Saravanan666/pypi-org huggingface dataset:
Package: gradpose
GradPoseWelcome to the GitHub repository for the GradPose tool.GradPose is a novel structural superimposition command-line tool and Python package for PDB files. GradPose uses gradient descent to incrementally approach the optimal rotation matrices (via quaternions) for alignment.  It is memory efficient and enables for the quick alignment of thousands to millions of protein structures to a template structure while also providing exact control over which chain and specific residues to align. The tool is designed to overcome the limitations of classical superimposition algorithms, which are not equipped to handle the large number of PDB files produced by researchers today. Our method scales linearly with the number of residues and can also use batch matrix operations effectively even when there are amino-acid insertions or deletions. This makes it more efficient than traditional methods, which tend to scale exponentially with the number of residues and process the pbds individually. Furthermore, if a GPU is available, it can use CUDA acceleration.This repository contains the source code and documentation for the GradPose tool. Please refer to the documentation for instructions on how to use the tool and for more information about its features and capabilities.We hope that this tool will be useful to researchers and practitioners in the field of bioinformatics. If you have any questions or suggestions, please don't hesitate to open an issue or submit a pull request. We welcome contributions and feedback from the community.InstallInstall GradPose from PyPI with pip:pip install gradposeExamples of usage:A folder containing N PDBs named 'example_pdb_folder'gradpose -i example_pdb_folderorgradpose example_pdb_folderThe aligned proteins are automatically stored in the folder 'output'. Using another folder name, or overwriting the current folder without creating a second is possible using the -o option.If the pdbs need to be aligned to a specific template:gradpose -i example_pdb_folder -t template_example.pdbIf only a spedific part of the proten needs to be aligned, for exmaple, the first 10 amino-acids, animo-acids 12, and the the aminoacids ranging between (and including) 20 and 30:gradpose -i example_pdb_folder -r 1:10 12 20:30(Instructions for options coming soon.)
Package: gradpyent
Gradpyent, a Python Gradient GeneratorGradpyent is a Python package for generating color gradients based on list-like inputs and start/end color values. The generated gradients are ideal for data visualization, user interfaces, or anywhere you want to convert a list of values into a color gradient.This package allows you to specify colors in a variety of formats including RGB, HTML, and KML, giving you the flexibility to match your specific needs.The gradient generation algorithm automatically scales input values outside the range of 0-1, ensuring the generated gradient remains consistent and visually pleasing.Table of ContentsInstallationUsageExamplesLicenseCode QualityTestsInstallationYou can install Gradpyent directly from PyPI:pipinstallgradpyentUsageBasic usage:fromgradpyent.gradientimportGradient# Define the start and end colors as RGB, HTML, or KMLstart_color='rgb(255,0,0)'# Red in RGBend_color='#0000ff'# Blue in HTML# Instantiate the gradient generator, opacity is optional (only used for KML)gg=Gradient(gradient_start=start_color,gradient_end=end_color,opacity=1.0)# Define the input listinput_list=[0,0.5,1]# Generate the gradientgradient=gg.get_gradient_series(series=input_list,fmt='html')print(gradient)ExamplesHere are some more examples demonstrating how to use different color formats and list inputs:RGB colors:start_color='rgb(255,0,0)'# Redend_color='rgb(0,0,255)'# Blueinput_list=[0,0.5,1]HTML colors:start_color='#ff0000'# Redend_color='#0000ff'# Blueinput_list=[0,0.5,1]KML colors:start_color='ff0000ff'# Redend_color='ffff0000'# Blueinput_list=[0,0.5,1]Scaling input values:start_color='rgb(255,0,0)'# Redend_color='#0000ff'# Blueinput_list=[-5,0,5,10]# Values outside 0-1 rangeJupyter notebook samples:See thenotebooksdirectory for more examplesLicenseThis project is licensed under the terms of the MIT license. See theLICENSE.mdfile for details.Code Qualityflake8p ./srcisort ./srcpydocstyle ./srcTestspytest --cov ./srcEnjoy the colorful world!
Package: gradslam
gradslam is a fully differentiable dense SLAM framework. It provides a repository of differentiable building blocks
for a dense SLAM system, such as differentiable nonlinear least squares solvers, differentiable ICP
(iterative closest point) techniques, differentiable raycasting modules, and differentiable mapping/fusion blocks.
One can use these blocks to construct SLAM systems that allow gradients to flow all the way from the outputs of the
system (map, trajectory) to the inputs (raw color/depth images, parameters, calibration, etc.).
Package: grad-tts
Grad-TTSA fork of theofficial implementationof the Grad-TTS model based on Diffusion Probabilistic Modelling. This fork cleans up the code to focus on easy installation and inference.InstallationInferenceSeegrad_tts_cli.pyfor how to use the model for inference.pythongrad_tts_cli.py\--file/PATH/TO/TEXT_FILE\--checkpoint/PATH/TO/GRAD_TTS_CHECKPOINT\--hifigan_checkpoint/PATH/TO/HIFIGAN_CHECKPOINT\--outdir/PATH/TO/OUTPUT_DIRYou can downloadGrad-TTSandHiFi-GANcheckpoints trained on LJSpeech.ReferencesHiFi-GAN model is used as vocoder, official github repository:link.Monotonic Alignment Search algorithm is used for unsupervised duration modelling, official github repository:link.Phonemization utilizes CMUdict, official github repository:link.
Package: gradual
This package provides the runtime type-checking semantics of Gradual
Typing for Python. Get a short introduction togradual typing here.InstallingThis package only works on Python 3. To installgradualon your
system, you must first get the Python 3 version ofpip-3.2:sudo apt-get install python3-pipNow, you can easily install the gradual package via:pip install gradualIf you wish to install it to your base system, then the above command
would require root. If you already havegradualand wish to
upgrade the existing package then you can use the--upgradeflag:pip install --upgrade gradualUsageOnce you have installed the package, fire up the Python 3 interpreter
and just do:from gradual import *

@typed
def calculate_total(a:int, b:int) -> int:
    return a + b//100
Package: graf
# GrafGraf was built as a daily graph drawing program.There is a powerfull graph drawing tool called [matplotlib][] but that is toopowerfull and complecated to use as a daily tool.The purpose of the Graf is to make it easier and simpler for daily graph drawingpowerd by wrapping matplotlib and giving some useful methods for loading oranalysing data.# ExamplePrepare example data in `raw` directory as `data.00.txt`, `data.01.txt`, ...etc.Save the following code as `example01.graf` and run `graf example01.graf````python# Load column 0 and 1 of data.00.txt, data.01.txt, ... in raw directorydataset = load('raw/data.??.txt', using=(0, 1))# Plot all datafor x, y in dataset:plot(x, y)# Showshow()```
Package: grafana_alerts
grafana-alerts Collects stats from a grafana server based on information available
from the Grafana Dashboards. Then compare those values to an alert table and
throws alert emails if the case is needed.SitesInstallation package:https://pypi.python.org/pypi/grafana_alertsProject Home:https://github.com/pabloa/grafana-alertsIssues and bugs:https://github.com/pabloa/grafana-alerts/issuesInstallationsudo pip install grafana-alertsif you get an error, perhaps it is because the version available is a development
version. In this case try with:sudo pip install --pre grafana-alertsConfigurationCreate a file /etc/grafana_alerts/grafana_alerts.cfg
with:#
# Grafana alerts configuration file.
#

# The URL where grafana server is listening. It must finish with the character '/' (default value: http://localhost:3130)
grafana_url = http://yourgrafanaserver.com/grafana/

# Grafana token with viewer access (default value: empty string)
grafana_token = qwertysDssdsfsfsdfSFsfsfEWrwrwERwrewrwrWeRwRwerWRwERwerWRwerweRwrEWrWErwerWeRwRwrewerr==

# email to use as alert sender (default value: grafana-alert@localhost)
email_from = alert@example.com

# smtp server to use (default value: localhost)
smtp_server = localhost

# smtp server host to use (default value: 25)
# if port is not 25, starts a tls session.
smtp_port = 25

# smtp server username to use if it is needed. Optional. Leave it commented if not used. (default value: no username)
#smtp_username = my_smtp_username

# smtp server password to use if it is needed. Optional. Leave it commented if not used. (default value: no password)
#smtp_password = my_smtp_passwordAdd a cron task to execute grafana_alerts for example each 3 minutes::*/3 * * * *     grafana_alertsMonitoring DashboardsDashboards to be monitored for alerts must be marked with the tag “monitored”In each monitored Dashboard, add a text panel with title ‘alerts’ and a description of your alerts. For example::50<=x<=100; normal; server@example.com

35<x<50; warning; server-mantainers@example.com

x<=35; critical; server-mantainers@example.com, sysop@example.comNotes:values depend of the graph in that dashboard.x is mandatory.Here is an example:https://drive.google.com/a/ailive.net/file/d/0B1LiPvzYYFN0TTlBRnFlTG5Ya1E/view?pli=1ChangesVersion 1.0.0.dev7:[FIXED]https://github.com/pabloa/grafana-alerts/issues/7KeyError: ‘hide’Version 1.0.0.dev6:[FIXED]https://github.com/pabloa/grafana-alerts/issues/4Runtime error when a grafana metric has not values.[MINOR] renamed variables. Minor changes in emails.
Package: grafana-api
grafana_apiWhat is this library for?Yet another Grafana API library for Python. Support Python 3 only.RequirementsYou need Python 3 and only therequestslibrary installed.Quick startInstall the pip package:pip install -U grafana_apiAnd then connect to your Grafana API endpoint:fromgrafana_api.grafana_faceimportGrafanaFacegrafana_api=GrafanaFace(auth='abcde....',host='api.my-grafana-host.com')# Search dashboards based on taggrafana_api.search.search_dashboards(tag='applications')# Find a user by emailuser=grafana_api.users.find_user('test@test.com')# Add user to team 2grafana_api.teams.add_team_member(2,user["id"])# Create or update a dashboardgrafana_api.dashboard.update_dashboard(dashboard={'dashboard':{...},'folderId':0,'overwrite':True})# Delete a dashboard by UIDgrafana_api.dashboard.delete_dashboard(dashboard_uid='abcdefgh')AuthenticationThere are two ways to autheticate to grafana api. Either use api token or basic auth.To use admin API you need to use basic authas stated here# Use basic authentication:grafana_api=GrafanaFace(auth=("username","password"),host='api.my-grafana-host.com')# Use tokengrafana_api=GrafanaFace(auth='abcdetoken...',host='api.my-grafana-host.com')Status of REST API realizationWork on API implementation still in progress.APIStatusAdmin+Alerting-Alerting Notification Channels+Annotations+Authentication+-Dashboard+Dashboard Versions-Dashboard Permissions+Data Source+Folder+Folder Permissions+Folder/Dashboard Search+-Organisation+Other+Preferences+Snapshot+Teams+User+Issue trackerPlease report any bugs and enhancement ideas using thegrafana_apiissue tracker:https://github.com/m0nhawk/grafana_api/issuesFeel free to also ask questions on the tracker.Licensegrafana_apiis licensed under the terms of the MIT License (see the fileLICENSE).
Package: grafana-calendar-annotator
Grafana Calendar AnnotatorGenerateannotationsin Grafana from events pulled from an ICS calendar.HacktoberfestThis project welcomesHacktoberfestcontributions! Any contributions to increase theOpenSSF Best Practicespercentage or thatclose an issuewill be given priority.Getting StartedCLI$grafana-calendar-annotator--helpUsage:grafana-calendar-annotator[OPTIONS]╭─Options─────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│*--grafana-url-gTEXTUrloftheGrafanainstancetopopulateannotationsinto│
│[required]│
│*--grafana-api-key-kTEXTAPIkeytoauthenticatetotheGrafanainstance[required]│
│*--calendar-url-cTEXTURLoftheICSCalendartousetopopulateeventsfrom│
│[required]│
│*--flatten/--no-flatten-f/-nfFlatteningeventswillcreateasingletimeannotation│
│insteadofaspan│
│[default:no-flatten]│
│[required]│
│*--flatten-direction-fd[start|end]Createtheannotationatthestartortheendoftheevent│
│iftheeventisflattened│
│[default:(start)]│
│[required]│
│*--tags-tTEXTListoftagstoaddtocreatedannotations│
│[default:(generated,)]│
│[required]│
│*--regenerate/--no-regenerate-r/-nrRegeneratingwilldeleteallannotationsthathavethesame│
│setoftagsbeforecreatingnewannotations│
│[default:regenerate]│
│[required]│
│--delete-only-dOnlydeleteannotationswithtags,donotcreatenew│
│annotations│
│--helpShowthismessageandexit.│
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯The following flags can be set with environment variables:FlagVariable Name--grafana-urlGRAFANA_URL--grafana-api-keyGRAFANA_TOKEN--flattenFLATTEN--flatten-directionFLATTEN_DIRECTIONgrafana-calendar-annotator--grafana-urlhttps://my-grafana.com--grafana-api-keyabcd1234--flatten--flatten-directionend--calendar-urlhttps://my-calendar.com/personal.ics# is the same as thisGRAFANA_URL=https://my-grafana.comGRAFANA_TOKEN=abcd1234FLATTEN=trueFLATTEN_DIRECTION=endgrafana-calendar-annotator--calendar-urlhttps://my-calendar.com/personal.icsInstallingPipFor the library and the clipipinstallgrafana_calendar_annotatorPipxPipx is useful forinstalling and running applications in isolated environments. I've always found it useful to ensure python applications are can be executed from anywhere in your system.pipxinstallgrafana_calendar_annotatorRunning the testsDeploymentBuilt WithContributor Covenant- Used for the Code of ConductPoetry- Used for build and packagingContributing.md GeneratorBillie Thompson's README TemplateContributingPlease readCONTRIBUTING.mdfor details on our code
of conduct, and the process for submitting pull requests to us.VersioningWe useSemantic Versioningfor versioning. For the versions
available, see thetags on this
repository.ContributorsContributorswho participated in this project.LicenseThis project is licensed under theMIT.
Package: grafanacli
grafanacliWhat the heck is that?GrafanaCLI is a Python library used to manage Grafana APIRequirementsPython :: 2
Python :: 3InstallationInstall the pip package:pip install grafanacliUsagefromgrafanacliimportGrafanaAdminga=GrafanaAdmin('http://127.0.0.1:3000')# Disable SSL verificationga.verify=False"""SSL verification must be disabled before use GrafanaAuth"""# Authentication using username and passwordga.GrafanaAuth(Username='admin',Password='admin')# Authentication using API-Keyga.GrafanaAuth(AuthType='APIKey',Key='xxxxxxxxxxxxx')# List your current organizationga.CurrentOrganization()# List all organizationsga.OrganizationList()# Search Organizationga.OrganizationSearch('MyOrganization')# Create Organizationga.OrganizationCreate('MyNewOrganization')# Update Organizationga.OrganizationUpdate('1','NewOrganizationName')Where"1"istheorganizationIdthatwillbeupdated.# Delete Organizationga.OrganizationDelete('1')Where"1"istheorganizationIdthatwillbedeleted.# Switch Organizationga.OrganizationSwitch('2')Where"2"istheorganizationIdwhatIwanttoswitch# Search dashboard whitout filterga.DashboardSearch()# Search dashboard by titlega.DashboardSearch(DashboardName='My Dashboard')# Search dashboard by tagga.DashboardSearch(Tag='My Tag')# Search starred dashboardsga.DashboardSearch(Starred=True)# Search dashboard aplying more than one condititionga.DashboardSearch(Starred=True,Tag='My Tag')ga.DashboardSearch(Name='My Dashboard',Tag='My Tag')ga.DashboardSearch(Name='My Dashboard',Tag='My Tag',Starred=True)# Download Dashboardga.DashboardDownload('DashboardUid','/tmp/mydash.json')# Upload Dashboardga.DashboardUpload('/tmp/mydash.json',Overwrite=True)ga.DashboardUpload('/tmp/mydash.json')ga.DashboardUpload('/tmp/mydash.json, FolderId=3'# Create, List, Get, Update and Delete Foldersga.FolderCreate('My Folder')ga.FolderList()ga.FolderGet('folderUID')ga.FolderUpdate('folderUID','My Folder New Name',version=x)# Current Folder's version ID (int)ga.FolderUpdate('folderUID','My Folder New Name',overwrite=True)# It will skip version confirmationga.FolderDelete('folderUID')# Star and Unstar a dashboardga.DashboardStar(dashboadID)ga.DashboardUnstar(dashboadID)# Get and Update Dashboard's permissionga.DashboardGetPermissions(dashboadID)ga.DashboardUpdatePermissions(dashboadID,new_json_permission)LicenseGrafanaCLI is licensed under the terms of the MIT License (see theLICENSEfile).
Package: grafana-color-constants
Grafana Color ConstantsUse this package to easily get Grafana HEX color values in your code:It also provides an easy way to iterate over these colors allowing for fast and flexible looping
without hard-coding the colors in your code.Install :pipinstallgrafana-color-constantsExample:fromgrafana_color_constantsimportGrafanaColorGrafanaColor.RED>>>'#E02F44'GrafanaColor.RED.normal>>>'#E02F44'GrafanaColor.RED.lighter>>>'#FF7383'GrafanaColor.PURPLE.darker>>>'#7C2EA3'You can use it as an iterator with thGrafanaColor.iteratorproperty:fromgrafana_color_constantsimportGrafanaColorfrommatplotlibimportpyplotaspltcolor=GrafanaColor.iteratorforiinrange(60):plt.bar([i+1],[1.05**i],color=next(color))plt.show()This will output a graph like so:There are 6 colors: [RED,ORANGE,YELLOW,GREEN,BLUE,PURPLE],
each with 5 shades [darker,dark,normal,light,lighter] for a total of 30 colors.Hope it's useful to you!#TODOs for next iterations:rgb and rgba conversionsdifferent iteration orderscustom color sets
Package: grafana-dashboard-builder
grafana-dashboard-builder is an open-source tool for easier creation of Grafana dashboards.
It is written in Python and uses YAML descriptors for dashboard
templates.This project has been inspired by Jenkins Job Builder that
allows users to describe Jenkins jobs with human-readable format. grafana-dashboard-builder
aims to provide similar simplicity to Grafana dashboard creation and to give users easy way how they can create
dashboard templates filled with different configuration.
Package: grafana-dashboards-builder
Grafana Dashboards BuilderA wrapper aroundgrafanalibwhich simplifies generating multiple dashboards.Why?Grafanalib is a fantastic tool which lets you generate Grafana dashboards from simple Python scripts. Unfortunately, it can only read single files as dashboard sources and doesn't have a concept of multiple output directories. Those limitations make it hard to provision an entire Grafana instance with many folders and multiple dashboard sources.Grafana Dashboard Builder recursively finds all.dashboard.pyfiles in a directory tree. It generates dashboards and places them in a subdirectories which representGrafana folders.It's written with Kubernetes in mind so it can also generate nested output directory structure even when loading sources mounted from a flat ConfigMap (seeexamplesbelow).Installationpip install grafana-dashboards-builderUsagegrafana-dashboards-builder [OPTIONS] INPUT_DIR [OUTPUT_DIR]

INPUT_DIR is the directory tree with dashboard sources.

OUTPUT_DIR is the directory where generated dashboards are placed (defaults to ./out).

Options:
--from-configmap  generate output directories based on a source files prefix and a '--' separator
--help            Show this message and exit.ExamplesSources in nested directoriesGrafana supports only one level of depth forfolders. So even when dashboard sources are nested in multiple subdirectories the output dashboards will have only one parent directory (the most shallow one). Source dashboards that don't have any parent directory will be placed in the defaultGeneralfolder.For example, given a following input directory tree:dashboards_in/
    main.dashboard.py
    kubernetes/
        workloads/
            pods.dashboard.py
            jobs.dashboard.py
        nodes/
            nodes.dashboard.py
    nginx/
        nginx_health.dashboard.pyA following output directory will be generated:dashboards_out/
    General/
        main.json
    Kubernetes/
        pods.json
        jobs.json
        nodes.json
    Nginx/
        nginx_health.jsonSources in a ConfigMapWhen running Grafana in Kubernetes cluster it's possible to run Grafana Dashboard Builder as a sidecar which loads dashboard sources from a ConfigMap and generates them into Grafana's/var/lib/grafana/dashboardsdirectory.ConfigMaps don't support nested directory structures so to enable mapping dashboards to different folders we can prefix the sources filenames with afolder--prefix. When Grafana Dashboard Builder runs with--from-configmapflag, it parses the filenames and generates output directories based on found prefixes. Filenames without a prefix will be placed in the defaultGeneralfolder.For example, given a following input directory:dashboards_in/
    main.dashboard.py
    kubernetes--pods.dashboard.py
    kubernetes--jobs.dashboard.py
    nginx--nginx_health.dashboard.pyA following output directory will be generated:dashboards_out/
    General/
        main.json
    Kubernetes/
        pods.json
        jobs.json
    Nginx/
        nginx_health.json
Package: grafana-dashboard-templater
Grafana dashboard templaterDescriptionThe Grafana dashboard templater create a valid Grafana dashboard as dictionary based on a template and injected values. You can find sample dashboardshere, but note that you will need to adjust the appropriate settings for your own data sources.Dashboard template folder structuredashboard-templates <- Folder of the dashboard templates
     database <- Dashboard type
        postgresql <- Dashboard name
            v13 <- Dashboard version
                dashboard.json.sample <- Dashboard templateInstallationpip install grafana-dashboard-templaterExamplefromgrafana_dashboard.modelimportModelfromgrafana_dashboard.dashboardimportDashboarddashboard_model:Model=Model(dashboard_templates_path="./dashboard-templates",dashboard_type="database",dashboard_name="postgresql",dashboard_version="v13")dashboard:Dashboard=Dashboard(dashboard_model)dashboard_json=dashboard.get_dashboard_json(template_values={"app_name":"PostgreSQL","prometheus_name":"k8s-sonarqube-postgresql"})ContributionIf you would like to contribute something, have an improvement request, or want to make a change inside the code, please open a pull request.SupportIf you need support, or you encounter a bug, please don't hesitate to open an issue.DonationsIf you would like to support my work, I ask you to take an unusual action inside the open source community. Donate the money to a non-profit organization like Doctors Without Borders or the Children's Cancer Aid. I will continue to build tools because I like it and it is my passion to develop and share applications.LicenseThis product is available under the Apache 2.0 license.
Package: grafana-inviter
grafana-inviterInviting people to join a Grafana organization is usually done from the Grafana UI. For smaller groups this might be easy but for a larger set of people one
rather would like to not fiddle around in the UI and instead do it in an automated fashion.This tool is intended to send invites to join a new Grafana organization to people obtained from LDAP.Installation$pythonsetup.pyinstallor$pipinstallgrafana-inviterUsageCopy theexample_config.jsonconfiguration and adjust it to your needsGenerate a Grafana API token with admin privileges (https://<YOUR_GRAFANA_URL>/org/apikeys)Ensure you have a LDAP service account user for searches created$grafana-inviter--grafana-token"<YOUR_GF_TOKEN_WITH>"--ldap-user<YOUR_SVC_ACCOUNT_USER>--configconfig.json--ask-ldap-password
LDAPpassword:
SendinginvitetoJohnDoe(JohnDoe@acme.org){'name':'John Doe','loginOrEmail':'John.Doe@acme.org','role':'Viewer','sendEmail':False,'orgId':10}>UserJohn.Doe@acme.orgisalreadyaddedtoorganization
SendinginvitetoJaneDoe(Jane.Doe@acme.org){'name':'Jane Doe','loginOrEmail':'Jane.Doe@acme.org','role':'Viewer','sendEmail':False,'orgId':10}>CreatedinviteforJane.Doe@acme.org

AvailableinviteURLs:['https://<YOUR_GRAFANA_URL>/invite/Vv4Q8SYVyk7ULGpeWvjMXl0iuWLl67']