Saravanan666/pypi-org huggingface dataset:
Package: chapter-marker
Chapter-markerWrite a chaptermark file for your podcast. The focus is thebinaergewitter podcastChapter-marker is to be used with hotkeys.Installationpipinstallchapter-markerWorkflowFor Binärgewitterexport PAD_APIKEY=<add-apikey-for-pad-here> 

CURRENT_SHOW=$(bgt-current-show)
showtitles="titles${CURRENT_SHOW}.lst"
bgt-get-titles "${CURRENT_SHOW}" > "$showtitles"

chapter-marker "$showtitles" "${CURRENT_SHOW}"
# ctrl-j -> start the show at "H" of Hallihallo, also start next chapter
# check by clicking left on the tray icon which is the next chapter

# finish up the show by right clicking on the tray and choose [save] 
# the chapter mark file is now stored at ~/.local/share/chapter-marker/${CURRENT_SHOW}_chapters.txtDevelopmentNixOSnix-shell# or build and test the whole thingnix-build
result/bin/chapter-markerLegacy OSRequires python headers:sudodnfinstallpython3-devel
sudoaptinstallpython3-devpoetryinstall
poetryrunchapter-marker"$showtitles""${CURRENT_SHOW}"LicenseSource Code under MIT (seeLicense)The Icons are Licensed under Apache 2.0, fromhttps://github.com/Templarian/MaterialDesign/
Package: chaptermarkers
chaptermarkers will creat chapter markers in MP4 files from a text file.Get Started!Here’s how to set upchaptermarkersfor local environment.1- Clone thechaptermarkerslocally:$gitclonehttps://github.com/cbitterfield/chaptermarkers.git2- Install your local copy into avirtualenv. Assuming you havevirtualenvwrapperinstalled, this is how you set up the package for local development:$sudomakeboostrap$mkvirtualenvchaptermarkers$pipinstall-rrequirements/dev.txt3- How to enable/disable virtualenv$workonchaptermarkers$...$deactivateUsage:usage: chaptermarkers [-h] [–version] [-d] [-f CHAPTERS] [-m FILENAME] [-o OUTPUT] [-t TITLE]Chapter markers creates markers in MP4 files from friendly time marksoptional arguments:-h,--helpshow this help message and exit--versionshow program’s version number and exit-d,--debugTurn on Debugging Mode-fCHAPTERS,--chapters-fileCHAPTERSText file with chapters in it. TimeStamp space Title-mFILENAME,--mpeg-videoFILENAMEMovie file MP4s only – Currently no checking-oOUTPUT,--mpeg-video-markersOUTPUTdefault is FILENAME_chapters.mp4-tTITLE,--titleTITLEdefault is My Default Movie, this is the title that will show when playingThe default value for FFMPEGCMD is /opt/local/bin/ffmpeg [MAC Ports]. If your binary is in a different location use export FFMPEG=/usr/bin/ffmpeg or
whatever is appropriate for your shell Temp files are written to /tmp and are remove if successful write occursCredits# ChangelogAll notable changes to this project will be documented in this file.The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).## [Unrelease]### Added
- 1.2.0 Added support for microseconds
- 1.1.0 Final Version with updated documentation
- 0.1.0 Initial Release[Unrelease] TBD-link
Package: chaptinator
chaptinatorAdd chapters on scene changes to videos (e.g. slide changes in presentations)Installchaptinatorrequiresffmpegto be installed on your system and for it to
be inPATH.
Follow the instructions onhttps://ffmpeg.org/and make sure the commandsffmpegandffprobeare available in your favorite shell (bash, zsh,
Powershell, ...).Then install this package via pip. For a global installation usesudopipinstallchaptinatorand for a user-local installation usepipinstall--userchaptinatorUsagechaptinatorVIDEO[-tTITLE][-aAUTHOR][-cCHANGE_THRESH][-s][-r][-v][-o][-d][-mMETADATA_FILE]-t TITLEsets the title in the metadata (default: filename)-a ARTISTsets the artist in the metadata-c CHANGE"value between 0 and 1 to indicate a new scene; a low value
reflects a low probability for the current frame to introduce a new scene,
while a higher value means the current frame is more likely to be one"
--https://ffmpeg.org/ffmpeg-filters.html#select_002c-aselect-sscales the tagged result video to a height 720 while keeping the aspect
ratio-rreduces the framerate to 5fps, which is optimal to save bandwidth when
powerpoint slides are the sole video content. Lower values cause problems with
some browser video players-oactivates the ffmpeg tune 'stillimage' that lowers the deblocking filter,
optimizing for still images like slides-vconverts the audio to MP3 with VBR (Variable BitRate) and a quality
setting of 8, which is optimal for speech with relatively long segments of
silence.
(Lame is compiled into the standardffmpeglibrary while the Frauenhofer AAC,
which supports VBR, is not)-ddownmixes both audio channels into a single mono audio channel-m METADATA_FILEdisables the cut detection and instead uses the provided
metadata file. This file has to have the structure described inhttps://ffmpeg.org/ffmpeg-formats.html#Metadata-1Example# increase cut detection threshold to 0.4, scale the video and reduce frameratechaptinatorfoo.mp4-t"Video Title"-a"Author Name"-c0.4-s-r# read cuts from metadata filechaptinatorfoo.mp4-mmetadata.txtUse Caseschaptinatorcould be used to add chapters to presentation slides that were
recorded in PowerPoint and exported as video.But of course it works with any video file that has cuts in it, just adjust
the-cparameter to your preference.
Package: char2image
# char2image.py[![PyPI version](https://badge.fury.io/py/char2image.svg)](https://badge.fury.io/py/char2image)
[![Python versions](https://img.shields.io/pypi/pyversions/char2image.svg)](setup.py)
[![Build Status](https://travis-ci.org/raviqqe/char2image.py.svg?branch=master)](https://travis-ci.org/raviqqe/char2image.py)
[![License](https://img.shields.io/badge/license-unlicense-lightgray.svg)](https://unlicense.org)Converts characters to font images in Python.## License[The Unlicense](https://unlicense.org)
Package: chara
# CharaChara enables developers to quickly create characterization tests.  Start by creating integration tests using whatever testing framework you prefer.  Using Chara you decorate those test functions to record interactions with specific dependencies.  Afterwards, you can replay the recording and those dependencies will behave as recorded.## UsageCreate production code and passing integration test (test_scraper.py):def scrape_headline(name):
    url, search = {
        'wired': (
            'http://www.wired.com',
            '<div class="headline headline1">\s*'
            '<h5>[^<]*</h5>\s*'
            '<h2>\s*<a[^>]*>([^<]*?)</a>\s*</h2>\s*'
            '</div>'
        )
    }[name]

    matches = re.search(search, get_html(url))

    return matches.group(1) if matches else None


def get_html(url):
    return urllib2.urlopen(url).read()


class DemoTest(TestCase):
    def test_scraper(self):
        self.assertEqual(
            'This Is What Happens When You Hack and '
            'Extort the \'Bitcoin Jesus\'',
            scrape_headline('wired')
        )Add chara.record decorator and run the test:class DemoTest(TestCase):
    @chara.record('test_scraper.get_html')
    def test_scraper(self):
        self.assertEqual(
            'This Is What Happens When You Hack and '
            'Extort the \'Bitcoin Jesus\'',
            scrape_headline('wired')
        )Switch to using chara.replay and notice that even if you turn get_html() to a no-op function the test still passes, so you know that the function’s normal functionality is being bypassed by Chara’s replay functionality.:def get_html(url):
    pass # nothing even happening here, but the test passes!

class DemoTest(TestCase):
    @chara.replay('test_scraper.get_html')
    def test_scraper(self):
        self.assertEqual(
            'This Is What Happens When You Hack and '
            'Extort the \'Bitcoin Jesus\'',
            scrape_headline('wired')
        )## LicenseUses the [MIT](http://opensource.org/licenses/MIT) license.
Package: charachorder.py
charachorder.pyA wrapper forCharaChorder'sSerial APIwritten in PythonWarning:This project is in beta; breaking changes will occur without notice. Please wait for v1.0.0FeaturesSupports all major versions of Python3.Exhaustive list of commands as in the Serial API.Events (coming soon).InstallationPython 3.8 or higher is required.# Linux/macOSpython3-mpipinstall-Ucharachorder.py# Windowspy-3-mpipinstall-Ucharachorder.pyTo install the development version, run the following:gitclonehttps://github.com/GetPsyched/charachorder.pycdcharachorder.py
python3-mpipinstall-U.UsagefromcharachorderimportCharaChorderfordeviceinCharaChorder.list_devices():# Method 1withdevice:print(device.get_id())# Method 2device.open()print(device.get_id())device.close()LinksDocumentationCharaChorder's Official Discord Server
Package: characterai
💬 CharacterAIAn unofficial API for Character AI for Python using PlaywrightDiscord ServerIf you have any questions/problems/suggestions or you just want to talk about AI and CharacterAI - welcome to my new Discord serverdiscord.gg/ZHJe3tXQkfᅠ💻 Installationpipinstallcharacteraiᅠ📚 DocumentationFor a complete understanding of the library, there isdocumentationᅠ🔑 Get TokenDO NOT SHARE IT
The token is needed for authorization and operation of requests from your accountOpen DevTools in your browserGo to Storage -> Local Storage -> char_tokenCopyvalueᅠ📙 ExamplefromcharacteraiimportPyCAIclient=PyCAI('TOKEN')char=input('Enter CHAR: ')chat=client.chat.get_chat(char)participants=chat['participants']ifnotparticipants[0]['is_human']:tgt=participants[0]['user']['username']else:tgt=participants[1]['user']['username']whileTrue:message=input('You: ')data=client.chat.send_message(chat['external_id'],tgt,message)name=data['src_char']['participant']['name']text=data['replies'][0]['text']print(f"{name}:{text}")ᅠ⚠️ IssuesDescribe how to cause an error, when the error is called, how often, whether it was before, etc.
You can write about the error in Github Issues, and you can also write to Discord server
Package: character-encoding-utils
Character Encoding UtilsSomecharacter encodingutils.Now support:GB2312Big5Shift-JISKS-X-1001Installationpipinstallcharacter-encoding-utilsUsageGB2312fromcharacter_encoding_utilsimportgb2312bs=gb2312.encode('abc中国')assertgb2312.decode(bs)=='abc中国'Big5fromcharacter_encoding_utilsimportbig5bs=big5.encode('abc中國')assertbig5.decode(bs)=='abc中國'Shift-JISfromcharacter_encoding_utilsimportshiftjisbs=shiftjis.encode('abc日本')assertshiftjis.decode(bs)=='abc日本'KS-X-1001fromcharacter_encoding_utilsimportksx1001bs=ksx1001.encode('abc가쳰')assertksx1001.decode(bs)=='abc가쳰'LicenseUnder theMIT license.
Package: charactergpt-prompts
CharacterGPTThis library is designed to make the creation of characters for rollplay in ChatGPT much easierInstallationpip install charactergpt-promptsUsageCreate character from scratchfromcharactergpt_prompts.prompt_generatorimportGptPromptprompt_example=GptPrompt(**kwargs)currently supported parameters:jailbreak_type(str) #Use one of the premade jailbreaksdefaultcustom_jailbreak(str) #Pass your own jailbreakcharacter_description(dict) #Dictionary of character characteristicsNote: For better results, you should add "Name" and "Character information"story_initial_message(str) #String containing the beginning of the storystory_start_context(str) #Context of the beginning of the story so model can better understands where she isuser_name(str) #Name of the character the user will playNote: all {{user}} in character_description, story_initial_message and story_start_context will be replaced by this parametertokens_limit(int) #Limit the number of tokens to be generatedaverage_tokens(int) #Less strict token limitdebug_mode(bool) #Adds the ability for the user to update the behavior of the model during role-playNote: to call debug mode simply write DebugMode: before changes that you want to makemodel_author #Model author dataimport_data(dict) #If this parameter passed it will try to load prompt data from itImport existing characterfromcharactergpt_prompts.prompt_generatorimportGptPromptexample_prompt=GptPrompt.import_existing_prompt(prompt_name="Sakura")#orexample_prompt=GptPrompt.import_existing_prompt(filename="example.json")Note: if you pass prompt_name as a parameter it will import character from character examples folderList of "ready to go" characters:AlysAmiSakuraUpdate prompt parametersfromcharactergpt_prompts.prompt_generatorimportGptPromptexample_prompt=GptPrompt.import_existing_prompt(prompt_name="Sakura")#update jailbreak messageexample_prompt.jailbreak_text="new jailbreak text"#character descriptionexample_prompt.character_description["Name"]="Ami"#or if you want to update multiple parametersdescription_extension={"Age":"23","Dislikes":["being rude","sadness","when {{user}} is angry"]}example_prompt.add_description_parameters(description_extension)#initial messageexample_prompt.initial_message="new initial message"#story start contextexample_prompt.story_start_context="new story start context"#user nameexample_prompt.user_name="New user"#tokens limitexample_prompt.tokens_limit=100#avarage tokensexample_prompt.average_tokens=150#debug modeexample_prompt.debug_mode=True#model authorexample_prompt.model_author="New model author"Export prompt as txtprint(prompt_example.generate_prompt())#orprompt_example.generate_prompt_and_save_to_file("example.txt")Export prompt as jsonprompt_example.export_prompt("example.json")
Package: characteristic
characteristicis anMIT-licensed Python package with class decorators that ease the chores of implementing the most common attribute-related object protocols.You just specify the attributes to work with andcharacteristicgives you any or all of:a nice human-readable__repr__,a complete set of comparison methods,immutability for attributes,and a kwargs-based initializer (that cooperates with your existing one and optionally even checks the types of the arguments)withoutwriting dull boilerplate code again and again.This gives you the power to use actual classes with actual types in your code instead of confusingtuples or confusingly behavingnamedtuples.So put down that type-less data structures and welcome some class into your life!characteristic’s documentation lives atRead the Docs, the code onGitHub.
It’s rigorously tested on Python 2.6, 2.7, 3.3+, and PyPy.Authorscharacteristicis written and maintained byHynek Schlawack.The development is kindly supported byVariomedia AG.It’s inspired by Twisted’sFancyEqMixinbut is implemented using class decorators becausesub-classing is bad for you, m’kay?The following folks helped formingcharacteristicinto what it is now:Adam DangoorGlyphItamar Turner-TrauringJean-Paul CalderoneJulian BermanRichard WallTom Prince
Package: characterizethis
# characerizeTHISTools to find out what we should characterize!### AssumptionsAssume all planets have atmospheres (this is likely true for most planets)Assume no planets have clouds or hazes (this is unlikely)Assume a circular orbit (this is largely true)Assume HST WFC3 for followup instrument (this is reasonable)Assume 1 second exposure time with a scan rate of 0.15s (this could be improved for each target)Assume HST WFC3 has no saturation limit. (This could be acheived with scanning)Assume one observation is taken (this is an underestimate)Assume 50 pixels of the detector are illuminated for the scan (this is reasonable)Assume 5 scale heights of atmsophere (this is an approximation)Assume atmosphere is purely hyrdogen (this is likely to be wrong for most small planets)Assume atmosphere is entirely opaque in the WFC3 bandpass (this is an overestimate)Assume starspot free (this is unlikely)Where masses are unknown, assume mass-radius relation from Weiss 2014 (this is an approximation)Assume 2MASS photometry is correct (this is reasonable)Assume planets have no reflection, all light us absorbedAll told, this will provide an overestimate of the signal or the ‘best case’ scenario.
Package: character-range
Character rangeThis package does exactly what it says on the tin:
Create a string or bytes range.fromcharacter_rangeimport(ByteMap,character_range,CharacterMap,string_range,bytes_range)print(list(character_range('a','z')))# 'a', 'b', ..., 'y', 'z'forelementinstring_range('aaa','aba',CharacterMap.ASCII_LOWERCASE):print(element)# 'aaa', 'aab', ..., 'aay', 'aaz', 'aba'forelementinbytes_range(b'0',b'10',ByteMap.ASCII_LOWERCASE):print(element)# b'0', b'1', ..., b'9', b'00', b'01', ..., b'09', b'10'For more information, seethe documentation.InstallationThis package is availableon PyPI:$pipinstallcharacter-rangeContributingPlease seeContributingfor more information.
Package: characters-sn
Characters_SnFunctions for calculation group characters of the symmetric group SnThis code was written by Lizzie Hernandez
for Math 68 Algebraic Combinatorics course in Fall 2021
at Darmouth College[GitHub Link] (https://github.com/lizziehv/math68-final)
[Google Colab Link] (https://colab.research.google.com/drive/1GMeXdseX97ZfMtfsO6Tvf5pijP4Zslc6?usp=sharing)
Package: charactertrigramfuzzyset
Character trigram fuzzy set implementation providing cosine similarity-based
fuzzy matching.This library does that one thing on iterables of strings. Any beyond
that–Levenshtein distance, scoring, bigram fallback, etc.–is left as an
exercise to the reader.Usageimportos.pathfromtimeitimporttimeitimportrequests# Retrieve a file containing around 470,000 English wordsurl='https://github.com/dwyl/english-words/raw/master/words.txt'r=requests.get(url,stream=True)words_path=os.path.expanduser('~/words.txt')ifnotos.path.isfile(words_path):withopen(words_path,'wb')asf:forchunkinr.iter_content(chunk_size=1024):ifchunk:f.write(chunk)# Usageimportcharactertrigramfuzzysetasctfsitems=[line.rstrip()forlineinopen(words_path,'r')]fs=ctfs.CharacterTrigramFuzzySet(items)fs.get('bryan')# Profiling, generally around 10-20 ms per call on my machinetimeit("fs.get('bryan')",setup='''
import charactertrigramfuzzyset as ctfs
items = [line.rstrip() for line in open('{words_path}', 'r')]
fs = ctfs.CharacterTrigramFuzzySet(items)
'''.format(words_path=words_path),number=1000)
Package: charactr-api-sdk
charactr-api-sdk-pythonPython SDK to interact with the charactr API.TerminologyVC-Voice conversion- converting one voice from audio input to another voice.TTS-Text to speech- converting text to voice audio.Featuresmaking TTS requestsmaking VC requestsgetting lists of available voicesInstallationpipinstallcharactr-api-sdkUsageFor the detailed SDK usage, please refer to theSDK Referenceor the./examplesdirectory.Quickstartfromcharactr_apiimportCharactrAPISDK,Credentialssdk=CharactrAPISDK(Credentials(client_key="xxx",api_key="yyy"))tts_voices=sdk.tts.get_voices()tts_result=sdk.tts.convert(tts_voices[0]["id"],"Hello world")How to run examplesClone & install the SDK locallygitclonehttps://github.com/charactr-platform/charactr-api-sdk-pythoncdcharactr-api-sdk-python
pipinstall.Provide credentialsOpen./examples/credentials.pyand provide your credentials. You can find them in yourClient Panelaccount.Use TTSpythonexamples/tts.pyUse TTS Simplex Streamingpythonexamples/tts_stream_simplex.pyUse TTS Duplex Streamingpythonexamples/tts_stream_duplex.pyUse VCpythonexamples/vc.pyUse Voice Clonespythonexamples/clones.py
Package: charade
Charade: The Universal character encoding detectorDetectsASCII, UTF-8, UTF-16 (2 variants), UTF-32 (4 variants)Big5, GB2312, EUC-TW, HZ-GB-2312, ISO-2022-CN (Traditional and Simplified Chinese)EUC-JP, SHIFT_JIS, ISO-2022-JP (Japanese)EUC-KR, ISO-2022-KR (Korean)KOI8-R, MacCyrillic, IBM855, IBM866, ISO-8859-5, windows-1251 (Cyrillic)ISO-8859-2, windows-1250 (Hungarian)ISO-8859-5, windows-1251 (Bulgarian)windows-1252 (English)ISO-8859-7, windows-1253 (Greek)ISO-8859-8, windows-1255 (Visual and Logical Hebrew)TIS-620 (Thai)Requires Python 2.6 or laterCommand-line Toolchardet comes with a command-line script which reports on the encodings of one
or more files:% charade somefile someotherfile
somefile: windows-1252 with confidence 0.5
someotherfile: ascii with confidence 1.0AboutThis is a port of Mark Pilgrim’s excellent chardet. Previous two versions
needed to be maintained: one that supported python 2.x and one that supported
python 3.x. With the minor amount of work placed into this port, charade now
supports both in one codebase.The base for the work was Mark’s last available copy of the chardet source for
python 3000.The ReasonDoes everything have to have a reason? No, but in this case the reason was to
help outrequestsand anyone else who sorely
needed this.What about x, y, or z?If x, y, or z (a colloquialism for other projects that may do the same thing)
do exist and indeed existed before charade, then I’m disappointed that they
didn’t make themselves better known. It would have saved me quite a few hours.maintainer:Ian Cordasco1.0.3 – 2012-01-17Renamechardet.pyscript tocharade
Package: chararray
chararrayA standard mutable character array implementation for Python.>>>fromchararrayimportchararray>>>chars=chararray("abc")>>>charschararray('abc')>>>chars+'def'chararray('abcdef')>>>charschararray('abc')>>>chars+='def'>>>charschararray('abcdef')>>>chars[:3]chararray('abc')>>>chars[3:]chararray('def')>>>chars[3:]='ghi'>>>charschararray('abcghi')>>>chars[0]='A'>>>charschararray('Abcghi')InstallingGet it via pip:pip install chararrayTestingRunpytestType CheckingRunmypy .
Package: charbychar
CHARBYCHARSpice up your text by printing each individual letter instead of the entire string!InstructionsInstall:pip install charbycharAlternatively, you can use:py -m pip install charbycharWrite text:fromcharbycharimport*#use text using the default delay time (0.05s)write_string("Hello, world!")#write text using 1s delay timeslow_write("Hello, world!")#write text using 0.5 delay timemedium_write("Hello, world!")#write text using 0.005 delay timefast_write("Hello, world!")Chew some gum. Coding is always better with gum.
Package: char-classifer
Char Classifier---------Given a short phrase, train a neural network to classify it based on the characters that it contains.The trainer takes in a file of phrases (separated by new line) and a file of target values (separated by new line).To train on the sample data (parts of speech classification):```from phrase_classifier import PhraseClassificationTrainer, PhraseClassifierp = PhraseClassificationTrainer("sample/words", "sample/parts-of-speech")p.train([100, 100], 20, 100)p.save("sample", "example-run")```This will save a trained model with the tag 'example-run' in the sample directory. To use that model, run:```k = PhraseClassifier("sample", "example-run")print k.classify("dog")```