Saravanan666/pypi-org huggingface dataset:
Package: cdp-backend
cdp-backendData storage utilities and processing pipelines used by CDP instances.Council Data ProjectCouncil Data Project is an open-source project dedicated to providing journalists, activists, researchers, and all members of each community we serve with the tools they need to stay informed and hold their Council Members accountable.For more information about Council Data Project, please visitour website.Aboutcdp-backendis used to maintain the database models, infrastructure stack, and all pipelines for CDP Instance web applications.The central goal is to create a single library that manages the whole backend of any CDP Instance.InstallationStable Release (with just data access dependencies):pip install cdp-backendStable Release (with full pipeline dependencies):pip install cdp-backend[pipeline]Development Head:pip install git+https://github.com/CouncilDataProject/cdp-backend.gitDev Installation:For devs, please ensure that you havedot / graphvizinstalled before working with tests and auto-documentation generation.InfrastructurePlease seedev-infrastructurefor defaults on dev deployments.DocumentationFor full package documentation please visitcouncildataproject.org/cdp-backend.DevelopmentSeeCONTRIBUTING.mdfor information related to development of this repository.CitationIf you have found CDP software, data, or ideas useful in your own work, please consider citing us:Brown et al., (2021). Council Data Project: Software for Municipal Data Collection, Analysis, and Publication. Journal of Open Source Software, 6(68), 3904,https://doi.org/10.21105/joss.03904@article{Brown2021,doi={10.21105/joss.03904},url={https://doi.org/10.21105/joss.03904},year={2021},publisher={The Open Journal},volume={6},number={68},pages={3904},author={Eva Maxfield Brown and To Huynh and Isaac Na and Brian Ledbetter and Hawk Ticehurst and Sarah Liu and Emily Gilles and Katlyn M. f. Greene and Sung Cho and Shak Ragoler and Nicholas Weber},title={{Council Data Project: Software for Municipal Data Collection, Analysis, and Publication}},journal={Journal of Open Source Software}}LicenseMIT License
Package: cdp-connector
cdp-connectorA readonly CDP client for Python. This can be used to execute queries against CDP and load the data into python.UsageInstallationInstall the package from Pypi using the commandpip install cdp-connectorQuick StartWe have to create an instance of the SalesforceCDPConnection to connect to CDP.The object can be created as follows:Using Username and Passwordfrom salesforcecdpconnector.connection import SalesforceCDPConnection
conn = SalesforceCDPConnection(
        'login_url', 
        'user_name', 
        'password', 
        'client_id', 
        'client_secret'
    )Using OAuth Tokensfrom salesforcecdpconnector.connection import SalesforceCDPConnection
conn = SalesforceCDPConnection(login_url, 
       client_id='<client_id>', 
       client_secret='<client_secret>', 
       core_token='<core token>'
       refresh_token='<refresh_token>'
   )Once the connection object is created the queries can be executed using cursor as followscur = conn.cursor()
cur.execute('<query>')
results = cur.fetchall()The query results can also be directly extracted as a pandas dataframedataframe = conn.get_pandas_dataframe('<query>')Creating a connected AppLog in to salesforce as an admin. In the top right corner, click on the gear icon and go to stepIn the left hand side, under Platform Tools, go to Apps > App ManagerClick on New Connected AppFill in the required Basic Information fields.Under API (Enable OAuth Settings)Click on the checkbox to Enable OAuth Settings.Provide a callback URL.In the Selected OAuth Scopes, make sure that refresh_token, api, cdp_query_api, cdp_profile_api is selected.Click on Save to save the connected appFrom the page that opens up, click on the Manage Consumer Details to find your client id and client secretFetching Refresh TokenFrom the connected app, note down the below details:Client IdClient SecretCallback URLObtain the codeFrom browser, go to the below url.<LOGIN_URL>/services/oauth2/authorize?response_type=code&client_id=<client_id>&redirect_uri=<callback_url>This will redirect you to the callback url. The redirected url will be of the form<callback url>?code=<CODE>Extract the CODE from the address bar to be used in next step. Check the network tab of browser if the addressbar doesn't show this.Get core and refresh tokensMake a post call using curl or postman to the below url using the code retrieved in previous step.<LOGIN_URL>/services/oauth2/token?code=<CODE>&grant_type=authorization_code&client_id=<clientId>&client_secret=<clientSecret>&redirect_uri=<callback_uri>The response to the above post call will be a json with access_token and refresh_token
Package: cdpDumpingUtils
cdpDumpingUtilsThis project exists to dump files form cahier-de-prepa.fr web site. While some students try to recover every file manually, this tool can export most of the files.DISCLAIMER : THIS TOOL IS NOT MEANT TO DEFEAT INTELLECTUAL PROPERTY, IT IS JUST A TOOL TO HELP STUDENTS.InstallationInstallPython3Automatic installation (recommended)pip install cdpDumpingUtilsManual installationDownload the repository:git clone https://github.com/Azuxul/cdpDumpingUtils.gitInstall the dependency:pip install -r requirements.txtNow you can use cdpDumpingUtils but instead of thecdpDumpingUtilscommand you have to use this command:python cdpDumpingUtils/main.pyUsagecdpDumpingUtils -husage: cdpDumpingUtils [-h] [--edit-cfg] [-v] [-l USERNAME] [-p PASSWORD] [-o OUTPUT] [-u URL]

options:
  -h, --help            show this help message and exit

arguments optionnels:
  --edit-cfg            Modification du fichier de configuration
  -v, --verbose         Augmente la quantité de texte affiché
  -l USERNAME, --username USERNAME
                        Nom d'utilisateur du compte cahier de prepa (utilisation sans compte possible)
  -p PASSWORD, --password PASSWORD
                        Mot de passe de connexion cahier de prepa
  -o OUTPUT, --output OUTPUT
                        Chemin d'acces du dossier de sortie, par default le dossier actuel
  -u URL, --url URL     URL de l'instance cahier de prepaTo run cdpDumpingUtils with a config file (if no config file it will be created) :cdpDumpingUtils -o ./outputTo run cdpDumpingUtils and specify an url without an account:cdpDumpingUtils -u https://cahier-de-prepa.fr/XXX/ -o ./outputTo run cdpDumpingUtils  and specify an url  with an account:cdpDumpingUtils -u https://cahier-de-prepa.fr/XXX/ -l username -p password -o ./outputLimitationsThis tool may be unusable if cahier-de-prepa is updated. This tool only download documents. Grades, calendars and other features of cahier-de-prepa are not implemented.LicenseThis project is licensed under the GNU General Public License v3.0
Package: cdp-gh-utils
cdp-gh-utilsUtility functions and scripts to manage CDP (and other) GitHub repositories.InstallationStable Release:pip install cdp-gh-utilsDevelopment Head:pip install git+https://github.com/CouncilDataProject/cdp-gh-utils.gitBackfilling Instances⚠️ ⚠️ Note: prior to using this library, be sure to create aGitHub Personal Access Tokenand store it to aGITHUB_TOKENenvironment variable (.envfile also works). ⚠️ ⚠️❯ backfill-cdp-instance -h

usage: backfill-cdp-instance [-h] [--outfile OUTFILE] [--iter_days ITER_DAYS] [--overlap_days OVERLAP_DAYS] [--token TOKEN] [--workflow_filename WORKFLOW_FILENAME] [--ref REF]
                             [--ignore_errors] [--debug]
                             owner repo start_datetime end_datetime

Iteratively triggers the Event Gather Pipeline workflow via GitHub Actions to backfill a CDP instance. Only one workflow run will ever happen at a single time.

positional arguments:
  owner                 The organization which hosts the instance. i.e. 'CouncilDataProject'
  repo                  The organization which hosts the instance. i.e. 'seattle'
  start_datetime        The start datetime of the backfill in ISO format. i.e. '2022-01-01'
  end_datetime          The end datetime of the backfill in ISO format. i.e. '2023-01-01'

options:
  -h, --help            show this help message and exit
  --outfile OUTFILE     Path to the where the backfill results should be stored to CSV.
  --iter_days ITER_DAYS
                        The number of days to backfill during each workflow run.
  --overlap_days OVERLAP_DAYS
                        The number of days to overlap each workflow run by.
  --token TOKEN         GitHub Personal Access Token to use for initializing workflow runs.
  --workflow_filename WORKFLOW_FILENAME
                        The name of the workflow file which acts as the event gather pipeline action definition.
  --ref REF             The branch or git ref name to trigger the workflow on.
  --ignore_errors       Try to backfill all batches regardless of errors.
  --debug               Run with debug logging.backfill-cdp-instanceevamaxfieldcdp-dev2023-02-012023-03-01DocumentationFor full package documentation please visitCouncilDataProject.github.io/cdp-gh-utils.DevelopmentSeeCONTRIBUTING.mdfor information related to developing the code.MIT License
Package: cdpipelines
This repository holds various bioinformatics pipelines.DependenciesMany of the pipeline dependencies can be obtained using thepreparesubmodule (see below). Additionally, a working Python environment is
needed along with some of the common scientific python packages. I
recommend usingAnaconda
pythonsince it includes
most of the needed packages. If you are using Anaconda, I’d recommend
making new environments for different projects. Besides the default
Anaconda packages, you will need the following (available throughcondaorpip):HTSeqpandaspysam (this is available through conda but currently it’s an old
version so you have to get it usingpip)PyVCFrpy2Installingrpy2can be tricky. Different versions ofRandrpy2don’t work well together, so it’s recommended to make a local
installation ofRusing thepreparesubmodule and compilerpy2against this installation. You can installRusingprepare.download_rand installrpy2usingprepare.download_install_rpy2.prepare.download_install_rpy2will prompt you to set your PATH, LDFLAGS, and LD_LIBRARY_PATH to
correctly installrpy2. After installingrpy2, you need to set
your PATH and LD_LIBRARY_PATH using these commands for every bash
session where you want to use thisrpy2. I’d recommend putting the
commands in a file that you source every time you load the project’s
Anaconda environment.Submodulesgeneralgeneralcontains methods used in multiple pipelines. Some pipelines
use similar but different versions of some methods, so the pipelines
will have their own versions of those methods. Sometimes it may make
sense to add options to a particular method that is used in multiple
pipelines (where each pipeline has slightly different versions) and add
the method intogeneral.prepareThepreparemodule contains functions for downloading various
software and reference files needed for the different pipelines.rnaseqThis pipeline currently starts from fastq files and has two steps. For
detailed information on each step, so the docstrings for each method.
The first step isalign_and_sortwhich (optionally) removes
duplicates, aligns the reads, and makes coverage bigwig files for use
with the UCSC genome browser or IGV. The read alignments are output in
both genomic and transcriptomic coordinates. The second step isget_countswhich counts reads overlapping genes for gene
differential expression and exonic bins for use with DEXSeq.
Package: cdp-monitoring
cdp-monitoringfastapi prometheus + opentelemetry sdkInstall packageVERSION=0.1.0
pipinstallgit+https://github.daumkakao.com/cdpdev/cdp-monitoring.git#${VERSION}Usage1. Tempo url 을 환경변수로 설정설정되어 있지 않은 경우 모니터링도 비활성화exportTEMPO_URL=""2. 모니터링 대상 FastAPI 앱을 init_monitoring 함수의 인자로 전달# app 생성fromfastapiimportFastAPIapp=FastAPI(title="My FastAPI App")# 모니터링 설정 적용fromcdp_monitoringimportinit_monitoringinit_monitoring(app)Uninstall packagepipuninstallcdp-monitoring
Package: cdp-py
cdp-pyThe Ciholas Data Protocol (CDP) provides a method of communication between devices and services. CDP data is transmitted over Ethernet as User Datagram Protocol (UDP) packets.cdp-pycontains a set of structural definitions of the CDP data items that make up these UDP packets.To get started with CDP, see the officialdocumentation. For more information regarding the individual data items, visit thedata items documentation.Getting StartedPrerequisitesYou need Python 3 or higher to usecdp-py. Make sure you have Python installed and that the expected version is available from your command line. You can check this by running:$ python --versionInstallingcdp-pycan be installed using pip. To install the latest version use:$ pip install cdp-pyNow thatcdp-pypackage is installed, you can start using thecdpmodule by adding the following import statement to your Python script:importcdpFor a tutorial about how to use thecdpmodule, visit:Using CDP - Python.UpgradingTo upgrade to the latest version use:$ pip install --upgrade cdp-pyLicenseThis work is licensed under theCreative Commons Attribution 4.0 InternationalLicense.
Package: cdproj
# cdprojcdprojis a really simple project location rememberer.## Installationsimply install via pip:pip install cdproj## UsageTocdto a project, simply type in your favorite shell:cdproj project_nameTo register a new project:cdproj add project_nameTo remove a project:cdproj rm project_nameTo list projects:cdproj lsThat’s all.# LICENSEMIT
Package: cd-randomizer
cd_randomizercd_randomizeris a Python package for randomizing CDs.InstallationYou can installcd_randomizerusing pip:pipinstallcd_randomizerUsageHere is a simple example of how to usecd_randomizer:fromcd_randomizer.randimportRandomizerasrandoa_list=[1,2,3,4,5]# Example usageitem=rando.random_list_item(a_list)print("random item",item)rando.randomize_list(a_list)# it will shuffle in place, no nee to make another listprint(a_list)decimal=rando.random_decimal(2.50005,4.0,round_to=3)print("random decimal(float)",decimal)list_item=rando.random_list_item(a_list)print("random list item",list_item)rand_number=rando.random_number(1,100)print("Random whole number between 1 and 100",rand_number)rand_items=rando.random_sample_of_a_list(a_list,3)print("3 random list items",rand_items)ExamplesFor more examples, please refer to theexamplesfolder.ContributingContributions are welcome! For major changes, please open an issue first to discuss what you would like to change.More documentation at:Code DoctaLicenseMIT
Package: cd-rss-reader
RSSReaderA robust Python-based RSS feed reader that fetches, parses, and manages updates for RSS and Atom feeds. It supports efficient conditional GET requests to minimize bandwidth and server load by utilizingLast-ModifiedandEtagHTTP headers.FeaturesParses different RSS and Atom feed formats.Extracts key details such as titles, links, descriptions, and associated images.UtilizesLast-ModifiedandEtagheaders to perform conditional GET requests, avoiding unnecessary data transfer if the feed has not been updated since the last fetch.RequirementsPython 3feedparserlibraryInstallationFirst, ensure that you have Python installed on your machine. Then, you can install the requiredfeedparserlibrary usingpip:pipinstallcd-rss-readerUsage
To use the RSSReader class, create an instance with the URL of the RSS feed you wish to parse:fromcd_rss_readerimportRSSReader# Initialize the reader with the feed URLurl="https://www.example.com/rss_feed_url.xml"reader=RSSReader(url)# Fetch and parse the feedreader.fetch()# Get basic information about the feedprint(f"Feed Title:{reader.get_title()}")print(f"Feed Link:{reader.get_link()}")print(f"Feed Description:{reader.get_feed_description()}")# Iterate over the feed entriesforentryinreader.get_entries():print(f"Title:{entry.title}")print(f"Link:{entry.link}")print(f"Published Date:{entry.published}")print(f"Summary:{entry.summary}")image_link=reader.get_image_link(entry)ifimage_link:print(f"Image Link:{image_link}")else:print("No image available.")Replacehttps://www.example.com/rss_feed_url.xmlwiththeURLoftheRSSfeedyouwanttoread.Contributing
Contributions are welcome! For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.More documentation at:Code DoctaLicense
This project is open-sourced software licensed under the MIT license.
Package: cds4-computation
My CalculatorThis package computes the various computations of Maths like :Greatest Common DivisorLowest Common MultipleReducing FractionInstallationsThrough pypi package$pipinstallmy-calculatorUsageAfter the package is installed, several operation can be performed like:Greatest Common Divisorfrommy_calculatorimportCalculatorCalculator.gcd(8,16,24)# Output : 8Calculator.gcd(10,12)# Output : 2Lowest Common Multiplefrommy_calculatorimportCalculatorCalculator.lcm(10,20,30)# Output : 60Calculator.lcm(10,5)# Output : 10Fraction reducerfrommy_calculatorimportCalculatorCalculator.reduce_fraction(10,12)# Output : (5,6)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.TO DO:Other Mathematical functions addition
Package: cdsapi
InstallInstall viapipwith:$ pip install cdsapiConfigureGet your user ID (UID) and API key from the CDS portal at the addresshttps://cds.climate.copernicus.eu/userand write it into the configuration file, so it looks like:$ cat ~/.cdsapirc
url: https://cds.climate.copernicus.eu/api/v2
key: <UID>:<API key>
verify: 0Remember to agree to the Terms and Conditions of every dataset that you intend to download.TestPerform a small test retrieve of ERA5 data:$ python
>>> import cdsapi
>>> cds = cdsapi.Client()
>>> cds.retrieve('reanalysis-era5-pressure-levels', {
           "variable": "temperature",
           "pressure_level": "1000",
           "product_type": "reanalysis",
           "date": "2017-12-01/2017-12-31",
           "time": "12:00",
           "format": "grib"
       }, 'download.grib')
>>>LicenseCopyright 2018 - 2019 European Centre for Medium-Range Weather Forecasts (ECMWF)Licensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.In applying this licence, ECMWF does not waive the privileges and immunities
granted to it by virtue of its status as an intergovernmental organisation nor
does it submit to any jurisdiction.
Package: cdsapitaka
InstallInstall viapipwith:$ pip install cdsapiConfigureGet your UID and API key from the CDS portal at the addresshttps://cds.climate.copernicus.eu/userand write it into the configuration file, so it looks like:$ cat ~/.cdsapirc
url: https://cds.climate.copernicus.eu/api/v2
key: <UID>:<API key>
verify: 0Remember to agree to the Terms and Conditions of every dataset that you intend to download.TestPerform a small test retrieve of ERA5 data:$ python
>>> import cdsapi
>>> cds = cdsapi.Client()
>>> cds.retrieve('reanalysis-era5-pressure-levels', {
           "variable": "temperature",
           "pressure_level": "1000",
           "product_type": "reanalysis",
           "date": "2017-12-01/2017-12-31",
           "time": "12:00",
           "format": "grib"
       }, 'download.grib')
>>>LicenseCopyright 2018 - 2019 European Centre for Medium-Range Weather Forecasts (ECMWF)Licensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.In applying this licence, ECMWF does not waive the privileges and immunities
granted to it by virtue of its status as an intergovernmental organisation nor
does it submit to any jurisdiction.
Package: cdsdashboards
ContainDS Dashboards for JupyterHubA Dashboard publishing solution for Data Science teams to share results with decision makers.Run a private on-premise or cloud-based JupyterHub with extensions to instantly publish apps and notebooks as user-friendly
interactive dashboards to share with non-technical colleagues.Currently supported frameworks:Jupyter notebooks (Voilà)StreamlitappsPlotly DashappsBokeh/Panelapps and notebooksR ShinyappsAny custom server or frameworkThis open source package allows data scientists to instantly and reliably publish interactive
notebooks or other scripts as secure interactive web apps.Source files can be pulled from a Git repo or from the user's Jupyter tree.Any authorised JupyterHub user can view the dashboard, or choose to give permission only to named users.Seefull documentationHow it worksData scientist creates a Jupyter Notebook as normal or uploads Python/R files etcData scientist creates a new Dashboard to clone their Jupyter serverOther logged-in JupyterHub users see the dashboard in their listClick to launch as a server, using OAuth to gain accessUser sees a safe user-friendly version of the original notebook - served by Voilà, Streamlit, Dash, Bokeh, Panel, R Shiny etc.All of this works through a new Dashboards menu item added to JupyterHub's header.Data scientist creates a Jupyter Notebook as normalData scientist creates a new Dashboard to clone their Jupyter serverOther logged-in JupyterHub users see the dashboard in their listUses OAuth to gain accessOther user sees a safe user-friendly Voilà version of the original notebookOr other app frameworksRequirementsBasic requirements:JupyterHub 1.xPython 3.6+Note that JupyterHub 2.x is not supported. You will need to install a version 1.x (e.g. 1.5).You should be able to use any authenticator for users to login - for example, corporate Google email sign in, or LDAP.Any JupyterHub distribution should be suitable, depending on configuration. Seerequirements.InstallationFullSetup and Installation detailsare in the documentation.Contact and SupportPlease see LICENSE for details.Please do get in touch if you try out the package, or would like to but need some support. I would be very interested to find out how it can be used, and to work (without charge) to help you get it running. The project needs feedback in order to develop further!Contactsupport@containds.comwith any comments or questions at all.There is aGitter roomfor general chat with other community members, e.g. for confguration and use case tips.
Package: cdshealpix
CDSHealpixThis is a BSD-licensed HEALPix package which is wrapped around thecdshealpix Rust crate.cdshealpixis multi-platform and is currently deployed on PyPI for i686, x86_64 and aarch64 archs.pipinstallcdshealpixOrcondainstall-cconda-forgecdshealpixReminder on conda activation/deactivation:condaconfig--setauto_activate_basefalsecondaactivatebase
condadeactivateTest:importcdshealpixfromcdshealpiximporthealpix_to_lonlatlon,lat=healpix_to_lonlat(0,0)assertlon.rad[0]==0.7853981633974483FeaturesNested and Ring HEALPix notationsupportedCone searchElliptical-Cone searchPolygon searchBilinear interpolationlonlat_to_healpixandhealpix_to_lonlatsupports numpy broadcastingRust allows easy concurrency. Anum_threadsoptional parameter can be used to allow parallelism. By default, concurrency is disabled.Get theworld vertices corresponding to an HEALPix cellGet theneighbours of an HEALPix cellDocumentationHere is the link to thedocumentationfor informations about how to use this package.