Saravanan666/pypi-org huggingface dataset:
Package: mikatools
MikatoolsMikatools provides fast and easy methods for common Python coding tasks.
Some functionality:script_path()gives the location of the current Python scriptjson_dump(data, file_path)saves a dictionary in UTF-8 in a pretty format with indentation, real unicode characters (no unreadable escaped letters) and sorts the keys.json_load(file_path)loads json with UTF-8 encodingdownload_file(url, path, show_progress=False)downloads a file and saves it on the diskopen_read(file, password=None, salt=""")opens a UTF-8 file for reading and optionally decrypts itopen_write(file, password=None, salt="")opens a UTF-8 file for writing and optionally encrypts itSuper easy multitasking!Read the wiki for moreThe library mostly provides functionality for my other libraries.Cite:@software{mika_hamalainen_2020_3977549,
  author       = {Mika Hämäläinen},
  title        = {mikahama/mikatools 1.0.0},
  month        = aug,
  year         = 2020,
  publisher    = {Zenodo},
  version      = {1.0.0},
  doi          = {10.5281/zenodo.3977549},
  url          = {https://doi.org/10.5281/zenodo.3977549}
}Need for NLP solutions for your business?My company,Rootroo offers consulting related to multilingual NLP tasks. We have a strong academic background in the state-of-the-art AI solutions for every NLP need. Just contact us, we won't bite.
Package: mikeapted-myconstruct
Welcome to your CDK TypeScript Construct Library project!You should explore the contents of this project. It demonstrates a CDK Construct Library that includes a construct (MyConstruct)
which contains an Amazon SQS queue that is subscribed to an Amazon SNS topic.The construct defines an interface (MyConstructProps) to configure the visibility timeout of the queue.Useful commandsnpm run buildcompile typescript to jsnpm run watchwatch for changes and compilenpm run testperform the jest unit tests
Package: mike-brady
# Repo Blueprinter## Overview
The goal of this project is to provide an easy way to create a “repo blueprint template” from which developers can build their own projects. You can create placeholders in the template and populate the values when the new repo is created.## Features
* Uses the [jinja2](http://jinja.pocoo.org/) template engine for easy and powerful templates
* Limit templated files to specific file types
* Template filenames and folders## Why not just fork?
Forking is great if you want to potentially merge back with the main project. In this case, we want to provide developers with a basic blueprint, let them fill in their own values, but they won’t be merging back into the main project.## Installation$ pip install repo-blueprint## Usage
Package: mikecore
MIKE Core for PythonA project to facilitate use of the MIKE Core components with Python, targeting Windows as
well as Linux.The MIKE Core Python classes have an API which is almost identical to the MIKE Core .NET API, to the extend possible.
Since Python does not support all the language constructions that .NET/C# does (as e.g. method overriding),
the API's are not completely identical. Also, the number of classes in the Python version is also smaller,
since Python classes can be formed while being used. However, the examples and documentation for the
.NET/C# API is to a high degree applicable also for the use of MIKE Core Python. For details, visit:MIKE for Developers/MIKE CoreThis library is the foundation forMIKE IO.Installationpip install mikecore
Package: mikeio
MIKE IO: input/output of MIKE files in PythonRead, write and manipulate dfs0, dfs1, dfs2, dfs3, dfsu and mesh files.MIKE IO facilitates common data processing workflows forMIKE files in Python.RequirementsWindows or Linux operating systemPython x64 3.8 - 3.12(Windows)VC++ redistributables(already installed if you have MIKE)More info about dependenciesInstallationFrom PyPI:pip install mikeioOr development version:pip install https://github.com/DHI/mikeio/archive/main.zip:warning:Don't use conda to install MIKE IO!, the version on conda is outdated.Getting startedThe material from the last Academy by DHI course is available here:Getting started with Dfs files in Python using MIKE IOWhere can I get help?Documentation -https://dhi.github.io/mikeio/General help, new ideas and feature requests -GitHub DiscussionsBugs -GitHub IssuesTestedMIKE IO is tested extensively.See detailed test coverage report below:---------- coverage: platform linux, python 3.11.1-final-0 -----------
Name                              Stmts   Miss  Cover
-----------------------------------------------------
mikeio/__init__.py                   38      2    95%
mikeio/base.py                       26      5    81%
mikeio/data_utils.py                111      5    95%
mikeio/dataarray.py                 992    152    85%
mikeio/dataset.py                   772    100    87%
mikeio/dfs0.py                      299     24    92%
mikeio/dfs1.py                       67      3    96%
mikeio/dfs2.py                      188      8    96%
mikeio/dfs3.py                      186     26    86%
mikeio/dfs.py                       288     36    88%
mikeio/dfsu/__init__.py               3      0   100%
mikeio/dfsu/dfsu.py                 592     56    91%
mikeio/dfsu/factory.py               41      2    95%
mikeio/dfsu/layered.py              180     20    89%
mikeio/dfsu/spectral.py             127      6    95%
mikeio/dfsutil.py                   129     15    88%
mikeio/eum.py                      1324     12    99%
mikeio/exceptions.py                 25      8    68%
mikeio/generic.py                   433     16    96%
mikeio/interpolation.py              60      5    92%
mikeio/pfs/__init__.py                4      0   100%
mikeio/pfs/pfsdocument.py           242     16    93%
mikeio/pfs/pfssection.py            220      9    96%
mikeio/spatial/FM_geometry.py      1118    102    91%
mikeio/spatial/FM_utils.py          293     30    90%
mikeio/spatial/__init__.py            0      0   100%
mikeio/spatial/crs.py                50      4    92%
mikeio/spatial/geometry.py           90     33    63%
mikeio/spatial/grid_geometry.py     558     42    92%
mikeio/spatial/utils.py              38      0   100%
mikeio/spectral.py                   90      5    94%
mikeio/track.py                     100     14    86%
mikeio/xyz.py                        12      0   100%
-----------------------------------------------------
TOTAL                              8696    756    91%

=========== 697 passed, 3 warnings in 46.01s ========Cloud enabledIt is possible to run MIKE IO in your favorite cloud notebook environment e.g.Deepnote,Google Colab, etc...
Package: mikeio1d
MIKE IO 1D: Read MIKE 1D in pythonRead res1d and xns11 files.For other MIKE files (Dfs0, Dfs1, Dfs2, Dfsu,...) use the related packageMIKE IORequirementsWindows operating system (Support for Linux is experimental)Python x64 3.6, 3.7 or 3.8VC++ redistributables(already installed if you have MIKE)InstallationFrom PyPI:pip install mikeio1dOr development version:pip install https://github.com/DHI/mikeio1d/archive/main.zipFor MIKE IO 1D to work .NET runtime environment (version 3.1 and above) is needed. On Linux operating systems this is not available per default. For example, on Ubuntu distribution to get .NET 7.0 runtime call:sudo apt install dotnet-runtime-7.0Where can I get help?New ideas and feature requests -GitHub DiscussionsBugs -GitHub IssuesGeneral help, FAQ -Stackoverflow with the tagmikeioExamplesRead Res1D file Return Pandas DataFrame>>>frommikeio1d.res1dimportRes1D,QueryDataReach>>>df=Res1D(filename).read()>>>query=QueryDataReach("WaterLevel","104l1",34.4131)>>>df=res1d.read(query)For more Res1D examples see thisnotebookRead Xns11 file Return Pandas DataFrame>>>importmatplotlib.pyplotasplt>>>frommikeio1dimportxns11>>># Query the geometry of chainage 58.68 of topoid1 at reach1>>>q1=xns11.QueryData('topoid1','reach1',58.68)>>># Query the geometry of all chainages of topoid1 at reach2>>>q2=xns11.QueryData('topoid1','reach2')>>># Query the geometry of all chainages of topoid2>>>q3=xns11.QueryData('topoid2')>>># Combine the queries in a list>>>queries=[q1,q2,q3]>>># The returned geometry object is a pandas DataFrame>>>geometry=xns11.read('xsections.xns11',queries)>>># Plot geometry of chainage 58.68 of topoid1 at reach1>>>plt.plot(geometry['x topoid1 reach1 58.68'],geometry['z topoid1 reach1 58.68'])>>>plt.xlabel('Horizontal [meter]')>>>plt.ylabel('Elevation [meter]')
Package: mikelint
MikelintYet another attempt at a static analysis tool for CSSE1001.PrerequisiteYou need Python 3.9 or above to run this project. Python 3.8 or below will not work.Setting upClone this repogit clone https://github.com/mike-fam/mikelint.gitcd into the repo and create a new virtual environmentcdmikelint
python3.9-mvenvvenv&&sourcevenv/bin/activateInstall the required packagespipinstall-rrequirements.txtHow to use the linterCreate a config YAML file, an example of a config file is atconfig.example.yaml.
The key-values of the YAML file go from Criteria > Sub-criteria > Analyser/checker.Runpython run.py -c config.yaml -s some_file.py, withconfig.yamlbeing your
configuration file andsome_file.pybeing the file to run the analyser on.How to contributeIf you want to contribute, DM me on Facebook or email me atmikepham1207@gmail.com.
I'll give you editor access to the repo.Then, clone this repo and make a new branch, and write your implementation on that
branch. Make a new pull request when you're ready. You'll be asked to go through a
checklist before opening the PR.Once I approve the PR, you can merge it to the main branch.Check out the documentation in thedocsdirectory for more implementation details.
Package: mikemazzi
2022_assignment1_users_dbGruppoMichele Angelo Marcucci851905m.marcucci1@campus.unimib.itDavide Mazzitelli851657d.mazzitelli5@campus.unimib.itProgettoLink GitLab:https://gitlab.com/mik3sw/2022_assignment1_users_dbQuick startQuesta applicazione gesisce un database di utenti, raccogliendo informazioni come nome, email, password, genere, età ecc...
In particolare è composta da due modulipackage/database.pyche gestisce la creazione e l'accesso e le modifiche al database;package/functions.pyche gestisce l'output delle query;package/csvdata.pyche serve a fini di test su grandi quantità di dati;Le librerie utilizzate sono già all'interno del pacchetto python e non è necessario installarlesqlite3osPipelinestages:
  - build
  - verify
  - testing
  - package
  - upload
  - productionBuild: al momento non servono dipendenze particolari per il funzionamento del software, usa sqlite3 già integrata in Python;Verify: usaprospectorebanditper analizzare il codice all'interno della cartella./package(jobs paralleli);verifyProspectorverifyBanditTesting: usapytestper effettuare unit e integration tests, valutati separatamente e in parallelo;unitTestintegTestPackage: usasetup.pyewheelper creare il pacchetto da distribuire;Release: usatwineper eseguire l'upload del pacchetto appena creato;Deploy: fase di doploy su macchina virtuale (AWS) scarichiamo il pacchetto e lo usiamo in un file python di test per controllare l'output corretto
Package: mikenye-pyizone
pyizoneThis python module aims to implement query and control of WiFi-enabled iZone 310 and compatible family of climate control devices.Installing pre-requisitesClone the repository, change into the directory and runpip install -r requirements.txt.It will require python3, and has been tested with version 3.5 and later.Using as a command line toolYou can import this module to use it as a command line tool.You could also set an alias, for example:aliasizone='python3 -m pyizone'View help$ python3 -m pyizone
usage: izone [-h] [--verbose] {discover,get,set} ...

Control a control-bridge equipped iZone airconditioning system

optional arguments:
  -h, --help          show this help message and exit
  --verbose, -v

Available subcommands:
  {discover,get,set}Discover devices$ python3 -m pyizone discover
Found 1 iZone Controls-Bridge:
  Device ID: 000000XXX (at: xxx.xxx.xxx.xxx:xxxxx)
Run 'export IZONE_DEVICE=xxx.xxx.xxx.xxx' to automatically target this controls-bridge for all future izone commands.$ export IZONE_DEVICE=xxx.xxx.xxx.xxxQuerying settings$ python3 -m pyizone get fan
xxx.xxx.xxx.xxx: System fan is: low$ python3 -m pyizone get mode
xxx.xxx.xxx.xxx: System mode is: ventSetting settings$ python3 -m pyizone set power on
xxx.xxx.xxx.xxx: System power is: on$ python3 -m pyizone set mode vent
xxx.xxx.xxx.xxx: System mode is: vent$ python3 -m pyizone set fan low
xxx.xxx.xxx.xxx: System fan is: lowUsing as a Python Module>>>importpyizone>>>pyizone.discover()[{'port':'xxxx','id':'000000XXX','ipaddr':'xxx.xxx.xxx.xxx'}]>>>pyizone.get_system_settings("xxx.xxx.xxx.xxx"){'Temp':'0.0','Setpoint':'22.0','NoOfConst':1,'UnitType':'Unknown','CtrlZone':13,'ACError':'','EcoMax':'26.0','SysOn':'on','Tag2':'','AirStreamDeviceUId':'000000XXX','Id':0,'Supply':'0.0','Warnings':'filter','Tag1':'iZone 310','SleepTimer':0,'UnitLocked':'false','AirflowLock':'off','EcoMin':'22.0','SysType':'310','NoOfZones':7,'SysFan':'low','DeviceType':'ASH','RAS':'master','SysMode':'vent','EcoLock':'true'}Getting HelpDocstringsEach function has docstrings, so you can get help using python'shelp()function, for example:>>>help(pyizone.discover)Returns:Help on function discover in module pyizone.__pyizone__:

discover(discovery_timeout_seconds:float=5.0, socket_timeout_seconds:float=1.0, izone_cb_id=None) -> list
    Attempts discovery of iZone 1.x Controls Bridges (CB)

    Args:
        discovery_timeout_seconds: (float) Number of seconds to wait for CBs to respond after sending discovery datagram
        socket_timeout_seconds: (float) Socket timeout in number of seconds
        izone_cb_id: (str) Look for a specific id only, and return as soon as it is found

    Returns:
        A list of dict objects containing the id (str), ipaddr (str) and port (str) of each CB discovered, eg:
        [{'ipaddr': '192.168.0.9', 'id': '000002323', 'port': '12107'}]Open an issuePlease feel free toopen an issue on the project's GitHub, and I'll do my best to help you.I also have aDiscord channel, feel free tojoinand converse.
Package: mikePlotLib
# mikePlotLib## OverviewA collection of plotting / coloring tools I've been using here and there. Finally I'm putting them into one place.One safe place.## InstallationShould be as simple aspip install mikePlotLib## SineBow - turn values into colours### create an rgb sinebow that spans a portion of the color wheel between 0 and 100 with 1000 stepsfrom mikeplotlib.sineBow import SineBowSB = SineBow(100, mapType='rgb')### get the rgb tuple for value=57.1SB.makeColor(57.1)                       # (0, 245, 9)### get it as a #hex stringSB.makeColor(57.1, hexFormat=True)       # #00f509### get 25 colours evenly spaced over the regioncols = SB.getNColors(25)## StackedbarGraph - code for making purdy stacked bar graphs### Example usage 1from stackedBarGraph import StackedBarGrapher()SBG = StackedBarGrapher()SBG.demo()### Example usage 2import numpy as npfrom matplotlib import pyplot as pltfrom stackedBarGraph import StackedBarGrapherSBG = StackedBarGrapher()d = np.array([[101.,0.,0.,0.,0.,0.,0.],[92.,3.,0.,4.,5.,6.,0.],[56.,7.,8.,9.,23.,4.,5.],[81.,2.,4.,5.,32.,33.,4.],[0.,45.,2.,3.,45.,67.,8.],[99.,5.,0.,0.,0.,43.,56.]])d_widths = [.5,1.,3.,2.,1.,2.]d_labels = ["fred","julie","sam","peter","rob","baz"]d_colors = ['#2166ac', '#fee090', '#fdbb84', '#fc8d59', '#e34a33', '#b30000', '#777777']fig = plt.figure()ax = fig.add_subplot(111)SBG.stackedBarPlot(ax,d,d_colors,xLabels=d_labels,yTicks=7,widths=d_widths,scale=True)plt.title("Scaled bars with set widths")fig.subplots_adjust(bottom=0.4)plt.tight_layout()plt.show()plt.close(fig)del fig## cbCols - Easy access to the colorbrewer2.org maps### Example usage 1 - see all available coloursfrom cb2cols import Cb2Cols as CB2cb2 = CB2()cb2.demo()### Example usage 2 - the first three colours from qualset1from cb2cols import Cb2Cols as CB2cb2 = CB2()col_set = "qualSet1"colours = cb2.maps[col_set].values()[0:3]## HelpIf you experience any problems using mikePlotLib, open an [issue](https://github.com/minillinim/mikePlotLib/issues) on GitHub and tell us about it.## Licence and referencingProject home page, info on the source tree, documentation, issues and how to contribute, see http://github.com/minillinim/mikePlotLibThis software is currently unpublished## CopyrightCopyright (c) 2014 Michael Imelfort. See LICENSE.txt for further details.
Package: mikeracingf1
MikeRacingF1 PackageTheMikeRacingF1package is a Python package that provides a simple and easy-to-use interface to the F1Stats API. The F1Stats API provides data about Formula 1 races, circuits, constructors, drivers, and more.Installationpipinstallmikeracingf1UsageTo use the MikeRacingF1 package, you first need to import the MikeRacingF1 class:fromMikeRacingF1importMikeRacingF1You can then create a new instance of the MikeRacingF1 class, which provides methods for accessing the F1Stats API:f1stats=MikeRacingF1()The MikeRacingF1 class provides the following methods:get_circuits(year):Returns information about F1 circuits for the given year.get_constructor_results(year):Returns results for F1 constructors for the given year.get_constructor_list():Returns a list of F1 constructors.get_constructorstandings():Returns standings for F1 constructors.get_driversinfo(year):Returns information about F1 drivers for the given year.get_driverstandings(year):Returns standings for F1 drivers for the given year.get_races(year):Returns information about F1 races for the given year.get_results(year, round):Returns results for an F1 race for the given year and round.Each method sends a GET request to the corresponding endpoint of the F1Stats API, and returns the JSON response as a Python object.Here's an example of how to use the MikeRacingF1 class to retrieve information about F1 races and circuits:fromMikeRacingF1importMikeRacingF1f1stats=MikeRacingF1()# Retrieve information about F1 circuits for the year 2023circuits=f1stats.get_circuits(2023)print("Circuits:")print(circuits)print()# Retrieve information about F1 races for the year 2023races=f1stats.get_races(2023)print("Races:")print(races)print()This code creates a new instance of the MikeRacingF1 class, and calls its get_circuits and get_races methods with the year 2023. It then prints the JSON responses from the F1Stats API.License
This package is licensed under the MIT License. See the LICENSE file for details.
Package: mikes-toolbox
ToolboxToolbox is a Python package that contains handy functions.
It's main goal, however, is to demonstrate how to create
a package and demonstrate how to upload it to PyPi.Check outthisarticle for a detailed explanation on how to create your
custom Python package and upload it to PyPi!Installation and updatingUse the package managerpipto install Toolbox like below.
Rerun this command to check for and install  updates .pipinstallgit+https://github.com/Muls/toolboxUsageFeatures:functions.listChunker  --> generator that chunks and interable in evenly sized chunksfunctions.weirdCase    --> converts a string to a totally unreadable formatfunctions.report      --> prints to the console with a timestampdecorators.singleton  --> used for decoratint your class to make it a singletonDemo of some of the features:importmikes_toolboxfrommikes_toolboximportreportmessage=mikes_toolbox.functions.weirdCase("The mikes_toolbox package is ready for use")report(message)list_of_numbers=[1,2,3,4,5,6,7,8,9,10,11]forchunkinmikes_toolbox.functions.listChunker(lst=list_of_numbers,dsize=3):print(chunk)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.LicenseMIT
Package: mikla
A command line tool to edit text files encrypted with GnuPG while keeping the decrypted plaintext
solely in RAM and off the hard drive. Preventing the plaintext from being recovered. This is
achieved using the POSIX shared memory API. If you have no available memory, Mikla will not work.Currently, only works inPython 3.5.InstallationYou can installMiklausing pip:$pipinstallmiklaUsageUse themiklacommand to run Mikla:$ mikla --help

Usage:
  mikla [--editor=<editor>] [--tmpfs=<path>] <encrypted-file>
  mikla (-h | --help | --version)

Options:
  --version                   show program's version number and exit.
  -h, --help                  show this help message and exit.
  -e, --editor=<editor>       specify the editor to use [default: $EDITOR].
  -t, --tmpfs=<path>          the path to a temporary file system [default: /dev/shm].LicenseCopyright © 2015Matt Deacalion Stevens, released under TheMIT License.
Package: miko-analyzer
Miko-Analyzerコードで占う巫女。
Miko using code to perform divinition.An analysis plugin forDeep Potentialbased chemical research.Supporting simple calculation workflow with the help ofDPDispatcher.InstallationTo install, clone the repository:git clone https://github.com/cloudac7/miko-analyzer.gitand then install withpip:cd miko-analyzer
pip install .
Package: mikoto-py
Mikoto.pyWarning: Mikoto.py is still in early development and is not ready for production use.Mikoto.py is the official Python library for interacting with the Mikoto API.ExampleimportmikotoMIKOTO_TOKEN='<bot token>'bot=mikoto.MikotoClient()@bot.messages.on_createasyncdefmessaging(msg:mikoto.Message):ifmsg.content=="!ping":awaitbot.messages.send(msg.channelId,"pong!")@bot.client.readyasyncdefready():# fires when the bot has fully connected to the APIprint('Ready!')bot.login(MIKOTO_TOKEN)
Package: mik-py
Downloading this python package will also download the Eicar file as part of the python packagehttps://www.eicar.org/download-anti-malware-testfile/.The Eicar file is a file used widely to test anti-malware software against malware and viruses. The Eicar file downloaded as part of this package is not malware but most anti-malware solutions will detect the Eicar file as malware or a virus and will trigger an alert. Please use this package with caution. This python package was created for testing purposes. Please use with caution as it will trigger alerts.
Package: mikro-napari
mikro-naparimikro napari enables napari on the mikro/arkitekt platformDEVELOPMENTIdeaThis is a napari plugin, that provides a simple user interface to use napari with mikro you can view and annotate
data on the mikro platform (synchronised between all of your napari instances) and use napari within arkitekt workflows
(can be extended with other plugins)InstallSimple install this plugin via naparis plugin-manager and enable it.
Login with your local mikro/arkitekt platform and start using it in workflowsYou can also install mikro-napari directly in your enviromentpipinstallmikro-naparinapari[pyqt5]