Saravanan666/pypi-org huggingface dataset:
Package: alsa-midi
This project provides Python interface to ALSA sequencer API.FeaturesPythonic API to most of the ALSA sequencer functionalityAccess to ALSA sequencer features not available when using other (‘portable’)
Python MIDI libraries:Precise timestamping of messages sent and receivedPort connection management, including connection between ports on different
clientsAccess to non-MIDI events, like announcements about new clients, ports and
connectionsPython 3.7 – 3.11 compatibilityBoth synchronous (blocking) and asynchronous (asyncio) I/OOnly Python code, no need to compile a binary module. Requirescffi, though.MIDObackend providedInstallationThis package requires ALSA library to be installed (libasound.so.2–
‘libasound2’ package on Debian-like systems). On a typical Linux system it is
probably already installed for some other audio or MIDI software.python-alsa-midi package may be installed with pip:python3 -m pip install alsa-midiThis should normally install a binary wheel compiled on a compatible system or
pure-python wheel working without compilation.If no compatible wheel is found build from source package will be triggered,
which will also require ALSA library development files (libasound2-dev).To force installing from source (and compiling the binary extension) use:python3 -m pip install --no-binary=alsa-midi alsa-midiTo force installing from source without compiling the extension:PY_ALSA_MIDI_NO_COMPILE=1 python3 -m pip install --no-binary=alsa-midi alsa-midiAlternatively one can just add the source directory (as checked out fromhttps://github.com/Jajcus/python-alsa-midi.git) to$PYTHONPATHand use the
packages directly, with no compilation.UsageDetailed documentation is available athttps://python-alsa-midi.readthedocs.io/Simple example:import time
from alsa_midi import SequencerClient, READ_PORT, NoteOnEvent, NoteOffEvent

client = SequencerClient("my client")
port = client.create_port("output", caps=READ_PORT)
dest_port = client.list_ports(output=True)[0]
port.connect_to(dest_port)
event1 = NoteOnEvent(note=60, velocity=64, channel=0)
client.event_output(event1)
client.drain_output()
time.sleep(1)
event2 = NoteOffEvent(note=60, channel=0)
client.event_output(event2)
client.drain_output()Using with MIDOpython-alsa-midi can be used as aMIDOback-end too:export MIDO_BACKEND=alsa_midi.MIDO_BACKEND
mido/examples/midifiles/play_midi_file.py file.mid
Package: alsangue
alsanguealsangueis a naive static website builder written inpython.Installationalsangueis available through thePython Package Index (PyPI). Pip is pre-installed ifpython >= 3.4has been downloaded frompython.org; if you're using a GNU/Linux distribution, you can find how to install it on thispage.After setting up pip, you can installalsangueby simply typing in your terminal# pip3 install alsangueUsagealsangueinstall a command line utility with the same name,alsangue. You can invoke command line help withalsangue --helpand get command options withalsangue <command> --helpYou can find an examplecontentdirectory in this repo which you can edit to build your own website. To build it just type:cd alsangue/example
alsangue content buildAboutThis program is licensed underGNU General Public License v3 or laterbyPellegrino Prevete. If you find this program useful, consider offering me abeer, a newcomputeror a part time remotejobto help me pay the bills.
Package: alsaseq
alsaseq is a Python 3 and Python 2 module that allows to interact with ALSA
sequencer clients. It can create an ALSA client, connect to other
clients, send and receive ALSA events immediately or at a scheduled
time using a sequencer queue. It provides a subset of the ALSA
sequencer capabilities in a simplified model. It is implemented in
C language and licensed under the Gnu GPL license version 2 or
later.
Package: als.bcs
als.bcsExtract data and metadata from text data files that were created by
the Beamline Controls System (BCS) at the Advanced Light Source (ALS)PurposeFacilitate the extraction of header information and scan input variables
from common BCS data file formats, such as:Time ScanSingle Motor ScanTrajectory Scanbcs.find moduleFind BCS data files that match provided criteria
(date, scan type, scan nmuber, etc.) within their native directory structure.bcs.data moduleRead scan output information and data from selected BCS data files.bcs.scan moduleFind and read scan input information BCS Trajectory Scan data files.bcs.ingest moduleRead header information from selected BCS data files.InstallationUsing pip# PyPIpython-mpipinstallals.bcs# -- OR --# Local copy of the project repositorypython-mpipinstall-rrequirements.txt-e.# -- OR --# Local tarball, uses static version file generated during buildpython-mpipinstallals.bcs-0.2.0.tar.gzCopyright Noticeals.bcs: Extract metadata from text data files that were created by
the Beamline Controls System (BCS) at the Advanced Light Source (ALS),
Copyright (c) 2022, The Regents of the University of California, through
Lawrence Berkeley National Laboratory (subject to receipt of any required
approvals from the U.S. Dept. of Energy). All rights reserved.If you have questions about your rights to use or distribute this software,
please contact Berkeley Lab's Intellectual Property Office atIPO@lbl.gov.NOTICE. This Software was developed under funding from the U.S. Department of
Energy and the U.S. Government consequently retains certain rights. As such,
the U.S. Government has been granted for itself and others acting on its
behalf a paid-up, nonexclusive, irrevocable, worldwide license in the
Software to reproduce, distribute copies to the public, prepare derivative
works, and perform publicly and display publicly, and to permit other to do
so.
Package: alsi-py
alsi-pyPython client for the ALSI API (Aggregated LNG Storage Inventory)Documentation of the API can be found on:https://alsi.gie.eu/GIE_API_documentation_v004.pdfDocumentation of the client API can be found on:https://roiti-ltd.github.io/alsi-py/Installationpython3 -m pip3 install alsi-pyUsageThe package is split in two clients:AlsiRawClient: Returns data in raw JSON format.AlsiPandasClient: Returns parsed data in the form of a pandas dataframe.from alsi.raw_client import AlsiRawClient
from alsi.pandas_client import AlsiPandasClient
from alsi.mappings import Area
from datetime import datetime
import asyncio

API_KEY = '<API_KEY>'

country_code = Area.ES # Also could be string: 'ES' or 'Spain'
company_code = '21X000000001254A'
facility_code = '21W0000000000370'

async def main():
    client = AlsiRawClient(api_key=API_KEY)

    # Functions that return JSON.
    client.query_data_for_facility(facility_code, company_code, country_code)
    client.query_agg_data_for_europe_or_noneurope(europe='eu')
    client.query_agg_data_by_country(contry_code='BE')
    client.query_data_by_company_and_country(company_code, country_code)

    # Filter results by time
    client.query_agg_data_by_country(country_code, start=datetime(2017,1,1), end=datetime(2018,1,1), limit=10)

    # Create pandas client. All functions are the same as the raw client.
    pandas_client = AlsiPandasClient(api_key=API_KEY)

    # In the end of the code, make sure to close the client session:
    await client.close_session()
    # or
    await pandas_client.close_session()

asyncio.run(main())For more information regarding company codes, facility codes and country codes visit:https://alsi.gie.eu/#/apiRunning unit testsTell pytest where to look for unit tests and create env for ALSI API keyexport PYTHONPATH=./alsi
export ALSI_KEY='...'Run unit tests in coverage modepython -m pytest ./tests --import-mode=append --covContributingPull the repository:git clone https://github.com/ROITI-Ltd/alsi-py.git
cd ./alsi-pySet up your working environment:python3 -m venv env
source env/bin/activateInstall required packages:pip3 install -r requirements.txt
pip3 install -r requirements-dev.txtBumping the package version after making changes:bumpversion major|minor|patch|buildFor more general guidelines on contributing see:Contributing to alsi-py.InspirationMany thanks to theentsoe-pylibrary for serving as inspiration for this library.
Package: alsmodule-pkg
Ambient Light Sensor (ALS) PackageCopyright (C) 2019 Jean-Jacques PuigThis module implements a trivial interface to access ambient light sensors
available on some Apple computers (iMac...).Usage is very simple; the 'als' module exports only one module method,
getSensorReadings(), which returns raw samples values as a list of two (Long)
integers.import als
print(als.getSensorReadings())
Package: also
## AlsoEver had lots of methods that do the same thing?!You want to set them to the same thing but dont want to do something lame like```pythondef method(self):passothermethod = method```Rather you want to do it with style like```python@also('othermethod')def method(self):pass```Then do I have a solution for you!## Installation```pip install also```## Usage```pythonfrom also import also, AlsoMetaClassclass Foo:__metaclass__ = AlsoMetaClass@also('getThing')@also('get_thing')def getthing(self):return 'go bears'foo = Foo()assert (foo.getthing() == foo.get_thing() ==foo.getThing() == 'go bears')```
Package: also-anomaly-detector
also_anomaly_detectorAttribute-wise Learning for Scoring Outliers (ALSO) is an unsupervised anomaly detection algorithm for multidimensional data.DescriptionPython implementation of ALSO. ALSO, orAttribute-wise Learning for Scoring Outliers, is an unsupervised anomaly detection algorithm for multidimensional data as described in Paulheim, H., Meusel, R. A decomposition of the outlier detection problem into a set of supervised learning problems. Mach Learn 100, 509–531 (2015).https://doi.org/10.1007/s10994-015-5507-yI am not the author, nor in any way affiliated with the authors of the paper above. This is an independent python implementation of the ALSO-approach.UsageFor a local install,cdto the root of this repository and simply;python setup.py developDocumentationDocumentation should be available athttps://eliavw.github.io/also_anomaly_detector.AdministrationOpen the foldernote/deployfor notebooks that contain annotated scripts for the different administrative tasks you may want to undertake with this software project.
Package: alsolib
alsolib v3.4alsolib开发者：苦逼者钟宇轩说明:本库为原创库，火焰工作室精心打造版权所有，侵权必究alsolib 一个最重要的功能想知道是谁在看你的学而思作品吗?
他来了~fromalsolib.xesimport*a=getnowuser()print(a)#正常:{'state':True,'user_id':"7821237", "user_name":"苦逼者钟宇轩"}#未登录:{"state":False,'user_id':"未登录","user_name":"未登录"}###alsolib(alsolib)主要库介绍说明
###注:alsolib介绍成功全为0，失败全为-1
内置函数 导入方式：fromalsolibimport*百度百科a=baidubaike("***")print(a)翻译a=translate("Hello")print(a)天气a=getweather("guangdong","guangzhou")#省，市的英文print(a)内置网页浏览器 title为自定义标题a=getweather("http://www.asunc.cn/","title")#一定要加http://或https://print(a)学而思库说明(alsolib.xes)###注:alsolib.xes介绍成功全为0，失败全为-1
导入方式fromalsolib.xesimport*a=LoadWork("一个作品的pid")学而思获取作品赞b=a.get_likes()print(b)学而思获取作品作者b=a.get_user()print(b)学而思获取作品踩的数量b=a.get_unlikes()print(b)学而思获取作品介绍b=a.get_description()print(b)学而思获取作者信息b=a.get_name_as_pid()print(b)学而思获取你对这个作品点赞没有~while1:b=a.is_like()ifb==0:print("你点赞了")ifb==-1:print("你踩了")ifb==1:print("你没点赞也没踩")hyChat库(alsolib.hychat)importalsolib.hychat###api库(alsolib.api)导库fromalsolib.apiimport*a=Alsoai()1.获取IP地理位置:print(a.get_ipaddress(ip,get_point))#第一个参数必填,第二个参数选填，填True后会返回城市名和这个城市的中心经纬度城市名#不填或False则只返回城市名#错误返回值为-1,成功为02.获取道路交通路况:print(a.get_traffic(road,city))#全部参数都要填，会返回这个道路的路况，像堵车，畅通......#错误返回值为-1,成功为03.制作AI音频:print(a.makevoice(text,filename,mode=1,speed=40))#第一二个参数必填,三四个选填,第一个参数填入发音的文字，第二个参数填路径#第三个参数填发音人(1为男人，5，6，7为三种不同声音的女人),第四个参数填声音范围(0-100)#返回值成功为0，错误返回-14.AI语音:print(a.speak(text,mode=1,speed=40))#第一个参数必填,二三个选填,第一个参数填入发音的文字,第二个参数填发音人#(1为男人，5，6，7为三种不同声音的女人),第三个参数填声音范围(0-100)#返回值成功为0，错误返回-15.AI智能聊天机器人:print(a.AI_chat(text,is_speak=False,mode=5))#第一个参数必填,二三个选填,第一个参数传入你想对机器人说的话，第二个传入#是否以AI说语音,第三个填发音人(1为男人，5，6，7为三种不同声音的女人)#成功返回0,AI智能聊天机器人的回答，失败返回-1,404为操作太快###结束:本介绍解释终归火焰工作室，感谢您的收看~~~
Package: alstat
alstat is advances logs statistics.
It’s collection of utils to analyze logs.FeaturesUnpack gzipped logfilesFastUsageThis commant print all lines from all log files in directory /var/log/nginx
if formathttp_method status http_referer:alstat -d /var/log/nginx/ -p "*access*" -f "base" http_method status http_referer

GET 200 http://google.com
.... to many lines
GET 404 http://ya.ru/
PUT 200 http://yandex.com/You can view fields list that you can use to display:alstat -d /var/log/nginx/ -p "*access*" -l

Alstat v0.0.1 start at Tue May  8 23:25:24 2012
You can use fieldnames: status, http_protocol, http_method, http_referer, remote_addr, url, time_local, http_user_agent, remote_user, sizeINSTALLATIONTo use alstat use pip or easy_install:pip install alstatoreasy_install alstatTODOAdd group by fields and countWeb interface with reportsCONTRIBUTEForkhttps://github.com/Lispython/alstat/, create commit and pull request.THANKSTo David M. Beazley forgeneratorsexamples.SEE ALSOpython pypi.
Package: altadata
ALTADATAPython library provides convenient access to the ALTADATA API from applications written in the Python language. With this Python library, developers can build applications around the ALTADATA API without having to deal with accessing and managing requests and responses.OverviewInstallationRetrieving DataDocumentationLicenseInstallationpip install altadataRetrieving DataYou can get the entire data with the code below. This function returns List of dict by default.client=AltaDataAPI(YOUR_API_KEY)data=client.get_data(PRODUCT_CODE).load()We currently have pandas dataframe support in the library. Users can optionally retrieve their datasets as pandas dataframe.
Ifdataframe_functionalityparameter is True function returns pandas dataframe.Note:This functionality requirespandas(v0.23 or above) to work.client=AltaDataAPI(api_key=YOUR_API_KEY,dataframe_functionality=True)data=client.get_data(PRODUCT_CODE).load()You can get data with using various conditions.client=AltaDataAPI(YOUR_API_KEY)data=client.get_data(PRODUCT_CODE)\.equal(condition_column=COLUMN_NAME,condition_value=CONDITION_VALUE)\.sort(order_column=COLUMN_NAME,order_method="desc")\.load()DocumentationRead the documentation online ataltadata-python.rtfd.ioOptionally, build documentation from thedocs/folderpip install sphinx
cd docs
make htmlLicensealtadata-python is under MIT license. See theLICENSEfile for more info.
Package: altair-ally
Altair AllyThis package is in early development and its name, API, etc might change rapidly. It is not yet on PyPI.Altair Ally ("Aly" for short) is an companion package to Altair,
which provides a few shortcuts to create common plots
for exploratory data analysis (EDA),
particularly those involving visualizing an entire dataset.
The goal is to encourage good EDA habits
by making it quick and simple to create these visualizations,
and to provide useful default interactions with the plots.Thanks to the excellent API in Altair / Vega-Lite,
some configuration is possible
by using the built-in methods of the returned chart objects,
but the general philosophy is that highly customized plots
are better made in Altair directly.
The package name is a nod to ggally
which complements ggplot2 in a similar,
but much more extensive manner.Check out the documentation for more info and examples.
Package: altair-data-server
Altair data serverThis is a data transformer plugin forAltairthat transparently serves data for Altair charts via a background WSGI server.Note that charts will only render as long as your Python session is active.The data server is a good option when you'll begenerating multiple charts as
part of an exploration of data.UsageFirst install the package and its dependencies:$ pip install altair_data_serverNext import altair and enable the data server:importaltairasaltalt.data_transformers.enable('data_server')Now when you create an Altair chart, the data will be served in the background
rather than embedded in the chart specification.Once you are finished with exploration and want to generate charts that
will have their data fully embedded in the notebook, you can restore the
default data transformer:alt.data_transformers.enable('default')and carry on from there.Remote SystemsRemotely-hosted notebooks (like JupyterHub or Binder) usually do not allow the end
user to access arbitrary ports. To enable users to work on that setup, make surejupyter-server-proxyis
installed on the jupyter server, and use the proxied data server transformer:alt.data_transformers.enable('data_server_proxied')ExampleYou can see this in action, as well as read some of the motivation for this
plugin, in the example notebook:AltairDataServer.ipynb.
Click the Binder or Colab links above to try it out in your browser.Known IssuesBecausejupyter-server-proxyrequires at least Python 3.5, the methods described inRemote Systemsdo not work do not work for older versions of Python.
Package: altair-easeviz
Altair-EasevizThis Python library is dedicated to providing resources for Vega-Altair, with the aim of enhancing the creation of
improved
and more accessible graphs. The development of this library involved a thorough exploration of both the Altair and
Vega-Lite APIs.InstallationThe library and its dependencies can be easily installed, using:pip install altair-easevizDocumentationDocumentation for this library can be foundhere.FeaturesInitial release of four accessible themes for Vega-AltairGenerate description for charts addedHTML with accessible functions addedModels for creation and customization themes of vega-lite specification addedExampleThis next example shows how to enable one of our four themes.
More examples are available in ourdocumentation.importaltairasaltimportpandasaspd# Enable Theme accessible_theme, dark_accessible_theme, filler_pattern_theme, print_themealt.themes.enable('accessible_theme')# Define a Chartsource=pd.DataFrame({'a':['A','B','C','D','E','F','G','H','I'],'b':[28,55,43,91,81,53,19,87,52]})alt.Chart(source).mark_bar().encode(x='a',y='b')Getting HelpFor bugs and feature requests, please open aGithub Issue.
Package: altair-express
Altair ExpressCreate interactive data visualizations in one line of code.Free software: MIT licenseDocumentation:https://altair-express.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2022-11-01)First release on PyPI.
Package: altair-extra-color-schemes
altair-extra-color-schemesAdditional named color schemes forAltairvia a custom renderer.QuickstartInstallationViapip:pipinstallaltair-extra-color-schemesViaPipenv:pipenvinstallaltair-extra-color-schemesViaPoetry:poetryaddaltair-extra-color-schemesViaPDM:pdmaddaltair-extra-color-schemesViaPyflow:pyflowinstallaltair-extra-color-schemesUsageimportaltairasaltalt.renderers.enable("extra_color_schemes")You can find some example charts in thedemo.ipynbnotebook.Color schemesColor scheme nameTypeSourceNotes"dvs"CategoricalData Visualization Standards (DVS)"Featured Colors" and "Qualitative Colors" > "Example Palette"DevelopmentPoetry(version 1.2.0)Add new color schemes to thealtair_extra_color_schemes/full_template.jinjafilepoetry config virtualenvs.in-project truepoetry installpoetry run jupyter labpoetry run black demo.ipynbpoetry checkDeploymentpoetry version minororpoetry version patchpoetry buildNotesdjLint:pipx install djlintdjlint altair_extra_color_schemes/template.jinja --checkdjlint altair_extra_color_schemes/template.jinja --reformatdjlint altair_extra_color_schemes/template.jinja --profile=jinjadjlint formatter.jinja --reformat --format-css --format-jsDefault color schemesDjHTML:pipx install djhtmldjhtml -i formatter.htmlcurlylint:pipx install curlylintcurlylint altair_extra_color_schemes/full_template.jinjaCloudscape Design System(Figma file)Poetry:Detection of the currently active Python (experimental)documentationCan't install Pandas on Mac M1issuepip --versionNullish coalescing operator (??): Short-circuiting
Package: altair-images
Serving interactive charts with images - based on AltairProject fully supports Google Colab. For more details seeexamplesInstallationpipinstallaltair-imagesHow to useimportnumpyasnpfromaltair_imagesimportplot_with_imageembedding_data=np.load('../tests/pca_data_100.npy')sample_images=np.load('../tests/sample_images_100.npy')labels=np.load('../tests/sample_labels_100.npy')plot_with_image(embedding_data,labels,sample_images)TODOAdd examples in readmeAdd CI for tagging and publishing new version from masterAdd testsExample of line_plot and pictures(speed and frame, weight and body)
Package: altair-saver
Altair SaverThis packge provides extensions toAltairfor saving charts
to a variety of output types. Supported output formats are:.json/.vl.json: Vega-Lite JSON specification.vg.json: Vega JSON specification.html: HTML output.png: PNG image.svg: SVG image.pdf: PDF imageUsageThealtair_saverlibrary has a single public function,altair_saver.save().
Given an Altair chart namedchart, you can use it as follows:fromaltair_saverimportsavesave(chart,"chart.vl.json")# Vega-Lite JSON specificationsave(chart,"chart.vg.json")# Vega JSON specificationsave(chart,"chart.html")# HTML documentsave(chart,"chart.html",inline=True)# HTML document with all JS code included inlinesave(chart,"chart.png")# PNG Imagesave(chart,"chart.svg")# SVG Imagesave(chart,"chart.pdf")# PDF ImageRendererAdditionally, altair_saver provides anAltair Rendererentrypoint that can display the above outputs directly in Jupyter notebooks.
For example, you can specify a vega-lite mimetype (supported by JupyterLab, nteract, and other
platforms) with a PNG fallback for other frontends as follows:alt.renderers.enable('altair_saver',['vega-lite','png'])InstallationThealtair_saverpackage can be installed with:$ pip install altair_saverSaving asvl.jsonand ashtmlrequires no additional setup.To install with conda, use$ conda install -c conda-forge altair_saverThe conda package installs theNodeJSdependencies described below, so charts can be
saved topng,svg, andpdfwithout additional setup.Additional RequirementsOutput topng,svg, andpdfrequires execution of Javascript code, whichaltair_savercan do via one of two backends.SeleniumTheseleniumbackend supports the following formats:.vg.json.png.svg.To be used, it requires theSeleniumPython package,
and a properly configured installation of eitherchromedriverorgeckodriver.On Linux systems, this can be setup as follows:$pipinstallselenium
$apt-getinstallchromium-chromedriverUsing conda, the required packages can be installed as follows (a compatible version ofGoogle Chromemust be installed separately):$condainstall-cpython-chromedriver-binarySelenium supportsother browsersas well,
but altair-saver is currently only tested with Chrome.NodeJSThenodejsbackend supports the following formats:.vg.json.png.svg.pdfIt requiresNodeJS, along with thevega-lite,vega-cli, andcanvaspackages.First install NodeJS either bydirect downloador via apackage manager, and then use thenpmtool
to install the required packages:$npminstallvega-litevega-clicanvasUsing conda, node and the required packages can be installed as follows:$condainstall-cconda-forgevega-clivega-lite-cliThese packages are included automatically when installingaltair_savervia conda-forge.
Package: altair_tiles
This package is in an early development stage. You should expect things to break unannounced until we release a version1.0.0.You can use altair_tiles to add tiles from any xyz tile provider such as OpenStreetMap to your Altair chart. It is a counterpart to the amazingcontextilypackage which provides this functionality formatplotlib.You can find the documentationhere. For a general introduction to plotting geographic data with Altair, seeGeoshape - Vega-AltairandSpecifying Data - Vega-Altair.Installationpipinstallaltair_tilesaltair-tiles requires at least Vega version5.26.0. If you use an IDE such as a Jupyter Notebook or VS Code, you usually don't have to worry about this.Developmentpython-mvenv.venvsource.venv/bin/activate
pipinstall-e'.[dev]'Run linters and tests withhatchruntestBuild and view the documentation withhatchrundoc:clean
hatchrundoc:build
hatchrundoc:serveTo run a clean build and publish, runhatchrundoc:build-and-publish