Saravanan666/pypi-org huggingface dataset:
Package: shove
Common object storage frontend that supports
dictionary-style access, object serialization
and compression, and multiple storage and caching
backends.Supported storage backends out of the box are:DBMFilesystemMemorysqlite (disk or memory)Current supported caching backends are:FilesystemMemorysqlite (disk or memory)The simplestshoveuse case…>>> from shove import Shove
>>> store = Shove()…which creates an in-memory store and cache.Use of other backends for storage and caching involves
passing an module URI or existing store or cache instance
toshovefollowing the form:>>> from shove import Shove
>>> <storename> = Shove(<store_uri>, <cache_uri>)Each module-specific URI form is documented in its module. The
URI form follows the URI form used by SQLAlchemy:http://www.sqlalchemy.org/docs/core/engines.htmlshoveimplements the Python dictionary/mapping API:http://docs.python.org/lib/typesmapping.html
Package: showast
# showast
An IPython/Jupyter notebook plugin for visualizing abstract syntax trees.Example usageExamples can be found in [this IPython notebook](https://github.com/hchasestevens/show_ast/blob/master/Example.ipynb).`python import showast ``python %%showast print 1 + 2 `![print 1 + 2 AST](http://i.imgur.com/vK3XTkX.png)`python from showast import show_source import antigravity show_source(antigravity) `![antigravity module AST](http://i.imgur.com/NJY6xhw.png)Installation` pip install showast `showast has the following Python dependencies:` ipython graphviz `You will also need to have [Graphviz](http://www.graphviz.org/Download..php) installed.Use of the alternative nltk-based rendering engine requires the following packages:` nltk pillow `When using this option, you will additionally need to have [Ghostscript](http://ghostscript.com/download/gsdnld.html) installed.ContactsName: [H. Chase Stevens](http://www.chasestevens.com)Twitter: [@hchasestevens](https://twitter.com/hchasestevens)
Package: showbackup
ShowBackup介绍showbackup是一个短小精干的MySQL数据库备份脚本，支持全库，指定库，指定表，定时快速备份。支持全库备份，指定库备份，指定表备份支持备份输出sql文件或压缩文件支持定时自动化备份任务支持清理过期历史备份文件安装$pip3installshowbackup配置首次使用必须先配置运行参数
运行showbackup --config来查看配置文件的位置，使用vi编辑它：$showbackup--config请通过编辑showbackup配置文件来完成配置vi/your/python/path/dist-packages/showbackup/conf.json配置文件说明{"mysql":{"host":"localhost","port":3306,"user":"root","pwd":"","source":[{"db":"testdb01","tables":["users","posts"]},{"db":"testdb02"}],"backup_path":"/opt/showbackup/mysql","is_zip":false,"every_day_at":"17:49","keep_days":"3"}}/*** host: 表示mysql的连接地址* port: mysql的端口号* user: 用于备份数据库的账号* pwd: 用于备份数据库的密码* source: 备份的数据内容（支持全库备份，指定库备份，指定表备份）- 全库备份source: []- 指定库，eg.备份testdb01和testdb02两个数据库source: [{'db':'testdb01'}, {'db': 'testdb02'}]- 指定表，eg.仅备份testdb01数据库中的users和posts表和备份testdb02数据库source: [{'db':'testdb01', 'tables':['users', 'posts']},{'db': 'testdb02'}]* backup_path: 填写备份文件存放的目录，默认 /opt/showbackup/mysql* is_zip: 是否启用压缩* every_day_at:- 每天执行备份的时间点，支持HH:MM:SS 或者 HH:MM- eg. 每天凌晨三点整，03:00- eg. 每天凌晨三点零八分二十六秒，03:08:26* keep_days: 历史备份文件保留最近几天*/使用手动执行# 手动执行一次数据库备份，备份完成程序自动退出$sudoshowbackupmysql所有任务均已完成，总耗时12.32秒

$tree/opt/showbackup/mysqlmysql└──201800712_135955├──testdb02│├──table_user.sql.gz│└──table_visitor.sql.gz└──test_len└──db_test_len.sql.gz后台运行# 开始一个数据库定时备份的后台任务$sudoshowbackupmysql-s&将于每天03:00开始执行备份任务...# 结束后台任务（找出showbackup的PID，杀掉PID）$ps-ef|grepshowbackup254151695801:35PMttys0010:00.24/usr/bin/python3/usr/local/bin/showbackupmysql-s
$kill-925415使用supervisor运行# supervisor配置文件
[program:showbackup]
command=/usr/local/bin/showbackup mysql -s ; 程序启动命令$supervisorctlstartshowbackupshowbackup:started
$supervisorctlstatusshowbackupRUNNINGpid18245,uptime0days,0:0:03
Package: showdialog
showdialogSimple module for showing GTK dialog.InstallpipinstallshowdialogUsageshowdialog.show_msg(title, text, sectext, btns, msgtype)Opens GTK MessageDialogArgsNameTypeDescriptionDefault valuetitlestrDialog captionRequiredtextTuple[Optional[str], bool] | Optional[str]Dialog primary text, str or tuple:(text, use_markup)RequiredsectextTuple[Optional[str], bool] | Optional[str]Dialog secondary text, str or tupleNonebtnsGtk.ButtonsTypeDialog buttonsGtk.ButtonsType.OKmsgtypeGtk.MessageTypeDialog message typeGtk.MessageType.INFOExample:fromshowdialogimportshow_msgshow_msg(title='',text='Hello world!')
Package: showdown
Showdown========This town is not big enough for both of our botsWhat is this?-------------Showdown is a game for two bots (and for the people to write those bots)The rules---------.. image:: https://nerdist.com/wp-content/uploads/2016/08/Good-Bad-Ugly-Trio.jpg:alt: Showdown (mexican standoff) from The Good, the Bad and the Ugly. (image from https://nerdist.com/)Basics^^^^^^This game is played by 2 bots (a.k.a players), implemented as 2 different command line programs.Each bot represents an opponent in a western movie style showdown. They both have a 6-bullet Colt, and start with one loaded bullet. The aim is to kill the opponent by shooting them while they are vulnerable.Player play at the same time by issuing one of the 3 allowed commands : ``shoot``, ``dodge``, ``reload``. Then, if both player survive, they see what their opponent did, and start over, etc.Who dies ?^^^^^^^^^^(A and B can be any of the 2 players)- If A shoots while B reloads, B dies- If A and B both shoot but B has no more bullets, B dies- If A shoots while B issues an invalid command or their program has exited, B dies- If B has not issued a command within one second (but their program is still running), B dies. This rule is to avoid bots that will slow the game at each and every turn.In all other cases, the game continues.Ammunition^^^^^^^^^^Each player start with 1 bullet in their gun. Shooting always removes a bullet from your gun (except if it's already empty). Reloading always adds a bullet to your gun (except if it already has 6 bullets and is full)Turns & victory^^^^^^^^^^^^^^^The game stops when an opponent is dead, or when at least one opponent takes more than one second to give its intructions, or after 100 turns.If there is no winner, the winner will be selected as the one who dodged the least frequently. If both opponent dodged the same amount of time, a winner is randomly selected.Inputs, outputs, timings^^^^^^^^^^^^^^^^^^^^^^^^Here, ``print`` means write in stdout, followed by a newline (`\n`), and ``read``means read from stdin until newline.The program should print its name (within 10 seconds after the start of the process)Then, as long as the game is on, the program should loop over the two following action.The program should print its action for the current turn among ``shoot``, ``dodge`` and ``reload``.Then, the program may read the action the opponent did. The action may be ``shoot``, ``dodge``, ``reload``, ``shoot_no_bullet`` if the opponent shot bu had no bullet left, ``stand`` if the opponent sent an invalid command.A program has one second after it receives the opponent's action to print its own action, otherwise the game will be terminated.The program-----------.. code::bashshowdown first command with args -vs- second command with args
Package: showdownpy
IntroA client forPokemon Showdown!for Python 3.4 and 3.5. This was written to make it easier to write bots, interact with users, moderate chat rooms, and collect data.SetupInstall the package withpip3 install --user showdownpy. This will also install the package'swebsocketsandaiohttpdependencies if you do not already have them.ExampleExamples have been provided in the./examples directory. Make sure to create your own versions of thelogin.txtandowner.txtfiles in./examples/data/directory. Templates for those files have been provided.The client on its own doesn't do very much, and is instead intended to be extended and modified. This can be done through various "hook" coroutines left in the base class. The following program uses theon_private_messagehook to echo back the content of any PMs it receives."""An example client that echoes back any message that isprivate messaged to it"""importshowdownwithopen('./examples/data/login.txt','rt')asf:username,password=f.read().strip().splitlines()classEchoClient(showdown.Client):asyncdefon_private_message(self,pm):ifpm.recipient==self:awaitpm.reply(pm.content)EchoClient(name=username,password=password).start()Other hooks includeon_connect,on_login,on_room_init,on_room_deinit,on_query_responseandon_chat_message.These hooks are by no means all inclusive (Showdown has somewhere upwards of 40 different types of messages it uses to interact with clients in its protocol), and so a catch-all hookon_receiveis also present. Each hook call is given its own task on the event loop, so you can have multiple active coroutines spawned from the same hook.The bot can also be used for collecting data on battles. The following bot anonymously joins ongoing matches in the format 'OU' and saves replays of them when a user finishes."""An example client that joins all OU battlesand saves replays."""importshowdownwithopen('./examples/data/login.txt','rt')asf:username,password=f.read().strip().splitlines()classReplayClient(showdown.Client):asyncdefon_query_response(self,response_type,data):ifresponse_type=='roomlist':forbattle_idinset(data['rooms'])-set(self.rooms):awaitself.join(battle_id)asyncdefon_receive(self,room_id,inp_type,params):ifinp_type=='win':withopen('./data/'+room_id,'wt')asf:f.write('\n'.join(self.rooms[room_id].logs))@showdown.Client.on_interval(interval=3)asyncdefcheck_ou(self):awaitself.query_battles(tier='gen7ou',lifespan=3)ReplayClient(name=username,password=password).start(autologin=False)It is recommended that you save local copies of these matches rather than upload them, as to not overwhelm Showdown's replay server.ContributionsThis package is still a work in progress, and any contributions would be great! I'm currently prioritizing documentation over new features, but if you have an idea for something let me know. Feel free to share anything you make with the client and if its succint enough I may add it to the pool of examples.
Package: showdown.ssh
showdownA tool to automate local network health checks on Cisco iOS devices.You will be prompted to enter a username/passwordA folder will be generated on your local desktopYou will then enter the FQDNshowdown will ssh to the deviceExecute each show command(NOT in enable)Defaults are; 'show ssh' + 'show ver'The command output is then saved to the folder on your local desktopYou will then be prompted to enter additional FQDN, to repeat the above using the original username/password entered at the start of sessionWhen finished, enter 'y'##RequiresPython 3.8Windows 10##Install:pip install showdown.ssh##Run:View install directory:pip show showdown.sshLaunch the app:navigate to directorynavigate to /showdown.ssh/showdownpython showdown.py##Uninstall:pip uninstall -y showdown.sshhttps://pypi.org/project/showdown.ssh/
Package: showenv
Show EnvReport of Project Environment_______//__________________/___/__\/__\|/|//_\/__\|//(__)////_//|/|//__////|///____/_//_/\____/|__/|__/\___/_//_/|___/It is a tool to show detailed information of:PythonPipLibrariesOSDisck usageby project.RequirementPython 3.7 or morepipPython Virtual Environment (recomended)Installpip3installshowenvRunningcd<REPOSITORY_TO_ANALYSE>
showenvOutput: Report of Project Environment2 files generated in current project.config_env.txtOS:
Linux
Distributor ID:	Ubuntu
Description:	Ubuntu 19.04
Release:	19.04
Codename:	disco

Python Version:
Python 3.7.3

Pip Version:
pip 19.1.1 from $HOME/projetos/challenges/kaggle/porto-seguro-safe-driver-prediction/src/environment/venv/lib/python3.7/site-packages/pip (python 3.7)

Jupyter Version:
4.4.0

--------------------------------------------------

Disk Usage:

data:
383M	data/

virtual env:
736M	src/environment/venv/

all:
1,3G	.struture_project.txt.
├── data
│   ├── kaggle_submission.csv
│   └── raw
│       ├── datasets.zip
│       ├── sample_submission.csv
│       ├── test.csv
│       └── train.csv
├── LICENSE
├── notebooks
│   └── porto_seguro_safe_driver.ipynb
├── README.md
├── references
│   └── porto-seguro-vector-logo.png
└── src
    └── environment
        ├── config_env.txt
        ├── container
        │   └── Dockerfile
        ├── create_requirements.sh
        ├── create_virtual_env.sh
        ├── __init__.py
        ├── jupyter_notebook_config.py
        ├── makefile
        ├── prepare_env.py
        ├── README.md
        ├── requirements.txt
        ├── show_config_env.sh
        ├── show_struture_project.sh
        ├── struture_project.txt
        ├── test_environment.py
        ├── venv
        └── virtualenv_requirements.txt

8 directories, 24 files
Package: showergel
Showergel is made to live asideLiquidsoap:
while a Liquidsoap script creates a radio stream,
Showergel provides complementary features like playlist logging or occasional
scheduling, with a (minimalist) Web interface.
It is made to run on a Linux box (with systemd) dedicated to your radio stream.This is work in progress!We’ll welcome both contributions and comments,
feel free to write in the Issues or Discussions tabs.License:GPL3.Take a lookIf you’d like to see what it looks like,
check out ourdemo installation.
It is only the visible part of Showergel,
running on fake data.
You can also use it as a stub back-endwhen developping that interface.Quick installOur automated script can install Liquidsoap and Showergel on an Ubuntu or Debian machine:wget https://raw.githubusercontent.com/martinkirch/showergel/main/installers/showergel_quickstart.sh && chmod +x showergel_quickstart.sh && ./showergel_quickstart.shThe script will need to runsudo.
It will start the radio, you should hear it as soon as you put sound files in the~/Musicfolder.
It will also register the radio as a system service, so the radio and its interface will start when the machine reboots, too.This script installs our “quickstart” LiquidSoap script.
After a first try we advise you to have a closer look to Showergel’s documentation onhttps://showergel.readthedocs.io/.
Package: showerpipe
Provides a Pythonic data pipeline for showering and hadronisation
programs in HEP.Currently wraps interface for Pythia 8, with plans for Herwig and
Ariadne in future releases.InstallationThis package requires Pythia 8 to be installed on your system, and
available in yourPYTHONPATH.It also requires thePYTHIA8DATAenvironment variable to be set.
This is the path to thexmldoc/directory under Pythia’ssharedirectory. You can do something like this in your shell config:exportPYTHIA8DATA=/home/$USER/pythia82xx/share/Pythia8/xmldocWithout an existing Pythia installation (using conda)If this is not already the case, a very convenient solution is to
install it viaconda. This is fast, and automatically sets thePYTHIA8DATAenvironment variable when you activate the virtual
environment. An environment file is provided in the root of this repo,
which will install all requirements and then showerpipe, automatically.
The virtual environment can be created using:condaenvcreate-fenvironment.ymlIf you have an existing conda environment, you can update it by
activating the environment and then using:condaenvupdate-fenvironment.yml--pruneWith existing Pythia installationSimply:pipinstallshowerpipe
Package: showfile
ShowFileA tool to show files with their proper syntax highlighting in the console🌟 Supports Over250 languages🚀 Blazingly Fast👶 Extremely Easy to Use🤖 Automatically detects File Types😏 Really Lightweight (3.55 KB)😍 Beautiful Syntax Highlighting using theMonokai ProthemeView DemoInstallationFirst make sure you havepythoninstalled and added to path then run the following commandpython-mpipinstallshowfileUsageTo show the contents of a file simply useshowfilefile.py
Package: show-h5
Show H5A simple python-based command-line interface for previewing the contents of HDF5 files, with various levels of detail.PyPiSource codeInstallpip install show_h5Command line usageOnce installed, you'll have a command line interface to view the contents of your HDF5 files.Basic use:show_h5 FILENAMEView usage:show_h5 -horshow_h5 --helpThe following flags are also provided:--section SECTION: View only the contents of the HDF5 group/dataset within the file--show_attrs: Show the attributes of the datasets (if not used, defaults to not showing attributes)--show_data SHOW_DATA: How much data to show in datasets: "none", "some", or "all"."none": [default] Show only the name, shape, and type of the data"some": Show the default amount of the data that numpy shows with a print statement"all": Show all the data.Warning: this may blow up with large datasets.API usagefromshow_h5importprint_h5print_h5(h5_filename,section=None,show_attrs=False,show_data=False)Parametersh5_filename: (str) Name/location of the file to showsection: (str, optional) Group or dataset of the file to show (the default is None, which shows the contents of the whole file)show_attrs: (bool, optional) Whether to show dataset attributes (the default is False, which only shows dataset contents)show_data: (one of: ["some", "none", "all"], optional) How much data to show in datasets."none": [default] Show only the name, shape, and type of the data"some": Show the default amount of the data that numpy shows with a print statement"all": Show all the data.Warning: this may blow up with large datasets.
Package: show-image
Interactive Show ImageDisplay images in Jupyter web UI, that is JupyterLab and Jupyter Notebook.Encodes the image directly into HTML (base64) without going through matplotlib.The compression format is customizable. A single function call can show multiple images in a grid.show(img_1, img_2)will draw each image on a separate rowshow([img_1, img_2])will draw both images in one rowshow([img_1, img_2], [img_3, img_4])will draw two rows of two imagesSpecifying the format:show(..., fmt='webp'): image format, usually png jpeg webpshow.set_default_image_format('webp')The default ispng, please usewebporjpegto reduce notebook file sizeWhether to try converting unusual shapes and datatypes to the needed RGB:show(..., adapt=True or False)Convenience functionsimread,imwriteare also provided (based on PIL).DemoTry thedemo notebook.Installationpip install show-imageorInclude the fileshow_image.pyin your projectEnsure libraries are installed:Pillow numpy matplotlib ipython
Package: show-in-browser
show_in_browserA simple python package to display pandas dataframes and matplotlib/plotly graphs
in a browser. This package is intended to be used from the command line, for better
visualisation of dataframes than viewing within the terminal. (E.g. to allow viewing of
the entire dataframe, scrolling etc). In addition, plots appear sequentially as
separate browser tabs, so they can be viewed in a deliberate sequence.To install use:pip install show-in-browserThe following code shows some example uses (in an ipython session):# import the show_in_browser functions as on the line below:
# (alternatively you can use `import show_in_browser as sib` and then access the functions
# with `sib.show_df()` etc.)
from show_in_browser import show_df, show_plt_plot, show_px_plot 

# other imports for the demo script
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import plotly.express as px

# ==============================================================================
# SHOW DATAFRAMES IN THE BROWSER
# this section shows how to use the `show_df()` function to display a dataframe
# in the browser

# create dataframe
df = pd.DataFrame({'score_1': np.random.normal(100, 10, 100),
                'score_2': np.random.normal(1000, 2, 100),
                'score_3': np.random.normal(10, 2, 100)})

# show a DataFrame in a browser
show_df(df, name='Complete DataFrame') # name is optional

# show a Series derived from the DataFrame in a browser
show_df(df['score_1'], name='A Single Column') # name is optional

# ==============================================================================
# SHOW MATPLOTLIB PLOTS IN THE BROWSER
# this section shows how to use the `show_plt_plot()` function to display a
# matplotlib plots in the browser

# 2D matplotlib plot
plt.figure()
plt.scatter(df['score_1'], df['score_2'])
show_plt_plot(name='Matplotlib Scatterplot') # name is optional

# 3D matplotlib plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(df['score_1'], df['score_2'], df['score_3'])
show_plt_plot(name='Matplotlib 3D Scatterplot') # name is optional

# ==============================================================================
# SHOW PLOTLY PLOTS IN THE BROWSER
# this section shows how to use the `show_px_plot()` function to display a
# matplotlib plots in the browser

# 2D plotly plot
fig = px.scatter(df, x='score_1', y='score_2')
show_px_plot(fig, name='Plotly Scatterplot') # name is optional

# 3D plotly plot
fig = px.scatter_3d(df, x='score_1', y='score_2', z='score_3')
show_px_plot(fig, name='Plotly 3D Scatterplot') # name is optionalThis code will give you output of the following form, in your default browser.
Each dataframe or plot that you have selected will show in separate tabs
in your default browser. The dataframes and plots will appear in the order in which you ran the commands:
Package: showlog
showlog介绍python的log，封装了些简单的方法安装教程使用pip安装普通方式安装pip3installshowlog使用阿里镜像加速安装pip3installshowlog-ihttps://mirrors.aliyun.com/pypi/simple使用说明导入importshowlog简单使用showlog.info('hello word!')showlog.warning('this is warning')showlog.error('this is error')保存log为文件只需要设置一次，后续的log将会被存储showlog.save_info('[your file name].log')showlog.save_warning('[your file name].log')showlog.save_error('[your file name].log')
Package: showme
ShowMe – Quick and easy debugging for PythonShowMe is a simple set of extremely useful function decorators for Python.
It allows you to view trace information, execution time, cputime, and function
documentation.InstallationTo useshowme, simply:pip install showmeor, if you must:easy_install showmeUsagePrint passed-in arguments and function calls.@showme.trace
def complex_function(a, b, c, **kwargs):


>>> complex_function('alpha', 'beta', False, debug=True)
calling haystack.submodule.complex_function() with
   args: ({'a': 'alpha', 'b': 'beta', 'c': False},)
   kwargs: {'debug': True}Print function execution time.@showme.cputime
 def complex_function(a, b, c):

 >>> complex_function()
      3 function calls in 0.013 CPU seconds

ncalls  tottime  percall  cumtime  percall filename:lineno(function)
     1    0.013    0.013    0.013    0.013 test_time.py:6(test)
     1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
     1    0.000    0.000    0.000    0.000 {range}Pretty print function documentation.@showme.docs
def complex_function():
        """Example Documentation for complex_function"""
        pass

>>> complex_function()
Example Documentation for complex_functionHistory1.0.0 (2010-09-05)Featureset completePublic release of showme to PyPiCleanup of project (removal of globals/locals)0.0.5 (2010-09-05)@showme.time support (simple but big feature)Color output added (via vendorized Colorama)0.0.4 (2010-09-04)Epic @showme.trace decorator written@showme.docs support0.0.3 (2010-09-01)General configuration in place@showme.cputime supportVendorization of decorator decorator