2.0
(LICENSEorhttp://www.apache.org/licenses/LICENSE-2.0)ContributionUnless you explicitly state otherwise, any contribution intentionally submitted
for inclusion in the work by you, as defined in the Apache-2.0 license, shall be
licensed as Apache-2.0, without any additional terms or conditions.
Package: miblepy
miblepy ·miblepyfetches data from various (Xiaomi/Mijia/Mi) Bluetooth LE devices and push it to a MQTT broker. For every device supported, there are already libraries or anything else to fetch the data from - and they work perfectly. But as they are separated and often run as distinct (cron)jobs, which are not aware of each other, or even as daemons... the fight for the BLE interface starts...miblepysolves this by acting as a "coordinator" to fetch the data in a controlled, sequential way.Currently this is a private project tailored to my needs - but open for PRsUsagemiblepyis available aspippackage andDocker image.Installvia pippipinstallmiblepymanualclone this repo & cd to itgitclonehttps://github.com/benleb/miblepy.git&&cdmiblepyinstall viapoetrypoetryinstallpippipinstall.ConfigurationCopymible.tomlto~/.mible.tomland adjust settings to your needs.~/.mible.tomlis the default location wheremibleexpects your configuration. You can change this via--config.RunStart a single round of fetching from your configured sensors in~/.mible.tomlmiblefetchtrymible --helpto get more info.To continously fetch data from your sensors check out the systemdtimerandservice. You can also use a classic cronjob or even an automation provided by your smart home system (home assistant for example)DockerThe:latesttag is built from master, other tags can be found onDocker HubMount your miblepy config to/miblepy/mible.tomldockerrun--privileged--volume"mible.toml:/miblepy/mible.toml:ro"benleb/miblepySupported devicesVegTrug / Mi Flora plant sensors (Flower Care)(Xiaomi?) Mijia Bluetooth Temperature Humidity sensors with LCD (LYWSD03MMC)(Xiaomi?) Mi Body Composition Scale 2 (XMTZC05HM / XMTZC02HM)Support a new deviceTODOCheck the already available plugins to see some examples.Thanks to@ChristianKuehnel|plantgwmiblepy's idea is based on his plantgw project@open-homeautomation|mifloraLibrary to interact with FlowerCare/MiFlora devices@JsBergbau|MiTemperature2Library to interact with Mi Bluetooth LCD Thermometers@lolouk44|xiaomi_mi_scaleLibrary to interact with Mi Body Composition Scale 2
Package: mibplugin
MIBPluginIntroductionMibPlugin is a standalone package that enables on the fly MIB compilation from a MIB format to a .py MIB file.RequirementsSoftwarePython >= 3.7PySNMP >= 5.0.2Operating SystemWindows 10 ( Other versions are not tested yet)Manjaro (Arch Linux)Other Linux Distributions are not tested.Installationpython-mpipinstallMIbPluginCHANGES0.0.1Added the MIB loader.Added on-the-fly MIB compiler and integrated it with the MIB loader.3-Clause BSD LicenseCopyright 2021 BSD LicenseRedistribution 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.Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.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.
Package: mic
Model Insertion Checker (MIC)Model Insertion Checker (MIC) is a command line wizard for users to add new calibrated models and their metadata.MIC is an application that asks the information of your model, model version, model configuration, parameters, inputs, outputs, authors and contributors.MIC has been tested in OSX and Linux. Windows is not currently supported. It is installed through a simple pip command.pip install micPlease report any issuehere.Full documentation available at:https://mic-cli.readthedocs.io/en/latest/FeaturesCreate a new model/model configuration entry including: Author, Contributors, Model Version, Model Configuration, Parameters, Inputs and Outputs.Save model metadata as a fileSubmit model metadata to the Model Catalog Server (you must have an account)Initializing a component making sure it is consistent with its metadataTesting that a component can be executed with local data.Upload a valid component to GitHubHelp initializing a Docker image for capturing the dependencies of a componentHelp building a Docker imageTest a Docker image with a componentSupport uploading a tested Docker image to DockerHubNext FeaturesAutomatically capture the invocation command of your model componentAutomatic creation of the Docker image needed to execute your modelAdvanced guidance to select parameters and inputs to expose in a model component.
Package: micado-parser
MiCADO ParserThe MiCADO component responsible for parsing and validating ADTsHistorically part of theMiCADO TOSCASubmitter, now a standalone library and command-line tool used inside MiCADO and on its own for validating single-file (YAML) and multi-file (CSAR) ADTs.DependenciesThe MiCADO Parser uses the following packages:TOSCA Parserruamel.yamlClickInstallationInstall the latest version of the MiCADO Parser from PyPI.pipinstallmicado-parseror from GitHub.gitclonehttps://github.com/micado-scale/micado-parser
pipinstallmicado-parser/.UsageCommand-lineFor some helpful tips, use the--helpoptionmicadoparser--helpTo validate an ADT, simply point at an ADT.micadoparser/home/ubuntu/adts/nginx.yamlMulti-file ADTs in .csar format are also supportedmicadoparser/home/ubuntu/adts/wordpress.csarThe tool can handle multiple files.micadoparser~/adts/nginx.yaml~/adts/wordpress.csarOr an entire directory.micadoparser~/adts/*For verbose output use the-voption (for even more verbosity use-vvor-vvv).micadoparser-v~/adts/nginx.yamlLibraryThe primary function of the MiCADO Parser is to return a validatedToscaTemplateobject.To use it in your own project, simply import theset_templatefunction and pass it the path to your ADT. You can optionally pass a dictionary of TOSCA inputs, if inputs are defined in your ADT.frommicadoparserimportset_templatetpl=set_template("/home/ubuntu/adts/nginx.yaml")tpl_with_params=set_template("home/ubuntu/adts/wordpress.csar",{"username":"jay","token":"ABD992LOKAL"})To use the package for validation only, use theset_templatefunction and catch theMultiErrorexception.frommicadoparserimportset_template,MultiErrortry:set_template("/home/ubuntu/adts/nginx.yaml")exceptMultiErrorase:print(e)Comparison with the OpenStack TOSCA ParserThe MiCADO Parser adds a few features compared to the upstream TOSCA Parser.MiCADO-specific validationsMiCADO-specific CSAR handlingInput resolutionSupport for some TOSCA v1.3 features
Package: micawber
A small library for extracting rich content from urls.what does it do?micawber supplies a few methods for retrieving rich metadata about a variety of
links, such as links to youtube videos.  micawber also provides functions for
parsing blocks of text and html and replacing links to videos with rich embedded
content.exampleshere is a quick example:importmicawber# load up rules for some default providers, such as youtube and flickrproviders=micawber.bootstrap_basic()providers.request('http://www.youtube.com/watch?v=54XHDUOHuzU')# returns the following dictionary:{'author_name':'pascalbrax','author_url':u'http://www.youtube.com/user/pascalbrax''height':344,'html':u'<iframe width="459" height="344" src="http://www.youtube.com/embed/54XHDUOHuzU?fs=1&feature=oembed" frameborder="0" allowfullscreen></iframe>','provider_name':'YouTube','provider_url':'http://www.youtube.com/','title':'Future Crew - Second Reality demo - HD','type':u'video','thumbnail_height':360,'thumbnail_url':u'http://i2.ytimg.com/vi/54XHDUOHuzU/hqdefault.jpg','thumbnail_width':480,'url':'http://www.youtube.com/watch?v=54XHDUOHuzU','width':459,'version':'1.0',}providers.parse_text('this is a test:\nhttp://www.youtube.com/watch?v=54XHDUOHuzU')# returns the following string:thisisatest:<iframewidth="459"height="344"src="http://www.youtube.com/embed/54XHDUOHuzU?fs=1&feature=oembed"frameborder="0"allowfullscreen></iframe>providers.parse_html('<p>http://www.youtube.com/watch?v=54XHDUOHuzU</p>')# returns the following html:<p><iframewidth="459"height="344"src="http://www.youtube.com/embed/54XHDUOHuzU?fs=1&amp;feature=oembed"frameborder="0"allowfullscreen="allowfullscreen"></iframe></p>
Package: micca
micca (MICrobial Community Analysis) is a software pipeline for the
processing of amplicon sequencing data,from raw sequencestoOTU tables,taxonomy classificationandphylogenetic treeinference. The pipeline can be applied to a range of highly conserved
genes/spacers, such as16S rRNA gene,Internal Transcribed
Spacer (ITS)18Sand28S rRNA. micca is an open-source, GPLv3-licensed
software.HomepageDocumentation (latest)IssuesGithub pageKey features:supportssingle-end(Roche 454, Illumina MiSeq/HiSeq ,Ion
Torrent) andoverlapping paired-endreads (Illumina MiSeq/HiSeq);multithreadde novo greedy, closed-reference, open-reference and swarm OTU
picking protocols;denoisingof Illumina reads;state-of-the-art taxonomic classificationalgorithms (RDP and
consensus-based classifier);fast and and memory efficientNASTmultiple sequence alignment (MSA);filters low quality sequences according to the maximum allowedexpected
error (EE) rate%;runs onLinux,Mac OS XandMS Windows(through Docker
containers)simple, easy to use.Dockerimages are available (compmetagen/micca) starting from version 1.2.2,
see the documentation (>=1.3.0) to learn how to use them.Docker hub page.How to cite: Davide Albanese, Paolo Fontana, Carlotta De Filippo, Duccio
Cavalieri and Claudio Donati.MICCA: a complete and accurate software for
taxonomic profiling of metagenomic data. Scientific Reports 5, Article number:
9743 (2015), doi:10.1038/srep09743,Link. Dataset download:ftp://ftp.fmach.it/metagenomics/micca/scirep/.micca wraps third party software packages and theseshould be
citedif they are used:VSEARCH (doi: 10.7717/peerj.2584) used inclassify,filter,mergepairs,otuandmsacommandsMUSCLE (doi: 10.1093/nar/gkh340) used inmsaandtreecommandsFastTree (doi: 10.1371/journal.pone.0009490) used in thetreecommandCutadapt (doi: 10.14806/ej.17.1.200) used in thetrimcommandRDP classifier (doi: 10.1128/AEM.00062-07) used in theclassifycommandswarm (doi: 10.7717/peerj.1420) used in theotucommand
Package: mice
Multi-iteration Stochastic EstimatorTheMulti-Iteration stochastiC Estimator(MICE) is an estimator of gradients to be used in stochastic optimization. It uses control variates to build a hierarchy of iterations, adaptively sampling to keep the statistical variance below tolerance in an optimal fashion, cost-wise. The tolerance on the statistical error decreases proportionally to the square of the gradient norm, thus, SGD-MICE converges linearly in strongly convex L-smooth functions.This python implementation of MICE is able toestimate expectations or finite sums of gradients of functions;choose the optimal sample sizes in order to minimize the sampling cost;build a hierarchy of iterations that minimizes the total work;use a resampling technique to compute the gradient norm, thus enforcing stability;define a tolerance on the norm of the gradient estimate or a maximum number of evaluations as a stopping criterion.Using MICEUsing MICE is as simple as>>> import numpy as np
>>> from mice import MICE
>>>
>>>
>>> def gradient(x, thts):
>>>     return x - thts
>>>
>>>
>>> def sampler(n):
>>>     return np.random.random((n, 1))
>>>
>>>
>>> df = MICE(gradient , sampler=sampler)
>>> x = 10
>>> for i in range(10):
...    grad = df(x)
...    x = x - gradHowever, it is flexible enough to tackle more complex problems.
For more information on how to use MICE and examples, check thedocumentation.
Package: miceapi
miceapi - Multi-Mouse APIA module for abstracting linux devices and making multiple simultaneous mice/pointer handling easier.For the purpose of creating the structures that support this abstraction, a program using this module has to have access to the files at/dev/inputand to Shared Memory manipulation. Please make sure both these requirements are met when running your program (Or just run it with superuser permissions withsudo).This project was built and is maintained by a single person, thus, it hasn't been thoroughly tested (except for very basic use cases), so please report any issues and suggestions to itsGitHub repository.Python module Documentation (At GitHub repo Wiki)
Package: miceless
MiceLessUtitlity that helps binding keyboard shortcuts for some of the operations that you do with mouse.UsecasePrimary usecase that this tool was written for is switching focus between windows on different monitors.
In some cases, e.g. multiple desktops, simpleAlt-TABwont help,
because it would either switch you to latest used app or would require you to press this combo several times,
until you reach target window. With this tool you can configure shortcuts so that, for example,Ctrl-Alt-1would
set window in left monitor in focus andCtrl+Alt+2would set focus for window in right monitor.InstallationVia PIP:pipinstallmicelessTo run the app, execute:python3-mmiceless.runManualMiceLess stores a mapping between key-combos and sequences of mouse clicks.
App config would be stored in home folder in.micelessfile.
The app should work anywhere wherepynputworks, yet it has been tested only on Ubuntu with X server.ModesThe tool has two operation modes:recordingandplayback. You can switch between modes by pressingCtrl+Alt+~.RecordingWhile inrecordingmode,Ctrl-Alt-<key>combo wouldappendclick in current mouse location to the list
of events for a given combo. Pressing special combinationCtrl+Alt+0would clear events list for last used key combo.PlaybackIn playback mode pressingCtrl+Alt+<key>combo would invoke a sequence of events stored for that combination.Known issuesPlayback clicks are executed withCtrl+Altpressed, because all combos have these keys in them.
This might be a problem for some applications.There might be collisions with app-specific hotkeys that would result in not desired firings of event sequences.Events capture is based onpynputwhich in turn usesXlib, thus there might be issues in non-X environments,
e.g. in Wayland.
Package: michaelPanExpediteLib
加速数组循环库(Accelerated array loop library)1. 简介(abstract)由于python语言的自身特性，导致其在循环上的效率很低，因此得采取一定措施提升速度。本库依托于numba库，加速数组循环的同时完成求差、和、均值等功能，目的是避免重复编写加速代码。
Due to the characteristics of the python language, its efficiency in the loop is very low, so some measures must be taken to improve the speed. This library relies on numba library to accelerate the array cycle while completing the difference, sum, mean and other functions, the purpose is to avoid repeated writing of acceleration code.2. 使用说明(Use Method)install the lib: pip install michaelPanExpediteLibimportnumpyasnpfrommichaelPanExpediteLib.expedite_array_circulationimportcirculation_arrayarr1=np.array([[1,2,3],[4,5,6],[7,8,9]])arr2=np.array([[1,2,3],[4,5,6],[7,8,9]])temp_array=np.ones((3,3))temp_array_num=np.zeros((3,3))x_dim=3y_dim=3# circulation_array(data1, data2, temp_array, y_dim, x_dim, data_fill, method, temp_array_num=None)temp_array,temp_array_num=circulation_array(arr1,arr2,temp_array,y_dim,x_dim,1,'add',temp_array_num)3.作者及联系方式# ***************************************************************
# Maintainers:
#     chuntong pan <panzhang1314@gmail.com>
# Date:
#     2023.8
# ***************************************************************
Package: michaelPanLogLib
Log function library1.IntroductionHello user, I am the author of this library. We often deal with logs in daily programming, although writing logs is not too difficult, but this library aims to make it easier to complete the various functions of the log2.Use method# pip install michaelPanLogLib"""from michaelPanLogLib,logs import AllKindLoga_log = AllKindLog()a_log.write_log_file(f"D:/pycharm_project/michaelPanLogLib/test1.yml","hello world")  # Write a content to log filea_log.write_log_file(f"D:/pycharm_project/michaelPanLogLib/test1.yml", "hi world")a_log.find_log_file(f"D:/pycharm_project/michaelPanLogLib/test1.yml", "world")  # Find every log that contains "hello"a_log.clear_log_file(f"D:/pycharm_project/michaelPanLogLib/test1.yml")  # clear the log filea_log.delete_file(f"D:/pycharm_project/michaelPanLogLib/test1.yml")  # delete the log file"""3.Contact information# ***************************************************************# Maintainers:#     chuntong pan <panzhang1314@gmail.com># Date:#     2023.11# ***************************************************************
Package: michaelPanPrintLib
Changing the console output style library1.IntroductionHello user, I am the author of this library. Are you still troubled by boring programming, are you used to the colorless black and white console output, are you still at a loss for which part of the code has a bug, using this library can perfectly solve these problems . This library relies on the colorama library and datetime library. When printing the information to be output, it will automatically add the name of the running file and the number of lines of code in front, and change the output color at the same time.2.Use method# pip install michaelPanPrintLib"""########change print########from michaelPanPrintLib.change_print import print_with_style# normalprint_with_style('what you want to output', color=color='red')  # color also have black,white,magenta,green,etc# circulationfor i in range(6):if i != 5:print_with_style(f"hello world | {i}", color='cyan', flush=True)else:print_with_style(f"hello world | {i}", color='cyan', flush=True, switch_line=True)print_with_style(f"hello world | {6}", color='cyan')#########check and install lib#########from michaelPanPrintLib.install_lib import check_and_install_libcheck_and_install_lib(['torch', 'numpy'])  # check torch and numpy lib, it will auto install if not exist"""3.Contact information# ***************************************************************# Maintainers:#     chuntong pan <panzhang1314@gmail.com># Date:#     2023.11# ***************************************************************