Saravanan666/pypi-org huggingface dataset:
Package: java-stream
Python StreamThe power of Java stream now available in PythonExplore the docs »View Demo·Report Bug·Request FeatureTable of ContentsTable of ContentsAbout The ProjectBuilt WithGetting StartedPrerequisitesInstallationUsageRoadmapContributingLicenseContactAbout The ProjectWhat is Stream?Stream represents a sequence of objects from a source, which supports aggregate operations.Following are the characteristics of a Stream:Sequence of elements− A stream provides a set of elements of specific type in a sequential manner. A stream gets/computes elements on demand. It never stores the elements.Source− Stream takes Collections, Arrays, or I/O resources as input source.Aggregate operations− Stream supports aggregate operations like filter, map, limit, reduce, find, and so on.Pipelining− Most of the stream operations return stream itself so that their result can be pipelined. These operations are called intermediate operations and their function is to take input, process them, and return output to the target. toList() and toSet() methods are terminals operation which is normally present at the end of the pipelining operation to mark the end of the stream.Automatic iterations− Stream operations do the iterations internally over the source elements provided, in contrast to Collections where explicit iteration is required.Built WithPythonGetting StartedFollow this steps for install this tool in the right way.PrerequisitesThat's all you need to use Streams:python3sudoaptinstallpython3pipsudoaptinstallpython3-pipInstallationInstall the module withpippipinstalljava-streamImport the module in your projectfromstreamimportStreamUsageHere some example of how to use Streams:Generate a list of 100 random numbersStream.randint(1,100).limit(100).toList()Print the numbers from 1 to 100Stream.integers().limit(100).forEach(print)Generate a list made of zeros with a length of 10Stream.constant(0).limit(10).toList()Generate a list of squares of the number from 1 to 20IntStream.integers().map(lambdax:x**2).limit(20).toList()Generate a set of the first 100 odds numberIntStream.odds().limit(100).toSet()Generate a list of all the primes number smaller than 1000Stream.primes().takeWhile(lambdax:x<1000).toList()RoadmapSee theopen issuesfor a list of proposed features (and known issues).ContributingContributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull RequestLicenseDistributed under the GNU License. SeeLICENSEfor more information.ContactAlessandro Mazzoli -@alessandro.py-developer.alessandro.mazzoli@gmail.comProject Link:https://github.com/alemazzo/python-java-stream
Package: java-test-genie
JavaTestGenieDemoClick on the image to watch the videoInstallationpipinstalljava-test-genieUsageBefore runninggenie, set your OpenAI API key withexport OPENAI_API_KEY=<API-KEY-HERE>. You can obtain it athttps://platform.openai.com/account/api-keysEnsure that you are in a at the same level withsrc/when running the tool.You need to create a config file named.genie.jsonwithin your java repository. This file should be at the same level withsrc/as well as where you will rungenie. In this file, you can specify which directories & files to include and exclude. The example below includes theservice/directory but excludesservice/interface. Similarly, you can specify file names.{"include":[{"parent_dir":"src/main/java/com/ase/restservice","dir_names":["service"],"file_names":[]}],"exclude":[{"parent_dir":"src/main/java/com/ase/restservice","dir_names":["service/interface"],"file_names":[]}]}The file is case-sensitive. Ensure that you do not list files in the "exclude" section unless they already match a path in the "include" section. Excluding a path will delete all matches, even if a specific class is explicitly listed in the "include" section. For instance, if you exclude "model/" but include "model/Account.java", it will not work. Instead, simply include "model/Account.java" and leave the "exclude" section empty, as the "model/" directory is already skipped.Finally, you can run it with:genieExampleHere is an example repo that you can use the config file above with.gitclonehttps://github.com/boraelci/kaiserschmarrn.gitArguments--help: Displays the help message and lists all available arguments.--mode: Allows you to switch between two modes:methods(default): Generates test methods for individual methods within the input class. This mode is suitable for large input classes.classes: Generates a complete test class, including imports, package name, and setup. This mode provides more comprehensive functionality but is not suitable for large input classes. If the input class is too large, you may encounter an error likeError: this file is too large.--do_overwrite: Enables automatic overwriting of existing test files without asking for confirmation. By default, this is set to false to protect existing test files. To enable automatic overwriting, just include--do_overwritewithout specifying a parameter.--batch-size: Specifies the number of methods to process at the same time. It defaults to 15, but you can adjust this value based on your requirements.LimitationsCurrently, only 1 class per Java file is supported. The tool may produce errors if you supply a path that corresponds to a file with more than 1 class in it.GrammarParsing Java files with the Tree-sitter library requires grammar files. They were obtained in the following way for this tool.For macOSgitclonehttps://github.com/tree-sitter/tree-sitter-java.gitcdtree-sitter-java
tree-sittergenerate
gcc-shared-olibtree-sitter-java.dylib-Isrcsrc/parser.cFor WindowsUsed the one provided asjava-grammar.so
Package: java-to-python-transpiler
JavaToPythonTranspilerTranspiles Java source code into Python source codeInstallationNotImplementedFunctionsjava_to_python_from_stringjava_to_python_from_string(user_input: str) -> str | TranspilerFailureThis is the primary function provided by this library.This function takes in a String (user_input) and transpiles it into a
result.This function will return either a String (which is the python source), or
it may fail, and return aTranspilerFailureobject. This object contains a
singular field,error_message, which is a String representing the error
that occurred.java_to_python_from_filejava_to_python_from_file( file_path: Optional[str] = None, file_object: Optional[TextIOWrapper] = None ) -> str | TranspilerFailureThis function is the secondary purpose of this library; it allows one to
transpile the contents of a file (of java source code) to Python source.file_path(optional) is a String that defaults to None; if set to None,
thenfile_objectmust have a value.file_object(optional) is a TextIOWrapper that defaults to None; if set
to None, thenfile_pathmust have a value.if bothfile_pathandfile_objecteach have a value of None, then a
ValueError will be thrown.DataTranspilerFailureThis class represents a failure that occurred in the Transpiler.error_message: strerror_messagerepresents the error that occurred; it is a String of
information that informs the user what went wrong.
Package: java-utilities
java-utilitiesjava-utilitiesis a helper package to run and introspect ajavabinary.
It can be used as a library, or with the provided standalone scripts.QuickstartAvirtual environmentis recommended.To use from the command line:pipinstalljava-utilities

java-home

java-propertyjava.specification.versionTo use from python:fromjava_utilitiesimportjava_home,lookup_propertyprint(f"Java home is '{java_home()}'")property_name="java.specification.version"print(f"Java specification version is '{lookup_property(property_name)}'")
Package: javec
# JAVEC
Just another virtual environment creator## InstallationInstall with pippython3 -m pip install javec## Usage### No arguments
If you run main.py with no additional arguments:javecIt will create virtual environment in current working directory with the same name as current working directory, but with dot in front (hidden file in Linux). To run the virtual environment run:source ./.virenvFolder/bin/activate### -a
Running main.py with -a argument:javec -aIn addition to creation of virtual environment it causes creation of script shell named “.activator.sh”. Now activation of virtual environment will require running following code:source .activator.sh### -g, –gitignore
Running main.py with -g argument:javec -gIn addition to creation of virtual environment it causes creation of .gitignore file. The .gitignore file is a copy of gitignore_example provided in the repository. It was taken from [this repository](https://github.com/github/gitignore).### –swap-gitignore <path>
It is possible to change the gitignore_example from this repository file with one you commonly use by using –swap-gitignore path:javec –swap-gitignore /path/to/your/own/.gitignoreIf used with -g argument the first action will be swapping gitignore_example and then creation of .gitignore in the current working directory.### -i, –install <packages>
Install given packages. This argument will simply call the following command:/path/to/virtualenvironment/bin/python3 -m pip install <packages>Moreover packages names will be added to requirements_javec.txt file. There is no need to previously activate the virtual environment but you have to call
it from the parent directory(where JAVEC created the virtual environment)### -r, -u, –remove, –uninstall <packages>
Uninstall given packages. This will simply call the following command:/path/to/virtualenvironment/bin/python3 -m pip uninstall -y <packages>Moreover packages names will be removed from requirements_javec.txt file. There is no need to previously activate the virtual environment but you have to call
it from the parent directory(where JAVEC created the virtual environment)### –versionRequirements
Create requirements.txt file with package version number. This calls following command:/path/to/virtualenvironment/bin/python3 -m pip freezeThe output is then filtered with package names installed with this tool (from requirements_javec.txt). requirements.txt will contain only package names that
you installed using JAVEC.### –print-gitignore
This argument will print the contents of current gitignore_example that is used to generate .gitignore file with -g commandjavec –print-gitignore## Have fun![![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)
Package: javelin-cli
JavelinCLI tool for managing Spearly deployments.RequirementsPython 3.10+GITHUB_ACCESS_TOKENenvironment variable set to aGitHub Personal Access Tokenwithreposcope (Ref)AWS IAM Userwithcodepipeline:StartPipelineExecutionpermission to the required resources (Ref)Installationbrewinstallpyenv
pyenvinstall3.10:latest[pyenvexec]pipinstalljavelin-cliUsagepython-mjavelin--helpContributionRun lintpylintjavelinIncrease version number in these filespyproject.tomljavelin/__init__.pyCreate and push release commitgitcommit-mv1.2.3
gittagv1.2.3
gitpush
gitpush--tagsBuild and publishpoetrybuild
poetrypublish
Package: javelin-sdk
Javelin: an Enterprise-Scale, Fast LLM GatewayThis is the Python client package for Javelin.For more information about Javelin, seehttps://getjavelin.ioJavelin Documentation:https://docs.getjavelin.ioInstallationpipinstalljavelin_sdkQuick Startfromjavelin_sdkimport(JavelinClient,Route,NetworkError,RouteNotFoundError,UnauthorizedError,)# create a route objectquery_data={"model":"gpt-3.5-turbo","messages":[{"role":"system","content":"You are a helpful assistant that translates English to French."},{"role":"user","content":"AI has the power to transform humanity and make the world a better place"},],"temperature":0.8,}# query the llmtry:response=client.query_route("test_route_1",query_data)exceptRouteNotFoundErrorase:print("Route Not Found")
Package: javiche
javicheSmall package to enable using ceviche with a JAX optimizer easily.InstallThis package is not yet published. As soon as it is install with:pipinstalljavicheorcondainstalljavicheHow to useImport the decoratorfromjavicheimportjaxitdecorate your function (will be differentiated using ceviches jacobian
-> HIPS autograd)@jaxit()defsquare(A):"""squares number/array"""returnA**2Now you can use jax as usual:grad_fn=jax.grad(square)grad_fn(2.0)Array(4., dtype=float32, weak_type=True)In this toy example that was already possible without thejaxit()decorator. Howeverjaxit()decorated functions can contain autograd
operators (but no jax operators):importautograd.numpyasnpadefsin(A):"""computes sin of number/array using autograds numpy"""returnnpa.sin(A)grad_sin=jax.grad(sin)try:print(grad_sin(0.0))exceptExceptionase:print(e)The numpy.ndarray conversion method __array__() was called on the JAX Tracer object Traced<ConcreteArray(0.0, dtype=float32, weak_type=True)>with<JVPTrace(level=2/0)> with
  primal = 0.0
  tangent = Traced<ShapedArray(float32[], weak_type=True)>with<JaxprTrace(level=1/0)> with
    pval = (ShapedArray(float32[], weak_type=True), None)
    recipe = LambdaBinding()
See https://jax.readthedocs.io/en/latest/errors.html#jax.errors.TracerArrayConversionError@jaxit()defcos(A):"""computes sin of number/array using autograds numpy"""returnnpa.cos(A)grad_cos=jax.grad(cos)try:print(grad_cos(0.0))exceptExceptionase:print(e)-0.0UsecaseThis library is intended for use with ceviche, while running a JAX
optimization stack as demonstated in theinverse design
example
Package: jawa
JawaJawa is a human-friendly library for assembling, disassembling, and exploring
JVM class files. It's highly suitable for automation tasks.NOTE: The assembler doesnotcurrently implement Stack Maps, an
artificially complex requirement for ClassFiles generated for Java 7 and
above to properly verify (unless you turn it off with -XX:-UseSplitVerifier).
However, assembled files targeting Java 6 will still work with 7 and above.DocumentationAPI documentation & examples are available athttp://jawa.tkte.chLicenceJawa is available under the MIT licence. See LICENCE.
Package: jawa-fixed
JawaJawa is a human-friendly library for assembling, disassembling, and exploring
JVM class files. It's highly suitable for automation tasks.NOTE: The assembler doesnotcurrently implement Stack Maps, an
artificially complex requirement for ClassFiles generated for Java 7 and
above to properly verify (unless you turn it off with -XX:-UseSplitVerifier).
However, assembled files targeting Java 6 will still work with 7 and above.DocumentationAPI documentation & examples are available athttp://jawa.tkte.chWhyjawa-fixed?The current version ofjawais not maintained anymore, as work is currently in progress for its replacement:lawu.
As such this project serves as a way to improve on the currently working library for Java bytecode manipulation.LicenceJawa is available under the MIT licence. See LICENCE.
Package: jawalang
Jawa-LanguageJawa-Language, Programming language for javanese people.
this language is based on python.RequiredPython 3.xInstallation>pip3installjawalangOr clone this repository and>pip3install-e.Run>jawalangrun<your_file.jw>Syntax HighlighterInstall Visual Studio Code extensionJawa-Language-SupportExampleYou can find more inexamplefoldera=0b=1# if a == byenapodokarob:nyetak("podo")# elif a != b:liyaneturabedokarob:nyetak("bedo")# elseliyane:nyetak("Bedo cuk")# Short hand if elsenyetak("Bedo")yenabedokarobliyanenyetak("podo")
Package: jawa-repo
RepoCommande et hooks Git pour l'environnement de développement des JAWAsInstallationPython 3(guides d'installation)gnome-keyring, si la machine est sous LinuxRepo peut ensuite être installé via la commande suivante :pip3installjawa-repoAlternativement, Repo et toutes ses dépendances sont installées lors de la configuration viajawa-setup.UtilisationPour configurer un dépôt Git pour le workflow JAWA, c'est-à-dire y ajouter les hooks nécessaires :reposetupPour commencer à travailler sur un ticket :repostart[feature|fix|cr|hf]<ticket_id>
Package: jawbone-up
JawboneUP APIThis is a wrapper for the Jawbone UP API.
It has convenience methods for auth, access token, refresh token, and api calls.For terminologies, refer to the documentation here:https://jawbone.com/up/developer/authenticationUsage:from jawbone import Jawbone
jb = Jawbone(client_id, client_secret, redirect_uri, scope=’’)The app can be authorized for accessing specific data using the “scope”
The parameter “scope”, by default is ‘basic_read’, which can be set as per the application’s requirements.
Multiple scopes can be authorized by using space delimiters.To see the list of available scopes, refer:https://jawbone.com/up/developer/authentication(under the heading The “scopes” allowed by the system are)So, to use the package:Initialization:jb = Jawbone(client_id, client_secret, redirect_uri, scope=’basic_read extended_read’)To make calls on behalf of the user, refer this documentation:https://jawbone.com/up/developer/authenticationTo get the authorization token:jb.auth()This call fetches the authentication URL. You should redirect the user to the generated authentication url. Upon successful authorization, the user is redirected to the “redirect_uri” specified. The “code” is specified as a GET parameter.If there was an error, the response would be to the “redirect_uri” with GET parameter “error”Access TokenOnce we have the code, you can get the auth code by callingtoken = jb.access_token(code)Save the generated token response json.The response, if 200 has the following components as json:access_token, token_type, expires_at, refresh_tokenStore these in the database, for future api calls.Refresh TokenThe generated token from the above step has an expiry of 1 year.
The refresh token provided as a part of the access_token() call, can be used to obtain the new credentialsresponse = jb.refresh_token_call(refresh_code)API Callsapi_call is a generic method for calling any endpoint.
Documentation on endpoints here:https://jawbone.com/up/developer/endpointsTo make an API call to get sleep data:endpoint = nudge/api/v.1.0/sleep
response = jb.api_call(access_token, endpoint)A response is a json with status_code (200, 400, etc). Parse the json for the response data
If response.status == 200, the response.get(“error”) contains the message.The library dependencies include:urllib
requests
Package: jawiki
jawikijawiki はウィキペディアからページ情報を取得する Python ライブラリです。>>> import jawiki
>>> jawiki.page("Wikipedia")
<WikipediaPage 'ウィキペディア'>
ウィキペディア（英: Wikipedia）は、ウィキメディア財団が運営しているインターネット百科事典である。コピーレフトなライセンスのもと、サイトにアクセス可能な誰もが無料で自由に編集に参加できる。世界の各言語で展開されている。
「ウィキペディア（Wikipedia）」という名前は、ウェブブラウザ上でウェブページを編集することができる「ウィキ（Wiki）」というシステムを使用した「百科事典」（英: Encyclopedia）であることに由来する造語である。設立者の1人であるラリー・サンガーにより命名された。

>>> jawiki.search("日本")
['日本', '日本の漫画作品一覧', '日本の鉄道駅一覧', '日本のインターチェンジ一覧', '日本実業出版社', '日本の鉄道路線一覧', '日本の資格に関する一覧の一覧', '日本百名湯', '年度別日本公開映画', '日本の郵便番号']

>>> page = jawiki.page("Python")
>>> page.title
'Python'
>>> page.url
'https://ja.wikipedia.org/wiki/Python'
>>> page.content
'Python（パイソン）は、汎用のプログラミング言語である。コードがシンプルで扱いやすく設計されており、C言語などに比べて、さまざまなプログラムを分かりやすく、少ないコード行数で書けるといった特徴がある。\n\n\n== 概要 ==\n文法を極力単純化してコードの可読性を高め、読みやすく、また書きやすくしてプログラマの作業性とコードの信頼性を高めることを重視してデザインされた、汎用の高水準言語である。反面、実行速度はCに比べて犠牲にされている。\n核となる本体部分は必要最小限に抑えられている。一方で豊富で大規模な文書 (document) や、さまざまな領域に対応する大規模な標準ライブラリやサードパーティ製のライブラリが提供され、本体にない機能はその都度呼び出して使用する。またPythonは多くのハードウェアとOS (プラットフォーム) に対応しており、複数のプログラミングパラダイムに対応している。
（以下省略）インストール方法$ pip install jawikiドキュメントドキュメント（英語）はhttps://wikipedia.readthedocs.io/en/latestで読めます。
日本のウィキペディアからページ情報を取得するという点以外は、パッケージhttps://pypi.python.org/pypi/wikipediaと同じです。
Package: jawiki-cleaner
Japanese Wikipedia CleanerSplit sentences at the proper position taking parentheses into account.Normalize Unicode characters by NFKC.Extract text from wiki linksRemove of unnecessary symbols.Apply this tool for a extracted text by WikiExtractor.$ jawiki-cleaner --input ./wiki.txt --output ./cleaned-wiki.txt
$ jawiki-cleaner -i ./wiki.txt -o ./cleaned-wiki.txt
$ jawiki-cleaner -i ./wiki.txt # output path will be `./cleaned-wiki.txt`ExampleBefore<doc id="5" url="?curid=5" title="アンパサンド">
アンパサンド

アンパサンド (&amp;、英語名：) とは並立助詞「…と…」を意味する記号である。ラテン語の の合字で、Trebuchet MSフォントでは、と表示され "et" の合字であることが容易にわかる。ampersa、すなわち "and per se and"、その意味は"and [the symbol which] by itself [is] and"である。
歴史.
その使用は1世紀に遡ることができ、5世紀中葉から現代に至るまでの変遷がわかる。
Z に続くラテン文字アルファベットの27字目とされた時期もある。
アンパサンドと同じ役割を果たす文字に「のet」と呼ばれる、数字の「7」に似た記号があった(, U+204A)。この記号は現在もゲール文字で使われている。
記号名の「アンパサンド」は、ラテン語まじりの英語「&amp; はそれ自身 "and" を表す」(&amp; per se and) のくずれた形である。英語以外の言語での名称は多様である。
手書き.
日常的な手書きの場合、欧米でアンパサンドは「ε」に縦線を引く単純化されたものが使われることがある。
また同様に、「t」または「+（プラス）」に輪を重ねたような、無声歯茎側面摩擦音を示す発音記号「」のようなものが使われることもある。
プログラミング言語.
プログラミング言語では、C など多数の言語で AND 演算子として用いられる。以下は C の例。
PHPでは、変数宣言記号（$）の直前に記述することで、参照渡しを行うことができる。
BASIC 系列の言語では文字列の連結演算子として使用される。codice_4 は codice_5 を返す。また、主にマイクロソフト系では整数の十六進表記に codice_6 を用い、codice_7 （十進で15）のように表現する。
SGML、XML、HTMLでは、アンパサンドを使ってSGML実体を参照する。

</doc>Runjawiki-cleaner -i wiki.txtAfterアンパサンド(&、英語名)とは並立助詞「...と...」を意味する記号である。
ラテン語の の合字で、Trebuchet MSフォントでは、と表示され "et" の合字であることが容易にわかる。
ampersa、すなわち "and per se and"、その意味は"and [the symbol which] by itself [is] and"である。
その使用は1世紀に遡ることができ、5世紀中葉から現代に至るまでの変遷がわかる。
Z に続くラテン文字アルファベットの27字目とされた時期もある。
アンパサンドと同じ役割を果たす文字に「のet」と呼ばれる、数字の「7」に似た記号があった(U-204A)。
この記号は現在もゲール文字で使われている。
記号名の「アンパサンド」は、ラテン語まじりの英語「& はそれ自身 "and" を表す」(& per se and)のくずれた形である。
英語以外の言語での名称は多様である。
日常的な手書きの場合、欧米でアンパサンドは「ε」に縦線を引く単純化されたものが使われることがある。
また同様に、「t」または「-(プラス)」に輪を重ねたような、無声歯茎側面摩擦音を示す発音記号のようなものが使われることもある。
プログラミング言語では、C など多数の言語で AND 演算子として用いられる。
PHPでは、変数宣言記号($)の直前に記述することで、参照渡しを行うことができる。
BASIC 系列の言語では文字列の連結演算子として使用される。
codice_4 は codice_5 を返す。
また、主にマイクロソフト系では整数の十六進表記に codice_6 を用い、codice_7(十進で15)のように表現する。
SGML、XML、HTMLでは、アンパサンドを使ってSGML実体を参照する。
Package: jaws-scraper
# Introduction
JAWS is a system for quickly designing web scrapers. It contains a framework for designing custom resources, parsers and outputs for entirely custom scrapers as well as a few implemenations for common use cases.# Dependenices
JAWS is written in Python, for Python2. The dependencies for the latest version are:
* mechanize==0.2.5
* requests==2.2.1JAWS can also be installed with easy_install or pip.# Components
The core components of the JAWS framework can be found in core.py.## Scraper
The Scraper class is a collection of all the core components into one object which can be easily instantiated and used to scrape all data into your specified output.## Resource
The JAWSResource class is the abstract class describing the interface by which pages are provided to the parser for scraping. A resource could be as simple as a file reader or as complex as a full Web crawler.## Parser
The JAWSParser class is the abstract class describing the way your scraper will turn input from the resource into a python dictionary of keys and values to be fed to the output.## Output
The JAWSOutput class is the abstract class describing what to actually do with that data you have scraped. It could describe a file output format (a csv is probably simplest), a database interface, or whatever else you can think of.# Future Work
* Automatic Schema Detection
* JSON parser
* Examples for README
* Better documentation in code
* Python3 compatibility# License
All code and content distributed with JAWS is released under the [GNU GPLv3](http://www.gnu.org/licenses/gpl-3.0.html) unless otherwise specified or prohibited.
Package: jawsume
JAWSumeUseAWSumeinJupyterto accessAWSresources.Installation$pipinstalljawsumeUsagefromjawsumeimportjawsumejawsume("<profile-name>")You will be prompted for the MFA token.Just likeAWSume, this will set the following environment variables:AWS_ACCESS_KEY_IDAWS_SECRET_ACCESS_KEYAWS_SESSION_TOKENAWS_REGIONAWSUME_PROFILEAWSUME_EXPIRATIONNon-interactive modeYou can also directly pass the MFA code:jawsume("<profile-name>","<mfa-token>")What can I do then?You can then for instance readApache Parquetfiles fromAmazon S3.importpandasaspddf=pd.read_parquet("s3://<bucket-name>/<path-name>.parquet/")