Saravanan666/pypi-org huggingface dataset:
Package: melon
MelonMelon is a lightweight package meant to simplify data processing for Deep Learning.It removes the need for boilerplate code to pre-process the data prior to (model) training, testing and inference.It aims at standardizing data serialization and manipulation approaches.The default formats align with the requirements by frameworks such asTensorflow/PyTorch/Keras.The tool also provides various level of customizations depending on the use-case.InstallationInstall and update usingpip:$ pip install melonSupported in Python >= 3.4.0ExamplesImagesWith defaultoptions:frommelonimportImageReaderdeftrain():source_dir="resources/images"reader=ImageReader(source_dir)X,Y=reader.read()...withtf.Session()ass:s.run(...,feed_dict={X_placeholder:X,Y_placeholder:Y})source_dirdirectory should contain images that need to be read. Seesample directoryfor reference.In the sample directory there is an optionallabels.txtfile that is described inLabeling.Since number of images may be too large to fit into memory the tool supports batch-processing.frommelonimportImageReaderdeftrain():source_dir="resources/images"options={"batch_size":32}reader=ImageReader(source_dir,options)whilereader.has_next():X,Y=reader.read()...This reads images in the batches of 32 until all images are read. Ifbatch_sizeis not specified thenreader.read()will read all images.With customoptions:frommelonimportImageReaderdeftrain():source_dir="resources/images"options={"data_format":"channels_last","normalize":False}reader=ImageReader(source_dir,options)...This changes format of data tochannels-last(each sample will beHeight x Width x Channel) and doesn’t normalize the data. Seeoptionsfor available options.OptionsImageswidthWidth of the output (pixels). default:255heightHeight of the output (pixels). default:255batch_sizeBatch size of each read. default: All images in a directorydata_formatFormat of the images datachannels_first-Channel x Height x Width(default)channels_last-Height x Width x Channellabel_formatFormat of the labels dataone_hot- as a matrix, with one-hot vector per image (default)label-  as a vector, with a single label per imagenormalizeNormalize data. default:Truenum_threads - number of threads for parallel processingdefault: Number of cores of the machineLabelingIn supervised learning each image needs to be mapped to a label.While the tool supports reading images without labels (e.g. for inference) it also provides a way to label them.Generating labels fileTo generatelabelsfile use the following command:$ melon generate
> Source dir:After providing source directory the tool will generatelabelsfile in that directory with blank labels.Final step is to add a label to each row in the generated file.For reference seesample labels:#legend
pedestrian:0
cat:1
parrot:2
car:3
apple tree:4

#map
img275.jpg:1
img324.jpg:2
img551.jpg:3
img928.jpg:1
img999.png:0
img736.png:4#legendsection is optional but#mapsection is required to map a label to an image.Format of the labelsLabel’s output format can be specified inCustom options. It defaults toone-hotformat.RoadmapSupport for video data (Q1 2019)Support for reading from AWS S3 (Q2 2019)
Package: melon-analytics-pricing
Melon analytics pricingThis package provides one class: ImmoNeighbors.
You should train one such instance per floor(number_of_rooms) from 1 to 6+.
Example code:'''
no_of_rooms = 3training_data = immo[np.floor(immo["rooms"]) == no_of_rooms]
neighbors = ImmoNeighbors(training_data.copy())apartments = apartments_to_benchmark[['lon','lat','area']].to_numpy()
dists,inds,rents = neighbors.k_neighbors(apartments)rent_percentiles = neighbors.weighted_percentiles(dists,rents,percentiles=[10,50,90])
'''Usually, problematic inputs will be ignored and have a corresponding row of NaNs in the output.
More details about that can be found in the documentation of the respective function.
Package: melon-chart.py
melon-chart.pymelon-chart.py is a Python API that retrieves the TOP 100 information from theMelon.Installationpip install melon-chart.pyQuickstartThe main usage of melon-chart.py is similar tobillboard.py.>>> from melon import *
>>> chart = ChartData(image_size=500)
>>> print(chart[0].json())
{
    "artist": "IVE (아이브)",
    "image": "https://cdnimg.melon.co.kr/cm2/album/images/112/11/297/11211297_20230327114349_500.jpg?7d9408105554f2f425c3d1d43ddd3d9f/melon/resize/500/optimize/90",
    "isNew": false,
    "lastPos": 1,
    "rank": 1,
    "title": "Kitsch"
}
>>> print(chart.name)
멜론차트_TOP100NOW
>>> print(chart.date)
2023-04-09 20:00:00ChartData ArgumentsimageSize– The size of cover image for the track. (default: 256)fetch– A boolean value that indicates whether to retrieve the chart data immediately. If set toFalse, you can fetch the data later using thefetchEntries()method.Chart entry attributesChartEntrycan be accessed using theChartData[index]syntax. AChartEntryinstance has the following attributes:title– The title of the trackartist– The name of the artistimage– The URL of the cover image for the tracklastPos- The track's last position on the previous period.rank– The track's current rank position on the chart.isNew– Whether the track is new to the chart.DependenciesrequestsLicenseThis project is licensed under the MIT License.
Package: melon-top100
MelonTop100This is a simple package that brings up the Top 100 list of Melon, a music site in Korea.If you use theget_songs()function, you can check Melon's Top 100 songs in the form of a list, and the items in the list are provided as a dictionary containing information such as song name and singer.Setup(Dev)$ python -m venv venv
$ .\venv\Scripts\activate
(venv) $ python -m pip install -U pip setuptools wheel pip
(venv) $ python -m pip install -U build twine
(venv) $ python -m build .
(venv) $ python -m pip install .\dist\melon_top100-1.0.0-py3-none-any.whl --force-reinstallUsefrommelon_top100importget_songs,get_like_count>>>top100=get_songs()...{'song_no':'34754292','title':'TOMBOY','album':'I NEVER DIE','artis '(여자)아이들'}, ...>>>get_like_count(34754292){'34754292':137492}
Package: melplot
melplotPlot melodeon[^dba] layout diagramsNotesInspirationstandard 21-key D/G with acc. notes highlighted and piano-key octave numbers marked:http://forum.melodeon.net/files/site/keyboards/2%20Row%20-%20D_G%20-%20with%20accidentals.jpgstandard 21-key D/G with notes on stave, fromMel Forum:http://forum.melodeon.net/files/site/DGwithStave.pdfas above, with ABC notation labels added, fromDaddy Long Les:https://www.daddylongles.com/_files/ugd/2a4ead_6501161c36fa470fbb1f64d24261ad9d.pdfDipper blank 30-key Anglo concertina scheme, with push/pull "pills" and piano keyboard with octaves highlighted:http://www.johndipper.co.uk/downloads/blank-scheme.pdf20-key Anglo concertina with fancy buttons and octaves notated,from concertina.com:http://www.concertina.com/fingering/images/anglo20-W1000H300.gifRick Mohr's layout, describedhere, simple and clean, effective use of colors:http://rickmohr.net/music/3row.pdfstandard 12-key G/C with notes on stave, fixed solfège, and octave numbers, from Mel Forum:http://forum.melodeon.net/files/site/keyboards/GC_with_accidentals_showing_notes_on_stave.pdf3-row D/G/acc with fixed solfège coloring treble buttons by octave, by Bob Ellis:http://forum.melodeon.net/files/site/Ellis3row.pdfTODOand ideasbasic diagram using mpldifferent ways to indicate octaves (e.g. color; piano key notation or wrt. root)different options for pitch labels (ABC, piano key notation, scale degrees)plotting notes on staveCLIfirst PyPI releaseHTML/CSS output optionfancier button style option (some 3-D-ness)draw connections in bellows direction for consecutive notes or chorddocs build with layout libraryInput formatASCII representation of the layout.Ideas:notes in ABC notation, push/pull separated by/or|, push/pull pairs separated by whitespacefor each row, specify horizontal offset in the layout (zero implicit; e.g. 0.5 for the second row in a typical 11/10 layout)maybe likex0.5instead of just0.5, to emphasize just spacebass chords also in ABC notation, but maybe also support the common+/-?Layout sourcesMel Forum 2-rowMel Forum 2.5-rowMel Forum 3-rowbass layouts from Squeezeheadvarious layouts and notes from Orest[^pop][^dba]:Diatonic button accordion(DBA) / melodeon / "box" / accordéon diatonique / diato / etc. Also may later extend to plotting the layouts of other button accordion family instruments like concertinas.
[^pop]: Be careful opening this link on mobile browsers, I've gotten annoying / potentially dangerous pop-ups.
Package: melt
A nucleotide sequence melt temp calculator for Python.Features:Usually within a few tenths of a degree C match to IDT’sOligoAnalyzerMono- and divalent cation corrections (fromhttps://www.idtdna.com/Calc/Analyzer/Home/Definitions#MeltTemp)Accurate nucleotide pair coefficents from Allawi and SantaLucia (1997)Limitations:Does not handle mismatches or dangling endsDoes not handle ambiguous basesDoes not handle RNA or DNA/RNA hybridizationIf you need these features, use BioPython’sMeltingTempmodule.Installation$pipinstallmeltUsageFrom the command line:$TmATGCATGC44.4$Tm--dna200--na50--mg3--dntp0.8ATGCATGC26.4As a library:>>>importmelting>>>melting.temp("ATGCATGC")44.387081560668946>>>melting.temp("ATGCATGC",DNA_c=200,Na_c=50,Mg_c=3,dNTPs_c=0.8)26.438734864285152AcknowledgementsThis code is largely built on existing code from:Sebastian Bassi (sbassi@genesdigitales.com)Greg Singer (singerg@tcd.ie)Nicolas Le Novere (lenov@ebi.ac.uk)Salt concentration equations adapted from IDT, with work fromErik Clarke,Sesh Sundararaman, andCalvin Morrison.
Package: meltano
The declarative code-first data integration engineSay goodbye to writing, maintaining, and scaling your own API integrations.Unlock 600+ APIs and DBs and realize your wildest data and ML-powered product ideas.IntegrationsMeltano Hubis the single source of truth to find any Meltano plugins as well asSingertaps and targets. Users are also able to add more plugins to the Hub and have them immediately discoverable and usable within Meltano. The Hub is lovingly curated by Meltano and the wider Meltano community.InstallationIf you're ready to build your ideal data platform and start running data workflows across multiple tools, start by following theInstallation guideto have Meltano up and running in your device.DocumentationCheck out the"Getting Started" guideor find the full documentation athttps://docs.meltano.com.ContributingMeltano is a truly open-source project, built for and by its community. We happily welcome and encourage your contributions. Start by browsing through ourissue trackerto add your ideas to the roadmap. If you're still unsure on what to contribute at the moment, you can always check out the list of open issues labeled as "Accepting Merge Requests".For more information on how to contribute to Meltano, refer to ourcontribution guidelines.CommunityWe host weekly online events where you can engage with us directly. Check out more information in ourCommunitypage.If you have any questions, want sneak peeks of features or would just like to say hello and network, join our community of over +2,500 data professionals!👋Join us on Slack!Responsible Disclosure PolicyPlease refer to theresponsible disclosure policyon our website.LicenseThis code is distributed under the MIT license, see theLICENSEfile.
Package: meltano.edk
Meltano extension developer kit|The Meltano extension developer kit is the fastest way to build custom Meltano extensions. If you're looking to build a custom extractor, loader, or tap then theSDKis actually what you're looking for.Creating a new extension using the EDKThis repo ships with acopierbased template to help developers get and new extension using theMeltano EDKup and running quickly.Prerequisites for using the templateInstall copier:pipxinstallcopierUse copier to initialize a new extensionStart a new EDK project using the supplied template (directly from Github):copiergh:meltano/edkmy-new-extensionInstall the project dependencies:cdmy-new-extension
poetryinstallDeveloping extensions using the EDKFor detailed instructions on developing Meltano EDK extensions, see theMeltano EDK documentationand review theWork-In-Progress Specification.For working examples of Meltano EDK extensions, see:dbt-extcron-ext
Package: meltanolabs-tap-gmail
tap-gmailtap-gmailis a Singer tap for Gmail.Built with theMeltano Tap SDKfor Singer Taps.Installationpipxinstalltap-gmailConfigurationAccepted Config OptionsA full list of supported settings and capabilities for this
tap is available by running:tap-gmail--aboutConfigure using environment variablesThis Singer tap will automatically import any environment variables within the working directory's.envif the--config=ENVis provided, such that config values will be considered if a matching
environment variable is set either in the terminal context or in the.envfile.Source Authentication and AuthorizationUsageYou can easily runtap-gmailby itself or in a pipeline usingMeltano.Executing the Tap Directlytap-gmail--version
tap-gmail--help
tap-gmail--configCONFIG--discover>./catalog.jsonDeveloper ResourcesInitialize your Development Environmentpipxinstallpoetry
poetryinstallCreate and Run TestsCreate tests within thetap_gmail/testssubfolder and
then run:poetryrunpytestYou can also test thetap-gmailCLI interface directly usingpoetry run:poetryruntap-gmail--helpTesting withMeltanoNote:This tap will work in any Singer environment and does not require Meltano.
Examples here are for convenience and to streamline end-to-end orchestration scenarios.Your project comes with a custommeltano.ymlproject file already created. Open themeltano.ymland follow any"TODO"items listed in
the file.Next, install Meltano (if you haven't already) and any needed plugins:# Install meltanopipxinstallmeltano# Initialize meltano within this directorycdtap-gmail
meltanoinstallNow you can test and orchestrate using Meltano:# Test invocation:meltanoinvoketap-gmail--version# OR run a test `elt` pipeline:meltanoelttap-gmailtarget-jsonlSDK Dev GuideSee thedev guidefor more instructions on how to use the SDK to
develop your own taps and targets.
Package: meltanolabs-tap-snowflake
tap-snowflaketap-snowflakeis a Singer tap for Snowflake.Built with theMeltano Tap SDKfor Singer Taps.Installationpipxinstallgit+https://github.com/MeltanoLabs/tap-snowflake.gitConfigurationAccepted Config OptionsA full list of supported settings and capabilities for this
tap is available by running:tap-snowflake--aboutConfigure using environment variablesThis Singer tap will automatically import any environment variables within the working directory's.envif the--config=ENVis provided, such that config values will be considered if a matching
environment variable is set either in the terminal context or in the.envfile.Source Authentication and AuthorizationStandardusernameandpasswordauth is supported.Enabling Batch MessagingThis tap is built using the Meltano SDK and therefore supports aBATCHmessage type, in
addition to theRECORDmessages of the Singer spec. This can be enabled either by adding the following to yourconfig.json:{// ..."batch_config":{"encoding":{"format":"jsonl","compression":"gzip"},"storage":{"root":"file://tests/core/resources","prefix":"test-batch"}}}or its equivalent to yourmeltano.ymlconfig:plugins:extractors:-name:tap-snowflakeconfig:batch_config:encoding:format:jsonlcompression:gzipstorage:root:"file://tests/core/resources"prefix:test-batchNote:This variant oftap-snowflakedoes not yet support theINCREMENTALreplication strategy inBATCHmode. Followherefor updates.UsageYou can easily runtap-snowflakeby itself or in a pipeline usingMeltano.Executing the Tap Directlytap-snowflake--version
tap-snowflake--help
tap-snowflake--configCONFIG--discover>./catalog.jsonDeveloper ResourcesInitialize your Development Environmentpipxinstallpoetry
poetryinstallCreate and Run TestsCreate tests within thetap_snowflake/testssubfolder and
then run:poetryrunpytestYou can also test thetap-snowflakeCLI interface directly usingpoetry run:poetryruntap-snowflake--helpTesting withMeltanoNote:This tap will work in any Singer environment and does not require Meltano.
Examples here are for convenience and to streamline end-to-end orchestration scenarios.Your project comes with a custommeltano.ymlproject file already created. Open themeltano.ymland follow any"TODO"items listed in
the file.Next, install Meltano (if you haven't already) and any needed plugins:# Install meltanopipxinstallmeltano# Initialize meltano within this directorycdtap-snowflake
meltanoinstallNow you can test and orchestrate using Meltano:# Test invocation:meltanoinvoketap-snowflake--version# OR run a test `elt` pipeline:meltanoelttap-snowflaketarget-jsonlSDK Dev GuideSee thedev guidefor more instructions on how to use the SDK to
develop your own taps and targets.
Package: meltano-tap-circle-ci
tap-circle-citap-circle-ciis a Singer tap forCircleCI.Built with theMeltano Tap SDKfor Singer Taps.StreamsPipelinesWorkflowsJobsWARNING: You must follow the projects in CircleCI to obtain their pipelines.InstallationYou can install this repository directly from the Github repo. For example, by running:pipxinstallhttps://github.com/MeltanoLabs/tap-circle-ci.gitConfigurationAccepted Config OptionsThe following configuration options are available:FieldDescriptionTypeRequiredDefaulttokenPersonal API Token you have generated that can be used to access the CircleCI APIstringyesorg_slugOrganization slug in the form vcs-slug/org-name. Example:org-slug=gh/CircleCI-Publicstringyesuser_agentUser-Agent to make requests withstringnotap-circle-ci/<version> Singer Tap for the CircleCI APIbase_urlBase URL for the CircleCI APIstringnohttps://circleci.com/api/v2A full list of supported settings and capabilities for this
tap is available by running:tap-circle-ci--aboutSource Authentication and AuthorizationLogin to your Circle CI account, go to thePersonal API Tokenspage,
and generate a new token.UsageYou can easily runtap-circle-ciby itself or in a pipeline usingMeltano.Executing the Tap Directlytap-circle-ci--version
tap-circle-ci--help
tap-circle-ci--configCONFIG--discover>./catalog.jsonDeveloper ResourcesInitialize your Development Environmentpipxinstallpoetry
poetryinstallCreate and Run TestsCreate tests within thetap_circle_ci/testssubfolder and
then run:poetryrunpytestYou can also test thetap-circle-ciCLI interface directly usingpoetry run:poetryruntap-circle-ci--helpTesting withMeltanoNote:This tap will work in any Singer environment and does not require Meltano.
Examples here are for convenience and to streamline end-to-end orchestration scenarios.Your project comes with a custommeltano.ymlproject file already created. Open themeltano.ymland follow any"TODO"items listed in
the file.Next, install Meltano (if you haven't already) and any needed plugins:# Install meltanopipxinstallmeltano# Initialize meltano within this directorycdtap-circle-ci
meltanoinstallNow you can test and orchestrate using Meltano:# Test invocation:meltanoinvoketap-circle-ci--version# OR run a test `elt` pipeline:meltanoelttap-circle-citarget-jsonlSDK Dev GuideSee thedev guidefor more instructions on how to use the SDK to
develop your own taps and targets.
Package: melter
melterIdentifies unsolved cases that should be analysed again.InstallationFor usersInstall melter in an environment with python 3.9:$pipinstallmelterFor developersClone the repository:$gitclonegit@github.com:Clinical-Genomics/melter.gitEnter the root folder of the project:$cdmelter/Create the melter environment:$condaenvcreate-fenvironment.yamlActivate the melter environment:$condaactivatemelterIf poetry is not installed, install poetry via:$curl-sSLhttps://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py|python-To configure your current shell:$source$HOME/.poetry/envInstall dependencies:$poetryinstallUsageTo see available commands:$melter--helpLicensemelterwas created by Henning Onsbring. It is licensed under the terms of the MIT license.
Package: melthon
Minimalistic static site generatorFree software: GNU GPLv3 licenseInstallationUse Docker (preferred way):# --rm           : Remove container after execution
# -u ${UID}      : Run container as current user
# -v"$(pwd):/src": Make source and output accessible inside container
docker run --rm -u ${UID} -v"$(pwd):/src" jenswbe/melthonUse pip:pip install melthonDocumentationhttps://python-melthon.readthedocs.io/Changelog2.1.0 (2020-04-21)Refresh project by adding support for Docker, improving unit tests and freezing dependencies2.0.0 (2020-05-22)Simplify project by dropping support for all Python versions except for the current version (3.8)Add support for repeated pages (e.g. events -> event details)1.4.0 (2020-01-19)Add Python 3.8 supportDrop Python 3.4 supportDon’t remove output folder, but remove it’s contents instead. Removing the
folder would cause permission issues, when serving with a local web server for development.1.3.0 (2019-11-27)Add option to render Mako exceptions1.2.0 (2019-10-18)Set default input encoding to UTF-81.1.0 (2019-10-08)Added subdirectory supportAdded support for pretty urls (default)Both <PAGE NAME>.template.mako and <PAGE NAME>.part.mako files won’t be rendered now1.0.0 (2019-09-25)Template rendering is workingAdded YAML data file supportImproved program verbosity0.1.0 (2019-09-21)Drop support for Python 2Implement middlewares0.0.0 (2019-09-21)First release on PyPI
Package: meltsubtitles
Melt subtitles(融化字幕)====只留具有生词的字幕，并给出生词的释义，[思路来源](https://zhuanlan.zhihu.com/p/25854872)可以选择只保留生词和释义。生词是是指词库以外的单词，所以每个人的生词库是不一样的，可以自己寻找适合自己的词库。Introduction====Meltsubtitles take the subtitles *.srt in and spill out  new subtitles in which the English words that you already know will be removed and it will provide the meaning of the words you don't know.思路====1. 词库假定是你认识的单词2. 将字幕里在词库中的单词去掉，3. 通过查询有道网页得到生词的释义4. 将释义加入到新的字幕文件中，5. done效果====![原始](img/ori.jpg)![给出生词释义](img/cn.jpg)![二刷](img/sec.jpg)安装和使用====0. 安装python 2.7.9 以上，推荐[python 3.5](https://www.python.org/downloads/release/python-353)1. pip install -r requirements.txt2. python main.py zimu.srt如果指定单词库，单词库在文件夹wordsRepo, 加上"-w wordsRepo/文件", 默认使用5000的。如果指定文件夹,命令行加上"--path 文件夹"或者对多个字幕转换 python main.py *.srt如果希望是英文释义，在命令行加上 "-e"如果是二刷，在命令行加上 "-2"词库有[5000](http://www.wordfrequency.info/free.asp),[10000](https://github.com/first20hours/google-10000-english)====To do====1. [x] 英文释义选择2. [x] 批量转换3. [ ] 可以放到一个网页，使用的人可以不用安装python，只需上传下载。4. [ ] 可以用map函数式的思想减少for的使用5. [ ] 如果有人需要，可以打包成exe，这样就不用安装Python。5. [ ] 如果有需要，可以将生词导出到一个文件中，用于以后记忆，或者导入查词软件，比如有道的单词本里，用于自己日后复习。
Package: melt-to-gephi
melt_to_gephiA simpler way of restructituring Meltwater data to a gephi ready data fileFree software: MIT licenseDocumentation:https://melt-to-gephi.readthedocs.io.FeaturesCreates agephiready file with the columnsGephi File Structuresourcetargettweettrendurlpost_type@s1@tar1some tweet text#tag1Tweet 1 urlRT@s2@tar2Another tweet text#tag2Tweet 2 urlQTCreditsThis package was created withCookiecutter.History0.1.0 (2021-02-26)First release on PyPI.