Saravanan666/pypi-org huggingface dataset:
Package: gerdison-imagem-processo
RepositÃ³rio com desenvolvimento dos cÃ³digos, e arquivos, para entrega do Projeto do Curso de Python para Cientistas de dados: CriaÃ§Ã£o de Pacotes de Processamento de Imagens; da plataformaDIO - Digital Innovation One.Processamento de ImagensDescriÃ§Ã£o:O pacote 'processamento_de_imagem' pode ser usado para:Processamento:
	- CorrespondÃªncia de Histograma;
	- Similaridade Estrutural;
	- Redimensionamento de Tamanhos

UtilitÃ¡rios:
	- Leitor de Imagem;
	- Salvador de Imagem;
	- Exibidor de Imagens;
	- Exibidor de Resultados;
	- Exibidor de HistogramaInstalaÃ§Ã£o:Use o gerenciador de pacotespippara instalaÃ§Ã£o do pacote 'processamento_de_imagem':pipinstallprocessamento_de_imagensUso:frompackage_name.module1_nameimportfile1_namefile1_name.my_function()RepositÃ³rio com desenvolvimento dos cÃ³digos, e arquivos, para entrega do Projeto do Curso de Python para Cientistas de dados: CriaÃ§Ã£o de Pacotes de Processamento de Imagens; da plataformaDIO - Digital Innovation One.Processamento de ImagensDescriÃ§Ã£o:O pacote 'processamento_de_imagem' pode ser usado para:Processamento:
	- CorrespondÃªncia de Histograma;
	- Similaridade Estrutural;
	- Redimensionamento de Tamanhos

UtilitÃ¡rios:
	- Leitor de Imagem;
	- Salvador de Imagem;
	- Exibidor de Imagens;
	- Exibidor de Resultados;
	- Exibidor de HistogramaInstalaÃ§Ã£o:Use o gerenciador de pacotespippara instalaÃ§Ã£o do pacote 'processamento_de_imagem':pipinstallprocessamento_de_imagensUso:frompackage_name.module1_nameimportfile1_namefile1_name.my_function()Autor:Esse Projeto: GerdisonLicenseMIT
Package: gerel
GeReLGeReL is a simple library for genetic algorithms applied to
reinforcement learning.NOTE: GeReL is in development.Example:The following usesREINFORCE-ESto solve openaicartpole environmentfromgerel.genome.factoriesimportdensefromgerel.algorithms.RES.populationimportRESPopulationfromgerel.algorithms.RES.mutatorimportRESMutatorfromgerel.model.modelimportModelimportgymimportnumpyasnpfromgerel.populations.genome_seedersimportcurry_genome_seederfromstringimportTemplatedefcompute_fitness(genome):model=Model(genome)env=gym.make("CartPole-v0")state=env.reset()fitness=0action_map=lambdaa:0ifa[0]<=0else1# noqafor_inrange(1000):action=model(state)action=action_map(action)state,reward,done,_=env.step(action)fitness+=rewardifdone:breakreturnfitnessif__name__=='__main__':genome=dense(input_size=4,output_size=1,layer_dims=[2,2,2])weights_len=len(genome.edges)+len(genome.nodes)init_mu=np.random.uniform(-1,1,weights_len)mutator=RESMutator(initial_mu=init_mu,std_dev=0.1,alpha=0.05)seeder=curry_genome_seeder(mutator=mutator,seed_genomes=[genome])population=RESPopulation(population_size=50,genome_seeder=seeder)report_temp=Template('generation: $generation, mean: $mean, best: $best')forgenerationinrange(100):forgenomeinpopulation.genomes:genome.fitness=compute_fitness(genome.to_reduced_repr)population.speciate()data=population.to_dict()mutator(population)report=report_temp.substitute(generation=generation,mean=data['mean_fitness'],best=data['best_fitness'])print(report)Tests:To run all unittests:nosetests
Package: gerent
gerentGerent is a simple and lightweight web-framework for MicroPython.pypi link:https://pypi.org/project/gerent/TODO:beautify pyproject.toml✅ add post and put methods✅ add custom http_headers optioncreate docs (how does it work, pictures)add favicon.ico support✅ create API root, with all url'sadd examplesbeutify micropython code?add unitest testsbeautify web root site, add unified stylequery paramsoptimize create_root_siteCurrently supported devices:Raspberry Pi Pico WESP8266Example:importgerent,socket@gerent.route("/hello/world")defhello_world(request):return(200,{},"Hello from gerent framework!")# create socketaddr=socket.getaddrinfo('0.0.0.0',80)[0][-1]s=socket.socket()s.bind(addr)s.listen(1)# run gerent clientwhileTrue:gerent.listen(s)Docs:How does it work?While defining routes, for example:@gerent.route("/hello/world",['POST'])defhello_world(request):return(200,{},"Hello from gerent framework!")Gerent backend creates an entry in url linker register:{'route':'/hello/world','methods':['POST'],'function':<functionhello_worldat0x2000c1c0>}Url linker contains basic informations about route, avaliable methods and linked function for defined url.While Gerent client is running:whileTrue:gerent.listen(socket)it's listening for incoming traffic, analyzing requests and properly responding to client's requests.
Package: gerepotools
Repo-tools for Guichet Entreprises_              _     
                           | |            | |    
 _ __ ___ _ __   ___ ______| |_ ___   ___ | |___ 
| '__/ _ \ '_ \ / _ \______| __/ _ \ / _ \| / __|
| | |  __/ |_) | (_) |     | || (_) | (_) | \__ \
|_|  \___| .__/ \___/       \__\___/ \___/|_|___/
         | |                                     
         |_|InstallationYou can download the latest version of repo toolshereConfigurationThe conf file is located in the upref user's folder  :C:\Users\Michel\AppData\Roaming\.upref\Usageusage: repo-tools.py [-h] [--windows] [--verbose] --filename filename
                 [--url url] [--login login] [--password url] --group
                 group --repo_id repo_id [--version version]
                 [--extension extension] [--jira] [--jira_url jira_url]
                 [--jira_login jira_login] [--jira_password jira_password]
                 [--jira_project jira_project]This program take a file or a directory and send it into a repo.Positional arguments--filename filename, -f filename
                    file to upload. {artifact}-{version}.{extension}
--group group, -g group
                    group
--repo_id repo_id, -r repo_id
                    repo_idOptional argumentsThis program take a file and upload it on repo-h, --help            show this help message and exit
--windows, -w         Define if we need all popups windows.
--verbose, -v         Put the logging system on the console for info.
--url url, -u url     url of repo
--login login, -l login
                    login
--password url, -p url
                    password

--version version, -V version
                    artifact version
--extension extension, -e extension
                    Extension of the file, this can be usefull if the file
                    extension is tar.gz.
--jira, -j            jira login
--jira_url jira_url, -U jira_url
                    jira url
--jira_login jira_login, -L jira_login
                    jira login
--jira_password jira_password, -P jira_password
                    jira password
--jira_project jira_project, -o jira_project
                    jira projectExampleupload end create a Jira BL :>python repo-tools.py -w -f www-2019.10.11 -g fr.ge.gpart -r releases -j
Package: geringoso
geringosoA Spanish to Geringoso library and filterExampe usage:$ geringoso hola, sol
hopolapa, sopol
$ head -n 7 hombres_necios.txt | geringoso


    Hopombrepes nepeciopos quepe apacupusápais
    apa lapa mupujeper sipin rapazópon
    sipin veper quepe sopois lapa opocapasiópon
    depe lopo mipismopo quepe cupulpápais:
Package: gerlida-cpf
package_nameDescription.
The package gerlida_cpf is used to:
- Generate a random CPF number
- Check if a CPF number is validInstallationUse the package managerpipto install package_namepipinstallgerlida_cpfUsagefromgerlida_cpf.gera_cpfimportgerador_cpfgerador_cpf.geracpf()fromgerlida_cpf.valida_cpfimportvalidacpfvalida_cpf.validacpf()AuthorMy_nameLicenseMIT
Package: germail
Germailصانع اميلات مؤقتة تستخدم خدمة من موقع
mail.tm
و تم عمل لها برنمج بسيط من خلال بايثون
طريقة التثبيت هيInstall germailامر التثبيت هوpip3 install germail -UImport Germailلما تنتهي من التثبيت يمكنك استدعاء المكتبة بكتابة كودimport germailCreate mailسيظهر لك الاميل و كلمة السر بعد كتابة الكود هذا :user=germail.Germail()Show messagesستظهر لك جميع الرسائل بستخدام الكود التالي :messages=user.get_messages()Show last messageاظهار فقط اخر رسالةlast=user.get_last_message()Show message by ID of messageاظهار الرسالة عن طريق
id
الخاص فيها (ملاحظة يمكنك العثور على
id
من خلال اظهار جميع الرسائل ستظهر معها
id )msg=user.read_message("515454465414494ds444554")Login into other mailيمكنك تسجيل الدخول الى اميل اخر تم صنعه من قبل من خلال الكود :user.login("email@exmple.com","pasword")Delete mail or Renew email or Create other new Mailيمكنك حذف الاميل او تجديد الاميل او صنع اميل جديد من خلال هذي الاكواد التاليةuser.delete_account()oruser.renew_account()oruser.new_account()Exemple Code for how to useهذا مثال للكود لكن لا تنسى ان ترسل رسالة حقيقية لهذا الايميل من اميل اخرimport germail
from time import sleep
user=germail.Germail()


input("wait message press enter")
sleep(5)
try:
    #get last message
    message= user.get_last_message()
    print("text of message : ", message.text)
    print("id of message : ",message.id_)
    print("html of message : ",message.html)

except:
    print("\n\nnot have a message")

#get info email and pass
email=user.get_mail()
password=user.get_password()
user=None

# parametre create=False = "not create new mail"
user2=germail.Germail(create=False)
user2.login(email,password)
print("\n\n\n#######################################################\n",
            "Print all message",
            "\n################################################\n\n\n")
print(user2.get_messages())

user2.renew_account()
user2.delete_account()
Package: germalemma
GermaLemmaDecember 2019, Markus Konradmarkus.konrad@wzb.eu/Berlin Social Science CenterA lemmatizer for German language textGermalemma lemmatizes Part-of-Speech-tagged German language words. To do so, it combines a large lemma dictionary (an excerpt of theTIGER corpus from the University of Stuttgart), functions from the CLiPS "Pattern" package, and an algorithm to split composita.InstallationEasy option: Installing from PyPI viapipYou can install the package fromPyPIviapip:pip install -U germalemmaDownloading and installing from sourceIn order to use GermaLemma, you will need to install some additional packages (seeRequirementssection below) and then download theTIGER corpus from the University of Stuttgart. You will need to use the CONLL09 format,notthe XML format.
The corpus is free to use for non-commercial purposes (seeLicense Agreement).Then, you should convert the corpus into pickle format for faster loading by executinggermalemma.pyand passing the path to the corpus file in CONLL09 format:python germalemma.py tiger_release_[...].conll09This will place alemmata.picklefile in thedatadirectory which is then automatically loaded.Part-of-Speech (POS) TaggingYou will need to applyPart-of-Speech (POS) taggingto your text before you can lemmatize its words. Seethis blog poston how to do that.UsageYou have set up GermaLemma to use the TIGER corpus (as explained above). You have tokenized your text (e.g. with NLTK). You have POS-tagged your tokens. Now you can use GermaLemma:fromgermalemmaimportGermaLemmalemmatizer=GermaLemma()# passing the word and the POS tag ("N" for noun)lemma=lemmatizer.find_lemma('Feinstaubbelastungen','N')print(lemma)# -> lemma is "Feinstaubbelastung"Valid POS tagsYou can pass POS tags from theSTTS tagset, however, only four POS tags can be processed:'N...' (nouns)'V...' (verbs)'ADJ...' (adjectives)'ADV...' (adverbs)All other POS tags will result in aValueErrorso you should wrap the call tofind_lemmain atry-except block.AccuracyGermaLemma's accuracy was evaluated using a sample of 696 POS tagged and manually lemmatized words from a sample of paragraphs from proceedings of the European Parliament, Goethe's "Werther", Kafka's "Verwandlung" and a news article from the website of the WZB (see samples in folder "eval_texts").Under the assumption that the POS tag is correct(only those words were selected), GermaLemma finds the correct lemma in 99.43% of the cases. For comparison,Patternachieved 95.11% for the same sample.RequirementsPython 3.6 or newerrequired packagePyphenoptional packagePatternLite(This package is optional but highly recommended as it boosts the lemmatizer's accuracy.)LicenseApache License 2.0. SeeLICENSEfile.The TIGER corpus isnotpart of this repository and has to be downloaded separately under separate license conditions.
Package: german
German PreprocessingPreprocess German texts to do some serious natural-language processing.clean textsremove stopwords (as defined byspaCy)lemmatizelower-case, and remove all punctions, digits are replaced with "0"Installationpip install germanUsagefromgermanimportpreprocesspreprocess(['Johannes war einer von vielen guten Schülern.','Julia trinkt gern Tee.'],remove_stop=True)# ['johannes gut schüler', 'julia trinken tee']LicenseMIT.SponsoringThis work was created as part of aprojectthat was funded by the GermanFederal Ministry of Education and Research.
Package: germanetpy
germanetpyWelcome. This is the Python API for the German wordnet GermaNet. GermaNet is a lexical-semantic net that relates German nouns, verbs, and adjectives semantically by grouping lexical units that express the same concept into synsets and by defining semantic relations between these synsets.
This API can be used to extract structured information from the GermaNet with python.
More information about GermaNet can be found on the following page:https://uni-tuebingen.de/en/142806InstallationYou can install germanetpy from PyPI (https://pypi.org/project/germanetpy/):pip install germanetpyGet the GermaNet data as XML files and put all files in a data directory. When you use the API to load the data, the path pointing to the directory containing the XML files needs to be specified. The API is supported with Python 3.How to useYou can read the documentationhereThe API provides functionality that can be used to load the data from GermaNet and query it. The data has to be retrieved
via a license agreement from the University of Tübingen, Seminar für Sprachwissenschaften:https://uni-tuebingen.de/en/142828To use the data for queries you first have to create a Germanet object, which loads the data specified as an argument once. This takes a few seconds:from germanetpy import germanet

germanet_object = germanet.Germanet(path_to_the_GermaNet_XML_files)This repository also provides a Tutorial [https://github.com/Blubberli/germanetpy/blob/master/germanetpy_tutorial.ipynb] that shows how to use the API to query GermaNet.
If you want to use the tutorial as an interactive jupyter notebook, clone this repository:git clone https://github.com/Germanet-sfs/germanetTutorials.gitand follow the instructions in the READMEhttps://github.com/Germanet-sfs/germanetTutorials
Package: german-foodemoji
foodemojiDecorate a German text (e.g. restaurant menu) with food emojisExample>>>importfoodemoji>>>text="""Hähnchenbrust mit ApfelrotkrautVegetarische MaultaschenKartoffelknödelPaniertes Schnitzel mit Pommes fritesRinderbraten, Rotweinsauce und Spätzle""">>>print(foodemoji.decorate(text))"""Hähnchenbrust :rooster: mit Apfelrotkraut :red_apple:Vegetarische :green_heart: MaultaschenKartoffelknödel :potato:Paniertes Schnitzel mit Pommes frites :french_fries:Rinderbraten :cow:, Rotweinsauce :wine_glass: und Spätzle""">>>importemoji>>>print(emoji.emojize(foodemoji.decorate(text)))"""Hähnchenbrust 🐓 mit Apfelrotkraut 🍎Vegetarische 💚 MaultaschenKartoffelknödel 🥔Paniertes Schnitzel mit Pommes frites 🍟Rinderbraten 🐮, Rotweinsauce 🍷 und Spätzle""">>>text2="""Gegrillte Hähnchenbrust mit gekochter HähnchenbrustGebratenes Hähnchen mit Hähnchenschnitzel""">>>print(foodemoji.decorate(text2))"""Gegrillte Hähnchenbrust :rooster: mit gekochter Hähnchenbrust :rooster:Gebratenes Hähnchen :rooster: mit Hähnchenschnitzel :rooster:""">>>print(foodemoji.decorate(text2,line_by_line=True))"""Gegrillte Hähnchenbrust mit gekochter Hähnchenbrust :rooster:Gebratenes Hähnchen mit Hähnchenschnitzel :rooster:"""Installpip install german-foodemojiSee:https://pypi.org/project/german-foodemoji/RequirementsPython 3.7+To actually print the unicode emojis and for the units tests the packageemoji>=2.1.0 is required:pip install emoji
Package: german-gender-finder
German-gender-finderFind the gender of the German word.You can use this script to find out what article your german word needs. Der, Die or DasUsageFinding the gender of the word "Besuch" directly from the command line (cmd):Or from within a scriptimportfind_genderprint(find_gender.get_gender_of_word('mutter'))#{'word': 'mutter', 'definite_article': 'die', 'indefinite_article': 'eine', 'warning': 'Sure: Found in word list, highly reliable'}NotesThe script first searches a world list.If the script cannot find the word in the list it will use grammar rules to find its gender.All words that are exceptions to rules should be in the list.return valuesThe script always returns a dictionary with a warning message detailing the reliability:# very reliable{'word':'somewordyouchose','definite_article':'die','indefinite_article':'eine','warning':'Sure: Found in word list, highly reliable'}# very reliable{'word':'somewordyouchose','definite_article':'der','indefinite_article':'ein','warning':'Sure: male due to masculine ending'}# not sure, see warning message!{'word':'somewordyouchose','definite_article':'der','indefinite_article':'ein','warning':'Unsure: However 80% of words ending in "en" are masculine'}# all messages you could get:'warning':'Sure: Found in word list','warning':'Sure: male due to masculine ending','warning':'Sure: female due to feminine ending','warning':'Sure: neuter due to neuter ending','warning':'Unsure: However 80% of words ending in "en" are masculine','warning':'Unsure: However 60% of nouns ending in "el" are masculine','warning':'Unsure: However 60% of nouns ending in "er" are masculine','warning':'Unsure: However 90% of nouns ending in "e" are masculine','warning':'Unsure: However 90% of nouns starting with "ge" are feminine','warning':'Unsure: Most nouns ending in -t originating from verbs are feminine.','warning':'Not_found: word not found',The words in the word list are taken from:https://github.com/mejutoco/german-grammar-statisticsI removed all words without a gender assigned.
Package: germaniumdrivers
This is the optional drivers package.Germanium is a set of extensions on top of the regular WebDriver API, allowing
for a super easy creation of tests. It’s opensource and free:pip install -U germanium[germaniumdrivers]Simply put Germanium is a Web Testing API that doesn’t disappoint:from germanium.static import *
from time import sleep

open_browser("ff")
go_to("http://www.google.com")
type_keys("germanium pypy<enter>", Input("q"))
wait(Link("Python Package Index"))
click(Link("Python Package Index"))
sleep(5)
close_browser()Here is the [usage documentation](http://germaniumhq.com/documentation/), or as [PDF](http://germaniumhq.com/documentation/germanium-usage.pdf)
Package: german-lemmatizer
German LemmatizerA Python package (using a Docker image under the hood) tolemmatizeGerman texts.Built upon:IWNLPuses the crowd-generated token tables onde.wikitionary.GermaLemma: Looks up lemmas in theTIGER Corpusand usesPatternas a fallback for some rule-based lemmatizations.It works as follows. FirstspaCytags the token with POS. ThenGerman Lemmatizerlooks up lemmas on IWNLP and GermanLemma. If they disagree, choose the one from IWNLP. If they agree or only one tool finds it, take it. Try to preserve the casing of the original token.You may want to use underlying Docker image:german-lemmatizer-dockerInstallationInstallDocker.pip install german-lemmatizerUsageRead and accept thelicense terms of the TIGER Corpus(free to use for non-commercial purposes).Make sure the Docker daemons runs.Write some Python codefromgerman_lemmatizerimportlemmatizelemmatize(['Johannes war ein guter Schüler','Sabiene sang zahlreiche Lieder'],working_dir='*',chunk_size=10000,n_jobs=1,escape=False,remove_stop=False)The list of texts is split into chunks (chunk_size) and processed in parallel (n_jobs).Enable theescapeparameter if your text contains newslines.remove_stopremoves stopwords as defined by spaCy.LicenseMIT.
Package: german-nouns
German nounsA comma seperated list of ~100 thousand German nouns and their grammatical properties (tense, number, gender) as CSV file. Plus a module to look up the data and parse compound words. Compiled from theWiktionaryDE.The list can be found here:german_nouns/nouns.csvIf you want to look up nouns or parse compound words, install this package (for Python 3.8+) and follow the instructions below:Installationpip install german-nounsLookup wordsfrompprintimportpprintfromgerman_nouns.lookupimportNounsnouns=Nouns()# Lookup a wordword=nouns['Fahrrad']pprint(word)# Output:[{'flexion':{'akkusativ plural':'Fahrräder','akkusativ singular':'Fahrrad','dativ plural':'Fahrrädern','dativ singular':'Fahrrad','dativ singular*':'Fahrrade','genitiv plural':'Fahrräder','genitiv singular':'Fahrrades','genitiv singular*':'Fahrrads','nominativ plural':'Fahrräder','nominativ singular':'Fahrrad'},'genus':'n','lemma':'Fahrrad','pos':['Substantiv']}]# parse compound wordwords=nouns.parse_compound('Vermögensbildung')print(words)# Output:['Vermögen','Bildung']# Now lookup nouns['Vermögen'] etc.Compiling the listTo compile the list yourself, you need Python 3.8+ andPoetryinstalled.1. Clone the repository and install dependencies withPoetry:$gitclonehttps://github.com/gambolputty/german-nouns
$cdgerman-nouns
$poetryinstall2. Compile the list of nouns from a Wiktionary XML file:Find the latest XML-dump files here:https://dumps.wikimedia.org/dewiktionary/latest, for examplethis oneand download it. Then execute:$poetryrunpython-mgerman_nouns.parse_dump/path-to-xml-dump-file.xml.bz2The CSV file will be saved here:german_nouns/nouns.csv.Removegerman_nouns/index.txtto let the script recreate the word-index when using the lookup methods.
Package: germansentiment
German Sentiment Classification with BertThis package provides a very simple interface todetect the sentimentof German texts. It uses the Googles Bert architecture trained on 1.834 million samples. The training data contains texts from various domains like Twitter, Facebook and movie, app and hotel reviews. You can find more information about the dataset and the training process in thepaper.InstallTo get started install the package frompypi:pipinstallgermansentimentUsagefromgermansentimentimportSentimentModelmodel=SentimentModel()texts=["Mit keinem guten Ergebniss","Das ist gar nicht mal so gut","Total awesome!","nicht so schlecht wie erwartet","Der Test verlief positiv.","Sie fährt ein grünes Auto."]result=model.predict_sentiment(texts)print(result)The code above will output following list:["negative","negative","positive","positive","neutral","neutral"]Output class probabilitiesfromgermansentimentimportSentimentModelmodel=SentimentModel()classes,probabilities=model.predict_sentiment(["das ist super"],output_probabilities=True)print(classes,probabilities)['positive'][[['positive',0.9761366844177246],['negative',0.023540444672107697],['neutral',0.00032294404809363186]]]ResultsIf you are interested in code and data that was used to train this model please have a look atthis repositoryand ourpaper. Here is a table of the F1 scores that his model achieves on following datasets. Since we trained this model on a newer version of the transformer library, the results are slightly better than reported in the paper.DatasetF1 micro Scoreholidaycheck0.9568scare0.9418filmstarts0.9021germeval0.7536PotTS0.6780emotions0.9649sb10k0.7376Leipzig Wikipedia Corpus 20160.9967all0.9639CiteFor feedback and questions contact me via e-mail or Twitter@oliverguhr. Please cite us if you found this useful:@InProceedings{guhr-EtAl:2020:LREC,
  author    = {Guhr, Oliver  and  Schumann, Anne-Kathrin  and  Bahrmann, Frank  and  Böhme, Hans Joachim},
  title     = {Training a Broad-Coverage German Sentiment Classification Model for Dialog Systems},
  booktitle      = {Proceedings of The 12th Language Resources and Evaluation Conference},
  month          = {May},
  year           = {2020},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {1620--1625},
  url       = {https://www.aclweb.org/anthology/2020.lrec-1.202.pdf}
}