Saravanan666/pypi-org huggingface dataset:
Package: atlas-rfp
atlas-rfpRationaleMIT's reimbursement system is aging. Having a high-performance, statically-typed
interface to the RFP system enables higher-level financial scripts and programs
to be created.This script usestouchstone-auth, another one of my Python packages that is
a Python user-agent capable of properly two-factor authenticating your scripts,
without requiring a browser.InstallThis package is on Pip, so you can just:pip install atlas-rfpAlternatively, you can get built wheels from theReleases tab on Github.QuickstartTo perform Touchstone authentication, we need a client-side certificate.
Remember tonot hard-codeyour credentials!
The example here loads credentials from a json file calledcredentials.json:{
    "certfile": "some_client_credential.p12",
    "password": "horse-battery-staple-correct"
}Then, in your Python file, you can do the following:import json
from touchstone_auth import TouchstoneSession

with open('credentials.json') as cred_file:
    credentials = json.load(cred_file)

with TouchstoneSession(
    base_url='https://atlas.mit.edu',
    pkcs12_filename=credentials['certfile'],
    pkcs12_pass=credentials['password'],
    cookiejar_filename='cookies.pickle') as s:

    response = s.get('https://atlas.mit.edu/atlas/Main.action')For more examples on how to authenticate,
see thetouchstone-auth documentation.Complete ExamplesDeveloper installIf you'd like to hack locally onatlas-rfp, after cloning this repository:$ git clone https://github.com/meson800/atlas-rfp.git
$ cd gityou can create a local virtual environment, and installatlas-rfpin "development mode"$ python -m venv env
$ .\env\Scripts\activate    (on Windows)
$ source env/bin/activate   (on Mac/Linux)
$ pip install -e .After this 'local install', you can use and importatlas-rfpfreely without
having to re-install after each update.ChangelogSee theCHANGELOGfor detailed changes.## [0.1.8] - 2023-09-10
### Changed
- Added Pydantic field serializers for Money typeLicenseThis is licensed by the MIT license. Use freely!
Package: atlass3hook
Apache Atlas S3 hook in PythonThis python client uses a s3 client package s3fs to get the metadata of s3 entities such as Bucket, pseudo_dir and
object, then it inserts these metadata into Atlas instances.Quick startCreate a client to connect to an Atlas instancefromatlas_client.clientimportAtlas# login with your tokenhostname="https://atlas.lab.sspcloud.fr"port=443oidc_token="<your_token>"atlas_client=Atlas(hostname,port,oidc_token=oidc_token)# login with your username and passwordatlas_client=Atlas(hostname,port,username='',password='')Create a s3 metadata client to collect metadata of s3 entitiesfromatlas_s3_hook.S3MetadataClientimportS3MetadataClients3_end_point=''s3_access_key=''s3_secret_key=''s3_token=''s3_client=S3MetadataClient(s3_end_point,s3_access_key,s3_secret_key,s3_token)Load a single s3 entity into atlasIf you want to load the metadata of a single s3 entity, you can use the following code examplefromatlas_s3_hook.S3HookimportS3Hook# Indicate the path of the entity which you want topath=''description=''s3_hook=S3Hook(s3_client,atlas_client)# Get the class of the s3 entitypath_class=s3_client.get_class_from_path(path)print(path_class)# Get the metadata of the s3 entitymeta_data=s3_client.get_path_meta_data(path)# based on the class of the s3 entity, s3 hook provides different loaders. You need to choose the correct one# bucket loaders3_hook.create_atlas_bucket(meta_data,description)# directory loaders3_hook.create_atlas_ps_dir(meta_data,description)# object loaders3_hook.create_atlas_object(meta_data,description)Load multiple s3 entities into atlasIf you want to load the metadata of multiple s3 entities, you can use the following code example. The S3Scanner class
takes a path of s3 entity and load all the metadata of its contents (e.g. sub-directory, objects).fromatlas_s3_hook.S3ScannerimportS3Scanners3_entity_path=''entity_owner=''minio_scanner=S3Scanner(minio_client,atlas_client,owner=entity_owner)minio_scanner.scan_path(s3_entity_path)PrerequisitesThis tool only requires python 3.7 or aboveSupported OSWindows XP/7/8/10LinuxMacOSAuthorsPengfei LiuLicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for detailsAcknowledgementThis package was created by usings3fsproject
Package: atlassian-api-py
Python Wrapper for Atlassian REST APIWhat is this?This is a package wrapper of Atlassian REST API written in Python, currently, it supports JIRA and Bitbucket.This package was created to simplify the implementation of integration with JIRA and Bitbucket.QuickStartInstall from PyPI# install$pipinstallatlassian-api-py# upgrade to latest$pipinstallatlassian-api-py--upgradeEstablish connectionConnect with username and password>>>fromatlassianimportJira>>>jira=Jira(url='https://jira.company.com',username="username",password="password")Or connect with token>>>fromatlassianimportJira>>>jira=Jira(url='https://jira.company.com',token="yourToken")Or write your credentials in a configuration fileconfig.ini, and get the credential though the configuration file.[jira]
url = https://jira.company.com
username = username
password = password# Ortoken = yourToken>>>importconfigparser>>>config=configparser.ConfigParser()>>>config.read('config.ini')>>>jira_url=config['jira']['url']>>>jira_usr=config['jira']['username']>>>jira_psw=config['jira']['password']>>>jira_token=config['jira']['token']Get fieldsNext, you can get the issue's fields as follow:>>>issue=jira.issue('TEST-1')>>>print(issue.fields.status.name)Triage>>>print(issue.fields.description)thisisademojiraticket>>>print(issue.fields.status.name)Triage>>>print(issue.fields.issuetype.name)BugMore fields>>>print(issue.id)1684517>>>print(issue.key)TEST-1>>>print(issue.fields.assignee.key)xpshen>>>print(issue.fields.summary)JiraRESTAPIUnitTestExample>>>...Unittest and CoverageRun unittestcdtests
python-munittestRun coveragecdtests
coveragerun-munittest
coveragereport-m# to report on the resultscoveragehtml# to get annotated HTMLFAQQ1: Which Jira/BitBucket version I used to develop?For Jira I used Jira v8.5.9 and Jira Cloud.For BitBucket I used Bitbucket v5.13.1. not support Bitbucket cloud for now.
Package: atlassian-doc-builder
Atlassian Document BuilderCreating Atlassian Document in a programmatic way.DescriptionProvide an automatic way to generate documents and report on Atlassian Platform (e.g. Confluence, Jira).
Developer may automate report publication (e.g. functional verification report / requirement documents) into CI.Getting StartedDependenciesPython3.8+Installingpipinstallatlassian-doc-builderFeaturesTree-Like Document RepresentationJSON ADF Rendering and ParsingReusable Template with variable fillingDocument ValidationImplemented Node TypePlease refer tothis document.RoadmapCreate Base Class for ADF ObjectImplement Basic Features aboveDerive common classes for easy access (e.g. Text, Paragraph)Add short hands functions to create documentTable Editor and Table Row EditorMedia DisplayExamplesPlease refer tothe "examples" directory.Version History0.4Implement Table Objects with creation routineImplement set of Block Nodes with childrenIndex access to child nodes with[]. Multiple index supported. e.g.doc[1,2,3]0.3SupportADFText,ADFLinkand a bunch of one line classesADFObject Class Factory for quick Class Development0.2Add Test SuiteImprove ADFObject Implementations0.1Initial ReleaseContribution and ContactPull Requests and Discussion are welcome on GitHub.LicenseThis project is licensed under the MIT License - see the LICENSE file for detailsAcknowledgmentsThis Project is inspired by:pyadf project from Atlassian
Package: atlassianhw
atlassianhwA collection of simple functions to help with the homework.InstallpipinstallatlassianhwHow to useSimple way to load in the data usingAData():forname,datainAData().raw_data.items():print(f'Data source:{name}')display(data.head())/Users/jasonorawe/Documents/py_wd/git/atlassianhw/atlassianhw/utils.py:22: FutureWarning: Inferring datetime64[ns] from data containing strings is deprecated and will be removed in a future version. To retain the old behavior explicitly pass Series(data, dtype=datetime64[ns])
  'employee_details': pd.read_excel(pkgutil.get_data(__name__, '_data/Employee_details.xlsx')),

Data source: employee_details
Data source: glossary
Data source: manager_details
Data source: manager_mapping
Data source: promo_meta_data<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>emp_idAttritedkudos_received_so_farkudos_count_given_so_farjob_familytenure_in_days_newlevelmnths_in_teamlast_promotion_date0105.1570312Software Engineering1065Junior IC35.02022-10-011205.4664109Software Engineering1066Junior IC35.02022-04-012304.74412618Program Management1079Manager19.02021-07-163410.2619030Software Engineering154Director6.02020-03-304505.9185188Product Manager1079Manager35.02022-10-01<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>DatasetDataset infoColumn NameDescription0promo_meta_datahistorical promo metadatalevellevel of employee1promo_meta_datahistorical promo metadatamonths_for_promotionmonths for promotion in past2Manager_mappingManager mapping datasetmgr_idmanager ID3Manager_mappingManager mapping datasetemp_idemployee id4Attrition_Manager_infoManager meta datamgr_cum_churn_newtotal churns under manager<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>mgr_idmgr_cum_churn_newTenure_Mgrtotal_teams_mgrexp_as_mgr07582.00.0000006-12 mons1.090.016132.06.1362733-6 mons2.01489.027306.00.000000More Than 10 years2.01124.033712.02.8999621-2 years8.0579.04NaN0.00000001.01489.0<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>mgr_idemp_id07582.0116132.0227306.0333712.044NaN5<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>levelmonths_for_promotion0Junior IC37.01Junior IC40.02Manager30.03Director37.04Manager34.0
Package: atlassian-jwt
codebeat
badgeJSON Web Token(JWT) authentication and encoding
library for Python 2 and 3. Extendspyjwtto include Atlassian
Connect’s customquery string
hash(qsh) claim.This package is onpypiso you can use pip to install itpip install atlassian-jwtTenant informationThis package makes references to Atlassian Connect’stenant information
data
structure.
Specfically theclientKeyandsharedSecretfields are used when
encoding a JWT token. Here is an example of the complete tenant
information data structure as is passed to a Connect Addon with theinstalledlifecycle callback.{
  "key": "installed-addon-key",
  "clientKey": "unique-client-identifier",
  "publicKey": "MIGf....ZRWzwIDAQAB",
  "sharedSecret": "a-secret-key-not-to-be-lost",
  "serverVersion": "server-version",
  "pluginsVersion": "version-of-connect",
  "baseUrl": "http://example.atlassian.net",
  "productType": "jira",
  "description": "Atlassian JIRA at https://example.atlassian.net",
  "serviceEntitlementNumber": "SEN-number",
  "eventType": "installed"
}WhereclientKeyis an identifying key for the Atlassian product instance
that the add-on was installed into.sharedSecretis the string that should be used to sign outgoing JWT
tokens and validate incoming JWT tokens.AuthenticationThis package provides an abstract base class that can be subclassed to
provide authentication to an Atlassian Connect Addon. Here is an example
of that useimport atlassian_jwt

class MyAddon(atlassian_jwt.Authenticator):
    def __init__(self, tenant_info_store):
        super(MyAddon, self).__init__()
        self.tenant_info_store = tenant_info_store

    def get_shared_secret(self, client_key):
        tenant_info = self.tenant_info_store.get(client_key)
        return tenant_info['sharedSecret']

my_auth = MyAddon(tenant_info_store)
try:
    client_key, claims = my_auth.authenticate(http_method, url, headers)
    # authentication succeeded
except atlassian_jwt.DecodeError:
    # authentication failed
    passEncodingAtlassian Connect Addon can make API calls back to the host application.
These API calls include a JWT token for authentication. This package
provides anencode_tokenfunction to do this work. Here is an
example of its useimport atlassian_jwt

token = atlassian_jwt.encode_token(http_method, url, **tenant_info)
headers = {'Authorization': 'JWT {}'.format(token)}Understanding JWT for Atlassian ConnectUnderstanding JWT for Atlassian
ConnectUnderstanding
JWTCreating a query string
hashRunning the testspip3.8 install -e . && pip3.8 install -r requirements.txt && python3.8 -m pytest
Package: atlassian-jwt-auth
This package provides an implementation of theService to Service Authenticationspecification.InstallationTo install simply run$pipinstallatlassian-jwt-authUsing this libraryTo create a JWT for authenticationimportatlassian_jwt_authsigner=atlassian_jwt_auth.create_signer('issuer','issuer/key',private_key_pem)a_jwt=signer.generate_jwt('audience')To create a JWT using a file on disk in the conventional locationEach time you callgenerate_jwtthis will find the latest active key file (ends with.pem) and use it to generate your JWT.importatlassian_jwt_authsigner=atlassian_jwt_auth.create_signer_from_file_private_key_repository('issuer','/opt/jwtprivatekeys')a_jwt=signer.generate_jwt('audience')To create a JWT using a data uriimportatlassian_jwt_authfromatlassian_jwt_auth.keyimportDataUriPrivateKeyRetrieverkey_id,private_key_pem=DataUriPrivateKeyRetriever('Your base64 encoded data uri').load('issuer')signer=atlassian_jwt_auth.create_signer('issuer','issuer/key',private_key_pem)a_jwt=signer.generate_jwt('audience')To make an authenticated HTTP requestIf you use theatlassian_jwt_auth.contrib.requests.JWTAuthprovider, you
can automatically generate JWT tokens when using therequestslibrary to
perform authenticated HTTP requests.importatlassian_jwt_authfromatlassian_jwt_auth.contrib.requestsimportJWTAuthsigner=atlassian_jwt_auth.create_signer('issuer','issuer/key',private_key_pem)response=requests.get('https://your-url',auth=JWTAuth(signer,'audience'))One can also useatlassian_jwt_auth.contrib.aiohttp.JWTAuthto authenticateaiohttprequests:importaiohttpimportatlassian_jwt_authfromatlassian_jwt_auth.contrib.aiohttpimportJWTAuthsigner=atlassian_jwt_auth.create_signer('issuer','issuer/key',private_key_pem)asyncwithaiohttp.ClientSession()assession:asyncwithsession.get('https://your-url',auth=JWTAuth(signer,'audience'))asresp:...If you want to reuse tokens that have the same claim within their period of validity
then pass throughreuse_jwts=Truewhen callingcreate_signer.
For example:importatlassian_jwt_authfromatlassian_jwt_auth.contrib.requestsimportJWTAuthsigner=atlassian_jwt_auth.create_signer('issuer','issuer/key',private_key_pem,reuse_jwts=True)response=requests.get('https://your-url',auth=JWTAuth(signer,'audience'))To verify a JWTimportatlassian_jwt_authpublic_key_retriever=atlassian_jwt_auth.HTTPSPublicKeyRetriever('https://example.com')verifier=atlassian_jwt_auth.JWTAuthVerifier(public_key_retriever)verified_claims=verifier.verify_jwt(a_jwt,'audience')For Python versions starting fromPython 3.5, note this library no longer supports python 3.5,atlassian_jwt_auth.contrib.aiohttpprovides drop-in replacements for the components that
perform HTTP requests, so that they useaiohttpinstead ofrequests:importatlassian_jwt_auth.contrib.aiohttppublic_key_retriever=atlassian_jwt_auth.contrib.aiohttp.HTTPSPublicKeyRetriever('https://example.com')verifier=atlassian_jwt_auth.contrib.aiohttp.JWTAuthVerifier(public_key_retriever)verified_claims=awaitverifier.verify_jwt(a_jwt,'audience')
Package: atlassian-marketplace-python-client
Atlassian Marketplace Python ClientThe Python Client for the Atlassian Marketplace, which allows to easily get information from
the Atlassian Marketplace and setting information in it.Getting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.PrerequisitesThis project was written with Python 3.6. The results of running this with Python 2 will vary.InstallingThe requirements which are needed to run the atlassian_marketplace_python_client are set in the requirements.txt file and can be installed
by running the following command in your command line.pip install -r requirements.txtorvenv/bin/pip install -r requirements.txtVersioningVersion 0.1:
Supports getting products from a specific vendor(as json) and getting only the names of the products of a specific vendor.Version 0.3:
Update to requests 2.20.0 to fix potential vulnerability.AuthorsJean PetryLicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for details
Package: atlassian-python-api-cti
DocumentationDocumentation (beta)ExamplesFor everyday normal use, just install package using pippip install atlassian-python-apiHere’s a short example how to create a Confluence page:fromatlassianimportConfluenceconfluence=Confluence(url='http://localhost:8090',username='admin',password='admin')status=confluence.create_page(space='DEMO',title='This is the title',body='This is the body. You can use <strong>HTML tags</strong>!')print(status)And here’s another example how to get issues from Jira using JQL Query:fromatlassianimportJirajira=Jira(url='http://localhost:8080',username='admin',password='admin')JQL='project = DEMO AND status NOT IN (Closed, Resolved) ORDER BY issuekey'data=jira.jql(JQL)print(data)Also, you can use the Bitbucket module e.g. for get project listfromatlassianimportBitbucketbitbucket=Bitbucket(url='http://localhost:7990',username='admin',password='admin')data=bitbucket.project_list()print(data)Now you can use Jira Service Desk module. See docs.
Example to get your requests:fromatlassianimportServiceDesksd=ServiceDesk(url='http://localhost:7990',username='admin',password='admin')my_requests=sd.get_my_customer_requests()print(my_requests)Please make sure, you’ve checkedexamples/directory on how to build scripts using the API.
If you want to see response in pretty print format json. Feel free for use construction like:frompprintimportpprint# you code here# and then print using pprint(result) instead of print(result)pprint(response)Development and Deployment (For contributors)See theContribution guidelines for this projectfor details on how to make changes to this library.
Package: atl-cache-warmer
atl_cache_warmerLittle script to log in and warm up the cache of Jira or Confluence instances (just a basic http request)To Installpip install -U atl_cache_warmerTo UseFrom the command line:> atlwarmer --help
> usage: atlwarmer [-h] -u USERNAME -p PASSWORD [-j JIRA_URL] [-t JIRA_TARGET] [-c CONFLUENCE_URL] [-s SPACE] [-i]  [-v]

>optional arguments:
  -h, --help         show this help message and exit
  -u USERNAME        username to use
  -p PASSWORD        password to use
  -j JIRA_URL        url for jira
  -t JIRA_TARGET     path in jira to make request to
  -c CONFLUENCE_URL  url for confluence
  -s SPACE           confluence space to make request to
  -i                 when used in combination with -s, will attempt to iterate through and request all pages in the target space. Jira support coming soon(TM)
  -v                 Increase verbosity level, can used up to 2 timesNote: to work from the command line you need to make sure that python-scripts is in your PATH
Package: atlite
AtliteAtlite is afree software,xarray-based Python library for
converting weather data (like wind speeds, solar influx) into energy systems data.
It is designed to be lightweight, keeping computing resource requirements (CPU, RAM) usage low.
It is therefore well suited to be used with big weather datasets.Atlite can process the following weather data fields and can convert them into following power-system relevant time series for any subsets of a full weather database.Atlite was initially developed by theRenewable Energy GroupatFIASto carry out simulations
for theCoNDyNet project, financed by theGerman Federal Ministry for Education and Research (BMBF)as part of theStromnetze
Research Initiative.InstallationTo install you need a working installation running Python 3.6 or above
and we strongly recommend using either miniconda or anaconda for package
management.To install the current stable version:withcondafromconda-forgecondainstall-cconda-forgeatlitewithpipfrompypipipinstallatliteto install the most recent upstream version from GitHubpipinstallgit+https://github.com/pypsa/atlite.gitDocumentationPlease check thedocumentation.Support & ContributingIn case of code-relatedquestions, please post onstack overflow.For non-programming related and more general questions please refer to thepypsa mailing list.Todiscusswith other PyPSA and atlite users, organise projects, share news, and get in touch with the community you can use thediscord server.Forbugs and feature requests, please use theissue tracker.We strongly welcome anyone interested in providingcontributionsto this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on theGithub repository.Authors and CopyrightCopyright (C) 2016 - 2023 The Atlite Authors.See theAUTHORSfor details.LicenceThis work is licensed under multiple licences:All original source code is licensed underMITAuxiliary code from SPHINX is licensed underBSD-2-Clause.The documentation is licensed underCC-BY-4.0.Configuration and data files are mostly licensed underCC0-1.0.See the individual files for license details.