Saravanan666/pypi-org huggingface dataset:
Package: epibox
EpiBOX, the Python packageA Research Tool to Stimulate Collaboration Within Biosignal CollectionEpiBOX was developed as a way to enable researchers to escalate their data collection process by leveraging the human resources available. By providing a versatile, discreet, user-friendly and open-source system, operated through a mobile application, we hope to provide a collaboration tool for the acquisition of biosignals.Designed for use with a Raspberry Pi due to its unobtrusive design (but usable with any Linux device), it acts as an autonomous recording unit - allowing for sensor connectivity and data storage. EpiBOX mobile app provides the user interface and the near-real time visualization of the data.Currently, EpiBOX supports BITalino-based equipments allowing for the recording, storage and visualization of up to 12 channels simmultaneously. Nevertheless, this package can be easily integrated with other sensors, as long as a Python API is provided!RequirementsThis Python package is complementary the mobile app EpiBOX (available atEpiBOX);It also requires a Raspberry Pi set up as a wireless access point and MQTT broker in order to ensure communication between the mobile app and the recording unit (RPi itself or another Linux device).InstallationUse the package managerpipto install epibox.pipinstallepibox
orpipinstall--upgradeepiboxUsage# this will initiate the process - which should be continued by the user interface (EpiBOX app)python-mepiboxFeaturesStep-by-step interactions to start the acquisitionHistory of acquisition devicesDefault configurations for optimized interactionReal-time visualization of up-to 12 channelsIn-acquisition annotationsAdditional ResourcesWhy BITalino:Versatility of sensors & flexibility of wearable form-factorsRapid & cheap prototypingPeer-validated against gold-standardsWhy Raspberry Pi:DiscretenessAffordabilityEase of system replication - through shell script or RPi imagerComputational and storage powerGet to know our project @LinkedIn - PreEpiSeizuresLicenseMITContactFor any additional information about the mobile app or our project please contact me:anascacais@gmail.com=======
History0.1.0 (2021-07-08)First release on PyPI.
Package: epic2cf
# epic2cf#### A simple python library to find the CF standard name equivalent of an EPIC code.[EPIC codes](http://www.epic.noaa.gov/epic/document/epickey.htm)[CF standard names](http://cfconventions.org/Data/cf-standard-names/28/build/cf-standard-name-table.html)## Installation##### Stablepip install epic2cf##### Developmentpip install git+https://github.com/axiom-data-science/epic2cf.git## Usage##### Return contentsA `dict` like object is returned from a call to `get` and contains the following:```python{'cell_methods': None,   # If there are any cell_methods associated with this variable'cf_units': None,       # The units of the CF standard name'convert': None,        # A function to convert values from EPIC to CF'long_name': None,      # A description of the variable'standard_name': None,  # The CF standard_name'units': None           # The EPIC units}```##### Get a CF mapping from an EPIC code```pythonfrom epic2cf import mappingmapping.get(18){'cell_methods': None,'cf_units': 'm','convert': <function epic2cf.data.<lambda>>,'long_name': 'Sea Surface Height','standard_name': 'sea_surface_height','units': 'm'}mapping.get(26){'cell_methods': 'time: minimum','cf_units': 'K','convert': <function epic2cf.data.<lambda>>,'long_name': 'Water Temperature','standard_name': 'sea_water_temperature','units': 'degree_Celsius'}```##### Convert existing EPIC values into CF values###### Pass in a numpy array to the convert function```pythonimport numpy as npfrom epic2cf import mappingepic = mapping.get(9)print epic{'cell_methods': None,'cf_units': 'dbar','convert': <function epic2cf.data.<lambda>>,'long_name': 'Sea Water Pressure','standard_name': 'sea_water_pressure','units': 'mbar'}values = np.random.random(6)print values  # EPIC values in 'mbar'array([ 0.57136167,  0.98046873,  0.64963954,  0.39981203,  0.72433581, 0.16820297])cf_values = epic.convert(values)print cf_values  # CF values in 'dbar'array([ 0.00571362,  0.00980469,  0.0064964 ,  0.00399812,  0.00724336, 0.00168203])```## ContributingNot all EPIC codes have been mapped to CF standard names.  If you requirea mappnig that has not been done you can do one of the following:1.  Create an issue with the EPIC code number you would like mapped and as muchinformation about the variable as possible (how it is used, the units, etc).It may take some time for these to be included in `epic2cf`, especially if wecan not verify a correct mapping to CF.2. Fork the repository and add the mapping yourself into `epic2cf/data.py`.I will accept pull requests for updated mapping very quickly.
Package: epic7-bot
Epic7 BotDisclaimerThis software is an external tool designed to automate playing Epic Seven. It is designed to interact with the game only through existing user interfaces and comply with relevant laws and regulations. The package aims to provide simplified and user-friendly interaction with the game, and it is not intended to disrupt game balance in any way or provide any unfair advantages. The package will not modify any game files or game code in any way.This software is open source, free of charge, and for learning and exchange purposes only. The developer team has the final right to interpret this project. All problems arising from the use of this software are not related to this project and the developer team. If you encounter a merchant using this software to practice on your behalf and charging for it, it may be the cost of equipment and time, etc. The problems and consequences arising from this software have nothing to do with it.RequirementsAndroid Debug BridgePython 3.4+Usageepic7 --help
Usage:
    epic7 <command> [options]

All commands should be run when the game screen is in the lobby!

The most commonly used commands are:
    shop            Start secret shop auto buy
    arena           Start arena npc auto battle
    hunt            Start hunt auto battle
    daily           Start daily actions

Options:
    -h --help       Show this help message and exit
    -v --version    Show version and exitWorkingBluestacks running Epic7 above and Windows Powershell running the epic7-bot shop auto buy below.Getting StartedInstall Python +3.4https://www.python.org/downloads/release/python-392/.Install Chocolateyhttps://chocolatey.org/install#individual.Chocolatey is a package manager for Windows. It is easier to install Android Debug Bridge with it.Install Android Debug Bridge by runningchoco install adbon your terminal as admin.Android Debug Bridge is command-line tool that enable communication with a device. It enables to send inputs directly to the emulator.Install Epic7 Bot by runningpip install epic7-boton your terminal.Enable Android Debug Bridge on your emulator of choice.(Bluestacks is recommended.)Bluestacks: Settings > Advanced > Enable Android Debug Bridge.Nox: Settings > Device > Enable Network Bridge Mode.Future GoalsSecret shop refreshing.Hunt battling.Labyrinth.Automaton Tower.Hunt Expedition.Spirit Altar.Arena NPC battling.All daily actions, like daily summon and pet summon, sanctuary daily rewards, guild donations, etc.GUI development.Create a .exe installer.ContributionsIssue & Report a Bug|Fork & Open a New PRAll kinds of contributions including enhancements, new features, code improvements, issues and bugs reporting are welcome.Themainbranch of Epic7 Bot is the stable version, and all development is done in thedevelopmentbranch. So if you want to open a Pull Request, your commits need to be submitted to thedevelopmentbranch.⭐ If you like it, give it a star~ ⭐ContributorsThanks to the following contributors for their contributions to this project.
Package: epical
InstallationEpicalis coded in Python. It needs Python 3 (version 3.5.x) or a later
version for installation and execution.PrerequisitesPython 3pip3RTensorFlow(Only requires byAltumAge)NoteTensorFlowis not included as a Python
Dependency (refer to the section below) due to its substantial size and
occasional need for specialized installation procedures. Please follow
its providedinstallation instruction. Failure to installTensorFlowwill result
in the unavailability of theAltumAgecommand. If you opted for a Python
virtual environment to install TensorFlow, it is recommend to installEpicalwithin the same virtual environment.Python Dependenciespandasnumpyscipysklearnbx-pythonmatplotlibEpigeneticPacemakerNoteUsers do NOT need to install these packages manually, as they will be
automatically installed if you usepip3.Install Epical# install from PyPI
$ pip3 install epical

# install from github
$ pip3 install git+https://github.com/liguowang/epical.git

# test if *epical* is available and excutable
$ epical --version
epical 0.0.1NoteIf you used Python virtual environment to installTensorFlow, you need to run the
above command in the same virtual environment.UpgradeEpical$ pip3 install epical --upgradeUninstallEpical$ pip3 uninstall epicalRunEpicalPrint out usage and all theavailable clocks$ epical --help
 usage: epical [-h] [-v]
 {Horvath13, Horvath13_shrunk, Horvath18, Levine, ...}
 ...Example: run the “Horvath13” command# print usage of the "Horvath13" command
$ epical Horvath13 --help
...

# run example data
$ epical Horvath13 -m blood_N20_info.tsv -o output blood_N20_MethylationEPIC-v1.0_beta.tsv.gz
2024-01-04 07:52:11 [INFO]  The prefix of output files is set to "output".
2024-01-04 07:52:11 [INFO]  Loading Horvath13 clock data ...
2024-01-04 07:52:11 [INFO]  Clock's name: "Horvath13"
2024-01-04 07:52:11 [INFO]  Clock was trained from: "Pan-tissue"
2024-01-04 07:52:11 [INFO]  Clock's unit: "years"
2024-01-04 07:52:11 [INFO]  Number of CpGs used: 353
...Documentationhttps://epical.readthedocs.io/en/latest/
Package: epic-bitstore
Epic bitstore — Multi-tiered cloud-backed blob storage systemWhat is it?Theepic-bitstorePython library provides client access to a multi-tiered blob storage system based on cloud
backends, with the option to use API backends and caching mechanisms as well.UsageFor example, let's assume you store blobs in the following locations:In an AWS bucket:s3://aws_customer_data/files/<sha1>In a GCP bucket:gs://gcp_customer_data/blobs/<sha1>In another GCP bucket:gs://my_project/more_files/<sha1>Using epic-bitstore, you could fetch a blob from any of these storages using a singlegetcommand. The library would
iterate on the sources in order and would retrieve the data from the first matching source. This could also run in
parallel on multiple blobs, backed by theultimaparallelization library.To implement the above strategy, you create aCompositestore, and add each of your sources in order:fromepic.bitstoreimportSha1Composite,Sha1Store,S3Raw,GSRawblob_store=Sha1Composite()blob_store.append_source(Sha1Store(S3Raw(),"s3://aws_customer_data/files/"))blob_store.append_source(Sha1Store(GSRaw(),"gs://gcp_customer_data/blobs/"))blob_store.append_source(Sha1Store(GSRaw(),"gs://my_project/more_files/"))data=blob_store.get("4bc39c7d87318382feb3cc5a684c767fbd913968")You can then use parallelization to efficiently map an iterator of hashes into an iterator of byte buffers:fromultimaimportultimapdata_iter=ultimap(blob_store.get,iter_hashes,backend='threading',n_workers=16)API sources and caching layersLet's also assume that you have an API that can retrieve blobs given their SHA1.
You would like to use it for fetching blobs, but only when they're not found in the above "passive" sources.You can implement aSha1APISourcefor your API, and add it to theCompositeobject:fromepic.bitstoreimportSha1APISourceclassMyAPIStore(Sha1APISource):def__init__(self,api_client):super().__init__()self.api_client=api_clientdefapi_get(self,sha1):# return None for a blob that can't be foundreturnself.api_client.get_bytes(sha1)# ctd after adding the three passive storesblob_store.append_source(MyAPIStore(my_api_client))API sources are often expensive, either in cost or performance.
You can add a caching store, and configure the API source to store fetched blobs into the cache.
It is important to append the cachebeforeadding the API source, so that its cached blobs have precedence.Append the cache and the API source:fromepic.bitstoreimportSha1Cache,GSRaw# ctd after adding the three passive storesblob_store.append_cache(Sha1Cache(GSRaw(),"gs://cache_for_api/"))blob_store.append_store(MyAPIStore(my_api_client))Now, when you retrieve a missing blob for the first time, the API is used; and after that the cache is used.
Package: epicbot-images
Install$pipinstallepicbot-imagesUsageMemes:fromepicbot_imagesimportmemes# for a discord bot@bot.command()asyncdefdrake(ctx,first,second):awaitctx.reply(file=discord.File(memes.drake(first,second)))# it's so easy to useEffects:fromepicbot_imagesimporteffects@bot.command()asyncdefblur(ctx,user:discord.User):awaitctx.reply(file=discord.File(effects.blur(awaituser.avatar.read())))# 1 line go brrAdvanced Usage (recommended):fromepicbot_imagesimporteffectsfromfunctoolsimportpartial@bot.command()asyncdefwiggle(ctx,user:discord.User):awaitctx.reply(file=discord.File(awaitbot.loop.run_in_executor(None,partial(effects.wiggle,img=awaituser.avatar.read()))))I won't be making docs for these, refer to the source code or ask in the support server if you have any questionsMeme templatesdrake,disappointed,flex_tape,bernie,panik,doge,my_heartEffectsblur,flip,rotate,enhance,ascii,blend,wiggleLinksSupport|Invite EpicBot|Vote EpicBot
Package: epiccli
Epic by Zenotech - Command Line InterfaceEPICis a cloud platform for interfacing with HPC resources. This Python CLI demonstrates thepyepicmodule, which interfaces with the EPIC REST API.InstallationFrom PyPiYou can install the package from PyPi using pip withpip install epiccliDocumentationDocumentation is available onread the docs.UsageTo get started runepic configureand enter your EPIC configuration details. This will generate the configuration file for the program.Runepicto list commands:$ epic
Usage: epic [OPTIONS] COMMAND [ARGS]...

  CLI for communicating with the EPIC

Options:
  --help          Show this message and exit.

Commands:
  cluster    Cluster Management
  configure  Configure the CLI tool
  data       Data Management
  job        Manage your EPIC jobs
  project    Project Management
  team       Team ManagementAboutThe CLI is built usingClickto handle boilerplate and is packaged over pypi.Thepyepicmodule manages interactions with the EPIC REST API.For further documentation, a full API schema is available athttps://epic.zenotech.com/api/docs
Package: epic-common
Epic common — Useful Common UtilitiesWhat is it?Theepic-commonPython library provides many general useful utilities.
These are various functions and classes which are useful and helpful in almost any project and context.
Some save programming time on common tasks, some prevent falling into common pitfalls and some provide
functionality that, after getting used to it, you just can't live without.Modulesassertion:Utilities for assertion of parameter types.flow:Utilities for flow control.general:Many general useful utilities.importguard:Provide an installation hint upon import failure.inspection:Utilities relating to live object inspection.io:Pickling, reading and writing files, loading and dumping JSON files, etc.iteration:Utilities relating to iteration over iterables.nesteddict:Helpers for easily dealing with nested dictionaries.pathgeneralizer:An abstraction providing a common interface to accessing local and remote resources.time:Helpers for timing, setting a timeout and converting timestamps.queue:Provides a convenient iterable queue.
Package: epic-free-games
Epic Free GamesA wrapper for Epic Games Store free gamesAvailable resourcesGet Free GamesInstallation$pipinstallepic-free-gamesUsagefromepic_free_gamesimportEpicGamesepic_games=EpicGames()epic_games.get_free_games()ContributeClone the repository project:$gitclonehttps://github.com/hudsonbrendon/epic-free-gamesMake surePoetryis installed, otherwise:$pipinstall-UpoetryInstall the dependencies:$poetryinstallTo run the tests:$pytestDependenciesPython >=3.10LicenseMIT
Package: epic-jupyter
Epic jupyter — Conveniences for working in Jupyter Notebook or IpythonWhat is it?Theepic-jupyterPython library provides several utilities tailored to run under Jupyter
environments, and to help in writing libraries that adapt nicely to the environment they run in and
its capabilities.Main modulesepic.jupyter.ipythonAllows safe discovery of the current environment.get_ipython()gets the IPython manager if it is availableis_ipython()tells you whether you're in an IPython-based environmentis_jupyter_notebook()tells you specifically whether you're running in a Jupyter kernelepic.jupyter.displayProvides functions related to displaying content.display_if_ipython(...)allows for safe displaying of objects, with optional graceful degradation to printingmarkdown("# hey!")displays preformatted markdown contentside_by_side(...)displays arbitrary objects in a side-by-side table (and also in one-after-the-other columns)epic.jupyter.initializationProvides the functionevent_register_once(event, callback, ...)which registers an IPython event and removes it after
it has triggered for the first time.
This is intended to trigger initialization of internal structures upon some first time event.epic.jupyter.interpolateProvides the IPython magic%interpolateline and cell magic.
This magic is a debug helper: use it to simulate IPython's variable interpolation mechanism and review the results.Load this extension by calling%loadext epic.jupyter.interpolate.You can also load this and all future extenstions by calling%loadext epic.jupyter.epic.jupyter.nbcodeUse the functionuse_notebook_code('path/to/source.py')to start working with "notebook code" files.Notebook code files are python files that are loaded and then reloaded (usingexec) whenever they change.These files should help maintaining separation of concerns. When a significant amount of relatively generic
code is developed for the purposes of a notebook, keeping it in an adjacent file keeps the notebook itself focused
on the research narrative. The automatic reload mechanism in turn frees the user from having to go back and run
random code cells whenever some change is made to the underlying code.Ultimately, any useful code should make its way into a general purpose library.
During that time when its scope is limited to a specific notebook - notebook code files are here for you.
Package: epickledb
BSD 3-Clause LicenseCopyright (c) 2023, Tetsuya Saito, Ph.D.Redistribution 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: epiclean
epicleanThis is the package for the module clean_epigraphia athttps://github.com/ShreyasKolpe/epigraphia-data-cleaning/tree/main/automationFind it on PyPi athttps://pypi.org/project/epiclean/Instructions for Python packaging:https://packaging.python.org/en/latest/Summarizing these instructions:Change source code insrc/directoryMake sure to have the latest build package withpython3 -m pip install --upgrade buildFrom the directory wherepyproject.tomlis located, runpython3 -m buildThe.tar.gzand.whlfiles are generated in thedist/directory. These need to be uploaded to the PyPi distributionFirst, update twine withpython3 -m pip install --upgrade twineThen, runpython3 -m twine upload dist/*When prompted for username and password, use the credentials for logging in to PyPi
Package: epic-mace
MACE: MetAl Complexes EmbeddingMACE is an open source toolkit for the automated screening and discovery of metal complexes. MACE is developed byIvan Chernyshovas part of theEvgeny Pidko Groupin theDepartment of Chemical EngineeringatTU Delft. The main features of the MACE package are to discover all possible configurations for square-planar and octahedral metal complexes, and generate atomic 3D coordinates suitable for quantum-chemical computations. MACE shows high performance for complexes of ligands of high denticity (up to 6), and thus is well-suited for the development of a massive computational pipelines aimed at solving problems of homogeneous catalysis.Installationepic-macerequires Python 3.7 and the 2020.09 version of RDKit for a correct functioning!Earlier versions do not support dative bonds, and in later versions there are significant changes in the embedding and symmetry processing algorithms which are not well compatible with theepic-mace’s underlying algorithms. This noticeably increases number of errors for both stereomer search and 3D embedding.condaWe highly recommend to install MACE via thecondapackage management system. The following commands will create a new conda environment with Python 3.7, RDKit 2020.09, and the latest version ofepic-mace:>condacreate-nmace-crdkitpython=3.7rdkit=2020.09
>condainstall-nmace-cgrimgeniusepic-maceDo not forget to activate the environment before using epic-mace:>condaactivatemacepipepic-macecan be installed via (pip):>pipinstallrdkit
>pipinstallepic-maceHowever, we strongly recommend installation via conda, since the earliest available RDKit version on PyPI is 2022.03 which does not ensure the stable operation ofepic-mace. Though it is enough for demonstrational purposes or automatic documentation generation.In extreme cases, one can install MACE via pip to the conda environment with preinstalled RDKit 2020.09:>condacreate-nmacepython=3.7rdkit=2020.09.1-crdkit
>condaactivatemace
>pipinstallepic-macePlease note, that PyPI epic-mace package does not contain rdkit in the requirements list to avoid possible conflicts between conda and pip RDKit installations. Therefore, you must install RDKit manually beforehand.Main featuresStereomer search for octahedral and square-planar complexes.Generation of 3D atomic coordinates, including instruments for conformer sampling.Modification of ligands with predefined substituents.Generation of geometry of coordinated ligands formolSimplify.Two available interfaces:command-line interface for routine tasks;Python package for organizing complex computational pipelines.Useful linksDocumentationPerformanceCLI examples