Saravanan666/pypi-org huggingface dataset:
Package: torex
torex is an open source application for automatic torrent extraction.InstallationYou can install through PyPi:`bash pip install torex `Or just download the sources (manually or clone from GitHub) and run:`bash python setup.py install `RunningThe command for running torex is justtorex.The command-line interface is:`bash torex <config_path> <torrent_path> <label> `Where:
* config_path: Configuration file path
* torrent_path: The path to the downloaded torrent
* label: The torrent’s label (will be explained later on)uTorrent SetupThe script is particularly easy to run from uTorrent. Under Preferences, go to Advanced -> Run Program.
Then, set the program to be run:`bash torex <config_path> "%D" "%L" `Finally, when you add a torrent that should be extracted, just make sure it is assigned the correct label in uTorrent.LabelsSupported torrent labels:
* tv - A TV series torrent (Formatted likeBreaking Bad S01E01)ConfigurationThe configuration file is a YAML file, that tellstorexwhere it should extract the torrents to.
You can take a look atconfig_example.yamlfor an example of what a configuration file should look like.Under the label, you can define a rootpaththat the torrents will be extracted to.
Every torrent will be extracted to a subdirectory with the TV series’ name.You can define an array ofspecialtypes, each containing two fields:
* title: A regex for matching a torrent’s title
* path: The path that these torrents should be extracted toThespecialconfiguration is particularly useful when you have a big drive that holds all your downloads,
but you want some specific torrents to be extracted somewhere else.Torrent TypesRight now, the only supported torrents are torrents that are a single directory with a single.rarfile to be extracted.Logstorexwrites logs to~/.torex/logs.txt
Package: tor-expert
AboutThe main objective of this project is to create an instance of tor expert that canbe used in the same way as the tor browser.InstallationMost important thing is that you have python 3 installed on your machine.Deploy virtual environment for your projectInstall virtualenv library if you didn't already.pip3.7 install virtualenvFor this project, I'm using Python 3.7 if you have any other python 3 versionsbe sure to change the version number on pip.
Then create virtual environmentpy -3.7 -m virtualenv Envs/myprojectIn most cases on WinOS it will be created on pathC:\Users\YourUsername\EnvsActivate virtual environment for your projectActivate by simply calling this commandC:\Users\YourUsername\Envs\myproject\Scripts\activate.batfrom command prompt.Installing tor_expert librarypip install tor-expertUsageUsage example in Pycharmopen Pycharm and start a new project and name it however you wantselect existing interpreter and then browse toC:\Users\YourUsername\Envs\myproject\Scripts\pythonnow in the new project create a new python fileimport tor_expertfrom tor_expert import tor, settingsthen we need to install tor expert this is only done once or if you want to reinstall it. To do this we need to write the following linetor.install()by default tor expert directory will be installedC:\Users\YourUsername\Documents\Tornow you are ready to crawl data, check crawler_example.py to see an example of usage (https://github.com/DraganMatesic/tor_expert/tree/master/examples).
Package: torf
torf provides aTorrentand aMagnetclass.torf-cliandtorf-guiprovide user interfaces for torf.This project started as a fork ofdottorrentbut turned into a rewrite.FeaturesCreate aTorrentinstance from a path to the torrent’s content or by
reading an existing.torrentfileHigh-level access to standard metainfo fields via propertiesLow-level access to arbitrary metainfo fields viametainfopropertyOptional metainfo validation with helpful error messagesGenerate aBTIH magnet URIfrom a.torrentfile
(the reverse is also possible but the resulting torrent is incomplete due to
the lack of information in magnet URIs)Use multiple CPU cores to compute piece hashesRandomize the info hash to help with cross-seedingConveniently re-use piece hashes from an existing torrent fileExamplefromtorfimportTorrentt=Torrent(path='path/to/content',trackers=['https://tracker1.example.org:1234/announce','https://tracker2.example.org:5678/announce'],comment='This is a comment')t.private=Truet.generate()t.write('my.torrent')DocumentationEverything should be explained in the docstrings. Read it withpydoc3 torf.Torrentorpydoc3 torf.Magnet.Documentation is also available attorf.readthedocs.ioortorf.readthedocs.io/en/latestfor the development version.Installationtorf is available onPyPI.The latest development version is in the master branch onGitHub.ContributingI consider this project feature complete, but feel free to request new features
or improvements. Bug reports are always welcome, of course.LicenseGPLv3+
Package: torf-gui
# torf-gui[![GitHub Build Status](https://img.shields.io/github/actions/workflow/status/SavageCore/torf-gui/build.yml?style=flat-square&logo=pytest)](https://github.com/SavageCore/torf-gui/actions/workflows/build.yml)
[![Code Style: black](https://img.shields.io/badge/code%20style-black-black)](https://pypi.org/project/black/)[![PyPI - Downloads](https://img.shields.io/pypi/dm/torf-gui?style=flat-square&logo=pypi)](https://pypi.org/project/torf-gui/)
[![PyPI - Version](https://img.shields.io/pypi/v/torf-gui?style=flat-square)](https://pypi.org/project/torf-gui/)A quick and dirty port of
[dottorrent-gui](https://github.com/kz26/dottorrent-gui) for
[torf](https://github.com/rndusr/torf)![image](img/screenshot_light.png)![image](img/screenshot_dark.png)## FeaturesFast (capable of several hundred MB/s)Cross-platformFull Unicode supportUse multiple CPU cores to compute piece hashesAutomatic and manual piece size selection, up to 16MBBatch torrent creation modeFilename exclusion patterns (globs)HTTP/web seeds support [(BEP19)](http://www.bittorrent.org/beps/bep_0019.html)Private flag support [(BEP27)](http://www.bittorrent.org/beps/bep_0027.html)Randomize info hash to help with cross-seedingUser-definable source stringOptional MD5 file hash inclusion[Import/export ofprofiles](https://github.com/SavageCore/torf-gui/wiki/Profiles)
(trackers, web seeds, source string, filename exclusion patterns)Automatic dark mode!## Installation### Windows and macOSYou can find the latest releases [here](https://github.com/SavageCore/torf-gui/releases).On Windows, simply download and runtorf-gui-win64.exe. You may need
to download and install the [Microsoft Visual C++ Redistributable for
Visual Studio
2015](https://www.microsoft.com/en-us/download/details.aspx?id=48145).On macOS, download and extracttorf-gui-macOS.zipthen run the app.
You may need to allow the app to run in your security settings.### Linux#### RequirementsPython 3.3+PyQt5 5.7+libxcb-xinerama0 (Debian/Ubuntu)Latest stable release:pip install torf-guiDevelopment:git clonethis repository, thenpip install .To run:torf-gui## Portable Modetorf-gui can be configured to run in portable mode, good for running
from USB drives and network shares. To enable this, simply create an
empty file namedtorf-gui.iniin the same directory as the main
excecutable.## License© 2023 Oliver Sayers. Made available under the terms of the [GNU General
Public License v3](http://choosealicense.com/licenses/gpl-3.0/).[![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/E1E6P7VIQ)
Package: torfy
Copyright (C) 2016  F. Brezo and Y. Rubio, i3visio[![Version in PyPI](https://img.shields.io/pypi/v/torfy.svg)]()
[![Downloads/Month in PyPI](https://img.shields.io/pypi/dm/torfy.svg)]()
[![License](https://img.shields.io/badge/license-GNU%20General%20Public%20License%20Version%203%20or%20Later-blue.svg)]()1 - DescriptionOSRFramework is a GPLv3+ set of libraries developed by i3visio to perform Open Source Intelligence tasks. They include references to a bunch of different applications related to username checking, information leaks research, deep web search, regular expressions extraction and many others. At the same time, by means of ad-hoc Maltego transforms, OSRFramework provides a way of making these queries graphically.2 - License: GPLv3+This is free software, and you are welcome to redistribute it under certain conditions.This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.For more details on this issue, check the [COPYING](COPYING) file.3 - InstallationFast way to do it on any system:` pip install torfy `Under MacOS or Linux systems, you may need to do this as superuser:` sudo pip install torfy `This will manage all the dependencies for you.If you needed further information, check the [INSTALL.md](INSTALL.md) file.4 - Basic usageIf everything went correctly (we hope so!), it’s time for trying torfy.py. But first, you will need to start the Tor Bundle downloadable fromhttp://torproject.org. Execution examples:` onionGet.py-u"http://3g2upl4pq6kufc4m.onion/"`Type -h or –help to get more information about which are the parameters of the application.You can also use the functions as a library:` import torfy.tor as torwrapper url ="http://3g2upl4pq6kufc4m.onion/"data = torwrapper.getResponse(url) print data `5 - HACKINGIf you want to extend the functionalities of Torfy and you do not know where to start from, check the [HACKING.md](HACKING.md) file.6 - AUTHORSMore details about the authors in the [AUTHORS.md](AUTHORS.md) file.
Package: torgen
Django’s CBVs adapted to be used with Tornado along with SQLAlchemy and WTForms.
It’s highly recomended to read the docs here first:https://github.com/BeardyBear/tornado-generic-handlersChangelog0.2: new handler - DeleteHandler
0.2.5: fixed missing context in ProcessFormHandlerConfigurationThe only requirement is SQLAlchemy’s session stored in application’s db attribute.from sqlalchemy.orm import scoped_session, sessionmaker

class Application(tornado.web.Application):
    def __init__(self):
        self.db = scoped_session(sessionmaker(bind=engine))Basic usagefrom torgen.base import TemplateHandler
from torgen.list import ListHandler
from torgen.detail import DetailHandler
from torgen.edit import FormHandler, DeleteHandler
from my_alchemy_models import Post
from my_wtforms import LoginForm

class HomeHandler(TemplateHandler):
    template_name = 'home.html'

class BlogHandler(ListHandler):
    template_name = 'blog.html'
    paginate_by = 10
    context_object_name = 'post_list'
    model = Post

class PostHandler(DetailHandler):
    template_name = 'post.html'
    model = Post
    context_object_name = 'post'

class LoginHandler(FormHandler):
    template_name = 'login.html'
    form_class = LoginForm
    success_url = '/'

    def form_valid(self, form):
        self.set_secure_cookie('user', form.data['username'])
        return super(LoginHandler, self).form_valid(form)

class DeletePostHandler(DeleteHandler):
    template_name = 'confirm_delete.html'
    model = Post
    success_url = '/blog/'PaginationPagination can be used separately from generic handlers.from torgen.pagination import Paginator, EmptyPage, PageNotAnInteger

class BlogHandler(tornado.web.RequestHandler):
    @property
    def db(self):
        return self.application.db

    def get(self, page):
        post_list = self.db.query(Post).all()
        paginator = Paginator(posts, 15)
        try:
            posts = paginator.page(page)
        except PageNotAnInteger:
            posts = paginator.page(1)
        except EmptyPage:
            posts = paginator.page(paginator.num_pages)
        self.render('blog.html', posts=posts)You can find advanced docs here:https://github.com/BeardyBear/tornado-generic-handlersInstallationUsing pip:$ pip install torgen
Package: torii
Torii-HDLTorii is a fork ofAmaranth HDLthat has been modified for use atShrine Maiden Heavy Industries. It has merged several of the components that were separate into a single package, and also adds new functionality, as well as some internal changes for better integration into tooling.The evaluation board definitions have also been migrated and are located in thetorii-boardsrepository.There is also a list ofprojects using Toriithat are using Torii, and we'd love to add yours too!IntroductionPlease see theTorii Introductionon theonline documentationInstallationPlease see theinstallation instructionson theonline documentationSupported devicesTorii can be used to target any FPGA or ASIC process that accepts behavioral Verilog-2001 as input. It also offers extended support for many FPGA families, providing toolchain integration, abstractions for device-specific primitives, and more. Specifically:FPGAToolchainProprietaryFOSSLattice iCE40iCECube2Yosys+nextpnrLattice ECP5Lattice DiamondLattice MachXO3LLattice MachXO2Xilinx 7-seriesVivadoXilinx UltraScaleXilinx Spartan 6ISEXilinx Spartan 3AAltera/IntelQuartusQuicklogic EOS S3Yosys+VPRLicenseTorii is released under theBSD-2-Clause, the full text of which can be found in theLICENSEfile.
Package: torinja
Integrate Tornado Web Framework and Jinja2 TemplatesRequires Python >= 3.3 or Python 2.7.InstallationpipinstalltorinjaUsageConfigurationUse torinja’sJinja2Envas thetemplate_loaderof yourApplication.fromtornado.webimportApplicationfromtorinjaimportJinja2Envfromjinja2importPackageLoaderapplication=Application(handlers=[],template_loader=Jinja2Env(loader=PackageLoader('myapp','templates'),# You can pass any jinja2 loaders),**other_settings)Jinja2Envis ajinja2.Environmentsubclass, so it accepts all theoptionstojinja2.Environment.The only difference is thatautoescapeis set toTrueby default.HandlersIn your handlers, you can callRequestHandler.renderorRequestHandler.render_stringas you would do with tornado templates.classMyHandler(RequestHandler):defget(self):self.render('index.html',tornado='awesome',jinja2='rocks')TemplatesTo usexsrf_form_htmlin yourjinja2templates, use it as a variable.<form>{{ xsrf_form_html }}<inputtype="text"name="text"><!-- ... --></form>TestsTo run the tests:pythontests.py
Package: torip
toripPython library for Tornado web framework to locate IPs or server names.Torip will provide you information like country, city, zip code or the url of google maps.Installation$pipinstalltoripAvailable APIsTorip supports the following APIs:[abstractapi]ABAPIIt is also the default API.fromtorip.locatorimportLocatorlocator=Locator(api_name='abstractapi',api_token=<YourAPITOKEN>)orfromtorip.locatorimportLocatorlocator=Locator(api_token=<YourAPITOKEN>)# default API[ip-api]IPAPIfromtorip.locatorimportLocatorlocator=Locator(api_name='ip-api')Exampleimporttornadofromtorip.locatorimportLocatorip='<IP ADDRESS>'@tornado.gen.coroutinedeffunction():try:locator=Locator(api_token='<YOUR API TOKEN>')result=yieldlocator.locate(ip)print(result)exceptExceptionase:print(str(e))finally:ioloop.stop()ioloop=tornado.ioloop.IOLoop.instance()ioloop.add_callback(function)ioloop.start()Docsgithubpypireadthedocs
Package: torippy
poetry-template概要自分用のpoetryプロジェクトのテンプレート。つかいかたcloneしてよしなに。以下のようなシェルスクリプトを作ってPathを通しておくと、poetry-template [project-name]で「templateのclone」・「フォルダのrename」・「vscodeで開く」までできて楽。# poetry-template.ps1Param([string]$projectName)gitclonehttps://github.com/torippy1024/poetry-templateRename-Itempoetry-template$projectNamecode$projectName機能vscodeでファイル保存時、自動フォーマット (black)task run: src/main.py を実行task lint: flake8 で linttask build: pyinstaller で exe化task build-one: pyinstaller で exe化 (＋ 1つのファイルにまとめる)task test: pytest 実行
Package: torlib
torlibtorlib is an open source Python utility package that can help in many scenarios :DInstallationThis package can be installed fromPyPiby running:pip install torlibDocumentationYou can view thedocumentationfor torlib.To build the documentation locally, you can run the following command on your terminal (Sphinxis required):sphinx-build -b html docs/ docs/_build/ -D language="en"FeaturesCrawlerChangelogSee release notes for changeloghttps://github.com/noppadol-assava/torlib/releasesLicensetorlib is licensed under theMIT License.
Package: torloc
TorlocTorloc runs Tor services on local ports. So you can use many different ip addresses without having to start
each service manually.For Linux, Windows and MacOS.Installationpip install torlocOr download the tarball /git cloneand...python setup.py installUsageimporttorloc# Several portsprocesses=torloc.CreateMany(16)# threads is 8 by defaultports=processes.ports# {port: TorProcess}whilenotprocesses.ready:# Waiting for all ports to be readypassprocesses.stop(list(ports.keys())[0])processes.stop_all()# One portprocess=torloc.TorProcess(49152)stdout=process.stdout# file objectstderr=process.stderr# file objectwhilenotprocess.ip:# Waiting for the port to be readypassprocess.stop()
Package: torm
Tormmongodb style orm.mongodb,mysql are supported.Installgit clone https://github.com/cofepy/torm
cd torm
python setup.py installorpip install tormEnv fileadd .env file to top folder or copy one file in envs to top folder.if database has auth, set TORM_AUTH = on/off (default off).for example:TORM_DB_TYPE   = mongo
TORM_DB       = test_default

TORM_HOST     = 127.0.0.1
TORM_PORT     = 27017

TORM_CHARSET  = utf8mb4

TORM_AUTH     = on
TORM_USER     = root
TORM_PASSWORD = xxxUseagefromtorm.modelimportModelfromtorm.fieldimportStr,IntclassRecord(Model):# config file is ".env.mongo"; if not given, default config file is ".env".__configname__='mongo'# database type; if not given, will use db defined in config file# if no config file, torm will use "mongo" as default.__dbtype__='mongo'# database name: if not given, will use db defined in config file# if no config file, torm  will use "test" as default.__dbname__='test'# table name: if not given, torm  will use the snake name of the model class name as default__tablename__='record'hash=Str()subject=Str()promoter=Str()attachments_num=Int()mail_id=Str()commits=Str()group=Str()group_hash=Str()create_at=Str()update_at=Str()status=Str()tx_status=Str()recorder=Str()# 创建record=Record({"hash":"0x123","subject":"test"})Record.InsertOne(record)# 单条查询hash="0x123"record=Record.FindOne(hash)record=Record.FindOne(hash=hash)record=Record.FindOne({'hash':hash})print(record)# 批量查询records=Record.FindMany()print(records)
Package: torman
WhatThis script allows you to initialize multiple TOR instances and proxy to them using an API.The script automatically refreshes TOR IP's after a number of calls through each TOR Socket.RunningTo get started with Torman:Install with pip:$ pip install tormanThen Start:$ tormanYou should see the following output.,---------.    ,-----.    .-------.    ,---.    ,---.   ____    ,---.   .--. 
\          \ .'  .-,  '.  |  _ _   \   |    \  /    | .'  __ `. |    \  |  | 
 `--.  ,---'/ ,-.|  \ _ \ | ( ' )  |   |  ,  \/  ,  |/   '  \  \|  ,  \ |  | 
    |   \  ;  \  '_ /  | :|(_ o _) /   |  |\_   /|  ||___|  /  ||  |\_ \|  | 
    :_ _:  |  _`,/ \ _/  || (_,_).' __ |  _( )_/ |  |   _.-`   ||  _( )_\  | 
    (_I_)  : (  '\_/ \   ;|  |\ \  |  || (_ o _) |  |.'   _    || (_ o _)  | 
   (_(=)_)  \ `"/  \  ) / |  | \ `'   /|  (_,_)  |  ||  _( )_  ||  (_,_)\  | 
    (_I_)    '. \_/``".'  |  |  \    / |  |      |  |\ (_ o _) /|  |    |  | 
    '---'      '-----'    ''-'   `'-'  '--'      '--' '.(_,_).' '--'    '--' 
    ┌                                   ┐
    │  Manage TOR Proxies like a Boss!  │
    └                                   ┘

2021-12-11 21:13:48 mugendis-beast Torman[53081] INFO Started 4 TOR instances.
2021-12-11 21:13:48 mugendis-beast waitress[53081] INFO Serving on http://0.0.0.0:6930
30This confirms that Torman is ready and runnibng on thedefault port6930. Torman is now ready to start taking your requests and you can run the following CURL command.curl--requestGET\--urlhttp://127.0.0.1:6930/\--header'Content-Type: application/json'\--data'{"url" : "https://ipinfo.tw/ip"}'This should return a response showing your current TOR IP address.{"meta":{"proxy":{"port":9060,"remaining-requests":49},"took":"367ms"},"response":"185.220.101.170"}This shows the proxy port used, remaining-requests till the IP refreshes, the response as well as how long it took to get the response. Repeat the CURL command and note that the TOR proxies keep getting rotated with each proxy call.APIYou can pass arguments to fine tune how torman works.torman --helpwill show you all the available commands.--refresh-afterNumber of requests after which the TOR IP gets refreshed. You must provide a control passwoerd for this to work. Defaults to 50 requests.--control-passYour TOR control password. Used to renew TOR IPs whenrefresh-aftervalue has been reached.--serverThe port through which Torman listens for REST API requests. Default is 6930--instancesNumber of TOR instances to initiate. Default is 4. Torman will cycle through the TOR instances and allocate requests to each.--stopStop Torman and all TOR instances.--verboseShow/Log API requestsExamplestorman --verbosetorman --refresh-after 10 --control-pass my_passrefresh after 10 TOR requests wusing "my_pass" as the control passwordBeware!Stopping Torman using the--stopargument stops all running TOR and Torman instances. This includes any TOR processes not initiated by Torman. You might need to manually restart them, if any. That said, why would you be running TOR processes manually when you have Torman?Logo created byDesignEvo logo maker
Package: tormdb
tormdbtormdbstands for Transposed Object Relational Mapping Database.tormdbstores your objects into SQLite for maintaining the accessibility across runtimes without you inheriting any customized Classes.UsageSavetormdb.save(<object>)import dataclasses
from typing import List

import tormdb


@dataclasses.dataclass
class Person:
    name: str
    age: int


@dataclasses.dataclass
class Family:
    husband: Person
    wife: Person
    children: List[Person] = dataclasses.field(default_factory=list)


wife: Person = Person('Catherine', 24)
husband: Person = Person('Chris', 24)
daughter: Person
son: Person
daughter = son = Person('Alex', 0)

family = Family(
    husband=husband,
    wife=wife,
    children=[daughter, son])

tormdb.save(family)Load<object> = tormdb.load(<List[Class]>)import dataclasses
from typing import List, Optional

import tormdb


@dataclasses.dataclass
class Person:
    name: str
    age: int


@dataclasses.dataclass
class Family:
    husband: Person
    wife: Person
    children: List[Person] = dataclasses.field(default_factory=list)


family: Optional[Family] = tormdb.load([Family, Person])
Package: torment
DescriptionA Study in Fixture Based Testing FrameworkingA (probably) new structure for fixture organization and integration into
unittest.  A minimal layer on top of unittest that allows declarative fixtures
to define new tests.  Designed for unit testing but explores new integration
testing patterns as well.InstallationThis package is stored in PyPI and can be installed the standard way:pip install tormentThe latest release available is:Using TormentUsage of this package is documented with sphinx and available athttp://torment.readthedocs.org/en/latest/Developing TormentIf you would prefer to clone this package directly from git or assist with
development, the URL ishttps://github.com/kumoru/torment.Torment is tested continuously by Travis-CI and running the tests are quite
simple:flake8
nosetestsThe current status of the build is:AuthorsAlex Brandt <alunduil@alunduil.com>Known IssuesKnown issues can be found in the github issue list athttps://github.com/kumoru/torment/issues.TroubleshootingIf you need to troubleshoot an issue or submit information in a bug report, we
recommend obtaining logs (probably from nose) while enabling log capture of
torment.  Torment uses logging to submit informational and debug messages but
also sets a NullHandler by default.