Saravanan666/pypi-org huggingface dataset:
Package: gKey
gKeyPython library used to encrypt and decrypt strings in the simplest possible way, while also being incredibly secure.RequirementsPython3 or later.Several Python packages:pycryptodome, to help encrypt and decrypt messages.InstallationInstall some Python utilities along with some libraries and other stuff:pip install pycryptodome gkeyBasic usageEncrypting a message:>>> import gkey
>>> myEncryptedMessage = gkey.encrypt("I like trains", "password123")
>>> print(myEncryptedMessage)
M+Wykmlub0z7FhEdmA==*PvAbXRNx0SiSDHHxLsKZ5w==*ihQM/fdkgrX3G+yOItyAUQ==*QFNDmuUP1ysgo01/P2MNpg==The first parameter is the string you want to encrypt. The second parameter is the password, which will be used for decrypting the string.Decrypting a message">>> import gkey
>>> myDecryptedMessage = gkey.decrypt("M+Wykmlub0z7FhEdmA==*PvAbXRNx0SiSDHHxLsKZ5w==*ihQM/fdkgrX3G+yOItyAUQ==*QFNDmuUP1ysgo01/P2MNpg==", "password123")
>>> print(myDecryptedMessage)
I like trainsThe first parameter is the encrypted string and the second parameter is the password. If the password is incorrect, decrypt function will returnFalse.ExampleHere, we will be creating a simple "trial product key". This is useful if you have software that you would like people to use temporarily.
In this example, we will be letting the user use the product for 2 hours. The password we will be using isgKey is amazing.Code on the server side:import gkey
import time
hours = 2
messageToEncrypt = str(time.time() + hours * 60 * 60)
## Hours * 60 * 60 is necessary because we need to turn the hours into seconds, since the timestamp is in seconds.
gkey.encrypt(messageToEncrypt, "gKey is amazing")Code on the client side:import gkey
import time
import sys
#Function to verify that the key is valid:
def check_valid(key):
    message = gkey.decrypt(key, 'gkey is amazing')
    if message == False:
        #The key is incorrect!
        return False
    if float(message) >= time.time():
        return True
    else:
        #The key has expired!
        return False
userKeyInput = input("Please enter your product key.")
keyChecked = check_valid(userKeyInput)
if keyChecked == True:
    print("You are good to go!")
if keyChecked == False:
    print("You have either entered an invalid key or your time has expired. Sorry!")
    sys.exit()
Package: gkit
GkitGkit is a suite of utilities for processing geo-dataset allowing you to
manipulate raster datasets likenp.MaskedArray.Gkit supports Python3 and all OS which could install numpy, matplotlib,
gdal.In Python2, may have unpredictable bugs.Documents:https://titorx.github.io/gkit/html/Simple ExampleHere is examples of some basic features that Gkit provides.importnumpyasnpimportgkitasgk# Read the first band from .tifr=gk.read("lst.tif")# You could also specific point out which band you want to loadr=gk.read("lst.tif",2)# gk.read returns a Raster classtype(r)# Output:# gkit.core.Raster# Open an interactive window display raster using matplotlib(call plt.show)r.show()The screenshot:# Only draw raster without calling plt.show.importmatplotlib.pylabaspltr.plot()plt.xlabel("Lon")plt.ylabel("Lat")plt.title("LST(K)")plt.colorbar()plt.savefig("raster_plot.png")The screenshot:# Raster class inherits from np.ma.MaskedArray.# It has all features which MaskedArray has.r# Output:# masked_array(data =#  [[-- -- -- ..., -- -- --]#  [-- -- -- ..., -- -- --]#  [-- -- -- ..., -- -- --]#  ...,#  [242.5966339111328 242.6825408935547 242.79612731933594 ...,#   243.512451171875 243.46498107910156 243.45751953125]#  [241.1952667236328 241.18592834472656 241.19235229492188 ...,#   241.02757263183594 241.04196166992188 241.0919189453125]#  [241.97023010253906 242.03948974609375 242.05393981933594 ...,#   241.8543243408203 241.85800170898438 241.80813598632812]],#              mask =#  [[ True  True  True ...,  True  True  True]#  [ True  True  True ...,  True  True  True]#  [ True  True  True ...,  True  True  True]#  ...,#  [False False False ..., False False False]#  [False False False ..., False False False]#  [False False False ..., False False False]],#        fill_value = 1e+20)# Doing operation like common numpy masked array.tmp=(r-273.15)**3/4tmp=np.cos(r)tmp=np.abs(r)tmp=np.sqrt(r)print(r.shape)print(r.mean())print(r.max())print(r.min())# convert data typetmp=r.astype(np.float64)# Save to filer.save("out_file.tif")# Create a raster from numpy arrayimportnumpyasnpx,y=np.mgrid[-1:1:100j,-2:2:200j]array=np.sqrt(x**2+y**2)print(array.shape)# Output:# (100, 200)transform=[-100,0.1,0,0,0,-0.1]raster=gk.Raster(array,transform)raster.show()The screenshot:
Package: gkligo
gkligoCode to download GW Alert skymaps from Kafka, and optionally write them
out and/or convert them to MOC files at specified contours.The code is based on code written by Roy Williams and Leo Singer.It requires the following python packages:gcn-kafkahealpygkutilsdocoptpyYAMLnumpyligo.skymap (via conda install)astropymocpyThe command line utilities are:downloadGWAlert (Download the alert from Kafka)The config_example.yaml file is an example config file. Copy it and rename to config.yaml.
Get your credentials by following the first part of theKafka Notices via GCNtutorial. Leave the topics configuration unchanged.The code has been daemonised so one of the parameters will be start|restart|stop.Also included is a script called generateGWReports. This will generate coverage reports (CSV files) from the three database (ATLAS, all sky Pan-STARRS, O4 follwup Pan-STARRS).TO DO:Modify generateGWReports to load the GW meta into the database for convenience.
Package: gklr
GKLRGeneralized Kernel Logistic RegressionExplore the docs »View Demo·Report Bug·Request FeatureDescriptionGeneralized Kernel Logistic Regression.(back to top)InstallationIt is possible to install thegklrpackage usingpippip install gklr(back to top)AuthorsGKLR was mainly developed by José Ángel Martín Baos from the University of
Castilla-La Mancha (JoseAngel.Martin@uclm.es). The main authors of this
package are listed in theAUTHORSfile.(back to top)Known IssuesThere are no known issues at this moment.(back to top)LicenseGKLR is distributed under the MIT License. SeeLICENSEfor more information.(back to top)
Package: gkms
gkmsgkmsis a simple utility for using GCP Cloud KMS to encrypt and decrypt secrets and storing them in GCS.InstallationpipinstallgkmsSetupPlease seehttps://googleapis.github.io/google-cloud-python/latest/core/auth.htmlfor authentication with Google Cloud SDK.UsageCLIgkmsencrypt\--projectmy-project\--locationglobal\--ringmy-key-ring\--keymy-crypto-key\--bucketmy-bucket\--targetmy-target.txt\--secretmy-secret.txt

gkmsdecrypt\--projectmy-project\--bucketmy-bucket\--targetmy-target.txt

gkmsreencrypt\--projectmy-project\--bucketmy-bucket\--targetmy-target.txtPythonimportgkmsgkms.encrypt(project='my-project',location='global',keyring='my-key-ring',cryptokey='my-crypto-key',bucket='my-bucket',target='my-secret.txt',secret_name='my-secret.txt',)decrypted=gkms.decrypt(project='my-project',bucket='my-bucket',target='my-secret.txt',)gkms.reencrypt(project='my-project',bucket='my-bucket',target='my-secret.txt',)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Getting StartedSet up your virual environment however you like.pipinstall-e.[dev]You're ready to start developing!Running TestspytestDisclaimergkmsmerely allows you to keep your secrets in GCS buckets allowing you to specify permissions via IAM roles.This doesnotreplace projects like HashiCorp Vault!Attackers who gain access to your service accounts will have access to the secrets.
Package: gkquiztool
This is the homepage of our GKQUIZ project..This project is build on the basis of educational purposes.This is a GK quiz mini project that test your knowldege via ‘OBJECTIVE MCQ’.In this project include 4 different GK MODULES namely:
-> SCIENCE QUIZ
-> HITORY QUIZ
-> SOCIAL SCIENCE AND
-> GENERAL AWARENESS..Through this project you enhance your knowledge skills and also test your IQ level.We have create ‘GRADE’ SYSTEM in this project, so you can check your GRADE according to your performance.We have also include ‘NEGATIVE MARKING’ CONCEPT in this.Note: You have to type exact option that mentioned in the option scheme e.g.,
Q.) which is the capital of India ?
a) Delhi
b) Chandigarh
c) Mumbai
d) KolkataType your answer here : <Delhi>  # You have to type exact option like typed in this exampleI hope you would like and enjoy it, Please appreciate of our work.Thanks and regards
Ash bhatia Teamfor more information and queries, please contact us below mention mails:
Emailid:ashbhatia2@gmail.com,ashbhatia20@gmail.com
Package: gkutils
gkutils PackageA collection of useful python methods (some of which should now be replaced by astropy usage), along with some command line utilities.The command line utilities are:coneSearchCassandra (a tool for cone searching inside spatially indexed Cassandra repositories - requires gkhtm and cassandra-driver and access to a Cassandra table with HTM levels 10, 13 and 16 columns.)bruteForceConeSearchATLAS (a purely trigonometric tool for searching ATLAS exposure lists to check if they overlap an object of interest)getCSVColumnSubset (pull out a subset of colums from a CSV).There are more potential command line utilities, which will be made available in future versions - e.g. coneSearchMySQL.
Package: gl-1106
Installationpip install gl-1106Get startedHow to use this package:from get_data import *
to using the Polygon_data.py which is including the main function and unit function

# change to your currency pairs for test Max code
currency_pairs = [["AUD","USD",[],portfolio("AUD","USD")],
                  ["GBP","EUR",[],portfolio("GBP","EUR")],
                   ["USD","CAD",[],portfolio("USD","CAD")]]

main(currency_pairs)
Package: glab
glabAn online genealogy program built on top of Jupyter and Gramps.This extension is composed of a Python package namedglabfor the server extension and a NPM package namedglabfor the frontend extension.RequirementsJupyterLab >= 2.0InstallNote: You will need NodeJS to install the extension.pipinstallglab
jupyterlabbuildTroubleshootIf you are seeing the frontend extension but it is not working, check
that the server extension is enabled:jupyterserverextensionlistIf the server extension is installed and enabled but you are not seeing
the frontend, check the frontend is installed:jupyterlabextensionlistIf it is installed, try:jupyterlabclean
jupyterlabbuildContributingInstallThejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Move to glab directory# Install server extensionpipinstall-e.--prefix=~/.local/# Register server extensionjupyterserverextensionenable--pyglab--user# Check to see if it is installed:jupyterserverextensionlist# Install dependenciesjlpm# Build Typescript sourcejlpmbuild# Link your development version of the extension with JupyterLabjupyterlabextensioninstall.# Check to see if it is installed:jupyterlabextensionlist# Rebuild Typescript source after making changesjlpmbuild# Rebuild JupyterLab after making any changesjupyterlabbuildYou can watch the source directory and run JupyterLab in watch mode to watch for changes in the extension's source and automatically rebuild the extension and application.# Watch the source directory in another terminal tabjlpmwatch# Run jupyterlab in watch mode in one terminal tabjupyterlab--watchNow every change will be built locally and bundled into JupyterLab. Be sure to refresh your browser page after saving file changes to reload the extension (note: you'll need to wait for webpack to finish, which can take 10s+ at times).Uninstallpipuninstallglab
jupyterlabextensionuninstallglab
Package: glabels
This library is a simple wrapper aroundglabels-3-batchandglabels-batch-qt- extremely convenient utilities for creating labels from pre-created templates:Glabels-3 -https://github.com/jimevins/glabelsGlabels-qt -https://github.com/jimevins/glabels-qtInstallationpipinstallglabelsUsageglabels-batch-qtfromglabelsimportGLabelsBatchQTg=GLabelsBatchQT("/path/to/glabels-batch-qt")# If you call the function without the output parameter,# the output will be given in bytes as the result of executionout=g.run(template='path/to/template',copies=3,)print(out)# b'%PDF-1.4\n%\xc3\xa2\xc3\.........'# If you specify the path to the output fileout=g.run(template='path/to/template',output="path/to/output",copies=3,)print(out)# None# Instead of specifying the path to the template,# you can give it in bytesout=g.run(template=b'...',copies=3,)print(out)# b'%PDF-1.4\n%\xc3\xa2\xc3\.........'Sinceglabals-bath-qtitself does not issue errors instdout,subprocess.Popencannot catch errors. (At least, I do not know how)glabels-3-batchfromglabelsimportGlabels3Batchg=Glabels3Batch("/path/to/glabels-3-batch")# If you call the function without the output parameter,# the output will be given in bytes as the result of execution# Here you need to understand that there will be not only PDF in stdoutout=g.run(template='path/to/template',copies=3,)print(out)# b'LABEL FILE = /path/to/template\n%PDF-1.4\n%\xc3\xa2\xc3\.........'# If you specify the path to the output fileout=g.run(template='path/to/template',output="path/to/output",copies=3,)print(out)# None# Instead of specifying the path to the template, you can give it in bytesout=g.run(template=b'...',copies=3,)print(out)# b'LABEL FILE = /path/to/template\n%PDF-1.4\n%\xc3\xa2\xc3\.........'
Package: glabvars
GlabvarsA Python wrapper for retrieving Gitlab Ci/CD variables to enable injecting them into locally running GitLab CI/CD pipelines run withgitlab-ci-local.Features:Retrieveproject-level CI/CD variablesRetrieve (inherited)group-level CI/CD variablesSupport forenvironment-scoped CI/CD variablesSupport variable-type (normal) andfile-type CI/CD variablesExport togitlab-ci-localYAML configuration fileUsageRun theglabvarsCLI app inside a git repository with a Gitlab remote.
The application can return a YAML configuration string forgitlab-ci-localtostdout.
You can pipe this output to.gitlab-ci-local-variables.ymlso thatgitlab-ci-localcan use the variables.glabvars--targetgcl>.gitlab-ci-local-variables.ymlOutput targetsGitlab-CI-Local:gclWhen passing--target gcl,glabvarswill output tostdouta YAML configuration file that can be used bygitlab-ci-local.Environment:envWhen passing--target env,glabvarswill output.envfiles and file-type variable files.
These files are postfixed with.<environment_scope>if theenvironment_scopeof a CI/CD variable is not'*'. These files are written in the--env-pathdirectory (default:.gitlab)InstallationInstall withpipto install globally:pipinstallglabvarsOr alternatively withpipxto isolate dependencies ofglabvarsfrom other globally installed Python apps (requirespipx):pipxinstallglabvarsRequirementsYou must haveglabinstalled and be authenticated with the relevant Gitlab instance to retrieve the CI/CD variables.
Check whether you are authenticated by callingglab auth status.Future workMake it extensible to other targets.
Package: glacierestore
The tool for restore objects from AWS Glacier to AWS S3There is no way to restre objects under one folder to AWS S3, this tool can help you do thisprerequisitetake a look [here] to configure aws cli and ak, sk(https://docs.aws.amazon.com/zh_cn/cli/latest/userguide/cli-configure-quickstart.html#cli-configure-quickstart-config)installpip install galcierestorehow to use itgalcierestoreplease fellow the prompt to fill the required arguments
Package: glacier-lengths
glacier_lengths — Statistical glacier length calculationsOften when glacier lengths are calculated, only the glacier centerline is considered.
This is arguably not a statistically representative measure for the entire front, as it just considers one point on the glacier outline.
Theglacier_lengthspackage aims to simplify length calculations along an arbitrary amount of lines buffered around the glacier centerline.Installationpip install glacier_lengthspip install git+https://github.com/erikmannerfelt/glacier_lengths.gitDocumentationSee the documentation athttps://glacier-lengths.readthedocs.ioExampleCalculate the length change of Rhonegletscher:importgeopandasasgpdimportglacier_lengths# Read the example dataoutlines=gpd.read_file("examples/rhone/data/outlines.shp").sort_values("year")old_outline=outlines.iloc[0]new_outline=outlines.iloc[1]centerline=gpd.read_file("examples/rhone/data/centerline.shp").iloc[0]# Generate ~40 buffered lines around the glacier centerlineold_buffered_lines=glacier_lengths.buffer_centerline(centerline.geometry,old_outline.geometry)# Cut the newly generated lines to the new_outlinenew_buffered_lines=glacier_lengths.cut_centerlines(old_buffered_lines,new_outline.geometry)# Measure the lengths of the old and new glacier centerlines.old_lengths=glacier_lengths.measure_lengths(old_buffered_lines)new_lengths=glacier_lengths.measure_lengths(new_buffered_lines)# Print the results.print(f"""{old_outline['year']}:{old_lengths.mean():.1f}±{old_lengths.std():.1f}m{new_outline['year']}:{new_lengths.mean():.1f}±{new_lengths.std():.1f}m""")prints:1928:10783.6±38.8m2020:9699.9±7.6mPlot a figurepythonexamples/rhone/plot_rhone.pyTestingRunpython -m pytestin the cloned repo base directory.
Package: glacier-rsync
AWS Glacier Rsync Like UtilityRsync like utility to back up files and folders to AWS Glacier. Utility can compress files and store on Glacier. Archive
ids will be stored in an sqlite database.You have to log in to aws with aws cli and create a glacier vault beforehand.Run params:$grsync--help
usage:grsyncversion0.3.5[-h][--loglevel{CRITICAL,FATAL,ERROR,WARN,WARNING,INFO,DEBUG,NOTSET}][--dbdb]--vaultvault--regionregion[--compressCOMPRESS][--part-sizePART_SIZE][--descdesc]src

Rsynclikeglacierbackuputil

positionalarguments:srcfileorfoldertogeneratearchivefrom

optionalarguments:-h,--helpshowthishelpmessageandexit--loglevel{CRITICAL,FATAL,ERROR,WARN,WARNING,INFO,DEBUG,NOTSET}loglevel(default:INFO)--dbdbdatabasefiletostoresyncinfo(default:glacier.db)--vaultvaultGlaciervaultname(default:None)--regionregionGlacierregionname(default:None)--compressCOMPRESSEnablecompression.Onlyzstdissupported(default:False)--part-sizePART_SIZEPartsizeforcompression(default:1048576)--descdescAdescriptionforthearchivethatwillbestoredinAmazonGlacier(default:None)If compression is enabled, file will be read and compressed on the fly and uploaded to glacier multipart.Sqlite database scheme:CREATE TABLE 
    sync_history
(id          integer primary key,
 path        text,		/* full path of the backed up file */
 file_size   integer,	/* size of the file */
 mtime       float,		/* modification time */
 archive_id  text, /* archive id generated by glacier */
 location    text, /* archive url generated by glacier */
 checksum    text, /* checksum of the archive generated by glacier*/
 compression text, /* compression algorithm used. NULL if none */
 timestamp   text /* backup timestamp */
);Do not lose your databaseCurrently, there is no way to rebuild it from aws inventory.Known IssuesGlacier supports 1024 bytes of description, and I'm currently putting a description in this format:grsync|abs_file_path|size|mtime|user_descWhich is not posix compatible since there is no limit to the filename or full path. I can put a metadata in front of
every archive but this means that the data can be recovered only with the same toolIf the absolute file path changes, grsync will treat it as a different file and re-uploadCurrently, there is no way to recover the local database, but you can download the inventory with aws cli and download
individual files with the help of description. I maybe create a tool to re-create the local db with inventory
retrieval, but the first issue has to be addressed before.
Package: glaciersat
Glaciersat is a modular, open-source package for glacier remote sensingGlaciersat provides tools to monitor important glacier variables like snow
distribution on the glaciers, broadband albedo and melt area from different
platform and sensors. It put a special focus on quantifying uncertainties in
both input and derived variables.
Links
—–
- HTML documentation:https://glaciersat.readthedocs.org- Source code:http://github.com/jlandmann/glaciersat
Package: glade-api-python
AboutTo Learn more, visithttps://developer.gladefinance.co/docsGetting StartedYou need a Merchant ID and Key to authenticate against the API, please contactsupport@gladefinance.coto setup a demo account.InstallationYou include the class in your project or you can add the repo in your files as in the example below:Set environmentfrom src.glade_functions import Glade

merchantId = "YOUR_MERCHANT_ID"
merchantKey = "YOUR_MERCHANT_KEY"For Production environmentapi = Glade(merchantId, merchantKey, True)For Sandbox environmentapi = Glade(merchantId, merchantKey, False)MethodsBVN Verificationapi.bvnValidation(bvnNumber);Get Chargeable Banksapi.supportedChargeableBanks();Get Bank Listapi.bankList();Verify Account Nameapi.verifyAccountName(accountNumber, bankCode, bankName);Get Personalized Account Infoapi.personalizedAccount( accountName, accountEmail, accountBvn, reference, channel = "providus");Create Customerapi.createCustomer(name, email, phoneNumber, address);Get All Customersapi.getCustomers();Get A Single Customer's Detailsapi.getCustomerDetail(customerId);Get All Bill Categoriesapi.getBillCategory(category = None);Get Bill IDapi.getBillById(billId);Resolve Billapi.resolveBill(payCode, reference);Purchase Billapi.purchaseBill(payCode, amount, reference, orderReference = None);Verify Bill Purchaseapi.verifyBillPurchase(transactionReference);Make A Single Transferapi.transfer(amount, receiverAccountNumber, receiverBankCode, senderName, reference, narration);Verify Single Transferapi.verifySingleTransfer(reference);Make Bulk Transferapi.bulkTransfer(transferObjects);Create Payment Linkapi.createPaymentLink(title, description, amount, type, payerBearsFees, acceptNumber, notificationEmail, customLink = None, redirectUrl = None, customMessage = None, frequency = None);Create Ticketapi.createTicket(title, description, amount, type, payerBearsFees, acceptNumber, notificationEmail, ticketData, customLink = None,  redirectUrl = None, customMessage = None, frequency = None);Create Invoiceapi.invoice(customerId, chargeUser, shipping, vat, dueDate, allowedDiscount, invoiceItems, note, discountType = None, invoiceId = None);Return ValuesAll methods return an array.
Package: gladier
Gladier provides a simple software interface to enable researchers to rapidly create, manage, and deploy complex automation flows. It has been used as a programmable data capture, storage, and analysis architecture at experimental facilities including the Argonne Leadership Computing Facility and the Advanced Photon Source. Gladier makes it easy to connect heterogeneous data and computing substrates deployed across distributed compute and storage
systems and manage using Globus Flows.Whether you’re working in materials science, X-ray science, automated laboratores, genomics, or any other research field,
Gladier can help you streamline your data management and analysis workflows, so you can focus on your scientific discoveries.
Try Gladier today and see how it can enhance your research capabilities!You can install Gladier and Gladier Tools with the following:pipinstallgladiergladier-toolsSee theRead-The-Docsgetting started.