Saravanan666/pypi-org huggingface dataset:
Package: chartio
=======Chartio=======Chartio utilities for providing read-only user local database access.Version 6.0.1Introduction------------This project permits Chartio customers to provide database access byopening an SSH reverse tunnel from a Chartio server to the customerdatabase.Errors, comments, questions may be sent to support at chartio.comRequirements------------Requires a read-only database role and a local SSH client. Requires JSONsupport (Python 2.6 or Python 2.5 and simplejson).Supported Databases-------------------MySQLOraclePostgreSQLAmazon RedshiftInstallation------------To install, type::$ python setup.py installTo uninstall, remove the fileschartio_setupchartio_connectTroubleshooting-------------The log file~/.chartio.d/logs/chartio_connect.logcontains information about the chartio_connect process.Documentation-------------Further documentation may be found at https://support.chartio.com/docs/index/Package Contents----------------chartio_setupThe configuration wizardchartio_connectA script to keep the SSH tunnel aliveNotable Changes---------------Version 6.0.1- Deprecate chartio_setupVersion 5.0.0- Add support for PrestoDB- Remove inline datasource schema refresh. Status can be checked on the website.Version 4.0.0- Add support for AmazonRedshiftVersion 3.1.0- Add option to specify the hostname of the database server.Version 3.0.0- Backwards incompatible update for new Chartio permissions structure.Version 2.0.4- Change the ternary operator to if ... else so that Python 2.4.x does not raise a syntax error.Version 2.0.3- Update command-line error handling to work with a MySQL 5.6 WarningVersion 2.0.2- Copyright, e-mail, and text changesVersion 2.0.1- Backwards incompatible due to server URL changesVersion 1.1.19- Correct port type issueVersion 1.1.18- Specify SSH listen port to override local SSH configurationVersion 1.1.17- Change domain to chartio.comVersion 1.1.16- add option to post error information to ChartioVersion 1.1.13- add Oracle supportVersion 1.1.12- check Chartio versionVersion 1.1.7- permit manual entry of database and readonly user/passwordVersion 1.1.6- grant 'SHOW VIEW' access when creating mysql read-only database user- bug fix for handling of blank database administrator password
Package: chartlyrics
ChartLyrics APIThis is a simple wrapper for:http://api.chartlyrics.com. You can search for songs, artists and get the lyrics.InstallationpipinstallchartlyricsUsage ExamplefromchartlyricsimportChartLyricsClientclient=ChartLyricsClient()forsonginclient.search_text("starts with one"):if"park"insong.artist.lower():print(song.artist)# Linking Parkprint(song.lyrics)# Starts with one\n One thing I dont know why...You can also usesong.lyrics_objectwhich will return aLyricsobject that you can index strophes and verses on:lyrics=song.lyrics_objectprint(lyrics[0][-1])# first strophe last verseCheck thetestsfor more examples.DevelopmentFork the repo, run:poetryinstallAdd features, write tests, run:poetryrunpytestCreate a Pull request.
Package: chart_me
Chart MeCharting that keeps you in the EDA flowChart Me is a high-level charting library designed to expedite the Exploratory Data Analysis Process(eda). There are a few automated eda tools likesweet vizthat give a great initial set of visualizations.luxis a great tool to leverage - which gives a feel of AI assistance - but not always on the mark. The other alternative is hand-writing Altair code, which takes me out of the EDA flow looking up syntax or building functions...Chart Meserves to keep you in the data analytics flow of discovery by keeping visualization commands toone functionto remember.Chart Me DocumentationSeeRead the Docsfor more detailsUsage WarningsCurrently a proof-of-concept mode at this time. Limited to univariate & bivariate charts and doesn't support geographical data and is lightly tested.Installation$pipinstallchart-meSimple Usagechart_meto quickly generate visualizations during eda processimportchart_meascece.chart_me(df,'col_1','col_2')#<-- reads as c-e-chart_me
Package: chartparse
chartparseInstall it from PyPIpipinstallchartparseUsagefromchartparse.chartimportChartfromchartparse.instrumentimportInstrument,Difficultyc=Chart.from_filepath("/path/to/file.chart")# the first 7 BPM changes (including the initial one)c.sync_track.bpm_events[:7]# the first 8 time signature changes (including the initial one)c.sync_track.time_signature_events[:8]expert_guitar=c[Instrument.GUITAR][Difficulty.EXPERT]# the first 10 notes of the expert guitar chartexpert_guitar.note_events[:10]# the first 3 star power phrases of the expert guitar chartexpert_guitar.star_power_events[:3]See thedocumentationfor more detailed
guidance.Note: this software is tested only with .chart files that are written byMoonscraper.
Files written by other editors or are handwritten may produce undefined
behavior.DevelopmentRead theCONTRIBUTING.mdfile.
Package: chartpy
chartpy creates a simple easy to use API to plot in a number of great Python chart libraries like plotly (via cufflinks),
bokeh and matplotlib, with a unified interface. You simply need to change a single keyword to change which chart engine
to use (see below), rather than having to learn the low level details of each library. I’ve also created new stylesheets
and formatting to ensure that the default matplotlib styling looks more modern using Open Sans font. The library
also works well with Dash, plotly’s web server library built on top of Flask.
Package: chartree
chartreeGrow your own trees on a monospace grid. Choose the material (unicode) for your tree as well as the hue of the sky (also unicode). Heaps of other parameters as well!Installationpip install chartreeExamplefromchartreeimportEcosystemw=Ecosystem(material='7',background='.')# Grows a new tree, different each time.w.grow(n_iter=50,ang_mean=40,ang_range=10)# Shows currently grown tree. Can be used to experiment with materials.w.show(material='#',background='i')
Package: chart_releaser
Helm chart releaserThis toolrequirement helm binary in machine.The utility can create a helm package and upload it to the gitlab registry in thestableordevelopchannel.More information in gitlab documentationWhen uploading to develop channel, the same versions are allowed to be uploaded. When installing helm will take the last downloaded version.Uploading identical versions to stable channel is forbidden in the code.CLI and default vars-t || --token- token for registry. Override if envCHART_RELEASE_TOKENis exist.--ssl- path to SSL certificate for registry. Override if envSSL_PATHis exist. Default value/usr/local/share/ca-certificates/CA.crt.-u || --registry-url- registry URL, domain only like gitlab.com. Override if envREGISTRY_URLis exist. Defaultgitlab.com.-p || --project-id- CI_PROJECT_ID for gitlab registry. Override if envRELEASE_PROJECT_IDis exist.-n || --chart-name- chart name.-path- path to Chart.yaml.-c || --config- path to config file. Override if envTOOL_CONFIG_PATHis exist. Defaulthc-releaser.config. File exist in repository and need for local development, because for gitlab registy must use headers withJOB-TOKENif you usageCI_JOB_TOKENandPRIVATE-TOKENif you usage your private token. This is dynamic paramenter and by default usageJOB-TOKEN. If config does not exist usageJOB_TOKENalso.-b || --branch- branch for release_stage.UsageRun helm linthc-releaserhelmlinting-p<pathtohelmchart>Optional key-d||--debug- bolean. If set, helm running with debug mode.Create and upload pre release helm packagehc-releaserhelmrelease_stage-t<gitlab_token>-u<gitlaburl.Domainonly>-p<gitlab_project_id>-n<chart_name>-path<pathtodirwithChart.yaml>Create and upload release helm packagehc-releaserhelmrelease-t<gitlab_token>-u<gitlaburl.Domainonly>-p<gitlab_project_id>-n<chart_name>-path<pathtodirwithChart.yaml>Check version in package registryhc-releaserhelmcheck-t<gitlab_token>-u<gitlaburl.Domainonly>-p<gitlab_project_id>-n<chart_name>-path<pathtodirwithChart.yaml>
Package: chart-review
Chart ReviewMeasure agreement between chart annotators.Whether your chart annotations come from humans, machine-learning, or coded data like ICD-10,chart-reviewcan compare them to reveal interesting statistics like:AccuracyF1-score (agreement)Sensitivity and SpecificityPositive (PPV) or Negative Predictive Value (NPV)False Negative Rate (FNR)Confusion MatrixTP = True Positive (type I error)TN = True Negative (type II error)FP = False PositiveFN = False NegativeDocumentationFor guides on installing & using Chart Review,read our documentation.Example$ls
config.yamllabelstudio-export.json

$chart-reviewaccuracyjanejohn
accuracy-jane-john:
F1SensSpecPPVNPVTPFNTNFPLabel0.8890.81.01.00.54110*1.01.01.01.01.01010Cough000002000Fatigue000001100HeadacheContributingWe love 💖 contributions!If you have a good suggestion 💡 or found a bug 🐛,read our brief contributors guidefor pointers to filing issues and what to expect.
Package: charts.css.py
charts.css.pycharts.css.pyprovides a python API to convert your 2-dimension data lists into html snippet,
which will be rendered into charts by CSS, when serving inside a browser.The output ofcharts.css.pyisnotimages. Consequently,charts.css.pyis a pure Python package without any image library dependency.
You can usecharts.css.pyon any platform.The output ofcharts.css.pyis a normal HTML table.
Search engines and screen readers will be able to consume your data
even when CSS rendering is unavailable.Once the html snippet is delivered into the browser window,
the rendering is done by CSS, which is typicallyfaster than JS-heavy chart libraries.Since the output is normal HTML, you could customize its size and position,
by defining your own CSS styles.Installationpip install charts.css.pyUsageJust combine the output ofcharts.css.pyfunctions and the predefined CSS style<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/charts.css/dist/charts.min.css">into your html page.For example, the following code snippet can convert a 2-dimension list into column chart:fromcharts.cssimportcolumnSTYLESHEET='<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/charts.css/dist/charts.min.css">'chart=column([["Continent","1st year","2nd year","3rd year","4th year","5th year"],["Asia",20.0,30.0,40.0,50.0,75.0],["Euro",40.0,60.0,75.0,90.0,100.0],],headers_in_first_row=True,headers_in_first_column=True,)# Now, variable chart contains html snippet of "<table>...</table>", and# STYLESHEET is just a constant string of "<link href='https://.../charts.css'>".# You can somehow insert them into the proper places of your full html page.# Here in this sample, we take a shortcut by simply concatenating them.open("output.html","w").write(STYLESHEET+chart)The output.html will be rendered in browser like this:Advanced UsageThere are currently 4 different charts implemented:bar,column,line,area.
All those methods support many parameters to further customize the chart appearance.bar()andcolumn()also support stacking by value or stacking by percentage.
All those features are demonstrated in thedifferent samples in this document.Lastly, this package also provides a command-line toolcsv2chart.
You can use it to convert csv file into an html file.
For example,csv2chart sample.csv output.html.
You can also runcsv2chart -hto know all the parameters it supports.Versioningcharts.css.pyusesSemantic Versioning.
Package: chart-sos
Speed of Sound from 1970 chartThis project follow the echometer companyarticle.Data Extraction techniqueMake use ofWebPlotDigitizer.
It saves data in Tar files.Usagegas_sghas no unitpressureis psitempin Fahrenheitimportsosgas_sg=0.62pressure=0temp_f=40sos.get_interpolate_sos(gas_sg,temp_f,pressure)Show plotgas_sg = 0.62is not in the chart.
Package: chartstag
ChartStagv0.8.2ChartStag is an extension for theSciStagpackage
which supports you in your computer vision, data science and data engineering
projects.It extends SciStag with diagram and chart plotting capabilities. As of now solely by
integratingmermaid, an awesome diagram and
charting tool written in JavaScript, into SciStag VisualLog.mermaid is licensed under the terms of
theMIT license-
for further details about mermaid visithttps://github.com/mermaid-js/mermaidorhttps://mermaid.js.org/.At this point huge thanks toKnut Sveidqvistand the whole
mermaid team for their awesome work.Embedded tools versions:Mermaid 10.2.3ChartStag itself is as well licensed under the terms of the MIT license and
Copyright (c) 2023Michael Ikemann.For examples about how to use ChartStag in SciStag install scistag
viapip install scistag[common]and seehttps://github.com/SciStag/SciStag/tree/main/scistag/examples/vislog.
Package: chart-studio
chart-studioThis package contains utilities for interfacing with Plotly's Chart Studio service (both Chart Studio cloud and Chart Studio On-Prem).  Prior to plotly.py version 4, This functionality was included in theplotlypackage under theplotly.plotlymodule. As part of plotly.py version 4, the Chart Studio functionality was removed from theplotlypackage and released in thischart-studiopackage.
Package: chartsworth
ChartsworthChartsworth posts fromnotebookstoslack. This little metric monster lets you post plots, images, and anything else the slack sdk will let you post.Read more background and workflows around scheduling in theNotebook Reporting with Chart Monsters Post.Installation and Setuppip install chartsworthSet environment variableCHARTSWORTH_TOKENto your Slack App. You can create a new Slack AppCreate a new Slack Appandlearn more about creating a new slack app in the chartsworth post.UsagefromchartsworthimportChartsworthchartsworth=Chartsworth("#chartsy")new_users=11_003chartsworth.post(f"We have{new_users}new users")Note: many times you'll need to use a channel ID (e.g.C05HP8Z5ZPD), especially if the channel is private. Otherwise, images will not post (only text will).Posting PlotsChartsworth can take any PIL Image or Matplotlib Figure and post it to slack. This means you can post plots, images, and anything else you can think of.fromchartsworthimportChartsworthchartsworth=Chartsworth("C05HP8Z5ZPD")chartsworth.post("Who's ready for a 🏞️ stream plot? 🧵")importnumpyasnpimportmatplotlib.pyplotaspltx=np.linspace(-3,3,100)y=np.linspace(-3,3,100)X,Y=np.meshgrid(x,y)u=-1-X**2+Yv=1+X-Y**2speed=np.sqrt(u*u+v*v)## Create a figure we can pass to Chartsworth ##fig,ax=plt.subplots()strm=ax.streamplot(X,Y,u,v,color=speed,linewidth=2,cmap='autumn')fig.colorbar(strm.lines)## Post!chartsworth.post(fig)SchedulingSchedule your notebooks on Noteable from the notebooks UIOr run it withpapermillwith your own custom scheduling!
Package: chart-tools
chart-toolsInstall & UseMust have python 3.9+pip install chart-toolsimportchart_toolsasctct.load_data()# outputs available pre-defined data sourcesData InterfaceEasily load datasets and explore available sources with one line of codeTheload_data()function andDataSourceobject use Github's API to explore file structures in repositories containing.csvfiles, and easily load files into dataframes. Chart-tools has a pre-defined library (collection of repositories) for you to explore within your notebook and load data from.Robust caching system designed for Python notebooks, performing great with large datasets.Any dataframe you load gets cached in memory, remembering which pandas keyword arguments you used when loading the file. Next time you load it, you'll get acopyof the cached dataframe, unless you pass different keyword arguments. Not only is this great for performance with large datasets, but it also eliminates the common need to declare adf_raw = ...and then usedf = df_raw.copy()to get your original data again.Has a pre-defined library of data sources to explore, and lets you easily define your own librarySave an entire Github repository file structure (csv files only) to your desktopCharts & VisualizationsuperheatA "super" correlation heatmap you can't find elsewhere, designed for speed and ease of use.Marks are sized dynamically based on correlation strength, drawing your eyes straight to the most important relationships.Easily filter out variables whose coefficients average below a threshold, or simply mask/hide marks below a threshold.Examples
Package: charybdis
CharybdisTiny Hi-Rez API Python wrapper that I wrote to use in my Smite related projects
(and to play around with async).Hi-Rez API documentation:https://webcdn.hirezstudios.com/hirez-studios/legal/smite-api-developer-guide.pdfSee the Hi-Rez API documentation for available methods and their parameters.
The structure of the returned values is not described though, so some work is
required to figure out what information can actually be obtained from the API.Other Python wrappers:https://github.com/luissilva1044894/Pyrezhttps://github.com/DevilXD/aRezInstallationpip install charybdisUsageSyncimportosimportcharybdisapi=charybdis.Api(# These are also the default values.base_url=charybdis.Api.SMITE_PC_URL,dev_id=os.getenv("SMITE_DEV_ID"),auth_key=os.getenv("SMITE_AUTH_KEY"),)# Returns deserialized JSON.scylla_skins=api.call_method("getgodskins",# Method name."1988",# God ID - Scylla."1",# Language ID - English.)forscylla_skininscylla_skins:print(scylla_skin["skin_name"])# Output:# Standard Scylla# Bewitching Bunny# Child's Play# COG Scylla# and many more...Asyncimportasyncioimportcharybdisasyncdefmain()->None:asyncwithcharybdis.Api()asapi:patch_info_task=asyncio.create_task(api.acall_method("getpatchinfo"))gods_task=asyncio.create_task(api.acall_method("getgods","1"))patch_info=awaitpatch_info_taskgods=awaitgods_tasknewest_god=""forgodingods:ifgod["latestGod"]=="y":newest_god=god["Name"]breakprint(f"The current patch is{patch_info['version_string']}"+f" and the newest god is{newest_god}.")asyncio.run(main())# Output:# The current patch is 9.12 and the newest god is Maui.
Package: chas
ChasInstallationInstall library through pippipinstallchasAdd decorator to function in your script calledjob_jobname.py(note: it must start with prefixjob_) that you want to run as cron job. For example:fromchasimportchas@chas.job("08:00")defprint_hello_world():print("Hello, World!")Finally, you can start up a server by running. This starts the cron scheduler, which will execute the function at given times, and also you can view and manage jobs onlocalhost:5000.chasstart--http-serverCommand lineChas is convenient even from running jobs from your command line. You can dochaslistWhich prints out all the registered jobsJob                Next run             Last run             Last status
print_hello_world  22-12-2018 08:00:00  N/A                  N/AYou can run any of these jobs by typingchasrunprint_hello_worldDecoratorsAs already mentioned,@chas.job(time)registers a job at a particular time. There another decorator@chas.setup()which simply executes the script inside during the import time. This should be used for setting up environment variables. For example`importosfromchasimportchas@chas.setup()defsetup_environment():os.environ["foo"]="bar"@chas.job("09:00")defprint_env_var():print(os.environ["foo"])On run would printbar.PackagesIn case you structure your directory as a Python package, you will need to export all scripts with@chas.jobfrom the package. Then, you will run all shell commands as above, but with adding parameter--package folder_namewherefolder_namespecifies the entry point to your package.
For example, if you structure your package in the following way:.
|-- src
|   -- __init__.py
|   -- script_one.py
|   -- script_two.py 
|-- LICENSE
|-- README.mdThen you can runchas list --package src.PrometheusWhen starting the server with option--http-server,chasautomatically opens up Prometheus metrics endpoint on/metrics. This allows you to easily monitor your chas script with Prometheus and complementary tools like Grafana, Alertmanager etc.
The two metrics gathered are Counter-type objects namedjob_runs_totalandjob_runs_status_total, first denoting the number of times a job was run and the second also counting their statuses, eitherfailedorsucceeded.TroubleshootingWhat to do in case of ModuleNotFound error?This can happen due to incorrect PYTHONPATH environment variable. Make sure current working directory is in there. You can check it byecho $PYTHONPATH. Otherwise to append current working directory, runexport PYTHONPATH="${PYTHONPATH}:${PWD}".
Package: chaser
CHaser client for Pythonライブラリの利用PyPIにアップロードしているので、インストールにはpipコマンドを使えます。(venv)$ pip install chaser使い方は、example/simple.pyexample/mapper.pyを参考にしてみてください。ライブラリの開発ライブラリ開発で利用する依存モジュールはpipでインストールできます。$ pip install -e .[dev]
Package: chasgimqtt
# channels-asgi-mqttInterface between MQTT and ASGI and Channels 2.0 compatible## Installation```bashpip install chasgimqtt```## ConfigurationFirst you would to configure a valid `channel_layer` endpoint to consume and connect between chasgimqtt and channels.In `your_channel_application/asgi.py`:```pythonimport osimport djangofrom channels.routing import get_default_applicationfrom channels.layers import get_channel_layeros.environ.setdefault("DJANGO_SETTINGS_MODULE", "your_channel_application.settings")django.setup()# Applicationapplication = get_default_application()# Layerschannel_layer = get_channel_layer()```## Usage```bashchasgimqtt -H iot.eclipse.org -p 1883 --topic=some_topic:2 your_channel_application.asgi:channel_layer```## Options```chasgimqtt -husage: chasgimqtt [-h] [-H HOST] [-p PORT] [-v] [-U USERNAME] [-P PASSWORD][--topic TOPICS] [-n CHANNEL_NAME] [-s CHANNEL_SUB][-x CHANNEL_PUB]channel_layerSimple MQTT bridge for ASGIpositional arguments:channel_layer         The ASGI channel layer instance to use aspath.to.module:instance.pathoptional arguments:-h, --help            show this help message and exit-H HOST, --host HOST  MQTT broker host-p PORT, --port PORT  MQTT broker port-v, --verbosity       Set verbosity-U USERNAME, --username USERNAMEMQTT username to authorised connection-P PASSWORD, --password PASSWORDMQTT password to authorised connection--topic TOPICS        MQTT topics with qos to subscribe --topic TOPIC:QOS--topic /office/sensor:0 --topic /home/sensor:1 Ifempty (#, 2) is set as default-n CHANNEL_NAME, --channel-name CHANNEL_NAMEName of Channels's channel to send and receivemessages-s CHANNEL_SUB, --channel-sub CHANNEL_SUBName of Channels's channel for MQTT Sub messages,default is mqtt.pub-x CHANNEL_PUB, --channel-pub CHANNEL_PUBName of Channels's channel for MQTT Pub messages,default is mqtt.sub```**HOST**: MQTT broker host**PORT**: MQTT broker port, default 1883**USERNAME**: MQTT username to authorised connection**PASSWORD**: MQTT password to authorised connection**TOPICS**: MQTT topics with qos to subscribe. This option expect a valid topic name and a QOS value splited by `:`To subscribe to a list of topics use the same option `--topic`.```--topic some_topic:qos --topic another_topic:qos --topic home/kitchen_gas_sensor:2 --topic home/office_air_sensor:0```**CHANNEL_NAME** : Name of Channels's channel to send and receive messages, this `channel_name` must to exist in your channel's consumer, default is `mqtt`.**CHANNEL_SUB** : Name of Channels's channel for MQTT Sub messages, default is `mqtt.sub`.**CHANNEL_PUB** : Name of Channels's channel for MQTT Pub messages, default is `mqtt.pub`.
Package: chash
Package DescriptionThis package provides a hash function for computing the hash of the contents of
complex data structures. This can be useful for memoization of functions that
process complex data structures (assuming that the produced data structures are
not subsequently modified).Quick StartMake sure you havepipinstalled; once you do, install
the package as follows:pip install chashDevelopmentThe latest source code can be obtained from the project website onGitHub.Authors & AcknowledgementsSee the included AUTHORS.rst file for more information.LicenseThis software is licensed under theBSD License.
See the included LICENSE.rst file for more information.