Saravanan666/pypi-org huggingface dataset:
Package: canScan
canScanCANopen active scanner atop Christian Sandberg'sCANopen for Python. canScan
watches for CAN arbitration IDs, CANopen node IDs (as determined through
NMT/SDO analysis), and CANopen PDOs. canScan can scan the Object Dictionary
of a specified (or discovered) CANopen node using SDO Receive.canScan has been developed/tested against Python 2.7 and 3.7.UsageTwo arguments are required: a bus type and a device identifier. The bus types
are duepython-can, and can be found
in that project's documentation. Device identifier semantics are per-driver.
For virtual devices, usevirtualand the network device name. Other SocketCAN
devices usesocketcanand the network device name. The CanalystII usescanalystiiand the USB device index.Default behavior is to perform an SDO scan across the 128 CANopen IDs, then
perform dumps of the entirety of discovered nodes' Object Dictionaries. Both
steps will be periodically repeated. Discovered Object Dictionary entries will
be queried more regularly than failed IDs. The program exits on error or
keyboard interrupt. With the--oneshotflag, only an initial set of scans
will be performed, followed by the program's exit.The--passiveflag can be provided, in which case no frames will be
transmitted (the driver or hardware might send frames, especially
acknowledgements, on their own).If the--scanargument is provided, it expects a comma-delimited list of
numbers (either decimal, or hex with a prefix of0x). These IDs will see
their entire Dictionaries scanned whether they respond to the initial probe or
not.--passivecannot be used with--scanor--oneshot.The default local node ID is 64 (0x40), but it may be specified with--id.
Package: canseer
hpdm139_ACANSEERInstallationCanseer 0.1.3 is available on PyPI:https://pypi.org/project/canseer/pip install canseerDescriptionCanseer is a toolkit which allows the user to analyse data from NHS statistics on adherence to cancer diagnosis standards. The data can be downloaded, presented in dataframe and filtered using our data wrangling functions. There are different tools which can be employed to visualise the data, to display both trends over time and geographical variation.
The 'Canseer'package leverages multiple sources of NHS data, and allows seamless and flexible visualisation of NHS cancer targets on a map.MotivationImproving cancer diagnosis is a key pillar of the NHS Long Term Plan. The UK has lower cancer survival rates than other comparator countries (Arnold et al. Lancet Oncology 2019 DOI:https://doi.org/10.1016/S1470-2045(19)30456-5) and waiting times for cancer diagnostics is thought to contribute to the poor outcomes seen in the UK. From the 1st October 2023 new cancer diagnosis standards have been announced; Faster Diagnosis Standard: a diagnosis or ruling out of cancer within 28 days of referral (set at 75%), 31-day treatment standard: commence treatment within 31 days of a decision to treat (set at 96%), 62-day treatment standard: commence treatment within 62 days of being referred (set at 85%). In order to support and improve cancer diagnosis, there is a need to understand trends in the adherence to these standards at both national and regional levels. Comparing the adherence to these standards across different patient groups such as those awaiting particular treatment types or with certain cancers can allow better targeting of diagnostic resources.NHS statistics collects data nationally, on a provider NHS trust level and on a commissioning level on the cancer diagnosis standards. Our toolkit allows the user the ability to analyse the different datasets provided by NHS statistics in one place. The visualisation tools can help display trends, highlight geographical discrepancies and compare across different patient groups.#DataThis toolkit uses data provided by NHS statistics website for cancer diagnosis and treatment referrals.National data -https://www.england.nhs.uk/statistics/wp-content/uploads/sites/2/2023/12/CWT-CRS-National-Time-Series-Oct-2009-Oct-2023-with-Revisions.xlsxProvider (NHS Trust) data -https://www.england.nhs.uk/statistics/wp-content/uploads/sites/2/2023/12/CWT-CRS-2022-23-Data-Extract-Provider-Final.xlsx'This toolkit also uses data provided by the ONS to link NHS trust regions to geographical areas and a map (shapefile format) of Integrated Care Boards (ICBs); to supply organatisation codes for each NHS trust.Office for National Statistics Data -https://www.ons.gov.uk/methodology/geography/ukgeographies/healthgeographyUser guideThis is provided in the Juptyer Notebook entitled User guide.
Package: cansi
CURSES ANSI PARSERINSTALLATIONpip install cansiEXAMPLEimportcursesfromcansiimportCansidefevent_loop(stdscr):curses.curs_set(0)# hide the cursorcansi=Cansi(stdscr)lines=["\033[1;32mThis line is bright GREEN\033[0m","\033[1;31mThis line is bright RED\033[0m","\033[0;32mThis line is GREEN\033[0m","\033[0;31mThis line is RED\033[0m","\033[1mThis line is BOLD\033[0m","\033[4mThis line is BOLD\033[0m","\033[5mThis line BLINKS\033[0m","\033[7mThis line is REVERSE\033[0m","\033[0KmThis line won't be displayed\033[0m","\033[1;37mPress q to quit\033[0m",]whileTrue:forindex,lineinenumerate(lines):cansi.addstr(index,0,line)ifstdscr.getkey()=="q":breakcurses.wrapper(event_loop)REFERENCEShttps://docs.python.org/3/howto/curses.htmlhttps://docs.python.org/3/library/curses.htmlhttps://www.perlmonks.org/bare/?node_id=215785http://ascii-table.com/ansi-escape-sequences.phphttps://notes.burke.libbey.me/ansi-escape-codes/https://www.lihaoyi.com/post/BuildyourownCommandLinewithANSIescapecodes.html
Package: cansig
CanSig: Discovering de novo shared transcriptional programs in single cancer cellsA pipeline for single-cell cancer data sets analysis.This repository accompaniesour preprint.ResourcesFor tutorials and API description, see ourdocumentation.If you found a bug or have an idea for improvement,submit an issue.If you would like to contribute, see thecontribution guide.Installation$ pip install cansigMore information can be found in theGetting startedsection of our documentation.Code contributorsTo open-source the code, Git history was truncated. Hence, GitHub's statistics do not faithfully summarize the contributions. All persons listed below made major contributions to the code.Josephine YatesFlorian BarkmannPaweł CzyżElia Saquand
Package: cansii
CansiiCansii is a Python library that enables easy text colorization in the terminal using ANSI escape codes. It provides support for a variety of colors, styles, and combinations to enhance terminal output.InstallationThere's no specific installation required. Use the provided class methods to format your text with ANSI escape codes for display in the terminal.UsagefromcansiiimportCansii# Applying colorsprint(Cansii.red("This is red text"))print(Cansii.blue("This is blue text"))# Applying stylesprint(Cansii.bold("This is bold text"))print(Cansii.underline("This is underlined text"))# Applying combinationsprint(Cansii.red_bold("This is red and bold text"))print(Cansii.green_underline("This is green and underlined text"))LicenseThis project is licensed under the GNU General Public License v3.0. View the LICENSE file for further details.
Package: can-sniffer
Drv CanRepository that storages classes and functions used create a thread that can send,
and receive can messages. The node class will create a thread with a shared object
that receives the commands both for the can module and also the messages to send through can bus.
The commands that can be send to can are create and remove filter, and also send messages.The version 0.1.X forward is using posix ipc queues, if there is any problem with posix it will
possibly be due to the max messages in queue and the max message size limited by the system.
For more information checksystem-shared-tool githubTo see which is the max messages and the max message size in system run:cat /proc/sys/fs/mqueue/msg_max
cat /proc/sys/fs/mqueue/msgsize_maxIn order to change the max message or message size in queues run:sudo sh -c 'echo 200 > /proc/sys/fs/mqueue/msg_max'
sudo sh -c 'echo 200 > /proc/sys/fs/mqueue/msgsize_max'
Package: canswim
canswimDeveloper toolkit for CANSLIM investment style practitionersSetuppip install canswimInstall canswim package in dev modepip install -e ./Command line interface$ python -m canswim -h
usage: canswim [-h] {dashboard,train}

CANSWIM is a toolkit for CANSLIM style investors. Aims to complement the Simple Moving Average and other technical indicators.

positional arguments:
  {dashboard,gatherdata,uploaddata,modelsearch,train,finetune,forecast}
                        Which canswim task to run:
                        `dashboard` for stock charting and scans of recorded forecasts.
                        'gatherdata` to gather 3rd party stock market data and save to HF Hub.
                        'uploaddata` upload to HF Hub any interim changes to local data storage.
                        `modelsearch` to find and save optimal hyperparameters for model training.
                        `train` for continuous model training.
                        `finetune` to fine tune pretrained model on new stock market data. `forecast` to run forecast on stocks and upload dataset to HF Hub.

options:
  -h, --help            show this help message and exit
  --forecast_start_date FORECAST_START_DATE
                        Optional argument for the `forecast` task. Indicate forecast start date in YYYY-MM-DD format. If not specified, forecast will start from the end of the target series.

NOTE: NOT FINANCIAL OR INVESTMENT ADVICE. USE AT YOUR OWN RISK.Interactive Dashboard hosted on Hugging Face Hubhttps://huggingface.co/spaces/ivelin/canswim_playground
Package: cantal
=========Cantal-Py=========:Status: Beta:Documentation: https://cantal-py.readthedocs.io/:Parent Project: https://github.com/tailhook/cantalCantal is an expermimental heartbeating, monitoring and statistics solution.This is a python library for sending statistics data to cantal.Example=======.. code-block:: python:emphasize-lines: 3, 6, 10:linenos:import cantalticks = cantal.Counter(group="main_loop", metric="ticks")def main():cantal.start()while True:sleep(0.1)ticks.incr(1)if __name__ == '__main__':mainLicense=======Licensed under either of* Apache License, Version 2.0,(./LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)* MIT license (./LICENSE-MIT or http://opensource.org/licenses/MIT)at your option.Contribution------------Unless you explicitly state otherwise, any contribution intentionallysubmitted for inclusion in the work by you, as defined in the Apache-2.0license, shall be dual licensed as above, without any additional terms orconditions.
Package: cantaloupe
CantaloupeAn extensible framework for building browser automations.Note: This library is still very much WIP 🧪. This means that breaking changes can be introduced at any point in time.Getting StartedInstallation$pipinstallcantaloupeUsage$poetryruncantaloupe--helpExample WorkflowA workflow is a YAML file that describes a series of steps to be executed.
The following example workflow will open Google and type "cantaloupe" into the search bar.Note: nothing will actually happen until a cantaloupe plugin is installed that implements the logic to translate the
workflow steps into browser actions.
Please see thePluginssection for more information.name:"GoogleSearch"steps:-action:gotoconfig:url:"https://google.com"-action:typeconfig:selector:"input[name='q']"text:"cantaloupe"Pluginscantaloupe-playwrightcoming soonDevelopmentRequirementsPython >= 3.10PoetryCreating pluginsPlugins are created by implementing the cantaloupe hookspec.
Seecantaloupe/hookspecs.pyfor the hookspecs.
Package: cantal_tools
High level tools forcantalmetrics collection system.Documentation:http://cantal-tools.readthedocs.ioPackage contains utils for collecting metrics for
WSGI applications, Flask, Redis, Elasticsearch, SQLAlchemy and Django.
See docs for more.Basic usage:importcantalfromcantal_tools.werkzeug_servingimportCantaledWSGIServercantal.start()CantaledWSGIServer(port=8080,).serve_forever()
Package: cantok
Cancellation Token is a pattern that allows us to refuse to continue calculations that we no longer need. It is implemented out of the box in many programming languages, for example inC#and inGo. However, there was still no sane implementation in Python, until thecantoklibrary appeared.Quick startInstallit:pipinstallcantokAnd use:fromrandomimportrandintfromcantokimportConditionToken,CounterToken,TimeoutTokentoken=ConditionToken(lambda:randint(1,100_000)==1984)+CounterToken(400_000,direct=False)+TimeoutToken(1)counter=0whiletoken:counter+=1print(counter)Read more in thedocumentation!
Package: cantonese-romanisation
Cantonese RomanisationIt is a python version for the npm packagecantonese-romanisation.Cantonese romanization based onHong Kong Government Romanisation, which is widely adapted for assigning of names to HKID, streets and places.The pacakage also provides features ofpinyinsupporting the standards ofLSHKandYale.Demo is availablehere.Installpipinstallcantonese-romanisationUsagegetRomanfromcantoromanimportCantonesecantonese=Cantonese()print(cantonese.getRoman("梁國雄"))"""[['leung'], ['gwok', 'kwok'], ['hung']]"""print(cantonese.getLshk("梁國雄"))"""[['loeng4'], ['gwok3'], ['hung4']][['leung4'], ['gwok3'], ['hung4']]"""print(cantonese.getYale("梁國雄"))"""[['loeng4'], ['gwok3'], ['hung4']][['leung4'], ['gwok3'], ['hung4']]"""print(cantonese.pingyam("leung kwok hung",'roman'))"""[['俍', '倞', '啢', '啢', '喨', '悢', '惊', '椋', '湸', '綡', '緉', '緉', '蜋', '裲', '踉', '踉', '輬', '駺', '魎', '両', '亮', '倆', '兩', '梁', '樑', '涼', '粱', '糧', '良', '諒', '輛', '量', '娘'], ['嘓', '囗', '墎', '壙', '夼', '崞', '彉', '彉', '彏', '慖', '懭', '桄', '槨', '漍', '爌', '玃', '矌', '矍', '穬', '簂', '籗', '絖', '纊', '聝', '膕', '貜', '躩', '躩', '钁', '霩', '霩', '鞹', '馘', '廓', '國', '幗', '蟈', '郭', '擴', '漷'], ['仜', '倥', '倥', '倥', '哅', '嗊', '妅', '忷', '恟', '悾', '愩', '洚', '涳', '渱', '澒', '灴', '焢', '玒', '硿', '箜', '篊', '羾', '舼', '芎', '蕻', '蕻', '谼', '谾', '闀', '霟', '鞚', '魟', '齁', '烘', '兇', '凶', '匈', '哄', '孔', '崆', '恐', '控', '汞', '洪', '洶', '熊', '空', '紅', '胸', '葒', '虹', '訌', '雄', '鬨', '鴻', '黌', '吽']]"""print(cantonese.pingyam("loeng4 gwok3 hung4",'lshk'))"""[['俍', '椋', '綡', '蜋', '踉', '輬', '駺', '梁', '樑', '涼', '粱', '糧', '良', '諒', '量', '莨'], ['嘓', '囗', '墎', '崞', '彉', '彏', '慖', '槨', '漍', '玃', '矍', '簂', '聝', '膕', '貜', '躩', '钁', '霩', '馘', '攫', '摑', '廓', '國', '幗', '蟈', '郭', '擴', '漷'], ['仜', '妅', '洚', '渱', '玒', '篊', '羾', '舼', '蕻', '谼', '霟', '魟', '烘', '洪', '熊', '紅', '葒', '虹', '訌', '雄', '鴻', '黌']]"""print(cantonese.pingyam("leung4 gwok3 hung4",'yale'))"""[['俍', '椋', '綡', '蜋', '踉', '輬', '駺', '梁', '樑', '涼', '粱', '糧', '良', '諒', '量', '莨'], ['嘓', '囗', '墎', '崞', '彉', '彏', '慖', '槨', '漍', '玃', '矍', '簂', '聝', '膕', '貜', '躩', '钁', '霩', '馘', '攫', '摑', '廓', '國', '幗', '蟈', '郭', '擴', '漷'], ['仜', '妅', '洚', '渱', '玒', '篊', '羾', '舼', '蕻', '谼', '霟', '魟', '烘', '洪', '熊', '紅', '葒', '虹', '訌', '雄', '鴻', '黌']]"""DictionaryIf you would like to update the dictionary, you may checkout thedictionary.ContributeProject ownerchunlawis the initiator of the whole project. Everyone is welcome to contribute.LicenseMIT license
Package: cantoseg
cantosegCantonese segmentation tool 粵語分詞工具Install$pipinstallcantosegUsage>>>importcantoseg>>>cantoseg.cut('香港喺舊石器時代就有人住')['香港','喺','舊石器時代','就','有人','住']A generator version is also available:cantoseg.lcut.DesignSee articleCantonese Segmentation and Part-Of-Speech Tagging(in Chinese).
Package: canvas-api-cli
Canvas API WrapperThis is a CLI wrapper around theCanvas LMS APIInstallationInstallation requires Python 3.10$ pip install canvas-api-cli$ canvas --helpConfigurationThe config file should be located at$HOME/.config/canvas.toml, and look something like this:[instance]default="<nickname>"[instance.<nickname>]domain="domain.instructure.com"token="<API TOKEN>"To test that it's configured properly you can execute$ canvas get users/selfAnd confirm that the output is for your userCanvas InstancesEach customer or entity that Instructure deals with is given their own Canvas instance with a unique domain name. Each instance is added to your configuration like so:[instance.<nickname>]domain="domain.instructure.com"token="<API TOKEN>"The Canvas instance to use can then be selected when running a query$ canvas get users/self -i <nickname>If no instance is specified then the default will be used. If the configuration does not have a default, then you must specific an instance with every query[instance]default="<nickname>"[instance.<nickname>]domain="domain.instructure.com"token="<API TOKEN>"UsageYou can query Canvas endpoints using thequerysubcommand and it's aliases (get,post,putanddelete)$ canvas get <endpoint>Theendpointparameter will simply be the unique part of the API url.
For example: The URL:https://canvas.instructure.com/api/v1/accounts/:account_id/userswould be queried as$ canvas get accounts/:account_id/usersQuery ParametersQuery Parameters are added using the-qoption$ canvas get :course_id/assignments -q include[]=submission -q all_dates=trueRequest BodyThe request body for POST or PUT requests is passed in via the-doptionEither as a JSON string:$ canvas put courses/:course_id/assignments/:assignment_id  -d '
     {
       "assignment": {
         "name": "New Test Name"
       }
     }
     'Or a filename$ canvas put courses/:course_id/assignments/:assignment_id  -d @file.jsonPipingWhen you pipe the output ofcanvasto another program, syntax highlighting will not be added. This is convenient, because it allows you to pipe to other programs likejqvery easily.
Additionally, any info that is not the JSON response from Canvas is written tostderrinstead ofstdout, so you don't have to worry abou thoseThe JSON output will still be formatted. If you want to disable all of that you can use the--rawflag
Package: canvasautorubric
Canvas Auto RubricPlease find the detailed documentationhere.canvasautorubric- Sync the rubric on canvas.canvasautoplot- Plot the grade distribution.Installation(choose one of these methods)Install as a Python Librarypip3installgit+https://github.com/tc-imba/canvas-auto-rubric.git@masterLocal Install or Debuggitclonegit@github.com:tc-imba/canvas-auto-rubric.gitcdcanvas-auto-rubric# you can setup a virtual python env before install herepip3install-e.LicenceApache 2.0Dependenciescanvasapi==1.0.0clickpbrlogzeroscipypandasopenpyxlamatplotlibenlighten
Package: canvascli
canvasclicanvasclidownloads grades from Canvas,
converts them into the format required
for final submission to the FSC at UBC,
and creates a few helpful visualizations.Installationcanvasclirequires a recent version of Python and its package managerpip.
After installing those (e.g. via miniconda),
you can run this command from your terminal.python-mpipinstall-UcanvascliUsageAllcanvasclifunctionality requires that you havecreated an Canvas API access
token,
so do that first if you don't have one already.When runningcanvascli,
you can either paste your Canvas token when prompted at the command line
(ideally using a password manager, e.g.KeePassXC),
orstore it in an environment variablenamedCANVAS_PAT.Typingcanvascliat the command prompt will show the general help message
including the available sub-commands.
The most common use case
is probably to prepare final grades for FSC submission,
which you can do like so:canvascliprepare-fsc-grades--course-id53665This will save a CSV file in the current directory
which can be uploaded to the FSC.
The file should automatically be correctly formatted,
but it is a good idea to double check
in case there are unexpected changes
to how UBC inputs course info on Canvas.canvasclidrops students without a grade by default,
and creates a few helpful visualizations of the final grades
and assignment scores.
Runcanvascli prepare-fsc-grades --helpto view all available options.If you don't know the Canvas course id of your course,canvasclican check for you:canvasclishow-coursesThis will output a table with all the courses
your API token has access to.
Runcanvascli show-courses --helpto view all available options.Shell completion (optional, click to expand)If you want suggestions for subcommands and option flags when you pressTAByou can download the corresponding completion file
from the GitHub repository
and source it in your terminal's configuration file.
If you don't want to do this manually,
you can run one of the following commands
(don't forget to restart your shell afterwards).ZshFirst make sure that your zsh general shell completion enabled
by addingautoload -Uz compinit && compinitto your.zshrc;
it is important that this line is added before running the command below.curl-Sshttps://raw.githubusercontent.com/joelostblom/canvascli/main/canvascli-complete.zsh>~/.canvascli-complete.zsh&&echo". ~/.canvascli-complete.zsh">>~/.zshrcBashBash shell completion requires bash >= 4.0
(notably macOS ships with 3.x so use zsh instead).
If you are using GitBash for Windows,
change.bashrcto.bash_profilein the command below,
and note that you will only get shell completion after typingcavascli,
notcanvascli.exe.curl-Sshttps://raw.githubusercontent.com/joelostblom/canvascli/main/canvascli-complete.bash>~/.canvascli-complete.bash&&echo". ~/.canvascli-complete.bash">>~/.bashrcQuestions and contributingQuestions and contributions are welcome!
The best way to get in touch is toopen a new issue or discussion.
Remember to follow theCode of Conductwhen you participate in this project.
Package: canvas-client
Canvas clientA python client for grading canvas submissions.InstallMake sure you have installedpipandpython3Install the client:pip install canvas_clientSetupCreate and open a folder where you want to download the submissionsCreate aconfig.jsonfile by runningcanvas_clientin terminal (the config will be saved in the current folder)Fill the config properly (see the notes below):e.g:{
      "url": "canvas.university.edu",
      "access_token": "1234abcdef",
      "course_id": 157,
      "labs": {
          "L1": {
              "assignment_id": 1024
          },
          "L2": {
              "assignment_id": 1025
          }
      }
  }Note$^1$: you can find thecourse idandassingment idby opening the approriate assingment in canvas:Note$^2$: to get anaccess token: open canvas, go toYour profile->Settings->New access token->Generate Token-> copy the valueUsageDownload the submissions:canvas_client <assingment name> -de.g.:canvas_client L1 -dThis command downloads the submissions into theassigmentsfolder and creates anL1.xlsfile with the student names, comments, etc. Write the grades and comments into this file.To upload the grades and comments:canvas_client <assingment_name> -ue.g.:canvas_client L1 -uThis command uploads the content of theL1.xlsNote: the grades will appear on canvas after 10-15 seconds (refresh the page if necessary)
Package: canvas-cppgrader
This project aims at creating a toolkit for grading C/C++ submissions from Canvas LMS. The toolkit consumes a directory containing submissions and outputs a filtered, regorgainzed artifact and build reports.WarningThis project is under developmentTODOAdd support for multiple submissions per studentAdd more flexible anti-plagiarism techniques.Add support for multiple programming languagesAdd support for build systems other than Makefile/CMakeAdd support for cmdline arguments such asCXX_STANDARD