Saravanan666/pypi-org huggingface dataset:
Package: gcreds
supported python versionsgcredsInspired bycredstash, I ended
up puttingGoogle Cloud
DatastoreandGoogle Cloud KMS (CLOUD KEY MANAGEMENT
SERVICE)together to makegcredsto manage credentials in google cloud.gcredsallows you store (put) and access (get) your credential in
google cloud, and help to reduce security hole like keeping secrets
being stored from your source code control.InstallationJust run:pip install gcredsGetting startedBefore you can use it, it will require a little setup work here:Greate a KMS key ring ongloballocation, named it likegcreds.gcloud kms keyrings create gcreds --location globalUnder that key ring, create a crypto key namedgcreds.gcloud kms keys create gcreds --location global --keyring gcreds --purpose encryptionYou can customizedlocation,key-ring,cryopto-key.Once you have it setup, let’s try to put some credential.Storing the password:$ gcreds put mysecret SxtlB5fBvvAKT7P4
project_id is not provided, will use default project: [your-default-gcloud-project] instead.Retriving the password:$ gcreds get mysecret
project_id is not provided, will use default project: [your-default-gcloud-project] instead.
SxtlB5fBvvAKT7P4You can also redirect a file to it.Let’s have a file contain a super strong password by hand.$ cat a_super_password.txt
Y#7U*ubwZh=D^XEq3a_MMyX3NVL_gfk9K4eq2HXAnd Let’s use the redirect to enter the password$ gcreds put mysecret < a_super_password.txt
project_id is not provided, will use default project: [your-default-gcloud-project] instead.Let’s retrive the password$ gcreds get mysecret
project_id is not provided, will use default project: [your-default-gcloud-project] instead.
Y#7U*ubwZh=D^XEq3a_MMyX3NVL_gfk9K4eq2HX
Package: gcrnet
GCRNet: Sparse-Input Neural Networks with Group Concave RegularizationProject Page|PaperGCRNet is a Python library that implements a novel framework for sparse-input neural networks using group concave regularization. Leveraging the power of concave penalties, specifically MCP and SCAD, GCRNet provides a comprehensive approach for simultaneous feature selection and non-linear function estimation. The proposed framework considers all outgoing connections from a single input neuron as a group and applies an appropriate concave penalty to the $l_2$ norm of weights within each group. By selectively shrinking the weights of certain groups to exact zeros, GCRNet constructs a neural network that utilizes only a small subset of variables, enhancing both the accuracy and interpretability of the feature selection process. GCRNet offers versatile functionality, supporting regression or classification tasks with continuous, binary, or time-to-event outcomes.InstallationInstallation with pipTo install withpip, run the following command:pip install --user gcrnetInstallation from GitHubYou can also clone the repository and install manually:git clone 
cd gcrnet/python
python setup.py install --userUsageOnce you install the library, you can importGCRNetto create a model instance:from gcrnet import GCRNet
lam=np.exp(np.linspace(np.log(0.01),np.log(0.5), 50))
gmcp_net = GCRNet(task_type='regression',device=torch.device("cpu"), input_dim=train_data['X'].shape[1], output_dim=1, hidden_dims=[10,5], activation="relu",
    optimizer="Adam",learning_rate=0.001, batch_size=train_data['X'].shape[0], 
    alpha=0.01, lam=lam, penalty="MCP",drop_input=True)

# fit model and tune parameters
param_grid={"alpha":[0.03]}
gmcp_net= gmcp_net.fit_and_validate(X=train_data['X'], y=train_data['y'], 
                              param_grid=param_grid, init_num_epochs=2000, num_epochs=200, verbose=True, print_interval=200)For more details, please see our Colab notebooks:Regression exampleClassification exampleCox exampleAcknowledgements and ReferencesSome of our codebase and its structure are inspired byhttps://github.com/runopti/stg.If you find our library useful in your research, please consider citing us:@misc{luo2023sparseinput,
title={Sparse-Input Neural Network using Group Concave Regularization},
author={Bin Luo and Susan Halabi},
year={2023},
eprint={2307.00344},
archivePrefix={arXiv},
primaryClass={stat.ML}
}
Package: gcrypter
gcrypterIs an encryption algorithm based on bytes and their correspondent numbers to encode strings.ToEncrypt:It gets the length of the text given and encode both (text and lenght) into bytes then convert
the bytes'values into numbers and return a tuple with two tokens (numbers);ToDecrypt:It gets the tuple and retrieve both the values and reconvert them into bytes according to hisbit-lengthand then decode the byte to the original string (text);InstallationWindows:pipinstallgcrypterUnix/MacOS:python3-mpipinstallgcrypteror:sudopip3installgcrypter© 2019-2021Nurul-GC™ArtesGC Inc.™ArtesGC-DevSoft
Package: gcsa
Google Calendar Simple APIorgcsais a library that simplifies event and calendar management in Google Calendars.
It is a Pythonic object oriented adapter for the official API. See the fulldocumentation.InstallationpipinstallgcsaSeeGetting started pagefor more details and installation options.Example usageList eventsfromgcsa.google_calendarimportGoogleCalendarcalendar=GoogleCalendar('your_email@gmail.com')foreventincalendar:print(event)Create eventfromgcsa.eventimportEventevent=Event('The Glass Menagerie',start=datetime(2020,7,10,19,0),location='Záhřebská 468/21',minutes_before_popup_reminder=15)calendar.add_event(event)Create recurring eventfromgcsa.recurrenceimportRecurrence,DAILYevent=Event('Breakfast',start=date(2020,7,16),recurrence=Recurrence.rule(freq=DAILY))calendar.add_event(event)Suggestion: usebeautiful_dateto createdateanddatetimeobjects in your
projects (because its beautiful… just like you).ReferencesTemplate forsetup.pywas taken fromkennethreitz/setup.py
Package: gcs-aio-mapper
Example:import zarr
from gcs_aio_mapper import GCSMapperAio
from gcsfs import GCSMap
import logging

logging.basicConfig(level=logging.DEBUG)
n = 25

def build_gs_async():
    store = GCSMapperAio("gs://bucket/tmp/test.zarr", cache_size=n)
    g = zarr.open_array(store, shape=(n,), chunks=(3,), mode="w")
    for i in range(n):
        g[i] = i
    store.flush()


def build_gs():
    store = GCSMap("gs://bucket/tmp/test.zarr")
    g = zarr.open_array(store, shape=(n,), chunks=(3,), mode="w")
    for i in range(n):
        g[i] = i
Package: gcsam
GCSAMGas chromatography sample analyzer and managerUse CaseTired of labeling GC output peaks by hand?gcsamwill automatically digest the output from your gas chromatograph and give you usable data so that you can spend more time analyzing what matters.
This program is written entirely in python for easy hacking and designed to specifically work with Microsoft Excel.Prerequisitespython >= 3.6.3python packages:xlrdxlsxwriterMicrosoft ExcelInstallationpip install gcsam(coming soon, I hope!)UsageGo take a look at theexample/folder, which should have all you need to get started.ConfigurationA “Config” sheet (xlsx file) must be created that contains the following information:Sample IDs matching the sheet titles with:Dry weight of the sample (in mg)Amount of standard added (in mg)Known FAMEsOne column for the string identifier, this can be anything that makes sense to you (e.g. “c17.0” or “17:0”Another column for the expected retention time of the FAME.NOTE: all retention times everywhere must be in descending order!Notice that the Volume column is not used, as all of the entries (in mL) are 1. If this is ever not the case, the code will need to be adjusted accordingly.Required ArgumentsPlease note that the order of the arguments supplied does not matter.The config, from above, is required (-c).At least one input and one output are required. It is possible to have multiple input and output types.Inputs can be:One or more GC outputs (-i), read in with a particular format (-if)Previously saved files can be loaded (-l)Outputs can be:Saved data (-s) for use with loading or further analysis.Output data, (-o) with a custom format (-of)Graph visualization folder (-g).Specifying a standard is not required but you will likely want to include it with--standard. The default standard, "C17:0", may change in a future release.ExamplesConverting raw GC output to a GCSAM filegcsam -i "gcOutput.xlsx" -if "Harper" -c "configFile.xlsx" -s "savedGCdata.xlsx" --standard "C17:0"Removing lines from previously saved filesgcsam -l "savedGCdata.xlsx" –-not-lines "1" "abc" "foxes45" -s "newSavedGCdata.xlsx"Orgcsam -l "savedGCdata.xlsx" --only-lines "1" "abc" "foxes45" -s "newSavedGCdata.xlsx"Analyzing select lines from multiple, previously-saved filesgcsam -l "savedGCdata1.xlsx" "savedGCdata2.xlsx" –-only-lines "that" "I" "want" -o "analysisThatIWant.xlsx"
Package: gcsannex
This is agit-annexexternal special remote that supports Google Cloud
Storage (GCS).FeaturesSupports Standard, Durable Reduced Availability, and Nearline storage
classes.Accesses Google Cloud Storage via a Google Cloud service account.  Does
not use the Google Cloud Storage Interoperability API.Should support object sizes up to 5 TB.LicenseGNU General Public License, version 3 or later.Installingpip install gcsannexConfiguring Google Cloud StorageLog into theGoogle Developers Console.Create a project if you don’t already have one.  Remember its
project ID.In the project’s settings, go toAPIs & auth>Credentials.Click “Create new Client ID”, select “Service account”, then click
“Create Client ID”.A credentials file will be downloaded to your computer.  You will need
this file when configuring gcsannex.Adding a remotegit annex initremote <remotename> type=external externaltype=gcs encryption={none|shared|pubkey|hybrid} project=<gcs-project-id>Set theGOOGLE_APPLICATION_CREDENTIALSenvironment variable to the
path to your credentials file.  This is only necessary when runninginitremote; afterward, git-annex will remember your credentials.Mandatory settingsencryptionSee thegit-annex encryption documentation.projectYour project ID from the Google developer console.Optional settingsbucketThe bucket name, which must be globally unique within GCS.  The default
name is based on the remote name and UUID.chunkEnablechunking.embedcredsSet toyesto commit the login credentials to the Git repository
so other clones can read them.  When using GPG encryption, the default isyesand the credentials are stored encrypted.  Otherwise, the default
isno; if set toyes, anyone with access to the repo can also
access the GCS bucket.fileprefixA string, such asmydata/, to be prepended to the name of each object.
This allows a bucket to be shared by multiple remotes.locationThe physical location for the data.  Can be any of thelocation stringssupported by GCS, such asASIA,EU, orUS.  Defaults toUS.publicIfyes, newly-uploaded objects are made publicly readable.  Defaults
tono.readonlyIf set totruewhen enabling an existingpublicremote, files
can be retrieved without GCS credentials and without gcsannex installed.
Requires development version of git-annex.storageclassAstorage classsupported by GCS, such asSTANDARD,DURABLE_REDUCED_AVAILABILITY, orNEARLINE.  Defaults toSTANDARD.Release notesVersion 0.2Time out stuck requestsRetry after more types of errorsPermit encrypted public remotesSupport showing public URLs ingit annex whereisImprove compatibility with git-annex < 5.20141219Properly accept implicitencryption=hybridVersion 0.1Initial release
Package: gcsa-slots
Google Calendar Simple API Slotsorgcsa-slotsis an extension forGoogle Calendar Simple APIlibrary with slots (dates and times available for scheduling).Installationpip install gcsa-slotsSeeGetting started pagefor more details and installation options.Example usageList slots from free ranges (dates and times without events, available for scheduling)fromgcsa_slots.google_calendarimportGoogleCalendarcalendar=GoogleCalendar("your_email@gmail.com")forslotincalendar.get_slots(60):# 60 minutesprint(slot)# 2023-03-06 09:00:00-03:00 - 2023-03-06 10:00:00-03:00# 2023-03-06 11:00:00-03:00 - 2023-03-06 12:00:00-03:00# 2023-03-06 14:00:00-03:00 - 2023-03-06 15:00:00-03:00# 2023-03-06 15:00:00-03:00 - 2023-03-06 16:00:00-03:00# 2023-03-07 09:00:00-03:00 - 2023-03-07 10:00:00-03:00# 2023-03-07 10:00:00-03:00 - 2023-03-07 11:00:00-03:00# 2023-03-07 11:00:00-03:00 - 2023-03-07 12:00:00-03:00# 2023-03-08 09:00:00-03:00 - 2023-03-08 10:00:00-03:00# 2023-03-08 10:00:00-03:00 - 2023-03-08 11:00:00-03:00# 2023-03-08 14:00:00-03:00 - 2023-03-08 15:00:00-03:00# 2023-03-08 15:00:00-03:00 - 2023-03-08 16:00:00-03:00# ...List slots from slot-event ranges (an event that determines availability for scheduling)fromgcsa_slots.google_calendarimportGoogleCalendarcalendar=GoogleCalendar("your_email@gmail.com")forslotincalendar.get_slots(60,slot_summary="Free"):# 60 minutesprint(slot)# 2023-03-06 09:00:00-03:00 - 2023-03-06 10:00:00-03:00# 2023-03-06 11:00:00-03:00 - 2023-03-06 12:00:00-03:00# 2023-03-06 14:00:00-03:00 - 2023-03-06 15:00:00-03:00# 2023-03-06 15:00:00-03:00 - 2023-03-06 16:00:00-03:00# 2023-03-07 09:00:00-03:00 - 2023-03-07 10:00:00-03:00# 2023-03-07 10:00:00-03:00 - 2023-03-07 11:00:00-03:00# 2023-03-07 11:00:00-03:00 - 2023-03-07 12:00:00-03:00# 2023-03-08 09:00:00-03:00 - 2023-03-08 10:00:00-03:00# 2023-03-08 10:00:00-03:00 - 2023-03-08 11:00:00-03:00# 2023-03-08 14:00:00-03:00 - 2023-03-08 15:00:00-03:00# 2023-03-08 15:00:00-03:00 - 2023-03-08 16:00:00-03:00# ...List slots specifying time range, slot interval, max events per slot and calendar IDfromgcsa_slots.google_calendarimportGoogleCalendarcalendar=GoogleCalendar("your_email@gmail.com")calendar_id="your calendar id"forslotincalendar.get_slots(45,slot_summary="fReE",case_sensitive=False,time_min=datetime(2023,3,6),time_max=datetime(2023,3,7),events_per_slot=3,calendar_id=calendar_id,):print(slot)Create event in first available slotfromgcsa_slots.google_calendarimportGoogleCalendarcalendar=GoogleCalendar("your_email@gmail.com")slots=calendar.get_slots(90,slot_summary="Free")slot=next(slots)slot.summary="This is a test!"calendar.add_event(slot)
Package: gcs-basic
gcs_basic_functionsGoogle storage basic functionsGetting Startedimportgcs_basicgcs_basic.download(bucket_name,blob_path,down_path,project)gcs_basic.upload(bucket_name,blob_path,local_path,project)gcs_basic.list_blobs(bucket_name,blob_path,project)PrerequisitesThis is an example of how to list things you need to use the software and how to install them.python python-pipsudoapt-getinstallpython3python-pip#orsudopacman-Spythonpython-pipGoogle cloud SDK for credentials - temporarilywget https://dl.google.com/dl/cloudsdk/channels/rapid/downloads/google-cloud-sdk-364.0.0-linux-x86_64.tar.gz
tar -xvf google-cloud-sdk-364.0.0-linux-x86_64.tar.gz
cd google-cloud-sdk-364.0.0-linux-x86_64
bash google-cloud-sdk/install.sh
#open new terminal
gcloud init
gcloud auth application-default loginInstallationClone the repogitclonehttps://github.com/antonio258/gcs_basic_functions.gitInstall packagecdgcs_basic_functions
pipinstall.RoadmapDownload one file from storageUpload one file to storageDownload folder from storageUpload folder to storageList blobsCheck credentials in library
Package: gcshelpers-SaschaJust
About gcshelpersThe gcshelpers library provides helper functions and utility classes for themozintermittent microservicesto interact with the Google Cloud.ContentsClass: ConfigConfigis a wrapper for JSON configuration files. AccessingCONFIGthe first time leads to a
lazy initialization of the configuration object. The name of the configuration file is derived from
the calling instance, i.e. the packagegcshelpersis called from. This means usinggcshelpers.config.CONFIGfromhgminerwill load thehgminer.confconfiguration file. The
library will first look for a file in the current directory, then the user's home directory, and
finally/etc.If no configuration file can be found, the library attempts to create one from an example file in
the calling project'sassetdirectory. Assuminghgmineris executed and no configuration file is
present,gcshelpersattempts to copyhgminer/assets/hgminer.conf.exampleto the user's home
directory.The JSON file is converted into an object and can be subscribed to via properties or dictionary
access. This means that the following config will yield the below valid accesses:{"contact":{"email":"sascha.just@own-hero.net"}}CONFIG['contact']['email']If the localassetsdirectory contains a grammar (ANTLR4), the configuration is checked against
this grammar during construction, i.e. when the config is initially read during the first access.Grammar exampleThe example below requires a configuration that consists of a contact entry having anameandemailset, while the structure of those is defined in the terminal section.doc{contact:{name:NAME,email:EMAIL}}@terminalsNAME:[A-Za-z].*;EMAIL:[a-zA-Z0-9_\-\.\+]+'@'[a-zA-Z0-9_\-\.]+'.'[a-zA-Z]{2,};Class: MozLoggerThis class wraps the standard logger with a default configuration. This also provides means to log
to Pub/Sub. It features eager initialization and can directly be used. If no log configuration is
present, one is created on the fly.LOGGER.debug('Persisting%s',taskid)Function:pkgloadThis function lets you load assets from the package. Make sure you specify any assets in theManifest.into make sure they are installed together with the package.QUERY_INSERT=pkgload(__package__,'assets/insert_job.sql')The storage moduleThe module contains methods to interact with Google Cloud Storage.The telemetry moduleThe module contains methods to interact with Google Pub/Sub.
Package: gcshus
gcshusGCS Helper Utils for PythonHow to useUpload a fileimport gcshus
from google.cloud import storage

gcshus.upload(
    storage.Client(), "my-bucket", "/path/to/src.txt", "dst.txt"
)Generate a signed url for downloadimport gcshus
from google.cloud import storage

url = gcshus.generate_download_signed_url_with_token_refresh(
    storage.Client(), "my-bucket", "dst.txt", 5
)Download a fileimport gcshus
from google.cloud import storage

gcshus.download(storage.Client(), bucket, "some/remote/blob.txt", "local-file.txt")Run testdocker compose up
Package: gcsim-pypi
gcsim Binary for PyPIThis document provides guidelines for releasing thegcsimbinary to PyPI.Release MethodsThere are three primary methods to release a new version of the gcsim binary to PyPI:Automated Weekly Releases: The release workflow is automatically executed every Sunday.Manual Workflow Trigger: You can manually initiate the release workflow as needed.Creating a Release: Opt to create a release through GitHub, which triggers the release process.Important ConsiderationsBefore manually and locally publishing a release, it's crucial to run thescripts.pyfile to ensure all necessary preparations are complete. Use the following command:python scripts.py
Package: gcs-lock-thing
Welcome to gcs_lock_thingBasic mutex lock implementation with Google Cloud Storage with ttl and exponential backoffFree software: MIT licenseDocumentation:https://connor-ps.github.io/gcs_lock_thingFeaturesBasic mutex lock in GCPCreditsThis package was created withCookiecutterand thegiswqs/pypackageproject template.InstallationStable releaseTo install gcs-lock-thing, run this command in your terminal:pip install gcs_lock_thingThis is the preferred method to install gcs-lock-thing, as it will always install the most recent stable release.If you don't havepipinstalled, thisPython installation guidecan guide you through the process.UsageTo use gcs-lock-thing in a project:importgcs_lock_thing.lockasgcspublic_bucket_path="data-trf-test-mutex-lock"client=gcs.Client(bucket=public_bucket_path,lock_file_path="test-lock.txt",ttl=2)# get lockstatus=client.lock()# free lockclient.free_lock()
Package: gcs-oauth2-boto-env-plugin
gcs-oauth2-boto-env-plugin is a Python application whose purpose is to behave as an auth plugin for the boto auth plugin framework for use with OAuth 2.0 credentials for the Google Cloud Platform. This plugin is only compatible with service accounts, and it’s functionality is essentially a wrapper aroundgcs-oauth2-boto-plugin, with the added capability of passing the private JSON key as an environment variable for easy deployment.UsageCall the following program with the content of the JSON private key set asGOOGLE_OAUTH2_JSON_PRIVATE_KEYenvironment variable:import boto
import gcs_oauth2_boto_env_plugin

project_id = 'your-project-id'

header_values = {"x-goog-project-id": project_id}
uri = boto.storage_uri('', 'gs')
for bucket in uri.get_all_buckets(headers=header_values):
    print bucket.nameLicenseAll source code is licensed under theMIT License.
Package: gcs-oauth2-boto-plugin
gcs-oauth2-boto-plugin is a Python application whose purpose is to behave as an
auth plugin for the boto auth plugin framework for use with OAuth 2.0
credentials for the Google Cloud Platform. This plugin is compatible with both
user accounts and service accounts, and its functionality is essentially a
wrapper around oauth2client with the addition of automatically caching tokens
for the machine in a thread- and process-safe fashion.
Package: gcs-oauth2-boto-plugin-grow
gcs-oauth2-boto-plugin is a Python application whose purpose is to behave as an
auth plugin for the boto auth plugin framework for use with OAuth 2.0
credentials for the Google Cloud Platform. This plugin is compatible with both
user accounts and service accounts, and its functionality is essentially a
wrapper around oauth2client with the addition of automatically caching tokens
for the machine in a thread- and process-safe fashion.
Package: gcspath
GCSPathIMPORTANT: this library is not ready for useGCSPath provides a convenient Pythonic File-System/Path like interface to Google Cloud Storage usinggoogle-cloud-storagepackage as a driver.It is based on theS3Pathproject, which provides a similar interface for S3 buckets.InstallFrom PyPI:$pipinstallgcspathRequirementsPython >= 3.6google-cloud-storage
Package: gcspip
Copyright (c) 2017, ETHRONSOFT
All rights reserved.Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS”
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.Description: UNKNOWN
Keywords: pypi private repository gcs google cloud storage
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