Saravanan666/pypi-org huggingface dataset:
Package: beautifuldict
Info:Python package to manage configuration dictionaries.Author:Servicio de Informática y Banco de Datos <sibd@cantabria.es>FeaturesSimple wrapper around python dictionariesAccess to nested keys with dot notation:config.deeply.nested.keyor as dictionary keys:config['deeply']['nested']['key']Allows add dictionaries, remove keys or modify values by overriding dictionary methodsInstallationpipinstallbeautifuldictPackage:https://pypi.org/project/beautifuldict/Source:https://github.com/icane/beautifuldictQuick ExampleA Baseconfig object stores the configuration parameters as a parameter tree. It gives access to parameters in two ways: as dictionary keys or as attributes of the object.>>>frombeautifuldict.baseconfigimportBaseconfig>>>CONFIG_DICT={>>>'example1':'hello world',>>>'example2':{>>>'key1':1,>>>'key2':2}>>>}>>>config=Baseconfig(CONFIG_DICT)>>>config.example1# returns 'hello world'>>>config['example1']# returns 'hello world'>>>config.example2.key1# returns 1>>>config['example2']['key1']# returns 1
Package: beautifulplots
beautifulplotsPython plotting library for beautiful, easy, and sophisticated matplotlib based plots. Compatible with Matplotlib graphs, such as Pandas and Seaborn.MotivationData scientists use data visualization for analysis, investigation, insight, and story telling. In this endeavor, Matplotlib based plotting libraries are reputedly the most powerful and customizable. However, creating graphs for analysis, though necessary, often diverges from the primary goal. Furthermore, Graphs resulting from data science analysis inevitably populate reports, presentations, and even interactive web graphics. After some experience, use case after use case requires similar supporting code.GoalThe goal of the beautifulplots plotting library is to package graphing functions for the easy generation of beautiful graphs without the burden of distracting code.Installation$pipinstallbeautifulplotsUsage and ExamplesSee usage examples in examples.ipynb (Jupyter notebook) and readthedocsbeatifulplots readthedocs.Feature Requests and IssuesFeature requests and issues: please provide feedback and suggestions for improvements or issues via github issuesnew issue.Licensebeautifulplotswas created by Alberto Gutierrez. It is licensed under the terms of the MIT license.Creditsbeautifulplotspackage setup withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: beautiful-repr
Beautiful-reprHelps structure the formatting of objects in Python.Installationpip install beautiful-reprWhy Beautiful-repr ?Beautiful repr out of the boxGreat expansion possibilitiesVery small and simpleNo external dependenciesExamplefrombeautiful_reprimport*classShoppingCart(StylizedMixin):_repr_fields=(Field("token",value_transformer=lambdavalue:value[1:]),Field("products",value_getter=parse_length,formatter=TemplateFormatter("{value}products")),)def__init__(self,token:str,products:tuple[str,]=tuple()):self.token=tokenself.products=tuple(products)print(ShoppingCart("s12345",("Potato","iPhone","New Vegas")))output:ShoppingCart(token=12345, 3 products)
Package: beautifulsoup4
Beautiful Soup is a library that makes it easy to scrape information
from web pages. It sits atop an HTML or XML parser, providing Pythonic
idioms for iterating, searching, and modifying the parse tree.Quick start>>> from bs4 import BeautifulSoup
>>> soup = BeautifulSoup("<p>Some<b>bad<i>HTML")
>>> print(soup.prettify())
<html>
 <body>
  <p>
   Some
   <b>
    bad
    <i>
     HTML
    </i>
   </b>
  </p>
 </body>
</html>
>>> soup.find(text="bad")
'bad'
>>> soup.i
<i>HTML</i>
#
>>> soup = BeautifulSoup("<tag1>Some<tag2/>bad<tag3>XML", "xml")
#
>>> print(soup.prettify())
<?xml version="1.0" encoding="utf-8"?>
<tag1>
 Some
 <tag2/>
 bad
 <tag3>
  XML
 </tag3>
</tag1>To go beyond the basics,comprehensive documentation is available.LinksHomepageDocumentationDiscussion groupDevelopmentBug trackerComplete changelogNote on Python 2 sunsettingBeautiful Soup's support for Python 2 was discontinued on December 31,
2020: one year after the sunset date for Python 2 itself. From this
point onward, new Beautiful Soup development will exclusively target
Python 3. The final release of Beautiful Soup 4 to support Python 2
was 4.9.3.Supporting the projectIf you use Beautiful Soup as part of your professional work, please consider aTidelift subscription.
This will support many of the free software projects your organization
depends on, not just Beautiful Soup.If you use Beautiful Soup for personal projects, the best way to say
thank you is to readTool Safety, a zine I
wrote about what Beautiful Soup has taught me about software
development.Building the documentationThe bs4/doc/ directory contains full documentation in Sphinx
format. Runmake htmlin that directory to create HTML
documentation.Running the unit testsBeautiful Soup supports unit test discovery using Pytest:$ pytest
Package: beautifulsoup4-slurp
Slurp the beautiful soup===============BeautifulSoup4 packaged into a command line tool.Installation---------From the Python package index (Pypi_):(sudo) pip install beautifulsoup4-slurpor from Github_:git clone https://github.com/peterhil/slurp.gitcd slurp(sudo) python setyp.py installUsage-----Show help:slurp -hParse with html5lib and pretty print into stdout:slurp -i bookmarks.html -p 'html5lib' -yParse with lxml and pretty print into stdout:slurp -i bookmarks.html -p 'lxml' -yWrite pretty-printed to output to file:slurp -y -i bookmarks.html -o bookmarks_soup.htmlPipe into slurp:echo '<title>Slurp!</title><p><a href="https://github.com/peterhil/slurp/">Github</a>' | slurp -y.. _Github: https://github.com/peterhil/slurp/.. _Pypi: http://pypi.python.org/pypi/beautifulsoup4-slurpLicense------Copyright (c) 2015, Peter Hillerström <peter.hillerstrom@gmail.com>All rights reserved. This software is licensed under MIT license.For the full copyright and license information, please view the LICENSEfile that was distributed with this source code.
Package: beautiful-time
BeautifulTime is a python package for converting date string, datetime, time and timestamp.Installpipinstallbeautiful_timeUsageimportBeautifulTimedate_str='2016-10-30 12:30:30'dt=BeautifulTime.str2datetime(date_str)# with a custom formatdt=BeautifulTime.str2datetime(date_str,format='%Y-%m-%d%H:%M:%S')t=BeautifulTime.str2time(date_str)ts=BeautifulTime.str2timestamp(date_str)dt=BeautifulTime.str2datetime(date_str)t=BeautifulTime.str2time(date_str)ts=BeautifulTime.str2timestamp(date_str)s=BeautifulTime.datetime2str(dt)t=BeautifulTime.datetime2time(dt)ts=BeautifulTime.datetime2timestamp(dt)s=BeautifulTime.time2str(t)dt=BeautifulTime.time2datetime(t)ts=BeautifulTime.time2timestamp(t)dt=BeautifulTime.timestamp2datetime(ts)t=BeautifulTime.timestamp2time(ts)s=BeautifulTime.timestamp2str(ts)
Package: beautifurl
![CI](https://github.com/hintofbasil/Python-Beautifurl/workflows/CI/badge.svg?branch=master)# BeautifURL## InstallationBeautifURL can be installed from pippip install beautifurl## Usage>>> from beautifurl import Beautifurl
>>> beautifurl = Beautifurl()>>> beautifurl.get_random_url('aaA')
'BeautifulAdventurousGiraffe'>>> beautifurl.count_permutations('aaA')
9150136>>> for url in beautifurl.get_permutations('aaA', shuffle=True):
...     print(url)
...GloriousDeterminedPeafowl
NiceSuccessfulJackal
DepressedStupidPartridge
StormyStrangeGiraffe
AngryPleasantMonkey
…### Url formatThe examples above have a format string as their first argument.  This dictates which types of words the url should be made up of.  The examples all useadjective adjective Animal.  Any number or combination of keys may be used.  A full list of keys is available below.### Custom dictionariesThe Beautifurl object__init__function takes an optional parameterdictionaryPath.  This allows the default dictionaries to be swapped for user specified dictionaries.>>> beautifurl = Beautifurl(dictionaryPath='~/dictionaries')The dictionaries in this folder must be namedKEY_…whereKEYis a single character.  All keys should be unique.  Any characters after the underscore are ignored.  Seedictionariesfolder for examples.## DictionariesKey | Description | Size |— | ———– | —- |a   | Adjectives  | 223  |A   | Animals     | 211  |## Contributing### WordlistsAdditional words and lists may be submitted in pull requests.  Please run the new lists through the organise script located in the dictionaries folder.Please ensure you have permission to use any lists before submitting a pull request.  If a license is required please name the license file license.LIST_NAME../organise LIST_NAME [MAX_SIZE] > tmp
mv tmp LIST_NAME### CodePull requests are more than welcome.
Package: beautify-http-server
http.serverA (beautiful) replacement for thehttp.serverPython3 module.pip3 install beautify-http-serverFeatures:File download 🤷‍♂️Fileupload🤩Preview(pdf, text, image, music,video) 🧐List files in.zipand.tararchives remotely, with the ability toviewordownloada single entry 😮Mobile-friendly🤳ExamplePreview:Mobile:Dev Tips: force to view a zip-like file by passing#zipin the URL 😉UsageAfter installation (pip3 install beautify-http-server, see below), run:$# to serve current working directory, on 127.0.0.1:8000$http.server

$http.server--bind0.0.0.0--port8080--folder~/Downloads

$http.server-h
usage:http.server[-h][--bindBIND][--portPORT][--folderFOLDER][--debug|--no-output]optionalarguments:-h,--helpshowthishelpmessageandexit--bindBINDSpecifybindaddress[default:127.0.0.1]--portPORTSpecifyserverport[default:8000]--folderFOLDERSpecifywhichdirectorytoserve[default:currentworkingdirectory]--debugUse"flask.run"inDebugmodeinsteadof"waitress"WSGIserver--no-outputDisableserveroutput(setlogging.level>=WARNING)ATTENTION: this program is meant to be run locally, do not expose on Internet!InstallationAs easy as:$pip3installbeautify-http-serverOtherwise:$# (Optional)$virtualenvvenv&&sourcevenv/bin/activate

$gitclonehttps://www.github.com/lorenzodifuccia/http.server
$cdhttp.server
$pipinstall.

$python3-mhttp_server...
OR
$http.server...This project has the following dependencies:Python3 (seerequirements.txt)Flask [link]Waitress [link]Humanize [link]HTML5Bootstrap 5 (CSS + JS) [link]Bootstrap Icons [link]FutureKnown issues:HTML5 and Browsers do not fully support.mkvfilesMade with <3 byme
Package: beautifyPlot
beautifyPlotA simple matplotlib wrapper to avoid writing multiple plt. statements.Installationpip install beautifyPlotUsagematplotlib code:importnumpyasnpimportmatplotlib.pyplotaspltx=np.arange(0,100,1)y=x**3plt.plot(x,y,label='y=f(x)')plt.title("test plot")plt.xlim([0,10])plt.ylim([0,1000])plt.legend(fontsize=15)plt.tight_layout()Using beautifyPlotfrombeautifyPlot.bpltimportbeautifyPlotimportnumpyasnpx=np.arange(0,100,1)y=x**3plt.plot(x,y,label='y=f(x)')plotArgs={'title':['test plot'],## Use list to pass a set of arguments to the function'xlim':[0,10],'ylim':[0,1000],'legend':{'fontsize':15,'loc':'best'},## Use dictionary to specify arguments'tight_layout':[]## Leave list empty if there is nothing to pass}beautifyPlot(plotArgs)## Next steps: Save plotArgs as JSON or use the same plot arguments in a different subplot/plot.Using beautifyPlot (with shorthand notation)frombeautifyPlot.bpltimportbeautifyPlotimportnumpyasnpx=np.arange(0,100,1)y=x**3plt.plot(x,y,label='y=f(x)')plotArgs={'t':['test plot'],'xl':[0,10],'yl':[0,1000],'l':{'fontsize':15,'loc':'best'},'t_l':[]}beautifyPlot(plotArgs)Built-in shorthand notationsshorthandcommand"l"plt.legend"t_p"plt.tick_params"t_l"plt.tight_layout"t"plt.title"xl"plt.xlim"yl"plt.ylim"xt"plt.xticks"yt"plt.yticks"xlab"plt.xlabel"ylab"plt.ylabel"xs"plt.xscale"ys"plt.yscale
Package: beauty
beauty是图片网站55156图库-高清套图非官方的API。提供了更加清爽的套图浏览和下载接口，欢迎各位老司机使用，提issues或PR安装依赖项目根目录运行pip install beauty快速入门以下命令均在项目根目录运行### 查看Usage及支持的套图类型beauty -hUsage：
得知项目主要有两个方法scan和download，其中scan是浏览指定种类和数量的封面图片（小图），download是下载指定种类和数量的套图（大图）。Options： 参数的关键字及对应的解释Arguments：
目前支持的套图种类，为scan和download方法的必填项如果提示'beauty' 不是内部或外部命令，也不是可运行的程序，请将$PYTHON/Scripts添加到环境变量直接下载套图# 下载秀人套图 默认数量为10 默认路径是./pic
beauty download xiuren

# 下载秀人套图 指定数量为15
beauty download xiuren -n 15

# 下载秀人套图 指定路径为D:/
beauty download xiuren -p D:/完成后可在相应目录下看到下载结果image先浏览小图，根据个人喜好（套图质量）下载对应的大图# 浏览秀人套图 默认数量为10 默认路径是./pic/scan
beauty scan xiuren

# 浏览秀人套图 指定数量为15
beauty scan xiuren -n 15

# 浏览秀人套图 指定路径为D:/scan scan方法默认的图片会下载到指定（默认目录）的scan文件夹
beauty download xiuren -p D:/找到浏览套图文件夹scan，打开图片编辑器查看scan文件夹的图片image从上图中找到要完整下载的套图，运行下载命令# -n参数要和scan方法的参数一样 -f参数列表内部不要留空格
beauty download xiuren -n 10 -f [204774,204775,204832]完成后可在相应目录下看到下载结果image注意事项项目开发环境是Python2.7，如果发现项目不兼容的欢迎提issuesTODO[x] 提供先浏览后选择下载的功能 finish at 20170827[ ] 下载图片失败后重试[ ] 重试失败后删除失效的图片，或者在单独的文件夹中备注下载失败的信息Change Log20171017: 制作成pip安装包提供cli命令接口20170828:
重写了repository，重命名为beauty，提供了更加人性化的api方法20160220: 提供了re版本和BeautifulSoup版本的提取方法
Package: beautyacc
beautyacc is a library to access EPICS archiver values in Python. It is
designed for the EPICS RDB Archiver called “beauty”. The name beautyacc
is shorthand for ‘beauty access’.This package was crafted for Python 3.4 or newer.InstallationInstalling from PyPI is easy:pip install beautyaccResourcesGithub:https://github.com/pklaus/beautyaccPyPI:https://pypi.org/project/beautyacc/
Package: beautylog
Let your code generate logs automaticallyVersion:0.0.12020/8/17 原始版本Version:0.0.22020/8/17 修正debug.log路径Version:0.0.32020/8/17 修正debug.log路径Version:0.0.52020/8/18 将函数中的print输出记录到日志中Version:0.1.02020/8/19

1. 添加显示主函数对子函数调用关系的内容
2. 兼容用户定义函数中存在try-expect语句的情况
3. 将log修饰符从函数实现改为类实现Version:0.1.12020/9/2 skwood0105

修复__BeautyLogOut__路径问题Version:0.1.22020/9/3 skwood0105

增添判断调用是函数or方法的功能
当所调用函数首参数是对象，且其中含有同名的类内成员函数时，无法判断（bug）Version:0.1.32020/9/5 Aglargil

优化类内成员函数使用装饰器时log输出的内容Version:0.1.42020/9/5 skwood0105

使用函数__qualname__属性判断调用是函数or方法，且解决了0.1.2中出现的bugVersion:0.1.52020/9/9 Aglargil

log定制化：
1、可以指定某个函数的print输出是否需要改为定制输出（默认为需要）
2、可以指定全部函数的print输出是否需要改为定制输出（默认为需要）
Package: beauty-ocean
beauty-oceanCreate DigitalOcean droplets like a breeze through the command line.DocumentationYou may read thefull documentation on ReadTheDocs.PreparationBefore installing this package make sure you have an account toDigital Oceanand haveobtained a Digital Ocean API tokenThe recommended way of storing the token is via environment variable. Once
you copy it, do the following:$vim~/.profileornano~/.profile#makesurethefollowinglineisadded$exportDO_TOKEN="API TOKEN HERE"# or other name than DO_TOKEN$source~/.profileInstallationInstallation is just apip installaway:(virtualenv_name)$pipinstallbeauty-oceanYou are using virtualenv, don’t you? If not, install it inside your~/.localdirectory.$pipinstall--userbeauty-oceanNever ever use sudo!UsageFor the moment, this package implements the creation ofDigital Ocean dropletsbut very soon it will support the creation of Domains and Networks.
Once installed, thedropletcommand will be available at your disposal.
It accepts a single option--tokenor-tfor short. Defaults to"DO_TOKEN"which is the name of the environment variable that you
created earlier. If you used a different name then pass that name to the-toption.$droplet#or$droplet-tMY_ENV_NAME_FOR_TOKENYou may, also, pass a file path to the-toption where this file holds
the token only.$droplet--tpath/to/file/that/holds/the/tokenLastly,but not recommended, you may pass directly, to the-toption,
the token itself.$droplet--tTHE_ACTUAL_API_TOKEN_HEREOnce the token is resolved, a series of questions will be initiated in order
to get the available data from you, submit this data to the Digital Ocean
API and create the droplet. All the above come in a good-looking format
of questions.Finally, a json string will be returned with all the droplet data at your
disposal to use it in any way you want.FeaturesBeautiful command-line-interface questions flow with sensible defaultsSupports remote or local SSH keys addition and/or remote/local TagsDemoAn mp4 video demo can be foundhere.CreditsThis package was created using:Cookiecutteraudreyr/cookiecutter-pypackageproject templatepython-digitaloceanpython library for DigitalOcean APIinquirerto ask questions (based on theinquirejscommand line UI)coloredto color the promptyaspinto display a “loading” animation while fetching dataclickto create the command linesshpubkeysto parse/validate public key(s)DisclaimerI do not work at DigitalOcean, neither have any benefits (financial or
professional) from creating this package. This package was created because
it facilitates my workflow during droplet creation and website deployment
and I wanted to share it with other developers. Sharing is a good thing!History0.2.1 (2020-1-17)Fix a bug (NotFoundError) produced while creating the droplet.0.1.4 (2019-04-05)Fix exception occurred when token was imported by a file.0.1.3 (2018-09-18)Fixcreate_dropletfunction which did not return JSON data. Now it does.0.1.2 (2018-09-17)Fix Pipenv file and include Pipfile* files into the source distribution.0.1.1 (2018-09-16)Added check-manifest package and fix bump2version version error.0.1.0 (2018-09-15)First release on PyPI.
Package: beauty-print
bprintBeautiful print for Python.Why?Python'spprintis
supposed to be a "Data pretty printer" and claims the following:provides a capability to "pretty-print" arbitrary Python data structuresThis is simply not true, because it will choke on "arbitrary Python data".It's not even good at pretty-printing, since the indentation often goes
way too far to the right, and in general makes things unreadable.bprintaims at solving both of these issues.How?Thanks to Python's dynamic nature, we can query the attributes ofanyobject, and thus beautifully print them, even if they don't define__str__(which is in fact not queried at all for custom classes).Installation is done withpip install beauty-print.What?bprintwill help you beautifully print your objects, and is also easily
customizable, with a lot of freedom.Thepippackage is calledbeauty-printbecausebprintwas already taken, unfortunately.When?During one of the many moments when I'm procrastinating. You can install
it any time you want though!Where?In Python 3.6 and above, and PyPi asbeauty-print.How much?Free, as in beer and freedom!Who?Lonamiis the primary author and thanks also
toudf, but more contributors are welcome!
Package: beavers
BeaversDocumentation/Installation/Repository/PyPIBeaversis a python library for stream processing, optimized for analytics.It is used atTradewell Technologies,
to calculate analytics and serve model predictions,
for both realtime and batch jobs.Key FeaturesWorks inreal time(eg: reading from Kafka) andreplay mode(eg: reading from Parquet files).Optimized for analytics, using micro-batches (instead of processing records one by one).Similar toincremental, it updates nodes in a dag incrementally.Taking inspiration fromkafka streams, there are two types of nodes in the dag:Stream: ephemeral micro-batches of events (cleared after every cycle).State: durable state derived from streams.Clear separation between the business logic and the IO.
So the same dag can be used in real time mode, replay mode or can be easily tested.Functional interface: no inheritance or decorator required.Support for complicated joins, not just "linear" data flow.LimitationsNo concurrency support.
To speed up calculation use libraries like pandas, pyarrow or polars.No async code.
To speed up IO use kafka driver native thread or parquet IO thread pool.No support for persistent state.
Instead of saving state, replay historic data from kafka to prime stateful nodes.
Package: beaver_sqs
Beaver-SQSTransport module forPython-Beaverto deliver log entries via AWS SQS.UsageBeaver can optionally get data from a configfile using the -c flag. This file is in ini format. Global configuration will be under the beaver stanza. The following are global beaver configuration keys with their respective meanings:sqs_aws_access_key: Can be left blank to use IAM Roles or AWS_ACCESS_KEY_ID environment variable (see:https://github.com/boto/boto#getting-started-with-boto)sqs_aws_secret_key: Can be left blank to use IAM Roles or AWS_SECRET_ACCESS_KEY environment variable (see:https://github.com/boto/boto#getting-started-with-boto)sqs_aws_profile_name: Can be left blank to use IAM Roles AWS_SECRET_ACCESS_KEY environment variable, or fixed keypair (above) (see:https://github.com/boto/boto#getting-started-with-boto)sqs_aws_region: Default us-east-1. AWS Regionsqs_aws_queue: SQS queue, or comma delimited list of queues (must exist)sqs_aws_queue_owner_acct_id: Optional. Defaults None. Account ID or Principal allowed to write to queuesqs_bulk_lines: Optional. Send multiple log entries in a single SQS message (cost saving benefit on larger environments)Example# /etc/beaver/conf
[beaver]
sqs_aws_region: us-east-1
sqs_aws_queue: logstash-input1,logstash-input2
sqs_aws_access_key: <access_key>
sqs_aws_secret_key: <secret_key>

# logstash indexer config:
input {
  sqs {
    queue => "logstash-input1"
    access_key_id => "<access_key>"
    secret_access_key => "<secret_key>"
  }
}
output { stdout { debug => true } }ContributingSee:CONTRIBUTING.rstCreditsJamie CresseyJose Gonzalez
Package: beavr
beaverBeaver (n) - an animal that eats logsbeaverparses log files based on a given date and time range, so you don't have toQuick ExamplesPerhaps you'd like to see the logs for your project since the last time you pushed to production last Wednesday. This can be accomplished easily withbeaver:$ python3 beaver.py Wednesday to today
>> logfile1.log
2019-04-03 15:10:26,618 - simple_example - DEBUG - debug message
2019-04-03 15:12:45,124 - simple_example - DEBUG - debug message
...All of the following examples will work:python3 beaver.py 10:35 to 11:35
python3 beaver.py yesterday to today
python3 beaver.py Mar 2nd, 2012 to now
python3 beaver.py 2017-06-18 to May 3rd 2018 at 3:17pm
python3 beaver.py 1:23pm on August 15th 2017 to 10:35 PM on 2 April 2018...and many more!InstallationMore coming soon...Usageusage: beaver.py [-h] [-f FILE] [-o OUTPUT] [-r] range [range ...]

Beaver (n) - an animal that eats logs

positional arguments:
  range                 the range for which to parse logs

optional arguments:
  -h, --help            show this help message and exit
  -f FILE, --file FILE  a specific log file to parse (default: )
  -o OUTPUT, --output OUTPUT
                        if included, the file to which output will be writen
                        (default: )
  -r, --recursive       if included, beaver will search for log files
                        recursively starting from the current directory
                        (default: False)rangeis composed in the form ofSTART to END, where START and END can be almost any valid datetime format. Ifbeavercan't understand you, it will ask for clarification.Note that any datetime format that contains days, months, and years must either have days > months > years or years > months > days. The American format (06/18/1996 for June 18th, 1996) is not supported because it creates ambiguity.--file- use this if you only want to parse a specific file, not all log files. By default,beaversearches the current directory for any files ending in.logor.logs--output- write output to a file, rather thanstdout--recursive- look for log files recursively, starting in the current directory( θ ϖ θ )
Package: bebop-browser-gopher
This is a Gopher plugin for [Bebop][bebop], refer to its docs for details.[bebop]:https://git.dece.space/Dece/BebopRequires:Bebop >= 0.2.0It currently displays only the maps and the file item types.Avoid using the path navigation features of Bebop because they do not make much
sense in Gopher; Gopher URLs do not really represent a path as they can be
prefixed with an item type, so going up one level from a file item will usually
put you on a map item with the file item indicator still in the URL. Going to
the root URL and history navigation should still be fine though.
Package: be-brief
be-briefA Wagtail app for short form posts. Please bear with us while we prepare more detailed documentation.Compatibilitybe-brief's major.minor version number indicates the Wagtail release it is compatible with. Currently this is Wagtail 4.1.xInstallationInstall usingpip:pipinstallbe-briefAddbe_briefto yourINSTALLED_APPSsetting:INSTALLED_APPS=[# ...'be_brief'# ...]