Saravanan666/pypi-org huggingface dataset:
Package: proScatter
For visualizing pLink data from one or more experimentsby Katelyn McGary Shipper, Justin Jee, and Ilya ShamovskyDependenciesproScatter usespython,numpy,bokeh, andpandasBasic UseTo download, either download all 3 .py files into the same directory, or
download the zipped folder (see button on the bottom right)The inputs to proScatter include:A fasta file including the amino acid sequences of all the proteins
under consideration.A list of amino acids of interest (ex: K or CM)pLink output in.htmlformatThe outputs include:A summary file (.txt) containing the list of all links and their
frequenciesA scatter plotExample./proScatter.py examples/test.fasta examples/IdProTable_combine.htmlFeaturesproScatter enables multiple features, for example:python proScatter.py test.fasta K test.html--scale--zoom=Prot1-Prot2--evalue=0.001Details are given below:–scaleScales both plot and output so that only the amino acids of interest are
considered. Axes are in units of amino acids of interest (ex: 1st
lysine, 2nd lysine, etc)–zoom=Prot1-Prot2Zooms in on only one subplot (Prot1 vs Prot2). As an added feature,
clicking on any point in the scatter plot will print the coordinates of
that point in the console.–evalue=#Considers only links with a score below a certain number #. Scores are
expected to be in the 5th columnusage: proScatter.py [-h] [-a AMINOACIDS] [-z ZOOM] [-s] [-e EVALUE] [-u]
                     [-o OUTPUT] [-v]
                     fasta_file plink

positional arguments:
  fasta_file            fasta file with protein sequences
  plink                 pLink output .html file

optional arguments:
  -h, --help            show this help message and exit
  -a AMINOACIDS, --aminoacids AMINOACIDS
                        cross-linkable aminoacids. Defaults to Lysine (K).
  -z ZOOM, --zoom ZOOM  Prot1-Prot2 only display subplot for proteins Prot1 vs
                        Prot2
  -s, --scale           scale both plot and outputs so that only amino acids
                        of interest are considered
  -e EVALUE, --evalue EVALUE
                        e-value cutoff
  -u, --unjoin          unjoin plot axes
  -o OUTPUT, --output OUTPUT
                        output file (HTML) name
  -v, --verbose         increase output verbosity
Package: prose
proseModular image processing pipelines for Astronomyproseis a Python package to build modular image processing pipelines for Astronomy.powered byastropyandphotutils!ExampleHere is a quick example pipeline to characterize the point-spread-function (PSF) of an example imageimportmatplotlib.pyplotaspltfromproseimportSequence,blocksfromprose.simulationsimportexample_image# getting the example imageimage=example_image()sequence=Sequence([blocks.PointSourceDetection(),# stars detectionblocks.Cutouts(shape=21),# cutouts extractionblocks.MedianEPSF(),# PSF buildingblocks.Moffat2D(),# PSF modeling])sequence.run(image)# plottingimage.show()# detected stars# effective PSF parametersimage.epsf.paramsWhile being run on a single image, a Sequence is designed to be run on list of images (paths) and provides the architecture to build powerful pipelines. For more details checkQuickstartandWhat is a pipeline?Installationlatestproseis written for python 3 and can be installed frompypiwith:pipinstallproseFor the latest versionpipinstall'prose @ git+https://github.com/lgrcia/prose'ContributionsSee ourcontributions guidelinesAttributionIf you findproseuseful for your research, citeGarcia et. al 2022. The BibTeX entry for the paper is:@ARTICLE{prose,
       author = {{Garcia}, Lionel J. and {Timmermans}, Mathilde and {Pozuelos}, Francisco J. and {Ducrot}, Elsa and {Gillon}, Micha{\"e}l and {Delrez}, Laetitia and {Wells}, Robert D. and {Jehin}, Emmanu{\"e}l},
        title = "{PROSE: a PYTHON framework for modular astronomical images processing}",
      journal = {\mnras},
     keywords = {instrumentation: detectors, methods: data analysis, planetary systems, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Earth and Planetary Astrophysics},
         year = 2022,
        month = feb,
       volume = {509},
       number = {4},
        pages = {4817-4828},
          doi = {10.1093/mnras/stab3113},
archivePrefix = {arXiv},
       eprint = {2111.02814},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.4817G},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}and read about how to cite the dependencies of your sequenceshere.
Package: prosecode
Prose CodeLiterate programming in Python from markdown to LaTeXTheprosecodelibrary is being developed as a way to generate really neat LaTeX from markdown files.
It will support both tangling and weaving code.
That is, it can run the code from the markdown files and it can also extract the code into separate.pyfiles.It is assumed that the markdown file uses github style fenced code blocks with extra data as is used in the Markdown-Preview-Enhanced plugin for Atom and VSCode.Installation (coming soon)pip install prosecodeTanglingThe following will extract the python code frommyfile.mdand store it in files.$ prosecode tangle myfile.mdThere is an optional--srcdirparameter that tells where to put the tangled source code.$ prosecode tangle myfile.md --srcdir src/WeavingThe following will execute the code inmyfile.md, place the output inline, and then convert it to LaTeX.$ prosecode weave mdfile.md --execute=True --outfile someotherfile.texThe--outfileparameter is optional.  If omitted, it will simply replace.mdwith.tex.There is also an optional parameter--executethat tells whether or not to execute the code chunks.
The default value is false.
Package: prosegrinder
ProsegrinderA relatively fast, functional prose text counter with readability scoring.Installationprosegrinderis available on PyPI. Simply install it withpip:pipinstallprosegrinderUsageThe main use is via theprosegrinder.Proseobject.>>>fromprosegrinderimportProse>>>p=Prose("Some lengthy text that's actual prose, like a novel or article.")The Prose object will parse everything down and compute basic statistics,
including word count, sentence count, paragraph count, syllable count, point of
view, dialogue, narrative, and a set of readability scores. All objects and
attributes should be treated as immutable.I know this isn't great documentation, but it should be enough to get you going.Command Line InterfaceProsegrinder now includes a simple CLI for analyzing text in a file:$prosegrinder--help
Usage:prosegrinder[OPTIONS]FILES...Setupthecommandlineinterface

Options:-i,--indentINTEGERPythonpretty-printjsonindentlevel.-s,--saveFILENAMEFiletosaveoutputto.--helpShowthismessageandexit.Will provide basic statistics on text from a file or set of files including the
filename and sh256 of text in each file analyzed. Output is json to help
facilitate use in automation::[{"filename":"shortstory.txt","statistics":{"sha256":"5b756dea7c7f0088ff3692e402466af7f4fc493fa357c1ae959fa4493943fc03","word_character_count":7008,"phone_count":5747,"syllable_count":2287,"word_count":1528,"sentence_count":90,"paragraph_count":77,"complex_word_count":202,"long_word_count":275,"pov_word_count":113,"first_person_word_count":8,"second_person_word_count":74,"third_person_word_count":31,"pov":"first","readability_scores":{"automated_readability_index":0.281,"coleman_liau_index":9.425,"flesch_kincaid_grade_level":8.693,"flesch_reading_ease":62.979,"gunning_fog_index":12.079,"linsear_write":10.733,"lix":34.975,"rix":3.056,"smog":11.688}}},{"filename":"copyright.txt","statistics":{"sha256":"553bfd087a2736e4bbe2f312e3d3a5b763fb57caa54e3626da03b0fd3f42e017","word_character_count":222,"phone_count":169,"syllable_count":78,"word_count":46,"sentence_count":7,"paragraph_count":16,"complex_word_count":10,"long_word_count":12,"pov_word_count":1,"first_person_word_count":1,"second_person_word_count":0,"third_person_word_count":0,"pov":"first","readability_scores":{"automated_readability_index":1.404,"coleman_liau_index":8.073,"flesch_kincaid_grade_level":6.982,"flesch_reading_ease":56.713,"gunning_fog_index":11.324,"linsear_write":3.714,"lix":32.658,"rix":1.714,"smog":9.957}}}]Readability scoresThe set of scores automatically calculated:Automated Readability IndexColeman Liau IndexFlesch Kincaid Grade LevelFlesch Reading EaseGunning Fog IndexLinsear WriteLIXRIXSMOG
Package: prosemble
ProsembleA python project for prototype-based machine learning modelsInstallationProsemble can be installed using pip.pipinstallprosembleIf you have installed Prosemble before and want to upgrade to the latest version, you can run the following command in your terminal:
Prosemble can be installed using pip.pipinstall-UprosembleTo install the development version from GitHub using Git, run the following command in your terminal:pipinstallgit+https://github.com/naotoo1/prosembleBibtexIf you would like to cite the package, please use this:@misc{Otoo_Prosemble_2022,author={Otoo,NanaAbeka},title={Prosemble},year={2022},publisher={GitHub},journal={GitHubrepository},howpublished={\url{https://github.com/naotoo1/Prosemble}},}
Package: prosemirror
prosemirror-pyThis package provides Python implementations of the followingProseMirrorpackages:prosemirror-modelversion 1.18.1prosemirror-transformversion 1.8.0prosemirror-test-builderprosemirror-schema-basicversion 1.1.2prosemirror-schema-listThe original implementation has been followed as closely as possible during
translation to simplify keeping this package up-to-date with any upstream
changes.Why?ProseMirror provides a powerful toolkit for building rich-text editors, but it's
JavaScript-only. Until now, the only option for manipulating and working with
ProseMirror documents from Python was to embed a JS runtime. With this
translation, you can now define schemas, parse documents, and apply transforms
directly via a native Python API.StatusThe full ProseMirror test suite has been translated and passes. This project
only supports Python 3. The code has type annotations to support mypy or other
typechecking tools.UsageSince this library is a direct port, the best place to learn how to use it is
theofficial ProseMirror documentation.
Here is a simple example using the included "basic" schema:fromprosemirror.transformimportTransformfromprosemirror.schema.basicimportschema# Create a document containing a single paragraph with the text "Hello, world!"doc=schema.node("doc",{},[schema.node("paragraph",{},[schema.text("Hello, world!")])])# Create a Transform which will be applied to the document.tr=Transform(doc)# Delete the text from position 3 to 5. Adds a ReplaceStep to the transform.tr.delete(3,5)# Make the first three characters bold. Adds an AddMarkStep to the transform.tr.add_mark(1,4,schema.mark("strong"))# This transform can be converted to JSON to be sent and applied elsewhere.assert[step.to_json()forstepintr.steps]==[{'stepType':'replace','from':3,'to':5},{'stepType':'addMark','mark':{'type':'strong','attrs':{}},'from':1,'to':4}]# The resulting document can also be converted to JSON.asserttr.doc.to_json()=={'type':'doc','content':[{'type':'paragraph','content':[{'type':'text','marks':[{'type':'strong','attrs':{}}],'text':'Heo'},{'type':'text','text':', world!'}]}]}
Package: prosemirror-py-converter
prosemirror-py-converter中文指引Python simple implementation of converting ProseMirror doc to markdownCore featuresBased onProseMirror basic modelSupport custom extensionProseMirror document converter: Json to Markdown in ProseMirror formatMainly used for data analysis and display after spider ProseMirror documents.Quick startInstall prosemirror-py-converterpip3 install prosemirror-py-converterConvert ProseMirror document to Markdownfrom pmconverter import prose2markdown

doc = {
     "type": "doc",
     "content": [
         {
             "type": "heading",
             "attrs": {
                 "level": 3
             },
             "content": [
                 {
                     "type": "text",
                     "text": "Example heading."
                 }
             ]
         }
     ]
}
print(prose2markdown(doc))output markdown### Example heading.Standard ProseMirror implementationStandard ProseMirror implementationmark type listlinkboldstrongcodeitalicstrikesubscriptsuperscriptunderlinenode type listdocheadingparagraphimagebullet_listordered_listtableblockquotecode_blockhard_breakhorizontal_ruleCustom ProseMirror extension examplesiwiki doc convertercustom mark converter examplefrom pmconverter.basic_model import CommonSimpleMark
from pmconverter.model_factory import register_mark_class


class CustomMark(CommonSimpleMark):

    def __init__(self):
        super().__init__()
        self.type = "custom_mark"
        self.md_pre_mark = "<u>"
        self.md_after_mark = "</u>"


register_mark_class("custom_mark", CustomMark)custom node converter examplefrom pmconverter.basic_model import Node
from pmconverter.model_factory import register_node_class


class CustomeImage(Node):

    def __init__(self):
        super().__init__()
        self.type = "custom_image"

    def convert_to_markdown(self, **kwargs) -> str:
        name = self.get_attr("name", "")
        url = self.get_attr("url", "")
        return f"![{name}]({url})"
        

register_node_class("custom_image", CustomeImage)
Package: prosemirror-python
=====Prosemirror-python=====This is an unofficial and not production ready package. Contributions and improvements are welcome.This package does not attempt at importing all of Prosemirror in Python. It is merely trying to use those parts ofprosemirror-model and prosemirror-transform that are needed for serverside operations.**This package has not yet been extensively tested!**How to use it-----------1. Install with `pip install prosemirror`2. In your python code, import the two included functions with:from prosemirror import create_doc, transform_doc3. Then create a Document object:doc = create_doc(doc_data, spec_data) # spec_data = JSON.parse(JSON.stringify(view.state.schema.spec))4. Thereafter create an updated Document object with the given steps applied:updated_doc = transform_doc(steps_data, doc)5. To get the JSON version of a Document object, simply use the builtin toJSON method:updated_doc.toJSON()Speed-----------It is not setting any speed records so far. These tests were conducted with Python 2 with the test files in the repo (applying three steps to an existing doc):prosemirror-python: 0.024snodejs: 0.00013sjsonpatch (Python): 0.00024sSo it is around 200 times slower than nodejs and 100 times slower than using jsonpatch. It is possible that it could be sped up in various ways, for example by using pypy and a vm or alike. Please let me know if you figure something out!License questions-----------**Q - What license is this under?**A - AGPL-3, check the LICENSE file.**Q - I have spent the past month building a webbased text editing app. I am in stealthmode as my editor is really unique and I'll be the next IT Billionaire once Irelease it. Now I would like to use this library, but the AGPL requires me to sharechanges I make with others! It's not fair that you are standing between me and my fortune!**A - Right. If it is worth that much to you, you can try to pay me so that I'll put it undera more liberal license. Secondly, you could suggest taking over maintainership of thislibrary and promise extra features to get me to change my mind. Thirdly - you could juststart from scratch as long as it's not much code, but then we both lose out of any fixeseither one of us makes.We all need to live of something, I give a lot of code away for freeand the only requirement there is is that you contribute any changes you make back. Notthat expensive, if you think about it.
Package: prosessilouhinta
prosessilouhintaProcess mining (Finnish prosessilouhinta) from eventlogs.Given a CSV file containing an eventlog with case IDs, acitivities/tasks, user IDs,
and timestamps some evaluations are performed that may assist in process mining.License: MITDocumentationUser and developerdocumentation of prosessilouhinta.Bug TrackerFeature requests and bug reports are best entered in thetodos of prosessilouhinta.Primary Source repositoryThe primary source ofprosessilouhintalives somewhere on a mountain in Central Switzerland.
But, we use decentralized version control (git), so any clone can become the source to everyone's benefit, no central only code.
Anyway, the preferred public clones ofprosessilouhintaare:on codeberg- a democratic community-driven, non-profit software development platform operated by Codeberg e.V.at sourcehut- a collection of tools useful for software development.StatusExperimental.Note: The default branch isdefault.
Package: prose-wc
A prose- and Jekyll-aware wordcount utility.AboutGiven the proliferation of Markdown and the use of Jekyll as a blogging
platform, the builtinwcutility came up short.  Even for plain-text
prose,wccan leave much to be desired.  To that end,prose-wcwill
calculate proper word, paragraph, and character counts for a given plaintext,
or markdown file or stream through STDIN.Also, Madison wanted to learn how to package for PyPI.Installingpip install prose-wcRunningusage: prose-wc [-h] [-S] [-u] [-f [{yaml,json,default}]] [-i [INDENT]] file

Compute Jekyl- and prose-aware wordcounts

positional arguments:
  file                  file to count (or - for STDIN)

optional arguments:
  -h, --help            show this help message and exit
  -S, --split-hyphens   split hyphenated words rather than counting them as
                        one word ("non-trivial" counts as two words rather
                        than one)
  -u, --update          update the jekyll file in place with the counts. Does
                        nothing if the file is not a Jekyll markdown file.
                        Implies format=yaml, invalid with input from STDIN and
                        non-Jekyll files.
  -f [{yaml,json,default}], --format [{yaml,json,default}]
                        output format.
  -i [INDENT], --indent [INDENT]
                        indentation depth (default: 4).

Accepted filetypes: plaintext, markdown, markdown (Jekyll)Runningprose-wcagainst a file will generate a series of counts
that might be of use. You can get these counts in a simple,
tab-separated format, JSON, or YAML. If you’re working with a Jekyll
markdown file, you can also choose to have this data embedded in the
frontmatter as YAML.Other filetypesYou can usepandocto convert your file and pipe
it into prose-wc:pandoc -f latex -t plain my_great_story.tex | prose-wc -In a Jekyll siteYou can add wordcount information to your site by runningprose-wc-u<file>, which will update the Jekyll frontmatter to include the results in
YAML format.  This data can then be included on the page in some place handy such as at the top of a post in_layouts/post.htmlwith:{%ifpage.counts%}<p class="text-muted small">{{page.counts.paragraphs}}{%ifpage.counts.paragraphs==1%}paragraph{%else%}paragraphs{%endif%}&bullet;{{page.counts.words}}words
    </p>{%endif%}This would result in something likethis.You can add wordcounts to posts with a find command like:find . \( -name '*.md' -or -name '*.markdown' \) -exec prose-wc -u "{}" \;Further informationSource, issues, and further information:GitHubAuthorMadison Scott-Clary
Package: prosit
WelcomeProSiT - PROgressive SImilarity Thresholds is an algorithm for topic models.Documentation atreadthedocs.You can try ProSiT on thiscolab notebook.For technical details and citation, please refer to:Fornaciari T., Hovy D., Bianchi F. (2022).
*ProSiT! Latent Variable Discovery with PROgressive SImilarity Thresholds*.
arXiv
Package: prosody
prosodyPython Prosody API: Emotion & Prosody sensitive TTSHow To UseInstallingInstall prosody using pippython -m pip install prosodyCreating a ClientFromprosody_apipackage importClientclass, then create a Client object with your valid username and password.fromprosody.prosody_apiimportClientcli=Client('your_id','your_password')Creating a Voice ItemIn order to create a Voice item, which is needed for API server to generate actual WAV file, importVoiceclass fromvoice_itempackage and create an instance ofVoiceclass.
There are five public attributes inVoiceclass, two of them are necessary, and the rest is optional.Required Attributestext: The text user wants to convert to a WAV file.actor: User can choose the actor of generated voice.Optional Attributesemotionprosodysignature: Users cannot set an arbitrary signature on their own. After registering the Voice, the server will automatically give a signature.fromprosody.prosody_apiimportClientfromprosody.voice_itemimportVoice# Creating a new client and a new Voice object.cli=Client('your_id','your_password')new_voice=Voice('안녕하세요','lady1')registered_voice=cli.register_voice(new_voice)# Updating the Voice object.registered_voice.text='반갑습니다'cli.update_voice(registered_voice)# Removing the Voice object.cli.remove_voice(registered_voice)Generating WAV FileThen, you can callgenerate_voiceto create actual WAV file.cli.generate_voice(registered_voice)AuthorsYuneui Jeong-Main contributor-laviande22Suwon Shin-Boilerplates-shh1574
Package: prosoponym
Prosoponym Python LibraryPython library to format personal names (in onomastic terminology also known as prosoponyms).A personal name is the set of names by which an individual person is known, with the understanding that, taken together, they all relate to that one individual.  A personal name is generally composed of first names, middle names and last names, which order varies depending on the culture the personal name is related to (western or eastern lexical name orders).>>>frommajormode.perseus.model.localeimportLocale>>>frommajormode.prosoponymimportLexicalNameOrder>>>frommajormode.prosoponymimportformat_first_name>>>frommajormode.prosoponymimportformat_full_name>>>frommajormode.prosoponymimportformat_last_name>>>format_first_name("Aline Maria")'Aline Maria'>>>format_last_name("caune ly")'CAUNE LY'>>>format_full_name("alfred thanh phuc","pham",Locale('fra'))'Alfred Thanh Phuc PHAM'>>>format_full_name("alfred thanh phuc","pham",Locale('vie'))'PHAM Alfred Thanh Phuc'>>>format_full_name("alfred","pham",Locale('vie'),full_name="pham thanh phuc")ValueError:Noneofthefirstnamewordshasbeenfoundinthefullname>>>format_full_name("alfred phuc","pham",Locale('fra'),full_name="pham thanh phuc")ValueError:Thepartsofthefullnamearenotwrittenintheexpectedorder>>>format_full_name("alfred phuc","pham",Locale('fra'),full_name="alfred thanh phuc pham")'Alfred Thanh Phuc PHAM'>>>format_full_name("alfred phuc","pham",Locale('vie'),full_name="Phạm thanh phúc alfred")'PHẠM Thanh Phúc Alfred'>>># If a last name is composed of two or more words, while the full name>>># follows western lexical order, this two or more words SHOULD be>>># in the full name (otherwise the function won't be able to determine>>># included in the full name, but not necessary.>>>format_full_name("Aline","Caune ly",Locale('fra'),full_name="aline minh anh maria caune ly")# OK'Aline Minh Anh Maria CAUNE LY'>>>format_full_name("Aline","Caune",Locale('fra'),full_name="aline minh anh maria caune ly")# Still OK, even if incoherent input'Aline Minh Anh Maria CAUNE LY'>>>format_full_name("truc","nguyen",Locale('vie'),full_name="nguyen thi thanh truc maria")'NGUYEN Thi Thanh Truc Maria'>>># If a last name is composed of two or more words, while the full name>>># follows eastern lexical order, this two or more words MUST be included>>># in the full name (otherwise the function won't be able to determine>>># which parts of the name correspond to the last name or to the>>># possible middle name).>>>format_full_name("Thao nguyen","nguyen le",Locale('vie'),"Nguyễn Lê thị Thảo Nguyên")'NGUYỄN LÊ Thị Thảo Nguyên'# OK>>>format_full_name("Thao nguyen","nguyen le",Locale('vie'),"Nguyễn thị Thảo Nguyên")# Still OK, even if incoherent input'NGUYỄN Thị Thảo Nguyên'>>>format_full_name("Thao nguyen","nguyen",Locale('vie'),"Nguyễn Lê thị Thảo Nguyên")# Not OK! Part of the last name is missing.'NGUYỄN Lê Thị Thảo Nguyên'