Saravanan666/pypi-org huggingface dataset:
Package: mcgill-minerva
minerva=======This is a little python library that makes it easier for McGillstudents to programmatically access information from Minerva. As of thiswriting, it only supports retrieving unofficial transcript information.You need a McGill ID and PIN (or McGill email and password) to accessMinerva. You can pass these in to the `login()` function, or set the`MINERVA_USER` and `MINERVA_PASS` environment variables (you still need to call`login()` if you do this).```python>>> import minerva>>> isbadawi = minerva.login()```This retrieves your unofficial transcript.```python>>> transcript = isbadawi.transcript()>>> import pprint>>> pprint.pprint(transcript.get_courses())[<Course: COMP 531 - Advanced Theory of Computation>,<Course: COMP 547 - Cryptography & Data Security>,... snip ...]```This transcript object can be queried to get courses satisfying certainproperties. You can search by semester, course title, section, grade,average, or number of credits. For instance, this gets all Fall 2009 MATHcourses in which I got an A:```python>>> courses = transcript.get_courses(semester='Fall 2009',subject='MATH', grade='A')>>> pprint.pprint(courses)[<Course: MATH 235 - Algebra 1>,<Course: MATH 318 - Mathematical Logic>]```Some useful bits:```python# What grade did I get in MATH317?>>> transcript.get_courses(subject='MATH317')[0].gradeu'A'``````python# Has the grade for COMP762 been posted yet?>>> transcript.get_courses(subject='COMP762')[0].grade is not NoneFalse```Installation------------To install `minerva`, simply:```bash$ pip install mcgill-minerva```Note that one of the requirements is `lxml`, whose installation is sometimestroublesome because it depends on `libxml` and `libxslt`. For more detailedinstructions regarding this, refer to [the `lxml` website](http://lxml.de/installation.html).
Package: mcglm
Multivariate Covariance Generalized Linear Modelshttps://pypi.org/project/mcglm/The mcglm package brings to python language one of the most powerful extensions to GLMs(Nelder, Wedderburn; 1972), the Multivariate Covariance Generalized Linear Models(Bonat, Jørgensen; 2016).The GLMs have consolidated as a unified statistical model for analyzing non-gaussian independent data throughout the years. Notwithstanding enhancements to Linear Regression Models(Gauss), some key assumptions, such as the independence of components in the response, each element of the target belonging to an exponential dispersion family maintains.MCGLM aims to expand the GLMs by allowing fitting on a wide variety of inner-dependent datasets, such as spatial and longitudinal, and supplant the exponential dispersion family output by second-moment assumptions(Wedderburn; 1974)https://jeancmaia.github.io/posts/tutorial-mcglm/tutorial_mcglm.htmlThe mcglm python package follows the standard pattern of the statsmodels library and aims to be another API on the package. Therefore, Python machine learning practitioners will be very familiar with this new statistical model.To install this package, usepipinstallmcglmTutorial MCGLM instills on the library usage by a wide-variety of examples(https://jeancmaia.github.io/posts/tutorial-mcglm/tutorial_mcglm.html). The following code snippet shows the model fitting for a Gaussian regression analysis.modelresults=MCGLM(endog=y,exog=X).fit()modelresults.summary()
Package: mc-goods
mc-goodsmodel_catalogs catalogs for GOODSProject based on thecookiecutter science project template.How to UseInstallmodel_catalogsand this package of catalogs will be installed too.InstallationIf you need to install these yourself, you can with PyPI:pip install mc-goodsor with conda-forge:conda install -c conda-forge mc-goodsTo add a catalogPlace the new catalog file in the package directory (mc_goods).Add catalog name to__init__following other catalog files.Add catalog tosetup.pyfollowing others.Git commit and push to repo.Reinstall package since entry_points have changed.
Package: mcgpyutils
mcgpyutils(MCG Python Utilities) is a project containing utility classes
commonly used in Python projects atMCG
Strategic.RequirementsPython3, version >= 3.6UsageExample:from mcgpyutils import FileSystemUtils

fsu = FileSystemUtils()
print(fsu.get_path_to_script(__file__))DevelopmentChanges to this package can be tested by putting the path to the root of
this repository in the PYTHONPATH environment variable. PYTHONPATH will
take precedence over the installed package and allow new changes to be
used instead of the version installed via pip. To revert this, remove
the path to the root of this repository from the PYTHONPATH. Here are 2
aliases to make switching easy:# Enable development mode
alias pyutilsdev='export PYTHONPATH="/path/to/mcgpyutils:$PYTHONPATH"'

# Revert to installed package (this assumes there's nothing else in your PYTHONPATH)
alias pyutilsprod='export PYTHONPATH=""'
Package: mcgrep
Authors:Scott Torborg (storborg)Version:0.1A simple tool to grep through memcached. Uses the poorly-documented features outlined in the the 2010 Black Hat presentation by SensePost:http://www.sensepost.com/blog/4873.htmlNoteUse at your own risk!InstallationSimple as:$ easy_install mcgrepOr if you prefer, download the source and then:$ python setup.py build
$ python setup.py installInstalling the package installs both the mcgrep python module and the mcgrep
command-line utility.Licensemcgrep is released under the GNU General Public License (GPL). See the LICENSE file for full text of the license.
Package: mchat
MChatA console chat client for most Minecraft server versions. This project is a combination of@ammaraskar'sPyCraftclient library, and@willmcgugan'srich text libraryfor Python.InstallationFrom PIP# Install PyCraftpython3-mpipinstallhttps://github.com/ammaraskar/pyCraft.git# Install MChatpython3-mpipinstallmchatFrom SourceTo install from source using thePoetrybuild tool andpyenv, clone this repository, then run:pyenvinstall3.9.0
pyenvlocal3.9.0
poetryinstallUsageMChat can be run asmchatif installed from PIP or aspoetry run python3 -m mchatif running from the GIT repo.Usage is as follows:usage: mchat [-h] [-p PORT] [-u USERNAME] [-v VERSION] server_address

A console chat client for most Minecraft server versions

positional arguments:
  server_address        IP address of a Minecraft server

optional arguments:
  -h, --help            show this help message and exit
  -p PORT, --port PORT  Minecraft server port (default: 25565)
  -u USERNAME, --username USERNAME
                        Minecraft username or email
  -v VERSION, --version VERSION
                        Client -> Server protocol version to use (default: 1.16.4)You will be prompted for a username (if not passed as an argument), and password when running the program.FAQAre colors configurable?No. Terminal colors are not directly configurable from this program, as server-sent formatting data is fed directly into the rich text formatter. Your terminal emulator may allow you to customize your pallette though.What Minecraft versions are supported?Anything supported by PyCraft. Entering an invalid version when runningmchatwill tell you what is supported by the version of PyCraft you have installed. For example, this is the result at the time of writing:$mchat-v0.0.0example.com0.0.0isnotavalidMinecraftversion.Versionsfrom1.7.2to20w48aareallowed.You can update PyCraft from PIP to pull in new version support as needed.ScreenshotsDemo on mcctf.com
Package: mchp-flasher-essentials
HB20 Flasher require specific versions of Python packages to run properly. This package install all the necessary packages.How to installpipinstallmchp-flasher-essentialsList of packagescolorama==0.4.4.inputimeout==1.0.4.intelhex==2.3.0.psutil==5.8.0.PyDirectInput==1.0.4.pyelftools==0.27.pywin32==301.termcolor==1.1.0.
Package: mchplnet
mchplnetmchplnet is the Python implementation of the LNet protocol.It implements multiple LNet services to communicate to embedded systems/microcontrollers.Currently only pyserial interface is supported.It is recommended to use the pyx2cscope package, which offers a higher-level interface.Getting StartedNavigate to the Examples directory in the mchplnet project to explore the available examples or create a new .py file based on your requirements.Import the necessary classes:from mchplnet.interfaces.factory import InterfaceFactory
from mchplnet.interfaces.factory import InterfaceType as IType
from mchplnet.lnet import LNetCreate an interface according to your requirements and initialize the LNet with the interface:interface = InterfaceFactory.get_interface(IType.SERIAL, port="COM8", baudrate=115200)
l_net = mchplnet.LNet(interface))Use the appropriate functions, such as get_ram, to interact with variables by specifying their address and size:var_address = 0x00000000
var_size = 4 
var_value = l_net.get_ram(var_address, var_size) 
logging.debug(var_value)To modify the value of a variable, use the put_ram function:var_newValue = 500
l_net.put_ram(var_address, var_size, var_newValue)ContributeIf you discover a bug or have an idea for an improvement, we encourage you to contribute! You can do so by following these steps:Fork the repository.Create a new branch for your changes.Make the necessary changes and commit them.Push your changes to your forked repository.Open a pull request on the main repository, describing your changes.We appreciate your contribution!
Package: mcint
========================Monte Carlo integrator========================This package provides a Monte Carlo integrator which can be used to evaluatemulti-dimensional integrals. The results are numerical approximations which aredependent on the use of random number generation.Example 1=========In this example we compute :math:`\int_0^1 x^2 dx`::import mcintimport randomdef integrand(x): # Describe the function being integratedreturn (x**2)def sampler(): # Describe how Monte Carlo samples are takenwhile True:yield random.random()result, error = mcint.integrate(integrand, sampler(), measure=1.0, n=100)print "The integral of x**2 between 0 and 1 is approximately", resultThe second argument to the integrate() function should be an iterableexpression, in this case it is a generator. We could do away with this samplerusing the following::result, error = mcint.integrate(integrand, iter(random.random, -1), measure=1.0, n=100)This creates an iterable object from the random.random() function which willcontinuously call random.random() until it returns -1 (which it will never do asit returns values between 0.0 and 1.0.Example 2=========In this example we compute :math:`\int_0^1 \int_0^\sqrt{1-y^2} x^2+y^2 dx dy`::import mcintimport randomimport mathdef integrand(x):return (x[0]**2 + x[1]**2)def sampler():while True:y = random.random()x = random.random()if x**2+y**2 <= 1:yield (x,y)result, error = mcint.integrate(integrand, sampler(), measure=math.pi/4)
Package: mciplayer
This package should be built AND installed in WindowsTo build this package, you need:Python>=3.6pybind11 already installed in Python environment.If you just want to install (using wheel), then pybind11 is not required.Example code:frommciplayerimportMCIPlayerplayer=MCIPlayer()# Create a player instance, this will also create a MCI window.player.open('test.wav')# Open the audio fileplayer.play()# Play the audioplayer.wait()# Wait until the audio ends.UTF-8 support has been added.
Package: mcir
Multi-component Inversion Recovery Analysis of Cortical LayersA package for performing multi-component inversion recovery (IR) analysis of microstructural laminar patterns of the cortex.Free software: MIT licenseDocumentation:https://mcir.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.0.1 (2019-11-25)First release on PyPI.
Package: mciwb
mciwbMinecraft Interactive World BuilderThis project is intended as a fun way to learn the Python Programming Language.Experienced Python programmers can also use this library to create
Minecraft worlds with interactive Python features.Sourcehttps://github.com/gilesknap/mciwbPyPIpip install mciwbDocumentationhttps://gilesknap.github.io/mciwbReleaseshttps://github.com/gilesknap/mciwb/releasesQuick StartTo get started learning Python, seeIntroductionFor existing Python developers, seeAPI documentationExample BuildThe pagoda and castle with working portcullis were all created programmatically
with Python and the current version of MCIWB.https://github.com/gilesknap/mciwb/assets/964827/026b3551-f514-403a-bebe-8d168c7170b0GoalsMinecraft Interactive World Builder's goals are:Use Python to create anything inside of Minecraft worlds.Call Python code when events occur inside the world.Use an iPython prompt to interact with the world by typing Python commandsHave your player inside the world execute Python code by placing command
signs or activating switches/levers with Python actions.All instructions on how to set up a Minecraft Server and the Python developer
environment are included. There are step by step tutorials to
introduce Python Programming and the features of Minecraft Interactive World
Builder... note::This is a work in progress. There are now enough tutorials to learn the
fundamentals of Python and enough functionality to have some fun
interacting with Minecraft from Python code.

I will continue to expand the tutorials and add more features to the
library.CreditsThis project would not be possible withoutmcipc,
which provides the client library for Minecraft RCON.Seehttps://gilesknap.github.io/mciwbfor more detailed documentation.
Package: mckit
MCKIT: MCNP model and results processing utilitiesThe mckit package provides a programming framework and command line tools to manipulate complex MCNP models.
When a model is rather complex and its description occupies thousands of text lines it becomes hard to modify it and integrate several model manually.
The package automates integration process.Table of contentsMCKIT: MCNP model and results processing utilitiesUsageCommand line interfaceLibraryInstallationVersioningContributorsUsageCommand line interfaceUsage:mckit[OPTIONS]COMMAND[ARGS]...ToolstoprocessMCNPmodelsandresultsOptions:--override/--no-override--versionShowtheversionandexit.-v,--verboseLogdebugginginfotostderr.[default:False]-q,--quietSuppressinfotostderr.[default:False]--logfile/--no-logfileLogtofile.[default:True]--profile_memProfilepeakmemoryuse.[default:False]--helpShowthismessageandexit.Commands:checkReadMCNPmodel(s)andshowstatisticsandclashes.composeMergeuniversesandenvelopesintoMCNPmodelusingmerge...concatConcattextfiles.decomposeSeparateanMCNPmodeltoenvelopesandfillinguniversessplitSplitsMCNPmodeltotextportions(oppositetoconcat)transformTransformMCNPmodel(s)withoneofspecifiedtransformation.LibraryThe library allows subtraction and merging models, renaming objects (cells, surfaces, compositions, universes),
simplification of cell expressions (removing redundant surfaces), homogenization, computation of cell volumes and
material masses, and more.LOG.info("Loading c-model envelopes")envelopes=load_model(str(CMODEL_ROOT/"c-model.universes/envelopes.i"))cells_to_fill=[11,14,75]cells_to_fill_indexes=[c-1forcincells_to_fill]LOG.info("Attaching bounding boxes to c-model envelopes%s",cells_to_fill)attach_bounding_boxes([envelopes[i]foriincells_to_fill_indexes],tolerance=5.0,chunk_size=1)LOG.info("Backing up original envelopes")envelopes_original=envelopes.copy()antenna_envelop.rename(start_cell=200000,start_surf=200000)LOG.info("Subtracting antenna envelop from c-model envelopes%s",cells_to_fill)envelopes=subtract_model_from_model(envelopes,antenna_envelop,cells_filter=lambdac:cincells_to_fill)LOG.info("Adding antenna envelop to c-model envelopes")envelopes.add_cells(antenna_envelop,name_rule="clash")envelopes_path="envelopes+antenna-envelop.i"envelopes.save(envelopes_path)LOG.info("The model of HFSR in envelopes is saved to%s",envelopes_path)InstallationInstalling from pypi:pip3installmckitInstalling from github.com:pip3installgit+https://github.com/MC-kit/mckit.gitVersioningThis software followsSemantic VersioningContributorsRoman RodionovDmitri Portnov
Package: mckit-nuclides
ContentsDescriptionInstallationExamplesContributingReferencesDescriptionThe module presents basic information on chemical elements and nuclides including natural presence.
The data is organized as Pandas tables.
Pandas allows to use dataset approach on data indexing, joining and selecting.
There are also some tools to work with composition fractions.NoteThe documentation is in progress yet.InstallationExamplesContributingReferencesKim, Sunghwan, Gindulyte, Asta, Zhang, Jian, Thiessen, Paul A. and Bolton, Evan E..
“PubChem Periodic Table and Element pages: improving access to information on chemical
elements from authoritative sources” Chemistry Teacher International, vol. 3, no. 1, 2021, pp. 57-65.https://doi.org/10.1515/cti-2020-0006Elements table.https://pubchem.ncbi.nlm.nih.gov/rest/pug/periodictable/CSVCoursey, J.S., Schwab, D.J., Tsai, J.J., and Dragoset, R.A. (2018-06-14),
Atomic Weights and Isotopic Compositions (version 4.1). [Online]
Available:http://physics.nist.gov/Comp[year, month, day].
National Institute of Standards and Technology, Gaithersburg, MD.
Package: mcl
mcl-pythonmcl-pythonis a Python library that creates bindings formcllibrary byherumi. For now the only supported curve isMCLBN384_256.InstallationThis package requiresmclto be preinstalled.Use the package managerpipto install mcl-python.pipinstallmclUsageimportmclfr=newmcl.Fr()fr.setByCSPRNG()For more examples, please checktests.TestsTests are written inunittest.python3 -m unittest discover tests/ContributingPull 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.LicenseMIT
Package: mclass
mclass: convert python dict to python class objectWhat is it?mclassIt fully converts a python dict to a python class object and all dict keys and internal dict are converted to python class objects as well.# !pip install mclassExamplefrommclassimportDictClassimportpandasaspdimportnumpyasnpobj=DictClass({'id':1,'data':{'name':'John','age':31,'wife':{'name':'Jessica','age':np.nan}}})print(obj.id,obj.data.name,obj.data.wife.name)1 John Jessicaobj{'id': 1, 'data': {'name': 'John', 'age': 31, 'wife': {'name': 'Jessica', 'age': nan}}}
Package: mclauncher
A fully fledged launcher for Minecraft. Made in python, and supports almost all features of the official launcher. Not
tested on Windows.NoteThis package can be installed under both “mclauncher” and “pymclauncher”. The former is the default.DISCLAIMERThis is not a cracked client/launcher!You will be required to authenticate with Microsoft to use this program. If you have not migrated your Mojang account to
Microsoft, you will be required to do so before using this program. If you would like to see the source code for the
backend authentication, you can find ithere.This being said, this program may not check to see if you have a valid account. It may be possible to launch a cracked
client using this program, but it is not recommended (It’s against the terms of Minecraft to do so!). Hacked clients and
modded clients are fine.UsageInstallInstallmclauncherusing your favorite flavor of the pip package manager.pipinstallmclauncherRunningUse the help command to see a list of available commands. Pip should have added themclauncherpackage to
PATH, so you should be able to simply runmclauncherin your terminal.mclauncher-hIf that doesn’t work, a consistent fallback is to runmclauncherusing your favorite flavor of the python command.python-mmclauncher-h
Package: mclbn256
Python library that serves as an API for the BN254/256 pairing-friendly
curve implemented inMClin C.Package Installation and UsageThe package is available onPyPI:pip install mclbn256The library can be imported in the usual ways:import mclbn256  # Abstracted 'dumb' API over the scalar and point groups
from mclbn256 import mclbn256  # Extended attributes, internals, classes, test methodsExamplesThis library supports concise construction of elliptic curve points
(groups G1 and G2) and scalars (group Fr):from mclbn256 import G1, G2, Fr
>>> p = G1().hash("some row")
>>> q = G2().hash("another row")
>>> p.valid()
True
>>> q.valid()
True
>>> s = Fr(6)
>>> t = Fr(857462736753)
>>> ((p * s) @ (q * t)) == (p @ (q * s * t))
True
>>> ((p * s * ~t) @ (q * t)) == (p @ (q * s))
True
>>> ((p * s) @ q) == ((p * ~t) @ (q * s * t))
TrueData structures for the relevant curve subgroups and finite fields are
included as well:>>> len(Fr().randomize().serialize())
32
>>> len(G1().randomize().serialize())
32
>>> len(G2().randomize().serialize())
64
>>> len((G1().randomize() @ G2().randomize()).serialize()) <= 384
TrueThe representation of BN254 points and scalars in this library is compatible with the pure-Pythonbn254implementation thanks toECp_to_G1and the other similarly-named helpers.  We may also convert points in that library’s representation to the minimal-size MClserialformat usingECp_serialize.>>> Q = G1.random(); G1().deserialize(ECp_serialize(G1_to_ECp(Q))) == Q and Q.serialize() == ECp_serialize(G1_to_ECp(Q))
TruePlease see the packageoblivious(which extends this
package) for more examples of how to use the BN254 curve.ContributionsIn order to contribute to the source code, open an issue or submit a
pull request on theGitHub pagefor this library.VersioningBeginning with version 0.1.0, the version number format for this library
and the changes to the library associated with version number increments
conform withSemantic Versioning
2.0.0.Naming NotesBN-256 was an old name for the BarretoNaehrig(2,254) Weierstrass curve,
when it was though to have close to 256 bits of security. It has since
been estimated to have at least 90 bits of security (compared to
symmetric ciphers) and is now more commonly refered to by BN254, after
the number of bits in its prime modulus. Specifically,mclbn256is thenameof the subset of the MCl library containing the support for this
curve.
Package: mcleece
pymcleeceA python wrapper for thelibmcleeceencryption C/C++ library. C++ dependencies (libmcleece, libsodium) are included as a git submodule.git clone --recursive https://github.com/sz3/pymcleece.git
python setup.py build
python setup.py installor with pip:pip install mcleece... linux should work, macOScouldwork, windows is unknown at the moment.Usagefrom mcleece.crypto_box import PrivateKey, PublicKey, SealedBox
sk, pk = PrivateKey.generate()

ebox = SealedBox(pk)
ciphertext = ebox.encrypt(b'helloworld')

dbox = SealedBox(sk)
recoveredtext = dbox.decrypt(ciphertext)
Package: mcli
mcliMarketMaker CLIFree software: MIT licenseDocumentation:https://mcli.readthedocs.io.FeaturesSend commands to MarketMaker RPC API (http://127.0.0.1:7783) with a simplified cli fashion.UsageCheck that the marketmaker is running (on localhost, or via ssh tunnel) before testing thisThis tool require python 2.7 and pip at least to make things easier.Install it with$pipinstallmcliTest if the cli can connect to marketmaker, if you can see lot of commands, it works !$mcli--helpUsage:mcli[OPTIONS]COMMAND[ARGS]...Options:--helpShowthismessageandexit.Commands:autopricebalancebestfitblacklistbalancebuydeletemessagesdisabledividendselectrumenablegetcoingetcoinsgetmessagesgetpeersgetpricesgetrawtransactiongoalinventorylastnoncelistlistunspentmypricenotarizationsorderbookparselogpassphrasepauseportfoliopricearrayrecentswapsresumesecretaddressessellsendmessagesendrawtransactionsetconfirmssetpricesettingssnapshotstatsdispstatusstatusliststopswapstatustrustwithdrawYou can check the usage of every command like this :$mcliorderbook--helpUsage:mcliorderbook[OPTIONS]Options:--baseTEXT--relTEXT--durationTEXT--helpShowthismessageandexit.And then call the method :$mcliorderbook--baseKMD--relMNZ{"base":"KMD","numbids":1,"rel":"MNZ","bids":[{"address":"RVz1cJSqAfgLQcC9KX96Ba6tqmVb6uNmim","maxvolume":3.59287268,"minvolume":0.00147469,"coin":"MNZ","price":9.98495744,"numutxos":416,"depth":230.24036763,"pubkey":"d80a74847cd60899afdd673570f8b698e4089e5ad4d6e9e205b5e5891ec0c84f","age":29}],"asks":[],"timestamp":1515770670,"numasks":0}CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-01-10)First release on PyPI.