Saravanan666/pypi-org huggingface dataset:
Package: diogi
diogiDiog means to laze in Welsh. This package is to help me do less.Most of the functions and decorators included in thediogpackage
could be easily implemented with a single line of obscure python
but then I would have to implement (and test) them again and again.I'd rather not. I'm lazy.Functionsalways_a_list(obj: any) -> listwith aliasaaltakes any object and if it isn't a list already, it wraps it up in one.
It is also available as@always_a_listdecorator.default_if_none(obj: any, default: any) -> any:with aliasdinacts as a null coalescence.first_or_default(lst: list, default: any=None) -> any:with aliasfodreturns the first element of a list
if there is at least one element, or the default value.get_if_exists(obj: any, key: str, default: any=None) -> anywith aliasgie.
attempts to get a property of a dictionary or an attribute of an object, and if it doesn't exist or is None the default value is returned.list_is_optional(obj: any) -> anywith aliasliotakes any object and if it is a list with a single element
then it returns just the element, otherwise the list is returned.
It is also available as@list_is_optionaldecorator.list_without_nones(lst: list) -> listwith aliaslwnreturns copy of the list without any None values.
It is also available as@list_without_nonesdecorator.none_if_empty(obj: any) -> anywith aliasniereturns copy of the object unless it is an empty list or an empty directoryappend_if_not_none(obj: any, value: any, key: str) -> anywith aliasainnget_if_exists(obj: any, key: str) -> anywith aliasgieset_if_not_none(obj: any, value: any, key: str) -> anywith aliassinnConventionsto_datasometimes the object needs to be converted to a simpler data
representation of dicts and lists. In those cases my objects implement
a public methodas_data(self). Thediog.conventions.to_data(obj: any)takes an object or a list of object, and reduces the input to data.To Publishpipenv shell
pipenv install
python setup.py pytest
python setup.py bdist_wheel
Package: dio-image-processing
Creating an Image Processing PackageThis repository was initially intended to solve the code challenge about creating a processing
image package with Python in development of theDIO'sbootcamp "Geração Tech
Unimed-BH - Ciência de Dados".This repository contents a simple example about how to create a package using Python's Setuptools
package and publish it in the Pypi repository.DescriptionThe package image_processing is used to:
Processing:
- Histogram matching
- Structural Similarity
- Resize image
Utils:
- Read image
- Save image
- Plot image
- Plot result
- Plot histogramInstalationUse the package managerpipto install the image_processing
package.pipinstallimage_processingUsagefromimage_processingimportprocessing,utilsAuthorHadir GarciaLicenseMIT
Package: dio-img-processing
dio_img_processingDescription.
The package dio_img_processing is used to:
Processing:
- Histogram matching
- Structural similarity
- Resize image
Utils:
- Read image
- Save image
- Plot image
- Plot result
- Plot histogramInstallationUse the package managerpipto install dio_img_processingpipinstalldio_img_processingAuthorJosimar Gabriel R. de AraújoLicenseMIT
Package: diomindmap
DioMindmapDioMindmap allows you to createDraw.iomind map diagrams in a simple and intuitive way.Given a simple indented text file like this:Root
    First child
        First grandchild
        Second grandchild
    Second child
        First grandchild
        Second grandchildThe following diagram will be generated (in Draw.io compatible XML format):InstallationpipxinstalldiomindmapUsagediomindmapgenerate-i<input_file>-o<output_file>Usediomindmap generate --helpfor more information on command line arguments.Input file formatThe input file is a simple text file that uses indentation to define the hierarchy of the mind map. The indentation
can be either spaces or tabs, but must be consistent throughout the file.The file may contain multiple root nodes, for example:Root 1
    First child
        First grandchild
Root 2
    First childIn this case each root node will be rendered as a separate tab within Draw.io.Implementation detailsThe project structure is managed withProjen.Poetryis used for dependency management (integration with Projen).Typeris used for CLI related functionality.N2Gis used to generate the Draw.io compatible XML file.Maintenance and contributingYou are welcome to contribute to this project, but please note that I will not necessarily have time review and mergepull requests. I created this project to do one simple thing, and it does that well enough for my purposes.I don't currently plan to add any new features. If you would like to take this further, please consider forking the
project.IdeasEven though I don't plan on any new features, the following ideas might be worth considering:Support passing the layout algorithm as an argument.Support directories / glob patterns as input to batch process an entire directory of input files.Write tests.Add GitHub actions to run build the project and publish to PyPi.Is there a way to directly open the generated XML file in Draw.io?LicenseMIT LicenseCopyright (c) [2023] [Anrich van Schalkwyk]Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: dionysus
Dionysus is a computational topology package focused on
persistent homology. It is written in C++, with Python bindings.
The second version (previous version)
is re-written from scratch, which helps it accomplish a few goals:Modified BSD license(because GPL causes too many problems in academic software).No dependency on Boost.Python; Dionysus 2 uses (and includes)PyBind11instead, which greatly simplifies installation.Cleaner, more consistent internal design (for example, all algorithms support arbitrary fields).Some new algorithms, e.g.,omni-field persistenceand Wasserstein and bottleneckdistance computationfromHera.A fewplottingroutines, based onMatplotlib.Better integration withNumPy.Features that haven’t (yet) made it over fromDionysus 1include vineyards.
Alpha shape filtrations are available viaDioDe.Dependencies:Boost, although Dionysus 2 doesn’t link any of its libraries, so it’s considerably easier to build the project.(Optional)SciPyfor the LSQR routine used incircular coordinates.(Optional)Matplotlibfor plotting.Requirements:Boost needs to be at least version 1.55.If you are using GCC, the oldest supported version is 5.4.Contact:please use thedionysus mailing listfor all questions and discussion related to the library;GitHub’sissue trackeris a central location for bug reports and feature requests.Get, Build, InstallThe simplest way to install Dionysus, as a Python package, is fromPyPI:pip install --verbose dionysusPass--upgradetopip, if you have already installed some version of Dionysus.Alternatively, you can install it directly from the development repository (this gives you the latest version):pip install --verbosegit+https://github.com/mrzv/dionysus.gitAlternatively, you can clone and build everything by hand.
To get Dionysus 2, either clone itsrepository:git clonehttps://github.com/mrzv/dionysus.gitor download it as aZip archive.To build the project:mkdir build
cd build
cmake ..
makeTo use the Python bindings, either launch Python from.../build/bindings/pythonor add this directory to yourPYTHONPATHvariable, by adding:export PYTHONPATH=.../build/bindings/python:$PYTHONPATHto your~/.bashrcor~/.zshrc.DocumentationDocumentation for Dionysus can be foundhere.
Package: diophila
diophilaPython API Wrapper forOpenAlex.Entities / EndpointsOpenAlex currently describes five differentscholarly entity typesand their connections:AuthorsConceptsInstitutionsVenuesWorksEach entity type comes with an endpoint of the same name that can be queried
for a single (random or specific) entity or multiple (grouped or listed) entities.Installationpip (or pip3) install diophilaUsageFirst off, you need to initialize a client. The client offers all methods to query the API.fromdiophilaimportOpenAlexopenalex=OpenAlex()You can use the client to query for asingle random entitywith the methodget_random_<entity>:random_author=openalex.get_random_author()random_author['id']Or if you have aspecific entityin mind, you can use the client
using one of the entity's IDs via theget_single_<entity>method:specific_work=openalex.get_single_work("https://doi.org/10.1364/PRJ.433188","doi")specific_work['display_name']If you are interested inentities groupedinto facets,
use theget_groups_of_<entities>method:grouped_institutions=openalex.get_groups_of_institutions("type")forgroupingrouped_institutions['group_by']:group['key']And last but not least you can getmultiple entitiesfrom a type
in a list by using theget_list_of_<entities>method. Note that this method uses pagination,
eitherbasic pagingorcursor pagingdepending on whether thepagesparameter is supplied:# if no `pages` parameter is supplied, we use cursor pagingpages=None# if `pages` parameter is supplied, we use basic pagingpages=[1,2,3]filters={"is_oa":"true","works_count":">15000"}pages_of_venues=openalex.get_list_of_venues(filters=filters,pages=pages)forpageinpages_of_venues:# loop through pagesforvenueinpage['results']:# loop though list of venuesvenue['id']Bonus: If you want to retrieve allworksconnected to another entity,
you may use the entity'sworks_api_urlproperty with theget_works_by_api_urlmethod:works_api_url="https://api.openalex.org/works?filter=author.id:A1969205032"pages_of_works=openalex.get_works_by_api_url(works_api_url)forpageinpages_of_works:forworkinpage['results']:work['display_name']The Polite PoolIt's a good idea to use OpenAlexpolite poolwhich offers faster response times for users providing an email address.
If you would like to use it, simply initialize the client with your email address.fromdiophilaimportOpenAlexopenalex=OpenAlex("your-email@address.com")Rate limitsThe API currently doesn't haverate limits.
However, if you need more than 100,000 calls per day,
please drop the OpenAlex team a line atteam@ourresearch.orgor alternatively look intousing a snapshot.CitationIf you are using OpenAlex in your research,
the OpenAlex team kindly asks you to citehttps://doi.org/10.48550/arXiv.2205.01833
Package: dio-processador-imagens
Pacote de Processamento de imagensDescricao:
Pacote dio_processador_imagens indicado para:
Processamento:
- Correspondencia de histogramas
- Similaridade estrutural
- Redimensionamento de imagensUtils (auxiliares):
- Leitura de imagens
- Salvamento de imagens
- Plot de imagens, resultados e histogramasInstalacaoUtilize o gerenciador de pacotespippara instalar dio_processador_imagensAutoresKarina;
AgnerLicenseMIT
Package: dioptas
DioptasA GUI program for fast analysis of powder X-ray diffraction Images. It provides the capability of calibrating,
creating masks, having pattern overlays and showing phase lines.MaintainerClemens Prescher (clemens.prescher@gmail.com)Requirements* python 3.9+It is known to run on Windows, Mac and Linux. For optimal usage on a Windows machine it should be run with 64 bit
python. When used with 32 bit Dioptas occasionally crashes because of limited memory allocation possibilities.InstallationExecutablesExecutable versions for Windows, Mac OsX and Linux (all 64bit) can be downloaded from:https://github.com/Dioptas/Dioptas/releasesThe executable versions are self-contained folders, which do not need any python installation. Under Windows and Linux
the program can be started by running the executable (e.g. Dioptas.exe or Dioptas). Under MacOS X the folder will
contain an app folder which can be double-clicked for starting. Please accept the security prompts.CodeIn order to make changes to the source code yourself or always get the latest development versions you need to install
the required python packages on your machine.The easiest way to install the all the dependencies for Dioptas is to use the pip package manager:pipinstalldioptasand then run Dioptas by typing:dioptasin the commandline.Running the Program from sourceThe easiest way to create a working environment for Dioptas is to use the poetry package manager. A new environment is
created by running:poetryinstallThis will create a new environment with all the required packages. The environment can be activated by running:poetryshellAfterward the program can be started by running:dioptasIn order to run the program without activating the environment, the program can be started by running:poetryrundioptasIn case you want to run the Dioptas from source without poetry, you need to install the required packages yourself.
The packages are listed in the filepyproject.toml. The program can then be started by running:pythonrun.py
Package: dioptra
AboutDioptra is a ML intelligence platform. It provides real time observability of models in production as well as error analysis frameworks to understand model performance and inform retraining strategies.Quickstart1. Create your accountSign up for a free account by reaching out toinfo@dioptra.ai.2. Get your service API keyWhen you create an account, we generate a service API key.3. Instrument your codeInstall LibraryInstall the Dioptra library in an environment using Python > 3.5.3.$pip3installdioptraOr clone the repo:$gitclonehttps://github.com/dioptra-ai/collector-py.git
$python3setup.pyinstallRunnin the exampleYou can run the provided example to get a sense of how Dioptra works$exportDIOPTRA_API_KEY=<your_api_key>
$python3examples/image_classification.pyAnd log in to the dioptra app to see what happens :)
Package: dioptra-iris-client
🕸️ Iris Python ClientMinimalist Python client for theIrisAPI,
built on top ofAuthlibandhttpx.Installationpipinstalldioptra-iris-clientUsagefromiris_clientimportIrisClient,AsyncIrisClientbase_url="https://api.iris.dioptra.io"username="user@example.org"password="password"# Synchronous clientwithIrisClient(base_url,username,password)asclient:measurements=client.get("/measurements/").json()# Asynchronous clientasyncwithAsyncIrisClient(base_url,username,password)asclient:measurements=(awaitclient.get("/measurements/")).json()# Helper function to fetch all the results from a paginated endpoint,# available for both clients:all_measurements=client.all("/measurements/")Credential provider chainThe Iris client looks for credentials in a way similar to theAWS SDK:If one ofbase_url,usernameorpasswordis specified, these values will be used.If none of the previous values are specified, and one ofIRIS_BASE_URL,IRIS_USERNAMEorIRIS_PASSWORDenvironment variables are present, these values will be used.If none of the previous values are specified, and the file~/.config/iris/credentials.jsonexists,
the fieldsbase_url,usernameandpasswordwill be used.
Package: dioptra-zeph
🌬️ ZephZeph is a reinforcement learning based algorithm for selecting prefixes to probe based on previous measurements in order to maximize the number of nodes and links discovered. Zeph can be used on top of theIrisplatform.🚀 QuickstartZeph has a command line interface to configure and run the algorithm.First, install the Zeph package:pip install dioptra-zephZeph takes as input a list of /24 (IPv4) or /64 (IPv6) prefixes:# prefixes.txt8.8.8.0/242001:4860:4860::/64To start a measurement from scratch:zephprefixes.txtTo start from a previous measurement:zephprefixes.txtUUIDZeph relies oniris-clientandpych-clientfor communicating with Iris and ClickHouse. See their respective documentation to know how to specify the credentials.✨ Generate prefix lists from BGP RIBsYou can create anexhaustivelist of /24 prefixes from a BGP RIB dump:pyasn_util_download.py--latest# Connecting to ftp://archive.routeviews.org# Finding most recent archive in /bgpdata/2022.05/RIBS ...# Downloading ftp://archive.routeviews.org//bgpdata/2022.05/RIBS/rib.20220524.1000.bz2#  100%, 659KB/s# Download complete.zeph-bgp-convert--print-progressrib.20220524.1000.bz2prefixes.txt📚 Publications@article{10.1145/3523230.3523232,author={Gouel, Matthieu and Vermeulen, Kevin and Mouchet, Maxime and Rohrer, Justin P. and Fourmaux, Olivier and Friedman, Timur},title={Zeph &amp; Iris Map the Internet: A Resilient Reinforcement Learning Approach to Distributed IP Route Tracing},year={2022},issue_date={January 2022},publisher={Association for Computing Machinery},address={New York, NY, USA},volume={52},number={1},issn={0146-4833},url={https://doi.org/10.1145/3523230.3523232},doi={10.1145/3523230.3523232},journal={SIGCOMM Comput. Commun. Rev.},month={mar},pages={2–9},numpages={8},keywords={active internet measurements, internet topology}}🧑‍💻 AuthorsIris is developed and maintained by theDioptra groupatSorbonne Universitéin Paris, France.
Package: dios
DictOfSeriesDictOfSeries is a pandas.Series of pandas.Series objects which aims to behave as similar as possible to pandas.DataFrame.Nomenclatureseries/ser: instance of pandas.Seriesdios: instance of dios.DictOfSeriesdf: instance of pandas.DataFramedios-like: adiosor adfalignable object: adios,dfor aseriesFeatureseverycolumnhas its own indexuses much less memory than a misaligned pandas.DataFramebehaves quite like a pandas.DataFrameadditional align locator (.aloc[])Installtodo: PyPiimport dios

# Have fun :)DocumentationThe main docu is on ReadTheDocs at:dios.rtfd.iobut some docs are also available local:IndexingCookbookItypeTL;DRget it>>> from dios import DictOfSeriesempty>>> DictOfSeries()
Empty DictOfSeries
Columns: []

>>> DictOfSeries(columns=['x', 'y'])
Empty DictOfSeries
Columns: ['x', 'y']

>>> DictOfSeries(columns=['x', 'y'], index=[3,4,5])
     x |      y | 
====== | ====== | 
3  NaN | 3  NaN | 
4  NaN | 4  NaN | 
5  NaN | 5  NaN |with data>>> DictOfSeries([range(4), range(2), range(3)])
   0 |    1 |    2 | 
==== | ==== | ==== | 
0  0 | 0  0 | 0  0 | 
1  1 | 1  1 | 1  1 | 
2  2 |      | 2  2 | 
3  3 |      |      | 

>>> DictOfSeries(np.random.random([2,4]))
          0 |           1 | 
=========== | =========== | 
0  0.112020 | 0  0.509881 | 
1  0.108070 | 1  0.285779 | 
2  0.851453 | 2  0.805933 | 
3  0.138352 | 3  0.812339 | 

>>> DictOfSeries(np.random.random([2,4]), columns=['a','b'], index=[11,12,13,14])
           a |            b | 
============ | ============ | 
11  0.394304 | 11  0.356206 | 
12  0.943689 | 12  0.735356 | 
13  0.791820 | 13  0.066947 | 
14  0.759802 | 14  0.496321 | 

>>> DictOfSeries(dict(today=['spam']*3, tomorrow=['spam']*2))
  today |   tomorrow | 
======= | ========== | 
0  spam | 0     spam | 
1  spam | 1     spam | 
2  spam |            |
Package: dioscuri
Dioscuri provides classes and methods for working with Gemini WorkList (gwl) files.A Gemini worklist file is a text file that contains pipetting instructions for the Tecan Freedom EVO robots. Dioscuri uses the Freedom EVOware (v2.7) software’s specification of the gwl format.Install:pipinstalldioscuriWeb documentation:https://edinburgh-genome-foundry.github.io/Dioscuri/Github page:https://github.com/Edinburgh-Genome-Foundry/DioscuriLicense:MIT, Copyright 2020 Edinburgh Genome FoundryMore biology softwareDioscuri is part of theEGF Codonssynthetic biology software suite for DNA design, manufacturing and validation.
Package: dipbot
summaryThis is a discord bot which scrapes the current status of a game at
webdiplomacy and announces that information on discord.It also incorporates a very rudimentary cli tool which does the same
thing on the host.Note that at the moment dipbot can only handle a single game,
although the CLI functionality can fairly straightforwardly be
adjusted to parse different games (there's guidance on this below.)daemon functionalityThe daemon, which is run asdipbot daemon, spawns a discord bot
based on discord.py. It depends on a couple of environment variables
described below.Here is the bot's help dialogue, which describes the commands it
supports:Status:statusinstructsmetoreportonthestatusofmywebdipgame.status!sameas`$status`,butmentioning@everyonestatus?sameas`$status`,butwithadditionalinformationaboutthegamestatus?!sameas`$status?`,butmentioning@everyone
​NoCategory:helpShowsthismessage

Type$helpcommandformoreinfoonacommand.
Youcanalsotype$helpcategoryformoreinfoonacategory.A$statusrequest produces output in the
following format:"It is the [game-phase] of the [season] of [year].We are awaiting the orders of:[list of non-ready players with their order statuses]There are [N] days until the deadline, which is at [date]"run asdipbot report, dipbot will produce the output of$status.configurationbothdipbot daemonanddipbot reportreceive their configuration
from environment variables. Both need to know which game to look at;dipbot daemonalso needs to know its discord API key.compulsory environment variablesIn order to know which game to parse, the environment variable
WEBDIP_GAME_ID must be set to the corresponding webdiplomacy.com game
id. This is the number at the end of the webdiplomacy url for the
game; for instance, in the following URL, the id is 111111https://webdiplomacy.net/board.php?gameID=111111In addition, to host the discord bot yourself it's necessary to create
a bot account as describedhere, and
to set the environment variable DISCORD_API_KEY to the value of the
bot's token.theseenvironment
variablescan be set for a single session like this:$exportWEBDIP_GAME_ID=[game_id]$exportDISCORD_API_KEY=[api_key]that will let dipbot work in the current shell; to avoid having to run these commands, you can put the variable assignments in the config file for your shell (~/.bashrc, ~/.zshrc or whatever).handling multiple gamesBothdipbot daemonanddipbot reportwill get whatever game has
the id specified by WEBDIP_GAME_ID. You could therefore make little
wrapper scripts for dipbot report and get reports on as many games as
you liked. In future an option to specify the game id on the
commandline will be added to eliminate this minor inconvenience.installationthe most recent release is available from pip:$pipinstall--userdipbotafter which, so long as your PATH is properly configured, you should be able to run dipbot directly from the shell:$dipbotusagethere are two subcommands available:$dipbotreportwhich parses the status of the game and reports it to the shell before quitting, and$dipbotdaemonwhich attempts to initialize a discord bot corresponding to the token stored in DISCORD_API_KEY.