Saravanan666/pypi-org huggingface dataset:
Package: gen-py-module
Generate Python Modulegen_py_moduleis tool for generation PY Module.Developed inpythoncode:100%.The README is used to introduce the modules and provide instructions on
how to install the modules, any machine dependencies it may have and any
other information that should be provided before the modules are installed.Table of ContentsInstallationInstall using pipInstall using buildInstall using py setupInstall using dockerDependenciesTool structureDocsContributingCopyright and licenceInstallationCurrently there are three ways to install packageInstall process based on using pip mechanismInstall process based on build mechanismInstall process based on setup.py mechanismInstall process based on docker mechanismInstall using pipgen_py_moduleis located atpypi.org.You can install by using pip# python3pip3installgen-py-moduleInstall using buildNavigate to releasepagedownload and extract release archive.To installgen_py_moduletype the followingtarxvzfgen_py_module-x.y.z.tar.gzcdgen_py_module-x.y.z/# python3wgethttps://bootstrap.pypa.io/get-pip.py
python3get-pip.pypython3-mpipinstall--upgradesetuptools
python3-mpipinstall--upgradepip
python3-mpipinstall--upgradebuild
pip3install-rrequirements.txt
python3-mbuild--no-isolation--wheel
pip3install./dist/gen_py_module-*-py3-none-any.whl
rm-fget-pip.py
chmod755/usr/local/lib/python3.10/dist-packages/usr/local/bin/gen_py_module_run.py
ln-s/usr/local/lib/python3.10/dist-packages/usr/local/bin/gen_py_module_run.py/usr/local/bin/gen_py_module_run.pyInstall using py setupNavigate to releasepagedownload and extract release archive.To installgen_py_modulelocate and run setup.py with argumentstarxvzfgen_py_module-x.y.z.tar.gzcdgen_py_module-x.y.z/# python3pip3install-rrequirements.txt
python3setup.pyinstall_lib
python3setup.pyinstall_data
python3setup.pyinstall_egg_infoInstall using dockerYou can use docker to create image/container.Dependenciesgen_py_modulerequires next modules and librariesats-utilities - Python App/Tool/Script UtilitiesTool structuregen_py_moduleis based on OOPGenerator structuregen_py_module/├──conf/│├──gen_py_module.cfg│├──gen_py_module.logo│├──gen_py_module_util.cfg│├──project.yaml│└──template/│├──abstract_abc_class.template│├──abstract_base_class.template│├──class.template│├──empty.template│└──main.template├──__init__.py├──log/│└──gen_py_module.log├──pro/│├──__init__.py│├──read_template.py│└──write_template.py└──run/└──gen_py_module_run.py6directories,15filesDocsMore documentation and info atgen_py_module.readthedocs.iowww.python.orgContributingContributing to gen_py_moduleCopyright and licenceCopyright (C) 2017 - 2024 byvroncevic.github.io/gen_py_modulegen_py_moduleis free software; you can redistribute it and/or modify
it under the same terms as Python itself, either Python version 3.x or,
at your option, any later version of Python 3 you may have available.Lets help and support PSF.
Package: genpypress
genpypressThis library contains several code generator helpers. It is connected to thepresscode generator.This package will only run on Windows (submoduletableuses external binary as dependency, the binary only exists for Windows).UsageCommand line applicationph --help- zobrazí nápověduph apatch- provede patch TPT skriptů pro asynchronní stageph cc- připraví SQL a/nebo BTEQ skripty tabulek na podmíněné nasazeníMarkdown (mapping) parserfrompathlibimportPathfromgenpypressimportmapping# import a file in markdown formatfile=Path("TGT_ACCS_METH_RLTD_906_900_915_AMR_NIC_PCR_2_M2C.md",encoding="utf-8")map=mapping.from_markdown(file.read_text(encoding="utf-8"))# access table mapping propertyprint("Type of historization:",map.etl_historization)# access a column mapping property (case insensitive)print("hist_type =",map["hist_type"].transformation_rule)# nonexisting column will - of course - blow the code uptry:print(map["not available"])exceptKeyErroraserr:print(f"error:{err}")Table parserOnly supported on MS Windows.from genpypress import table
filename = "ddl_script.sql"
data = table.from_file(filename)
t = data[0]

# access to table properties and/or columns
print("table name", t.name)
print("first column", t[0])
print("column by name", t["column_name"])

# deletion of columns by name and/or index
del t["another_column"]
del t[O]
Package: genranddata
a function to create random usernamesTested against Windows / Python 3.11 / Anacondapip install genranddataGeneraterandomdatausingagivenfunctionandinputdata,whileensuringuniquenessandhandlingexceptions.Parameters:fu(callable):Thefunctionusedtogeneratenewdata.data(Union[list,tuple]):Theinputdatatobeusedinthegenerationprocess.created_already(list):Alistofdatathathasalreadybeencreated.limit(int):Themaximumnumberofnewdatatobegenerated.**kwargs:Additionalkeywordargumentstobepassedtothefunction.Returns:list:Alistofrandomlygenerateddata,withalengthnotexceedingthespecifiedlimit.fromgenranddataimportcreate_random_data,load_data,save_data,genfunctionu=["Agent","Alex","Alonzo","Amon","Angel","Annie","Anton","August","Bane","Buddy","Calvin","Candyman","Captain","Catherine","Chucky","Colin","Commodus","Count","Cruella","Darth","Davy","Deadly","Death","Dolores","Dr","Elijah","Erik","Ernst","Esther","Frank","Freddy","Ghostface","Godzilla","Gollum","Gordon","Gozer","Green","HAL","Harry","Howard","Immortan","Ivan","Jack","Jason","Jigsaw","John","Joker","Judge","Khan","Koba","Lee","Lex","Lil","Lord","Lots","Maleficent","Margaret","Max","Michael","Miranda","Miss","Mrs","Norman","Nurse","Palpatine","Pazuzu","Pennywise","Predator","Queen","Raoul","Regina","Roger","Roy","Sauron","Scar","Shere","Shooter","T","Terence","Thanos","The","Ursula","Vice","William","Xenomorphs",]empty=[]save_data(empty,"c:\\testusername.pkl")already_created=load_data("c:\\testusername.pkl")gendata=create_random_data(fu=lambdax,**kwargs:genfunction(x,**kwargs),data=u,created_already=already_created,limit=10,min_=2,max_=4,camel_case_percentage=20,uppercase_percentage=30,lowercase_percentage=30,join_values=("x","_",""),random_number_percentage=30,random_number_range=(0,100),)print(gendata)# ['maleficent_xenomorphs_alex_max', 'queenlexantonnorman', 'DarthxJack', 'WilliamMaxRaoulAlonzo', 'MissxIvanxCaptainxMax', 'SAURONFREDDYAGENTDR', 'CAPTAIN_JOHN_ROGER_GREEN', 'JOKERERIKFREDDYESTHER71', 'scar_roger_1', 'T_GHOSTFACE_ANGEL_4']
Package: genre
Introductiongenre, a simple and conciserequirements.txtgenerator.When usingpip freeze > requirements.txt, many indirect dependencies are listed, which is not elegant. This simple tool aims to provide a conciserequirements.txt, which means it only export direct third-party dependencies or imports in your project.Installpip install genreUsageusage: genre [-h] [-p PACKAGE_DIR] [-v {0,1}]optional arguments:
-h, --help            show this help message and exit
-p PACKAGE_DIR, --package_dir PACKAGE_DIR
your package path
-v {0,1}, --add_version {0,1}
add version (1) or not (0)FAQQ: What does "Below are unsure project names (manual check needed)" mean?A: Normally, this message should not appear in generatedrequirements.txt. If you see it unluckily, it means one third-party import in your project is mapped to multiple packages. Manual check is needed to verify which package(s) is/are real dependency(ies).
Package: gen-readme
Create README.md doc modulegen_readmeis tool for creating README.md doc module.Developed inpythoncode.The README is used to introduce the modules and provide instructions on
how to install the modules, any machine dependencies it may have and any
other information that should be provided before the modules are installed.Table of ContentsInstallationInstall using pipInstall using buildInstall using py setupInstall using dockerDependenciesTool structureDocsContributingCopyright and licenceInstallationCurrently there are three ways to install packageInstall process based on using pip mechanismInstall process based on build mechanismInstall process based on setup.py mechanismInstall process based on docker mechanismInstall using pipPython package is located atpypi.org.You can install by using pip#python3pip3installgen_readmeInstall using buildNavigate to releasepagedownload and extract release archive.To installgen_readmetype the followingtarxvzfgen_readme-x.y.z.tar.gzcdgen_readme-x.y.z/# python3wgethttps://bootstrap.pypa.io/get-pip.py
python3get-pip.pypython3-mpipinstall--upgradesetuptools
python3-mpipinstall--upgradepip
python3-mpipinstall--upgradebuild
pip3install-rrequirements.txt
python3-mbuild--no-isolation--wheel
pip3install./dist/gen_readme-*-py3-none-any.whl
rm-fget-pip.py
chmod755/usr/local/lib/python3.10/dist-packages/usr/local/bin/gen_readme_run.py
ln-s/usr/local/lib/python3.10/dist-packages/usr/local/bin/gen_readme_run.py/usr/local/bin/gen_readme_run.pyInstall using py setupNavigate torelease pagedownload and extract release archive.To installgen_readmelocate and run setup.py, type the followingtarxvzfgen_readme-x.y.z.tar.gzcdgen_readme-x.y.z#python3pip3install-rrequirements.txt
python3setup.pyinstall_lib
python3setup.pyinstall_egg_info
python3setup.pyinstall_dataInstall using dockerYou can use Dockerfile to create image/container.Dependenciesgen_readmerequires next modules and librariesats-utilities - Python App/Tool/Script UtilitiesTool structuregen_readmeis based on OOPGenerator structuregen_readme/├──conf/│├──gen_readme.cfg│├──gen_readme.logo│├──gen_readme_util.cfg│├──project.yaml│└──template/│├──README_AVR.template│├──README_CC.template│├──README_C.template│├──README_JS.template│├──README_PL.template│├──README_PY.template│├──README_RPI.template│├──README_SH.template│├──README_STM.template│└──README_VALA.template├──__init__.py├──log/│└──gen_readme.log├──pro/│├──__init__.py│├──read_template.py│└──write_template.py└──run/└──gen_readme_run.py6directories,20filesDocsMore documentation and info atgen_readme.readthedocs.iowww.python.orgContributingContributing to gen_readmeCopyright and licenceCopyright (C) 2020 - 2024 byvroncevic.github.io/gen_readmegen_readmeis free software; you can redistribute it and/or modify
it under the same terms as Python itself, either Python version 3.x or,
at your option, any later version of Python 3 you may have available.Lets help and support PSF.
Package: genre-expand
genre-expandExpand ID3 genre metadata using WikipediaUpdate or replace ID3 genre metadata of MP3 files using data extracted from Wikipedia. Can recursively expand metadata of music directories with or without the need for user confirmation. Allows for topic disambiguation by the user to improve precision, as well as the option to only fill in missing genres.Installationpip install genre-expandorpip install git+https://github.com/huntrar/genre-expand.git#egg=genre-expandorgit clone https://github.com/huntrar/genre-expand
cd genre-expand
python setup.py installUsageusage: genre-expand.py [-h] -d SEARCH_DIR [-r] [-l LEVEL] [-f] [-s] [-m] [-q]
                       [-v]

expand ID3 genre metadata

optional arguments:
  -h, --help            show this help message and exit
  -d SEARCH_DIR, --search-dir SEARCH_DIR
                        directory to search
  -r, --recursive       recursively search directories
  -l LEVEL, --level LEVEL
                        depth of directories to recurse
  -f, --force           do not prompt user ever
  -s, --force-save      save files without prompt
  -m, --missing-only    only expand missing genres
  -q, --quiet           suppress status and error messages
  -v, --version         display current versionAuthorHunter Hammond (huntrar@gmail.com)NotesChoosing the ‘force’ option will remove the need for prompts, but will also avoid making changes where a choice is ambiguous. If you want to disambiguate topics but skip other confirmations, use the ‘force save’ option.The ‘missing only’ option is available for only expanding tags with missing genre metadata, preventing overwrites of existing genres.News0.0.4Added six to requirements.txt as wellAdded missing future imports0.0.3Renamed main file to genre_expand.py0.0.2Fixed location of script entry pointAdded six module to dependency requirements0.0.1Initial commit
Package: gen-repr
gen-reprLightweight python library without any dependencies to automatically generate
the__repr__method for any class.Getting startedInstall this package throught pip$pipinstallgen-reprAfter that you can import it in your program like thisfromgenreprimportgen_reprExamplefromgenreprimportgen_repr@gen_repr()classPerson(object):def__init__(self):self.first_name=u""self.age=0self._hair=u"any color you like"peter=Person()peter.first_name=u"Peter"peter.age=-1repr(peter)# result: "<Person (first_name='Peter', age=-1)>:
Package: genrex
GenrexGenrex generates matching strings to a given regular expressions.Usecasesgenerate test datacalculate the cardinality of a regular expression.QuickstartRequirementsPyhton 3.xInstallpip install genrexFirst Stepsimportgenrexemails=genrex.parse(r'(John|Jane)\.(Doe|Smith)@(gmail|outlook|protonmail)\.com')print('random email address: ',emails.random())print('first email address: ',emails[0])print('number of email addresses: ',len(emails))print('')[print(email)foremailinemails]#print all emailsOutput:random email address:  Jane.Doe@gmail.com
first email address:  John.Doe@gmail.com
number of email addresses:  12

John.Doe@gmail.com
Jane.Doe@gmail.com
John.Smith@gmail.com
Jane.Smith@gmail.com
John.Doe@outlook.com
Jane.Doe@outlook.com
John.Smith@outlook.com
Jane.Smith@outlook.com
John.Doe@protonmail.com
Jane.Doe@protonmail.com
John.Smith@protonmail.com
Jane.Smith@protonmail.comFeaturesSupported Regular Expression Syntax.*+?{m}{m,n}|- Branch[...]- Set(...)- Group\d,\s, ... - CategoriesTODOsupport re flags (e.g.re.ASCII)AlternativesPackageLicenseexrexAGPL-3.0rstrBSD
Package: genrl
GenRL is a PyTorch reinforcement learning library centered around reproducible and generalizable algorithm implementations.Reinforcement learning research is moving faster than ever before. In order to keep up with the growing trend and ensure that RL research remains reproducible, GenRL aims to aid faster paper reproduction and benchmarking by providing the following main features:PyTorch-first: Modular, Extensible and Idiomatic PythonUnified Trainer and Logging class: code reusability and high-level UIReady-made algorithm implementations: ready-made implementations of popular RL algorithms.Faster Benchmarking: automated hyperparameter tuning, environment implementations etc.By integrating these features into GenRL, we aim to eventually supportany new algorithm implementation in less than 100 lines.If you're interested in contributing, feel free to go through the issues and open PRs for code, docs, tests etc. In case of any questions, please check out theContributing GuidelinesInstallationGenRL is compatible with Python 3.6 or later and also depends onpytorchandopenai-gym. The easiest way to install GenRL is with pip, Python's preferred package installer.$ pip install genrlNote that GenRL is an active project and routinely publishes new releases. In order to upgrade GenRL to the latest version, use pip as follows.$ pip install -U genrlIf you intend to install the latest unreleased version of the library (i.e from source), you can simply do:$ git clone https://github.com/SforAiDl/genrl.git
$ cd genrl
$ python setup.py installUsageTo train a Soft Actor-Critic model from scratch on thePendulum-v0gym environment and log rewards on tensorboardimportgymfromgenrlimportSAC,QLearningfromgenrl.classical.commonimportTrainerfromgenrl.deep.commonimportOffPolicyTrainerfromgenrl.environmentsimportVectorEnvenv=VectorEnv("Pendulum-v0")agent=SAC('mlp',env)trainer=OffPolicyTrainer(agent,env,log_mode=['stdout','tensorboard'])trainer.train()To train a Tabular Dyna-Q model from scratch on theFrozenLake-v0gym environment and plot rewards:env=gym.make("FrozenLake-v0")agent=QLearning(env)trainer=Trainer(agent,env,mode="dyna",model="tabular",n_episodes=10000)episode_rewards=trainer.train()trainer.plot(episode_rewards)AlgorithmsDeep RLDQN (Deep Q Networks)DQNDouble DQNDueling DQNNoisy DQNCategorical DQNVPG (Vanilla Policy Gradients)A2C (Advantage Actor-Critic)PPO (Proximal Policy Optimization)DDPG (Deep Deterministic Policy Gradients)TD3 (Twin Delayed DDPG)SAC (Soft Actor Critic)Classical RLSARSAQ LearningBandit RLMulti Armed BanditsEps GreedyUCBThompson SamplingBayesian BanditsSoftmax ExplorerContextual BanditsEps GreedyUCBThompson SamplingBayesian BanditsSoftmax ExplorerDeep Contextual BanditsVariation InferenceNoise sampling for neural network parametersEpsilon greedy with a neural networkBayesian Regression on for posterior inferenceBootstraped Ensemble
Package: gen-rpc
Generate RPC modulesgen_rpcis tool for generation of RPC modules.Developed inpythoncode:100%.The README is used to introduce the modules and provide instructions on
how to install the modules, any machine dependencies it may have and any
other information that should be provided before the modules are installed.Table of ContentsInstallationInstall using pipInstall using setuptoolsInstall using dockerDependenciesGeneration flow of RPC modulesRPC SystemRPC MapperTool structureDocsCopyright and LicenceInstallationUsed next development environmentCurrently there are three ways to install tool:Install process based on pipInstall process based on setup.py (setuptools)Install process based on docker mechanismInstall using pipPython package is located atpypi.org.You can install by using pip# python2
pip install gen-rpc
# python3
pip3 install gen-rpcInstall using setuptoolsNavigate to releasepagedownload and extract release archive.To install modules, locate and run setup.py with argumentstar xvzf gen_rpc-x.y.z.tar.gz
cd gen_rpc-x.y.z/
# python2
pip install -r requirements.txt
python setup.py install_lib
python setup.py install_data
python setup.py install_egg_info
# python3
pip3 install -r requirements.txt
python3 setup.py install_lib
python3 setup.py install_data
python3 setup.py install_egg_infoInstall using dockerYou can use docker to create image/container.Dependenciesgen_rpcrequires next modules and libraries:ats-utilities - Python App/Tool/Script UtilitiesGeneration flow of RPC modulesBase flow of generation process:RPC System1. Client encodes data through XDR Filter
2. Client passes XDR encoded data across network to remote host
3. Server decodes data through XDR Filter
4. Server encodes functional call result through XDR Filter
5. Server pass XDR encoded data across network back to Client
6. Client decodes RPC result through XDR Filter and continues processingRPC MapperTool structuregen_rpcis based on OOP.Generator structure:gen_rpc/
├── conf/
│   ├── gen_rpc.cfg
│   ├── gen_rpc_util.cfg
│   ├── project.yaml
│   └── template/
│       ├── template_xdr_rpc.yaml
│       └── xdr_rpc/
│           ├── rpc_client.template
│           ├── rpc_server.template
│           └── rpc_square.template
├── __init__.py
├── log/
│   └── gen_rpc.log
├── pro/
│   ├── config/
│   │   ├── __init__.py
│   │   ├── pro_name.py
│   │   ├── pro_selector.py
│   │   └── pro_type.py
│   ├── __init__.py
│   ├── read_template.py
│   └── write_template.py
└── run/
    └── gen_rpc_run.pyDocsMore documentation and info at:gen_rpc.readthedocs.iorpc mechanismwww.python.orgCopyright and LicenceCopyright (C) 2019 byvroncevic.github.io/gen_rpcgen_rpcis free software; you can redistribute it and/or modify
it under the same terms as Python itself, either Python version 2.x/3.x or,
at your option, any later version of Python 3 you may have available.Lets help and support PSF.
Package: genrss
genrssRSS generator for pythonInstallinggenrss using lxml library that required:libxml2 version 2.9.2 or later.libxslt version 1.1.27 or later.To install the required development packages of these dependencies on Linux systems,
use your distribution specific installation tool, e.g. apt-get on Debian/Ubuntu:sudoapt-getinstalllibxml2-devlibxslt-devInstall and update using pip:pipinstall-UgenrssA Simple ExamplefromdatetimeimportdatetimefromgenrssimportGenRSSfeed=GenRSS(title='SmartFridge',site_url='https://smartfridge.me',feed_url='https://smartfridge.me/feed/rss.xml')feed.item(title='black buns for burgers',description='For the first time black burgers appeared '\'in Japan. Unusual dark color buns complemented '\'with black cheese and sauce. Over time, the dish '\'has conquered the whole world. The main secret '\'ingredient in popular buns is the most common... '\'charcoal!',url='https://smartfridge.me/recipe/316b28-chernye-bulochki-dlya-burgerov/',author='@smartfridge',categories=['baking'],pub_date=datetime.utcnow())xml=feed.xml()LinksDocumentation:https://genrss.readthedocs.io/en/latest/
Package: gensafeprime
This module generates safe prime numbers using the OpenSSL library. A number p
is a safe prime number, if p is a prime number, and p = 2*q+1, and q is a prime
number too. These numbers are sometimes used in cryptography.Written by Erik Tews <erik@datenzone.de>
Python 3 compatibility by Peter Wagenaar <sakartu@gmail.com>
Package: gensarpy
GensarpyGensarpy is a Python package that includes different tests to distinguish series as convergent or divergent. This package provides an easy-to-use interface to check the convergence of series using various tests.InstallationYou can install Gensarpy using pip. To install the latest release, run:pip install gensarpyUsageTo use Gensarpy, import the functions you need from the package and call them with the appropriate arguments. Here's an example:from gensarpy.convergence_tests import check_convergence,isdivergent,integral_testseries1 = "1/n**2"
result1 = check_convergence(series1)
print(f"The series {series1} is {result1}.")series2 = "1/2**n"
result2 = isdivergent(series2)
print(result2)series3 = "(-1)**n/n"
result3 = integral_test(series3)
print(f"The series {series3} is {result3}.")This will output:The series 1/n**2 is convergent.
False
The series (-1)**n/n is divergent.Here is a list of functions in the gensarpy library:integral_testratio_testnth_term_testcheck_convergenseisconvergentisdivergentThey all take as a string as input. You should use 'x' as your variable.ContributingContributions to Gensarpy are welcome! To contribute, please fork the repository, create a branch for your changes, and submit a pull request. Before submitting a pull request, please make sure that your code passes the existing tests and that any new functionality is covered by new tests.LicenseGensarpy is released under the MIT License.
Package: gensaschema
GenSASchema is a static SQLAlchemy schema generator.Supported python versions are Python 2.7 and Python 3.6 and above.Development StatusBeta.Copyright and LicenseCopyright 2010 - 2023
André Malo or his licensors, as applicable.The whole package is distributed under the Apache License Version 2.0.
You’ll find a copy in the root directory of the distribution or online
at: <http://www.apache.org/licenses/LICENSE-2.0>.BugsNo bugs, of course. ;-)
But if you’ve found one or have an idea how to improve GenSASchema, feel
free to send a pull request ongithubor send a mail to
<gensaschema-bugs@perlig.de>.Author InformationAndré “nd” Malo <nd perlig.de>
GPG: 0x029C942244325167If God intended people to be naked, they would be born that way.
– Oscar Wilde
Package: genscrapeclient
Genscrape Client is the API Client library for Genscrape. To use the
Genscrape API, you will need to have an account there and a valid API
key and secret. To create an account, send an email tokaran@kodeplay.com.DependenciesThe only dependency isrequests-oauthlib.InstallationThis library is yet to be packaged and published to PyPI. Till then,
just clone the git repository and run,$ python setup.py installPreferably install inside a virtualenv.UsageSeedocs.