Saravanan666/pypi-org huggingface dataset:
Package: lektor-tinymce
lektor-tinymceLektor plugin for editing with theTinyMCE text editor.InstallationInstall the plugin from pypi with one of thestandard ways.CompatibilityThis plugin uses non-api mechanisms in Lektor/Flask to inject its own code into admin jinja template.
Due to frequent change in Lektor admin backend code, each version of this plugin shall most likely be compatible with specific version of Lektor.
Currently it is compatible with Lektor3.3.6API keyTo add an API key, create the fileconfigs/tinymce.iniin your lektor project folder with the following contents:[licence]
api-key = 'YOUR_API_KEY_HERE'Tiny MCE settingTo pass additional arguments (such as a list of plugins) intotinymce.init(), just add the following contents to the fileconfigs/tinymce.iniin your lektor project folder:
[config]
settings = 'YOUR_SETTINGS'Here is the example of the settings string:
[config]
settings = "plugins: 'image link lists autoresize table', image_advtab: true,"Note that this string is passed directly into tinymce.init(), so it must follow the given format.
Some plugins, such as image upload, may not be fully integrated with lektor by default.LicenseThe plugin is distributed under the MIT license
Package: lektor-twitter-embed
lektor-twitter-embedLektor template filter to convert twitter links to embedsInstallationpip install lektor-twitter-embedUsage{{ "https://twitter.com/MaiaFranklyn/status/1277100235928621058" | tweet }}It is possible to pass an optional 'params' object to configure the embed.
Any of the params documented athttps://developer.twitter.com/en/docs/twitter-api/v1/tweets/post-and-engage/api-reference/get-statuses-oembedmay be supplied{{
  "https://twitter.com/MaiaFranklyn/status/1277100235928621058" | tweet(
    params={'align': 'center', 'hide_thread': 'true'}
  )
}}By default if the request topublish.twitter.comfails, your page will not build.
This behaviour can be changed so that a failed request topublish.twitter.comwill fall back to rendering a link to the tweet.{{ "https://twitter.com/lucaviftw/status/1347311486012686336" | tweet(fallback=True) }}
Package: lektor-webpack-html-helper
lektor-webpack-html-helperThis is a plugin for Lektor that adds support for generating templates with webpacks HtmlWebpackPlugin. These templates can be generated into Lektors assets folder which will be observed for newly created or modified html files.
These files will then be copied over to Lektors templates folder so that they can be used by Lektor.
This plugin depends on thelektor-webpack-supportplugin to be really useful.webpack/webpack.config.jsconstpath=require("path");constMiniCssExtractPlugin=require("mini-css-extract-plugin");constHtmlWebpackPlugin=require("html-webpack-plugin");const{CleanWebpackPlugin}=require("clean-webpack-plugin");module.exports={mode:"production",entry:{main:"./src/index.js"},output:{filename:"[name].bundle.js",path:path.dirname(__dirname)+"/assets/generated"},optimization:{minimizer:[newHtmlWebpackPlugin({inject:false,filename:"layout_generated.html",template:"./src/layout_template.html"})],},plugins:[newCleanWebpackPlugin(),newMiniCssExtractPlugin({filename:"[name].css"})],module:{rules:[{test:/\.scss$/,use:[MiniCssExtractPlugin.loader,"css-loader","sass-loader"]}]}}webpack/src/layout_template.html<!DOCTYPE html><htmllang="en"><head><metacharset="UTF-8"><metaname="viewport"content="width=device-width, initial-scale=1.0"><metahttp-equiv="X-UA-Compatible"content="ie=edge"><title>{{ this.title }}&middot;{{ config.PROJECT.name }}</title><% for (var css in htmlWebpackPlugin.files.css) { %><linkhref="{{ '/generated/<%= htmlWebpackPlugin.files.css[css] %>' | asseturl }}"rel="stylesheet"><% } %></head><body><main>{% block content %}
        {% endblock content %}</main><% for (var chunk in htmlWebpackPlugin.files.chunks) { %><scriptsrc="{{ '/generated/<%= htmlWebpackPlugin.files.chunks[chunk].entry %>' | asseturl }}"></script><% } %></body></html>
Package: lektor-yandex-metrica
This plugin adds support forYandex MetricatoLektor CMSEnabling the Pluginlektorpluginsaddlektor-yandex-metricaConfiguring the PluginJust create a file namedyandex-metrica.iniin yourconfigs/folder and configureidkey with the provided counter id:id=YOUR_COUNTER_IDIn TemplatesNow you can add a Yandex Metrica counter to any of your templates by just using thegenerate_yandex_metricafunction in its tag as below.{{ generate_yandex_metrica() }}
Package: lektor-youtube-embed
lektor-youtube-embedLektor template filter to convert youtube links to embedsInstallationpip install lektor-youtube-embedUsage{{ "https://www.youtube.com/watch?v=9Yk9iRDESDo" | youtube }}{{ "https://youtu.be/BdXDT-5jci0" | youtube(width=640, height=480, attrs={'class': 'video'}) }}
Package: lelesk
Le's LeskA fast Python 3 Word-Sense Disambiguation package (WSD) using the extended LESK algorithmInstallleleskis available onPyPIand can be installed using pippipinstallleleskLelesk uses NLTK lemmatizer and yawlib wordnet API.
To install NLTK data, start a Python prompt,import nltkand then download the required data$python3Python3.6.9(default,Jan262021,15:33:00)[GCC8.4.0]onlinuxType"help","copyright","credits"or"license"formoreinformation.>>>importnltk>>>nltk.download(['stopwords','punkt','averaged_perceptron_tagger','wordnet'])Download and extractyawlibpre-built databasesto~/wordnet.For more information:Installing NLTK data:https://www.nltk.org/data.htmlInstalling Yawlib wordnets:https://pypi.org/project/yawlib/Command-line toolsTo disambiguate a sentence, run this command on the terminal:python3-mleleskwsd"I go to the bank to get money."To perform word-sense disambiguation on a text file, prepare a text file with each line is a sentence.For example here is the content of the filedemo.txtI go to the bank to withdraw money.
I sat at the river bank.you then can run the following command# output to TTL/JSON (a single file)
python3 -m lelesk file demo.txt demo_wsd_output.json --ttl json

# output to TTL/TSV (multiple TSV files)
python3 -m lelesk file demo.txt demo_wsd_output.json --ttl tsvIssuesIf you have any issue, please report athttps://github.com/letuananh/lelesk/issues
Package: lel-lang
# LEL Interpreter in PythonLel is a lisp like programming language. It is not meant for practical purposes, but more as a tool to learn how to write a programming language.This project comes with a Lel interpreter for running Lel programs, and a REPL for executing Lel expressions in real time.The pylel version is developed in Python.# InstallationIf you would like to install the interpreter and REPL to your machines` pip installlel-lang`# UsageTo use the REPL, simply call` pylel `or you can feed a lel file to the same command to run the code.` pylel filename.lel `# AcknowledgementThe first version of the language syntax and javaScript implementation is written by Frank Stokes.
Package: le-logging
LE Logging LibraryInstallation:pip install le-loggingThis library defines a standardized logging pattern for all Python based Projects inside LE Environment.It's based on Pythons integrated Logging System and makes it easy to use without redefining Layouts and Rotations
manually for every project.It's mandatory to generalize Logs to simplify debugging and problem solving.Available Log Levels are defined as ENUMclassLevel(Enum):DEBUG=10INFO=20WARNING=30ERROR=40CRITICAL=50The usage of the Library is simple:Defining a Rotating LogFile based on filesize:attribut is the maximum file size in Megabytes [Default is 32MB]
max_backup attribut defines the maximum stored Files before overwriting existing Files [Default is 14 Files]# Defining loglevel as integer:fromle_loggingimportRotatingLoglog=RotatingLog(name="Testlog",max_backups=5,max_size=64,level=10)# Defining LogLevel based on Enumfromle_loggingimportRotatingLog,Levellog=RotatingLog(name="Testlog",max_backups=5,max_size=64,level=Level.DEBUG)# Defining specific Pathfromle_loggingimportRotatingLog,Levellog=RotatingLog(name="Testlog",path="/var/log",max_backups=5,max_size=64,level=Level.DEBUG)Defining a Timed Rotating LogFile based on filesize:# Defining loglevel as integer:fromle_loggingimportTimedRotatingLoglog=TimedRotatingLog(name="Testlog",max_backups=5,max_size=64,level=10)# Defining LogLevel based on Enumfromle_loggingimportTimedRotatingLog,Levellog=TimedRotatingLog(name="TimedTestlog",max_backups=5,timer=1,level=Level.DEBUG)# Defining specific Pathfromle_loggingimportTimedRotatingLog,Levellog=TimedRotatingLog(name="TimedTestlog",path="/var/log",max_backups=5,timer=1,level=Level.DEBUG)Using defined LogFileslog.debug("This is a DEBUG message")log.info("This is an INFO message")log.warn("This is a warn message")log.error("This is an ERROR message")log.critical("This is a CRITICAL message")
Package: lemapp
lemonodor app framework.INSTALL=======::$ pip install lemappUSAGE=====...DEVELOP=======::$ git clone http://github.com/wiseman/lemapp lemapp$ cd lemapp$ makeRUNNING TESTS=============::$ make testChangelog=========0.5 (2017-06-06)----------------- Nothing changed yet.0.4 (2017-04-25)----------------- Nothing changed yet.0.3 (2016-01-31)----------------- Nothing changed yet.0.2 (2016-01-31)----------------- Nothing changed yet.0.1 (2016-01-31)----------------- Initial release.[John Wiseman]lemapp Copyright (c) 2012, John WisemanAll rights reserved.Redistribution and use in source and binary forms, with or withoutmodification, are permitted provided that the following conditionsare met:1. Redistributions of source code must retain the above copyrightnotice, this list of conditions and the following disclaimer.2. Redistributions in binary form must reproduce the above copyrightnotice, this list of conditions and the following disclaimer in thedocumentation and/or other materials provided with the distribution.3. The name of the author may not be used to endorse or promote productsderived from this software without specific prior written permission.THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS ORIMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIESOF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUTNOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANYTHEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OFTHIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Package: lemity
Lemity视频服务器, 视频资源可通过网络在其他设备(手机, 电视, 电脑) 使用浏览器进行播放, 只支持MP4视频格式安装pip install lemity --upgrade使用进入视频文件夹, 打开命令行>>> lemity run <port>
: Running on http://192.168.0.112:8000/ (Press CTRL+C to quit)打开浏览器, 输入:http://192.168.0.112:8000/port: 开放端口, 默认为 8000端口下次更新内容提供更多视频格式增加边转码边播放功能
Package: lemmagen3
Aboutlemmagen3is a Python 2/3 wrapper for theLemmagen lemmatizer(version2.2).It is different from other Lemmagen wrappers likethis one on PyPibecause it offers a clean, fast OO interface built with the excellentpybind11 libraryand supports an additional language (Croatian).Models for Slovene, Croatian and Serbian are significantly updated and make use of frequency data to prefer most frequent lemmas, e.g., for Slovene:je->bitiinstead ofje->jesti,mene->jazinstead odmene->mena,od->odinstead ofod->odaetc.In total, 19 languages are supported:Bulgarian:bgCroatian:hrCzech:csEnglish:enEstonian:etFarsi/Persian:faFrench:frGerman:deHungarian:huItalian:itMacedonian:mkPolish:plRomanian:roRussian:ruSerbian:srSlovak:skSlovene:slSpanish:esUkrainian:ukInstallation and requirementspipinstalllemmagen3will install the module and language model files. Please note that onpython <=3.5andpython 2.7the package will be built from source so you will need a C++ compiler.Note:If you usepython 3.5.0or3.5.1you will likely get the error shown below. This is a known bug in these two versions so please consider upgrading your Python.ImportError:..._lemmagen.cpython-35m-x86_64-linux-gnu.so:undefinedsymbol:_PyThreadState_UncheckedGetHow to useThe following snippet illustrates how to uselemmagen3.fromlemmagen3importLemmatizer# first, we can list all supported languagesprint(Lemmatizer.list_supported_languages())# then, create few lemmatizer objects using ISO 639-1 language codes# (English, Slovene and Russian)lem_en=Lemmatizer('en')lem_sl=Lemmatizer('sl')lem_ru=Lemmatizer('ru')# now lemmatize the word "cats" in all three languagesprint(lem_en.lemmatize('cats'))print(lem_sl.lemmatize('mačke'))print(lem_ru.lemmatize('коты'))# you can also change the language for an existing Lemmatizer object# lem_en will now become a French lemmatizer:lem_en.load_language('fr')# finally, you can also load your own Lemmagen modelmy_lem=Lemmatizer()my_lem.load_model('/path/to/my/model')Note that the functionlemmatizeaccepts single string tokens anddoes not split the input string! If you want to lemmatize a chunk of text you will have to tokenize it first, e.g.:sentence='cats hate dogs'tokens=sentence.split()sentence_lemmatized=' '.join([lem_en.lemmatize(token)fortokenintokens])Note also thatlemmagen3operates on unicode encoded strings so if you use python 2 make sure that your input string is encoded as unicode.LicensePlease note that this repository contains code and binary models compiled and built from different sources which are under different licenses:C++ files and headers come fromLemmagenand are modified and adapted to work as a Python module (LGPL)Binary models are built from Multext andMultext-eastsources:Language resources used to build Farsi/Persian, Macedonian, Polish, and Russian models are fornon-commercial use only.Language resource for other supported languages are released underCC BY-SA 4.0.The rest of the code in this repository was created by the author and is licensed under theMIT license.Authorslemmagen3is developed by Vid Podpečan (vid.podpecan@ijs.si).The Lemmagen lemmatizer was developed byMatjaž Juršič.
Package: lemmes
# Lemmes
Lemmas for Spanish## Install
After clone this repopython setup.py build && python setup.py install
python -m lemmes.download## Basic Usage# see test.py## Developer Stage
### Pre-InstallDocker 1.*### Runcd /[project_path]
docker build -t lemmes .
docker run -v $(pwd):/lemmes:rw -it lemmes bash
python -m lemmes.download### Testinvoke test### Work indocker run -v $(pwd):/lemmes:rw -it lemmes bash
Package: lemming
Generates the structure needed for a Python 3 project. Includes helpers for licenses and testing frameworks.InstallationTo install this software:$pipinstalllemmingUsageThe first time that you run lemming, you should execute the following:$lemmingconfigit’ll write.lemming.ymlto your$HOMEdirectory, which you can edit to automatically populate templates
with your details for all future runs.That file looks as follows:---lemming:author:Paul Stevensauthor_email:no-reply@xnode.co.zalicense:type:MITTo uselemmingto generate a project:$lemming<project_name>This obviously means that you can never name a projectconfig…The default license is the MIT license (rude, but this is the one that I use the most.) The other two choices are:Apache 2.0BSD 2-clause licenseTo select the APACHE license for your project:$lemmingtestprog--licenseapacheTo select the BSD 2-clause license for your project:$lemmingtestprog--licensebsdNoteCurrently supported licenses are:MIT (default)Apache 2.0BSD 2-clause licenseCopyrightCopyright 2017 Paul Stevens.LicenseLicensed under the MIT License. See LICENSE for details.
Package: lemmings
Lemmingslemmingsis an small yet powerful load testing tool.
It is intended for load testing of (web-)systems by test scenarios written in asynchronous way.Featurestest steps written as async methodsystem-independentIn most cases tests written inlemmingsare web-oriented, but it is possible to test almost any system if there is async way to communicate with it.metrics for generator  performanceEach running worker producePrometheus-ready metrics.It is possible either to pull current metrics from worker or push metrics toInflux.Quick startInstall library (Python >=3.7 required)pip install lemmingsCreate test suitefromlemmingsimport*classExampleTestPlan(TaskSet):@Task(weight=5)asyncdeftest_create_target(self,run):awaitself.service.create_entity(1,"test")@Task(weight=3)asyncdeftest_wait(self,run):awaitrun.sleep(self.timings.wait_time,"do nothing during wait time")awaitself.service.remove_entity(1)Create test suiteimportmultiprocessingfromlemmingsimport*if__name__=='__main__':prometheus=Prometheus()shared=multiprocessing.Value("i",0)g=TestExecutor()g.add_test_plan(ExampleTestPlan())g.start_all(shared)prometheus.dump_to_influx()prometheus.clean()# workaround against prometheus work with multiprocessingHow it worksTODOShared dataEach test suite is executing by pool of workers in parallel. Each worker run in diffent process withmultiprocessingIt is possible to use shared variable using standardmultiprocessingfeatures (Lock, Array, Value, manager, etc.)TODOLicenseOpen source licensed under the MIT license (seeLICENSEfile for details).Supported Python VersionsLocust is supported on Python >=3.7
Package: lemmy
🤘 LemmyLemmy is a lemmatizer for Danish 🇩🇰 and Swedish 🇸🇪. It comes ready for use. The
Danish model is trained on Dansk Sprognævn's (DSN) word list (‘fuldformliste’) and theDanish Universal Dependencies.
The Swedish model is trained on theSALDO's
morphologydataset and the SwedishUniversal Dependencies
(Talbanken). Lemmy also
supports training on your own dataset.The models included in Lemmy were evaluated on the respective Universal Dependencies dev
datasets. The Danish model scored > 99% accuracy, while the Swedish model scored > 97%.
All reported scores were obtained when supplying Lemmy with POS tags.You can use Lemmy as a spaCy extension, more specifcally a spaCy pipeline component.
This is highly recommended and makes the lemmas easily accessible from the spaCy tokens.
Lemmy makes use of POS tags to predict the lemmas. When wired up to the spaCy pipeline,
Lemmy has the benefit of using spaCy’s builtin POS tagger.Lemmy can also by used without spaCy, as a standalone lemmatizer. In that case, you will
have to provide the POS tags. Alternatively, you can use Lemmy without POS tags, though
most likely the accuracy will suffer. Currrently, only the Danish Lemmy model comes with
a model trained for use without POS tags. That is, if you want to use Lemmy on Swedish
text without POS tags, you must train your own Lemmy model.Lemmy is heavily inspired by theCST Lemmatizer for
Danish.InstallpipinstalllemmyBasic Usage Without POS tagsimportlemmy# Create an instance of the standalone lemmatizer.lemmatizer=lemmy.load("da")# Find lemma for the word 'akvariernes'. First argument is an empty POS tag.lemmatizer.lemmatize("","akvariernes")Basic Usage With POS tagsimportlemmy# Create an instance of the standalone lemmatizer.# Replace 'da' with 'sv' for the Swedish lemmatizer.lemmatizer=lemmy.load("da")# Find lemma for the word 'akvariernes'. First argument is the user-provided POS tag.lemmatizer.lemmatize("NOUN","akvariernes")Usage with spaCy Modelimportda_custom_modelasda# replace da_custom_model with name of your spaCy modelimportlemmy.pipenlp=da.load()# Create an instance of Lemmy's pipeline component for spaCy.# Replace 'da' with 'sv' for the Swedish lemmatizer.pipe=lemmy.pipe.load('da')# Add the component to the spaCy pipeline.nlp.add_pipe(pipe,after='tagger')# Lemmas can now be accessed using the `._.lemmas` attribute on the tokens.nlp("akvariernes")[0]._.lemmasTrainingThenotebooksfolder contains examples showing how to train your own model using
Lemmy.
Package: lemmy-image-purge
lemmy-image-purgeA simple utility that aims to purge the content of a community from a lemmy instnace, specifically covering purging data from pictrs and the lemmy database.UsageRun via DockerSubtitute the values below with ones for your own instancedockerrun-it--rm\--network="lemmy"\-eDATABASE_URL="postgresql://postgres@localhost:5432/lemmy"\-ePICTRS_URL="http://pictrs/"\-ePICTRS_API_KEY="aaaabbbbccccc1111222333"\ghcr.io/devops-pizza/lemmy-image-purge:latest\purge--community"https://lemmy.world/c/lemmyshitpost"--domain"devops.pizza"--days7Run via pipxpipxinstalllemmy-image-purgeexportDATABASE_URL="postgresql://postgres@localhost:5432/lemmy"exportPICTRS_URL="http://pictrs/"exportPICTRS_API_KEY="aaaabbbbccccc1111222333"lemmy-image-purgepurge--community"https://lemmy.world/c/lemmyshitpost"--domain"devops.pizza"--days7Run via Kubernetescat<EOF>job.yaml
apiVersion:batch/v1
kind:Job
metadata:name:lemmy-image-purgenamespace:lemmy
spec:template:spec:containers:-name:appimage:ghcr.io/devops-pizza/lemmy-image-purge:latestenv:-name:DATABASE_URLvalue:postgresql://postgres@localhost:5432/lemmy-name:PICTRS_URLvalue:http://pictrs/-name:PICTRS_API_KEYvalue:aaaabbbbccccc1111222333args:["purge","--community","https://lemmy.world/c/lemmyshitpost","--domain","devops.pizza","--days","7"]restartPolicy:NeverbackoffLimit:0EOF
Package: lemmy-mod-bot
LemmyModBotA Lemmy bot written in Python usingpylemmyto access comment and create reports.This bot is a work in progress and is expected to expand and grow.Toxic Content DetectionLemmyModBot can detect and report toxic written content on Lemmy communities using a 512-64-2 bag of words deep text classification Neural Network using Pytorch and a local dataset for training.The neural network with the supplied training dataset is currently achieving accuracies of around 75-80% in detecting toxic content.  Ongoing addition of ambiguous or misclassified data to the training set is hoped to improve this.RegexpLemmyModBot can currently detect posts using regular expressions that do not contain a question mark.  This functionality is planned to be expended to run arbitrary regular expressions.User WatchlistSelected users placed on a watachlist can be reported for moderator review.Matrix integrationMessages can be sent to a matrix room.Assessed post and comment historyHistory is stored in an SQLite databaseExample Usagefrom lemmybot import LemmyBotlemmy_world = LemmyBot(rebuild_model=True)lemmy_world.run()
Package: lemmy-post-automation
Lemmy Post AutomationA bot to automate regular image posts from a variety of sources.Running the BotIn its default configuration, the bot is set up to accept links to image boards in a CSV list.
It then processes the list on a schedule defined using cron syntax, checks the target community
for duplicates, and then posts the image (reuploaded to a provided hosting site) with a title in
the format ofTitle [Content Warning] (Artist). Below is an example configuration setup to post
images from data/post_list.csv to transfem every day at 6am:importosfromplemmyimportLemmyHttpfrompostautomationimportPostAutomationif__name__=="__main__":lemmy=LemmyHttp("https://lemmy.blahaj.zone")lemmy.login("username","hunter2")automation=PostAutomation.create(lemmy,"transfem","data/post_list.csv","0 6 * * *")automation.run()From this, custom upload targets can be provided, as well as custom scrapers.