Saravanan666/pypi-org huggingface dataset:
Package: pyjavaproperties3
================pyjavaproperties3================* Project hosting: <https://github.com/tgates42/pyjavaproperties/>.. contents::About------------------This is a "fork" of the "python replacement for java.util.Properties" recipeon ASPN: <http://code.activestate.com/recipes/496795/> and uploaded byAnand Balachandran Pillai.The project is maintained by Jesse Noller <jnoller@gmail.com>, Anand Pilla<abpillai@gmail.com>.License------------------As with all ASPN recipes not otherwise licensed prior to July 15, 2008 onaspn.activestate.com, the original recipe is under PSF License. For moreinformation, see the ASPN terms of service here:<http://code.activestate.com/help/terms/>While the licensing under the PSF license is sub-optimal, it is what it is. See<http://docs.python.org/license.html> for more information about the PSFlicense.What this is------------------This module is designed to be a python equivalent to the `java.util.Properties <http://java.sun.com/j2se/1.5.0/docs/api/java/util/Properties.html>`_ class.Currently, the basic input/output methods are supported, and there are plansto add the XML input/output methods found in J2SE 5.0.Fundamentally, this module is designed so that users can easily parse andmanipulate Java Properties files - that's it. There's a fair number of uspythonistas who work in multi-language shops, and constantly writing your ownparsing mechanism is just painful. Not to mention Java guys are notoriouslyunwilling to use anything which is cross-language for configuration, unlessit's XML, which is a form of self-punishment. :)Plans------------------Here is a rough plan of features:- Keep/maintain blank lines and comments found in the original file- Make the module compatible with the new methods in J2SE 5.0- Switch to/add python property access rather than direct dictionary get/set- Add unit tests- Add unicode support- When-Pigs-Fly: If running within Jython, switch to java.util.Propertiesunder the hood- Coercion/conversion to python types for valuesUsage------------------This is the easy part::from pyjavaproperties3 import Propertiesp = Properties()p.load(open('test2.properties'))p.list()print pprint p.items()print p['name3']p['name3'] = 'changed = value'print p['name3']p['new key'] = 'new value'p.store(open('test2.properties','w'))See also the Properties.list() method, which will return an iterator over theproperty keysChanges & News--------------0.6:- Fix license, whitespace.0.4:- Patch from Pepper Lebeck-Jobe for handling ! style comments.0.3:- Keys that are added which were not part of the original fileare simply appended to the index. Shenanigans.0.2:- Added an internal list (self._keyorder) to keep an ordered index of keysas they are encountered, so the file can we written-back out in thesame order.0.1:- Initial release/fork.- Added setup/packaging and doc- added in {foo} style references for previous properties, thanks to N Bon ASPN.
Package: pyjavaproperties-unicode
This is a tiny wrapper around the pyjavaproperties package that does
unicode en- and decoding transparently.The problem I tried to solve here is that Java Properties files only
support ISO-8859-1 content. If you need unicode, you have to use
something likenative2asciiorpropeditfor Eclipse which
converts content from unicode to ascii and stores it into the
respective file. In Python, obviously, you want the actual unicode
data and not the encoded version of the prop value and this is
exactly what this here does.To use it simply import thePropertiesclass from thepyjavapropertiesumodule instead ofpyjavapropertiesand use
thegetPropertymethod as before.Please note, though, that the data within the internal dict in the Properties
class is still encoded.
Package: pyjavaprops
Library to read Java style properties files. I don’t particularly like properties files but working with them in Java
is very easy. I recently had to support reading Java properties files using Python.This project is based on Benjamins Brent fork ofpyjavaproperties.The libraries main features are:Reads properties files.You can add new properties.You can save properties to file.It interprets variables in curly braces {} and dollar curly braces ${}.CaveatsThe library does not interpret unicode characters correctly. If you include charactes like u4500 it will interpret it
as , letter y and the number 4500.InstallationRequires Python 3.3 or better.$pipinstallpyjavapropsUsageLoading Java propertiesfilename=os.path.join(TEST_DATA_FOLDER,'iso-8859-1.properties')iso_8859_1_properties=JavaProperties()withopen(filename,encoding='iso-8859-1')asproperty_file:iso_8859_1_properties.load(property_file)name=iso_8859_1_properties['name']Saving Java properties to filefilename=os.path.join(TEST_DATA_FOLDER,'simple.properties')simple_java_properties=JavaProperties()withopen(filename)asproperty_file:simple_java_properties.load(property_file)simple_java_properties['country']='Angola'output_filename=os.path.join(OUTPUT_FOLDER,'simple_%s.properties'%datetime.now().strftime('%Y%m%d_%H%M'))withopen(output_filename,mode='w')asoutput:simple_java_properties.store(output)Exporting to jsonoutput_filename=os.path.join(OUTPUT_FOLDER,'simple_%s.json'%datetime.now().strftime('%Y%m%d_%H%M'))export_to_json(output_filename,java_properties)withopen(output_filename)asjson_data:json_properties=json.load(json_data)print(json_properties['Key10'])DevelopmentVirtual EnvironmentTo create the virtual environment$cd~/virtual_environments$python3/usr/local/lib/python3.4/site-packages/virtualenv.py--no-site-packagespyjavaprops_env$source./pyjavaprops_env/bin/activate(pyjavaprops_env)$Runnig Tests$coveragerun--sourcepyjavapropssetup.pytest
Package: pyjaws
PyJaws: A Pythonic Way to Define Databricks JaWs (Jobs and Workflows)PyJawsenables declaringDatabricks Jobs and Workflowsas Python code, allowing for:Code LintingFormattingParameter ValidationModularity and reusabilityIn addition to those,PyJawsalso provides some nice features such ascycle detectionout of the box.Folks who have used Python-based orchestration tools such asApache Airflow,LuigiandMagewill be familiar with the concepts and the API ifPyJaws.Getting StartedFirst step is installingpyjaws:pipinstallpyjawsOnce it's installed, define your Databricks Workspace authentication variables:exportDATABRICKS_HOST=...exportDATABRICKS_TOKEN=...Last, define your Workflow Tasks (seeexamples) and run:pyjawscreatepath/to/your/workflow_definitionsSample Job Definitionfrompyjaws.api.baseimport(Cluster,Runtime,Workflow)frompyjaws.api.tasksimportPythonWheelTaskcluster=Cluster(job_cluster_key="ai_cluster",spark_version=Runtime.DBR_13_ML,num_workers=2,node_type_id="Standard_DS3_v2",cluster_log_conf={"dbfs":{"destination":"dbfs:/home/cluster_log"}})# Create a Task object.ingest_task=PythonWheelTask(key="ingest",cluster=cluster,entrypoint="iot",task_name="ingest",parameters=[f"my_parameter_value","--output-table","my_table"])transform_task=PythonWheelTask(key="transform",cluster=cluster,entrypoint="iot",task_name="ingest",dependencies=[ingest_task],parameters=[f"my_parameter_value2","--input-table","my_table""--output-table","output_table"])# Create a Workflow object to define dependencies# between previously defined tasks.workflow=Workflow(name="my_workflow",tasks=[ingest_task,transform_task])Extra FeaturesContext ManagerforClusterdeclarations:# cluster created with context managerwithCluster(job_cluster_key="mycluster_2",spark_version=Runtime.DBR_13_ML,node_type_id="Standard_E4ds_v4",num_workers=3,)ascluster_2:task_2=SparkPythonTask(key="task_2",cluster=cluster_2,python_file="/Workspace/Repos/bob@mail.com/utils/task_2.py",source=Source.WORKSPACE,)Workflow preview/visualizationon notebooks:display(workflow)Result:Deploying JobsIf you have a folder containing multiple workflow definition files written in Python withPyJaws, it is quite simple to deploy all of them to your Databricks Workspace with a one liner:pyjaws create examples/simple_workflowThis would result in the following Workflow being deployed to your workspace:By default,pyjawsalso includes some useful tags into the workflows indicating which Git Repo hosts the Python definition, commit hash and when the workflow was last updated. For example:DocumentationPyJaws Documentation (Read the Docs)Development & TestingPyJawscan be tested locally for development purposes. To run unit tests, make suretox,pytest,pytest-cov, andcoverageare installed and from a bash terminal, simply runtox.DisclaimerPyJawsis not developed, endorsed not supported by Databricks. It is provided as-is; no warranty is derived from using this package. For more details, please refer to thelicense.Reporting Bugs and ContributingFeel free to create an issue if you feel something is not right. Contribution guidelines can be foundhere.
Package: pyJaya
pyJayaPython implementation of Jaya Algorithm and its variantsFree software: MIT licenseDocumentation:https://pyJaya.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-12-24)First release on PyPI.0.1.1 (2020-12-24)Add contributor.0.1.5 (2020-12-24)Documentation improvements.0.1.6 (2020-12-27)Flake8 fix.Adding examples.Update usage.0.1.7 (2021-01-05)Fix clasic, adaptive and quasi.0.1.8 (2021-02-18)Tests with monkeypatch.Add spaced numbers over a specified interval
Package: pyjazz
# Official Python client for JazzThis is the official Python Jazz client maintained by the Authors of Jazz.## Reference for version 0.2.1.99- Functions and classes [reference](reference.html)## Main Project Links- [kaalam.ai](http://kaalam.github.io/kaalam/)- [Jazz Reference](http://kaalam.github.io/jazz_reference/)- [Jazz Blog](http://kaalam.github.io/blog/)- [Jazz News](http://kaalam.github.io/news/)- [Jazz R client](http://kaalam.github.io/rjazz/)## The simplest way to start- [Using the Python package without a server](http://kaalam.github.io/jazz_reference/pyjazz_walkthough_client_only.html)- [Using the Python client with a server](http://kaalam.github.io/jazz_reference/pyjazz_walkthough_with_server.html)## LicenseJazz (c) 2018 kaalam.ai (The Authors of Jazz), using (under the same license):BBVA - Jazz: A lightweight analytical web server for data-driven applications.Copyright 2016-2017 Banco Bilbao Vizcaya Argentaria, S.A.This product includes software developed atBBVA (https://www.bbva.com/)Licensed under the Apache License, Version 2.0 (the "License");you may not use this file except in compliance with the License.You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed under the License is distributed on an "AS IS" BASIS,WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.See the License for the specific language governing permissions andlimitations under the License.
Package: pyjazzcash
PyJazzCashPython Boilerplate contains all the boilerplate you need to create a Python package.Free software: MIT licenseDocumentation:https://pyjazzcash.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-10-26)First release on PyPI.
Package: pyjazzclient
PyJazzClientis a simple python package for communicating with IBM Jazz.>>>frompyjazzclient.jazzclientimportJazzClient>>>frompyjazzclient.testcaseimportTestCase>>>server_url="https://jazz.net/jazz">>>default_projects={"qm":"__JVJ8e2eEeuHyM9xpDtK0B","rm":"__JVJ8e2eEeuHyM9xpDtK0C"}>>>jazz=JazzClient(server_url,"username","password",default_projects)>>>testcase=jazz.testcase(web_id=16197)>>>print(testcase.title)'The handheld device shall allow the meter reader to enter information about meters relocated on a particular route.'Pyjazzclient allows you to create, edit, update, delete, lock, and unlock various artifacts within IBM Jazz with little need to understand the RqmAPI or OSLCS.
Package: pyjce2
pyjce2参考了pyjce原版只是实现了反序列化,此版本加入了序列化功能v0.1.0 大改 使用pydantic验证类型 自动读写jce结构体v0.1.1 弃用python3.7支持,只支持py3.8+v0.1.2 加入自动加密解密方法, 用于解析非递归的结构体, 复杂的仍然需要手动完成下一步: 完善单元测试使用参考命令行python -m pyjce 1606e686a8e689b92100fa8618e4bda0e5b185e784b6e79c9fe79a84e8a7a3e5af86e4ba86
Package: pyjd
pyjdThis is a wrapper for the JDownloader API.InstallationpipinstallpyjdUsageThe documentation of the JDownloader API can be found herehttps://my.jdownloader.org/developers/. This library includes all of the
documented functions (but uses underscores instead of CamelCase).For examples, check out the sample scripts in the repository
(see here).Building auto-docsBuildGo to into thedocsdirectory and runmake html.You can remove thedocs/_builddirectory to make a clean rebuild.Reload modulesRunsphinx-apidoc -o source ../inside thedocsdirectory.
Then, remove thesetup.rstfile from the source folder.CreditsThe MyJD API authentication code is taken from here:https://github.com/mmarquezs/My.Jdownloader-API-Python-Library
Package: pyjdb
pyjdbPython interface with Java debugger through JDB.OverviewTheJdbProcessusespexpectto attach to ajdbprocess and record all the information that is obtained.For each instruction, we record a dictionary of the following format:{"return":10000,"thread":"main","class.method":"IterPower.iterPower()","method":"iterPower","line":15,"bci":17,"instruction":"return result;"}For each instruction, we can also obtain the dictionary of the current method's arguments, as well as all its local variables:({'base':10,'exp':0},{'result':10000})ExampleLet's assume that we have this Java file,IterPower.java:publicclassIterPower{publicstaticvoidmain(String[]args){// ... parse arguments ...System.out.println(iterPower(base,exp));}publicstaticintiterPower(intbase,intexp){intresult=1;while(exp>0){result*=base;exp-=1;}returnresult;}}which has been compiled with debugging information,javac -g IterPower.java. The following is a Python snippet:importpyjdbimportitertoolsp=pyjdb.JdbProcess("IterPower")p.spawn("10 4")variables={}whileTrue:# Try to make an additional step and retrieve local variablesresult=Nonetry:p.step()result=p.locals()exceptpyjdb.EOF:breakifresultisNone:continue# Store the values of each variable(args,locs)=resultfor(var,val)initertools.chain(args.items(),locs.items()):variables[var]=variables.get(var,list())variables[var].append(val)variables_unique_values={var:list(set(vals))for(var,vals)invariables.items()}print(variables_unique_values)The snippet will output a trace of the variable values of this program through its execution:{"args":["instance of java.lang.String[0] (id=495)"],"base":[10],"exp":[0,1,2,3,4],"result":[1,10,100,1000,10000]}InspirationThis project was inspired by atalk by Elena Glassmanin which she shows how to clusterdifferent implementations of the same solutionaccording to the trace of the internal variables. Her work, which includesOverCodeandfoobaz, focuses on Python programs. At my home institution, we use Java in our introductory classes. The initial goal of this project was to apply Dr. Glassman's techniques to Java assignments.Related projectsThere were several ambitious projects related to bringing a Java debugger to Python. These projects highlight how complex an undertaking it is to implement the actual JDWP protocol. This is why in this project, our approach has been to piggy-back onjdbso as to not need to reimplement protocol-level functionality.csuter/pyjdb(abandonned): A Python implementation of the JDWP specifications.soulseekah/pyjdb(abandonned): Ajdbreplacement with more user-friendly features.
Package: pyjdbc
PyJdbcpyjdbcprovides adb api 2.0compliant interface around anyJDBCdriver.pyjdbcis used by various other projects as the basis for their jdbc compatibility interface.Featureswrap jdbcDriverManagerfunctionalitycustom exception handlers to deliver better python-like exceptions and avoidingjavastack traces whenever possible.provide basicCursor,DictoCursor,Connectionclassesprovide basicTypeConversionclasses for commonjdbctopythoncases.interface for handling and validatingjdbcarguments and formatting connection stringsregistry to support downloading and managing drivers locally.
Package: pyjdbcconnector
pyJDBCConnectorpyJDBCConnectoris a high level JDBC connection API that was designed to provide a further abstraction for jdbc connections in python.
This package is designed as an introduction to jdbc connections in Python and as such provides much less customizability with a focus on
accessibility.MotivationThis package came about due to intricacies of dealing with the Denodo JDBC driver with SSL enabled.
Thejaydebeapipackage that this package is heavily reliant on doesn't provide the ability to specify
the location of a Trust Store file at JVM start-up. This was a big problem for us and we needed to solve this
for analysts with less engineering experience and enable them to get an introduction to Python programming
with familiar data.LimitationsCurrently this package has only been tested for the Denodo JDBC driverExamplesInstallation/Usage:This package is currently on PyPi and can be installed through:pipinstallpyjdbcconnectorThis package is driven primarily through config files.
To understand how config files are set up please see theDocumentationConnect to a Denodo JDBC with SSL enabled"""This example demonstrates how to use the DenodoConnectorapi for connecting to a Denodo based JDBC with a Trust Storefile"""importpandasaspdfrompyjdbcconnector.connectorsimportDenodoConnector# Initialize a DenodoConnector object# the DenodoConnector object acts as# a builder.dc=DenodoConnector()# Here, we build the connection using the built-in# builder functionsconn=dc\.from_config("path/to/denodo_config.ini")\.connect()# this connection acts as a normal sql connection and we can use it# as we would use any other connection in Python# Assuming we want to read a table into a pandas dataframeSQL_QUERY="select * from tablename"data=pd.read_sql(SQL_QUERY,conn)To connect to a JDBC without SSL, omit the lines that require a Trust Store.
Package: pyjdpu
pyjdpuSometimes you have to update many plugins during jenkins docker upgrade and waste a lot of time.
With  pyjdpu you can easily update your plugins.txt automaticly to the latest versions.installpipinstallpyjdpuquick startUpdate your plugins.txt wit cli:pyjdpu-iplugins.txt-oplugins_updated.txtGet latest version of an jenkins plugin:importpyjdpumy_api=pyjdpu.JenkinsPluginApi()my_version=my_api.get_latest_version('blueocean-git-pipeline')issue trackerhttps://github.com/portfolioplus/pystockfilter/issuese
Package: pyJect
pyject is a command line project managerpyject -c or –create-project [NAME] // for a new project
pyject -m or –add-module [PROJ] [MOD] <PACK> // add MOD to PROJ/<PACK>
pyject -p or –add-package [PROJ] [PACK] // add PACK to PROJ
pyject -l or –list-all // show projects in $HOME/projects
pyject -w or –work-project [PROJ] <PACK> // work in PROJ/<PACK>
pyject -h or –help // show similar help info
Package: pyjectt
pyjectWhat is Pyject?Pyject is a IocContainer for Python.It helps implementing the dependency injection principle.InstallationThe package is available on the PyPi:pipinstallpyjecttExamplesBaseNon-default typesSequence: ("Set", "List", "Tuple", "FrozenSet", "Sequence")Union: (Union, Optional)ForwardRefIteratorBasefromabcimportABC,abstractmethodfromtypingimportListfrompyjectimportContainerclassDuckInterface(ABC):@abstractmethoddefquack(self):raiseNotImplementedError()classQuackBehavior(ABC):@abstractmethoddefquack(self):raiseNotImplementedError()classSqeak(QuackBehavior):defquack(self):return"Quack_1"classDuckA(DuckInterface):def__init__(self,squeak:QuackBehavior):self._quack_behavior=squeakdefquack(self):returnself._quack_behavior.quack()classDuckC(DuckInterface):defquack(self):return"Quack_2"container=Container()container.add_singleton(QuackBehavior,Sqeak)container.add_transient(DuckInterface,DuckA)container.add_singleton(DuckInterface,DuckC)duck=container.get(DuckInterface)print(duck.quack())ducks=container.get_all(DuckInterface)forduckinducks:print(duck.quack())deftest2(ducks:List[DuckInterface]):result_=""forduckinducks:result_+=duck.quack()returnresult_assertcontainer.resolve(test2)=="Quack_1Quack_2"Non-default typesSequencedeflist_typing(ducks:List[DuckInterface]):result_=""forduckinducks:result_+=duck.quack()returnresult_defsequence_typing(ducks:Sequence[DuckInterface]):result_=""forduckinducks:result_+=duck.quack()returnresult_assertcontainer.resolve(list_typing)=="Quack_1Quack_2"assertcontainer.resolve(sequence_typing)=="Quack_1Quack_2"Uniondefunion_typing(quack:Union[QuackBehavior,DuckInterface]):returnquackdefoptional_typing(test:Optional[List]):returntestassertisinstance(container.resolve(union_typing),QuackBehavior)assertcontainer.resolve(optional_typing)isNoneForwardReffrompyject.typesimportForwardRefclassTest:def__init__(self,test2:ForwardRef["Test2"]):self.test2=test2deftest(self):returnself.test2.test2()classTest2:def__init__(self,test:ForwardRef[Test]):self.test=testdeftest2(self):return"123"container.add_singleton(Test,Test)container.add_singleton(Test2,Test2)test=container.get(Test)assertisinstance(test,Test)assertisinstance(test.test2,ForwardRef)assertisinstance(test.test2.test,ForwardRef)asserttest.test()=="123"asserttest.test()==test.test2.test2()Iteratordefiterator_typing(ducks:Iterator[DuckInterface]):result_=""forduckinducks:result_+=duck.quack()returnresult_assertcontainer.resolve(iterator_typing)=="Quack_1Quack_2"
Package: pyjedai
An open-source library that leverages Python’s data science ecosystem to buildpowerful end-to-end Entity Resolution workflows.OverviewpyJedAI is a python framework, aiming to offer experts and novice users, robust and fast solutions for multiple types of Entity Resolution problems. It is builded using state-of-the-art python frameworks. pyJedAI constitutes the sole open-source Link Discovery tool that is capable of exploiting the latest breakthroughs in Deep Learning and NLP techniques, which are publicly available through the Python data science ecosystem. This applies to both blocking and matching, thus ensuring high time efficiency, high scalability as well as high effectiveness, without requiring any labelled instances from the user.Key-FeaturesInput data-type independent. Both structured and semi-structured data can be processed.Various implemented algorithms.Easy-to-use.Utilizes some of the famous and cutting-edge machine learning packages.Offers supervised and un-supervised ML techniques.Open demos are available in:Google Colab Hands-on demo:InstallPyPIInstall the latest version of pyjedai[requires python >= 3.8]:pip install pyjedaiMore onPyPI.GitSet up locally:git clone https://github.com/AI-team-UoA/pyJedAI.gitgo to the root directory withcd pyJedAIand type:pip install .DependenciesSee the full list of dependencies and all versions used, in thisfile.StatusStatistics & InfoBugs, Discussions & NewsGitHub Discussionsis the discussion forum for general questions and discussions and our recommended starting point. Please report any bugs that you findhere.Java - Web ApplicationFor Java users checkout the initialJedAI. There you can find Java based code and a Web Application for interactive creation of ER workflows.JedAI constitutes an open source, high scalability toolkit that offers out-of-the-box solutions for any data integration task, e.g., Record Linkage, Entity Resolution and Link Discovery. At its core lies a set of domain-independent, state-of-the-art techniques that apply to both RDF and relational data.Team & AuthorsKonstantinos NikoletosJakub MaciejewskiGeorge PapadakisManolis KoubarakisResearch and development is made under the supervision of Pr. Manolis Koubarakis. This is a research project by theAI-Teamof the Department of Informatics and Telecommunications at the University of Athens.LicenseReleased under the Apache-2.0 license (seeLICENSE.txt).Copyright © 2023 AI-Team, University of AthensThis project is being funded in the context ofSTELARthat is anHORIZON-Europeproject.