Saravanan666/pypi-org huggingface dataset:
Package: access-logs-local
Load the content of gzipped Apache HTTP log files
Exclude bots, scrapers, etc., select URLs matching the provided regex(es), and generate a CSV of the relevant log entries.Take postprocessed logs and strip out multiple hits in sessions, and
resolve URLs to the chosenURI_SCHEME(e.g.info:doi).We strip out entries where the same (IP address * user agent) pair has accessed
a URL within the lastSESSION_TIMEOUT(e.g. half-hour)Additionally, we convert the URLs to ISBNs and collate request data by date,
outputting a CSV for ingest via the stats system.Release Notes:[0.0.7] - 2024-01-05Changed:Deletion of the spiders filter inprocess_download_logs.py[0.0.6] - 2023-08-13Changed:Refactored driver logicbreaking| Changed parameters for theRequest.__init__()methodRemovedre_match_dictparameterAddedtimestampanduser_agentparametersChanged Request.timestamp from typetimetodatetimeChanged LogStream to use the newRequest.__init__()Expanded range forLogStream.logfile_nameslogic to include files
within 1 day of the search_dateLogStream.lines()yieldsRequestobjects, notstrvaluesLogStream.filter_in_line_request()only yields one line per measure[0.0.5] - 2023-07-03Changed:Added start_date and end_date for searching in the log filesAdded the measure_uri to the result[0.0.4] - 2023-07-31Changed:Update file structure and name of the driver[0.0.3] - 2023-07-25Changed:Update requirementsUpdate using a pyproject.toml file as well as the new deployment structure[0.0.2] - 2023-07-11Added:UnittestsChanged:Moved the files out of the package and get the file’s data as parameters and return the filtered data.renamed the plugin to access-logs-local
Package: accessmysqlconverter
AccessMySQLConverterAccessMySQLConverter aims to provide a tool which converts MS Access database files (.mdb, .accdb) into a SQL file (compatible with PostgreSQL, MariaDB and MySQL) that can be run, generating It's structure (tables, ERM...) and It's dataInstallationTo install it you must have Python 3.x installed and run in the command promptpip install --no-cache-dir --upgrade accessmysqlconverterRun itFor executing the program run in the command prompt the following instructionpython -m accessmysqlconverter.applicationThe tool is limited by the driver so after converting an Access Database you should look for:Nullability of columns and Default valuesCheck ERM for missing 1:1, 1:N or N:NCollation, character setForeign Keys ON DELETE actionsLicenseSeeLICENSEfor more informationDonations
Package: access-niu
[![Build Status](https://travis-ci.org/accessai/access-niu.svg?branch=master)](https://travis-ci.org/accessai/access-niu)[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)# access-niuThis repository contains application to train models for Image classification and Regression tasks.## Tasks- [x] Create a basic app for training and inference- [ ] Support for training regression models- [ ] Support of training multi input/output models- [ ] Incorporate Bayesian Inference for finding uncertainty in the predictions.- [ ] Create Docker Image- [ ] Support for serving the application with gunicorn- [ ] Anything else?## Installation```bashpip install access-niu```## Training```bashpython -m access_niu.train --template access_niu/sample/colors/sample_template.yml```## Inference```bashpython -m access_niu.wsgi --project ./colors```Now use this curl command to parse```bashcurl -X POST \http://localhost:8000/parse \-F data=@image_leisure_0.jpg```## References- This project is inspired from [RASA-NLU](https://github.com/RasaHQ/rasa) project.
Package: access-outlook-email
Access Outlook EmailThis project contains the basic files to send and save an email/attachment through the moduleexchangelib.InstallationNote that the module requiresPython 3.6or higher.To install the module, run a pip command like the following:pip install access_outlook_emailUsage create_accountSimply import the modules via the following import statements:from accessOutlookEmail import create_account
account = create_account('user@provider.com', '***')Thecreate_accountfunction requires your Outlook-Exchange email-address and your password.Usage sendSimply import the modules via the following import statements:from accessOutlookEmail import send_emailThesend_emailfunction requires your account, subject, body, recipients and optional attachments.To send an email, the following code provides the core functionality:send_email(account, 'TestSubject', 'TestBody', ['recepient@provider.com'], ['path/to/your/attachments'])Usage saveSimply import the modules via the following import statements:from accessOutlookEmail import save_attachmentThesave_attachmentfunction requires your Outlook Exchange Folder, which needs to be located in your inbox. Also it needs a path where to save and an exchangelib account.To save an attachment, the following code provides the core functionality:save_attachment(account, 'TestSubject', 'TestBody', ['recepient@provider.com'])LicenseThis project is licensed by a MIT License.Project statusThe current released version is 0.1.5.
Package: access-parser
AccessDB Parser (Pure Python)Microsoft Access (.mdb / .accdb) database files parser. The parsing logic is fully written in python and works without any external binary dependencies.InstallingUse pip:pip install access-parserOr install manually:gitclonehttps://github.com/ClarotyICS/access_parser.gitcdaccess_parser
python3setup.pyinstallDemoUsage Examplefromaccess_parserimportAccessParser# .mdb or .accdb filedb=AccessParser("/path/to/mdb/file.mdb")# Print DB tablesprint(db.catalog)# Tables are stored as defaultdict(list) -- table[column][row_index]table=db.parse_table("table_name")# Pretty print all tablesdb.print_database()Known IssuesThis library was tested on a limited subset of database files. Due to the differences between database versions and the complexity of the parsing we expect to find more parsing edge-cases.To help us resolve issues faster please provide as much data as you can when opening an issue - DB file if possible and full trace including log messages.ThanksThis library was made possible by the great work by mdb-tools. The logic in this library heavily relies on the excellent documentation they havehttps://github.com/brianb/mdbtoolsHuge thanks to Mashav Sapir for the help debugging, CRing and contributing to this projecthttps://github.com/mashavs
Package: access-parser-c
AccessDB Parser (Pure Python)Microsoft Access (.mdb / .accdb) database files parser. The parsing logic is fully written in python and works without any external binary dependencies.InstallingUse pip:pip install git+https://github.com/McSash/access_parser_cOr install manually:gitclonehttps://github.com/McSash/access_parser_c.gitcdaccess_parser_c
python3setup.pyinstallDemoUsage Examplefromaccess_parser_cimportAccessParser# .mdb or .accdb filedb=AccessParser("/path/to/mdb/file.mdb")# Print DB tablesprint(db.catalog)# Tables are stored as defaultdict(list) -- table[column][row_index]table=db.parse_table("table_name")# Pretty print all tablesdb.print_database()Another Usage Examplefromaccess_parserimportAccessParserfromazure.storage.blobimportContainerClient# Download access file from azure blob storageBlobContainerClient=ContainerClient.from_connection_string("<StorageConnectionString>",container_name="<ContainerName>")access_object=BlobContainerClient.download_blob("<PathToFile>").readall()# Bytes object of .mdb or .accdb filedb=AccessParser(access_object)# Print DB tablesprint(db.catalog)# Tables are stored as defaultdict(list) -- table[column][row_index]table=db.parse_table("table_name")# Pretty print all tablesdb.print_database()Known IssuesOLE fields are currently not supportedOnly a subset of memo fields are parsedThis library was tested on a limited subset of database files. Due to the differences between database versions and the complexity of the parsing we expect to find more parsing edge-cases.To help us resolve issues faster please provide as much data as you can when opening an issue - DB file if possible and full trace including log messages.ThanksThis fork was made possible by the great work by claroty:https://github.com/claroty/access_parser
Package: access-sftp-server
Access SFTP ServerThis project contains the basic files to up- and download files from a SFTP Server.For further information contactValentin Baier.InstallationThe installation can be achieved by usingpip:python -m pip install access_sftp_serverRun via ShellTo run the application via shell you need to either execute:python -m cibc_sftp_server.upload_filesorpython -m cibc_sftp_server.download_filesUsageThe package can be executed from any computer having the required credentials to the server.LicenseThis project is licensed by a MIT License.Project statusThe current released version is 0.1.0.
Package: access-spotify
access_spotifyThis project is for all the music obsessives out there.It will eventually evolve into a package that offers advanced functionality for utilizing the Spotify API.Currently, the CLI interface queries Spotify for the specified artist (default = 'The Beatles' because who else?) and
downloads all the album art, and all the album audio features and analysis for the artist.You can also import individual album data directly into a data-frame via a script or notebook.The album audio features and analysis are pickled as separate data-frames, which can then be read into
pandas and analyzed, visualized etc.It is recommended that the user work in their own virtual environment.Get your own Client_ID and Client_Secret fromhttps://developer.spotify.com/dashboard/applicationsFor detailed information on the API and what audio features and audio analysis you can get via this script, please
refer tohttps://developer.spotify.com/documentation/web-api/reference/tracks/Installation and UsageInstall the access-spotify packagepip install access-spotifySee the help menuaccess_script.py --helpQuery the Spotify API via CLIaccess_script.py --artist_name 'Led Zeppelin' --client_id 'your-client-id' --client_secret 'your-client-secret'This saves all the album art (high resolution) and album track information (audio features and audio analysis)
into pickled data-frames in the data/ folder.Getting data for individual albums from the Spotify APISee the example notebook on GithubAlsoThis is still very new, and I will continue to update the Documentation, functionality and add unit tests.
Please let me know if you find any bugs or if you have any specific ideas for extending the functionality.To-DoDocumentationUnit testsImprove the argparse functionalityCool visualizations perhaps?Predictive Modeling? How sad will the next Radiohead album be?This project would not have been possible without Spotipy -->https://spotipy.readthedocs.io/en/2.13.0/-- Go buy them a coffee and give their github repo a star!
Package: accfifo
TODO: Provide a complete README fileUsageCheck tests to see examples.DevelopmentNix shell is provided:nix-shellYou can choose between different Python versions:nix-shell --arg python "\"python39\""
nix-shell --arg python "\"python310\""Once you are inside the Nix shell, you can then run Visual Studio Code:code .TestingIf you are inside the Nix shell:python test_accfifo.pyWithout entering the Nix shell, for Python 3.9:nix-shell --arg python "\"python39\"" --command "python test_accfifo.py"... and for Python 3.10:nix-shell --arg python "\"python310\"" --command "python test_accfifo.py"LicenseThis library is licensed underBSD 2-Clause.
Package: accinv
(acc)-1accinv - Python project for inverse modeling of accelerator latticesNote:This project is in proof-of-concept stage and therefore lacks more advanced features
of some of the implemented methods.In its current state, the package provides functionality for inverse modeling of linear optics
via fitting of orbit response matrix (ORM) data, typically referred to as linear optics
from closed orbits. It supportscpymadas a backend.The main class isaccinv.loco.Locowhich requires one of the models fromaccinv.model, as well as
a method for computing Jacobians, as an argument.
Two methods for Jacobian computation are available.AnalyticalJacobianMethod: This method uses an analytical formula to compute the Jacobian of the ORM
with respect to quadrupole gradient errors and BPM and steerer gain errors. The data for the
analytical formula is obtained from a single Twiss call for the current lattice configuration.NumericalMJacobianMethod: This method uses a finite difference approximation scheme to compute the Jacobian of
the ORM with respect to the quadrupole gradient errors. Thus, the number of ORMs that will be computed
is proportional to the number of quadrupoles.The inverse modeling process can be started by creating aLocoobject and calling itsrunmethod:fromaccinv.jacobianimportAnalyticalJacobianMethodfromaccinv.locoimportLoco,OrmMeasurementfromaccinv.modelimportMadxmodel=Madx(path='path/to/script.madx')loco=Loco(model_and_jacobian_method=(model,AnalyticalJacobianMethod),quadrupoles=[...],# names of quadrupoleshbpms=[...],# names of horizontal BPMshsteerers=[...],# names of horizontal steerersvbpms=[...],# names of vertical BPMsvsteerers=[...],# names of vertical steerersorm_measurement=OrmMeasurement(orm=np.load('path/to/measured_orm.npy'),uncertainty=np.load('path/to/orm_uncertainty.npy'),),)result=loco.run()Please consider the documentation of theLococlassfor more details.
Package: accio-api
模块类的设计Request.py封装request方法，可以支持多协议扩展（get\post\put）Config.py读取配置文件，包括：不同环境的配置，email相关配置Log.py封装记录log方法，分为：debug、info、warning、error、criticalEmail.py封装smtplib方法，运行结果发送邮件通知Assert.py封装assert方法Hash.py封装常用加密方法Session.py封装获取登录cookies方法run.py核心代码。定义并执行用例集，生成报告
Package: acclaim-badges
Issue badges from Acclaim upon edx course completion.Acclaim Badges for EDXOverviewAdds a djangoapp to edx which provides a UI and API backend into Acclaim.  Once installed, EDX adminstrators
will be able to add Acclaim auth tokens and select badges to be issued upon course completion.  This app
then listens for course complete events, and issues badges if the student obtains a passing score.InstallInstall “acclaim_badges” using pip:pip install acclaim_badgesAdd “acclaim_badges” to your INSTALLED_APPS setting for EDX lms like this:INSTALLED_APPS = [
    ...
    'acclaim_badges',
]Note: this file is usually located at/edx-platform/lms/envs/common.pyInclude the acclaim_badges URLconf in your project urls.py like this:urlpatterns += (
    url(r'^acclaim/', include('acclaim_badges.urls')),
)The authorization token field is encypted.  create a AES-256 keyset using keyzar:$ mkdir fieldkeys
$ keyczart create --location=fieldkeys --purpose=crypt
$ keyczart addkey --location=fieldkeys --status=primary --size=256Add keyset location to/edx-platform/lms/envs/common.py:ENCRYPTED_FIELDS_KEYDIR = '/path/to/fieldkeys'Run./manage.py lms syncdb--settingsawsto create the acclaim_badges lms app.UsageThe following useful URLs are made available after installation:/acclaim/tokens//acclaim/badge-courses/Add Acclaim organization and authorization token using/acclaim/tokens/Define a mapping between badge and course by accessing/acclaim/badge-courses/Note: when defining a mapping, the dropdown will populate with badge templates
if the Acclaim API call is successful (valid token and orgainzation combination are used).DocumentationThe full documentation is athttps://acclaim-badges.readthedocs.org.LicenseThe code in this repository is licensed under the AGPL 3.0 unless
otherwise noted.Please seeLICENSE.txtfor details.How To ContributeContributions are very welcome.Please readHow To Contributefor details.Even though they were written withedx-platformin mind, the guidelines
should be followed for Open edX code in general.PR description template should be automatically applied if you are sending PR from github interface; otherwise you
can find it it atPULL_REQUEST_TEMPLATE.mdIssue report template should be automatically applied if you are sending it from github UI as well; otherwise you
can find it atISSUE_TEMPLATE.mdReporting Security IssuesPlease do not report security issues in public. Please emailsecurity@edx.org.Getting HelpHave a question about this repository, or about Open edX in general?  Please
refer to thislist of resourcesif you need any assistance.Change LogUnreleased[0.1.0] - 2017-05-10AddedFirst release on PyPI.
Package: accli
Accelerator terminal CLI and python APIUser GuideRequirementsPython >=3.7.17Installationpip install accli --userUsage as modulepython -m accliUsage as executableYou might receive following similar warning during installationWARNING: The script accli.exe is installed in 'C:\Users\singhr\AppData\Roaming\Python\Python311\Scripts' which is not on PATH.
  Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.You could also add executable directory path in PATH environment variable. Please follow following links for instruction on adding executable directory path to PATH environemnt variable.Updating PATH on windowsUpdating PATH on linuxCommandaccli --helpOutputUsage: accli [OPTIONS] COMMAND [ARGS]...Note: You may need to prepend the command with either./(in linux) or.\(in winodws).Developer GuideGeneral build and upload instructionsPlease followthis link.Release processCommit with right version on accli/_version.pyRun 'python scripts/tag.py'python -m build
Package: acc-lib
Acc LibAccelerator physics library containing plotting tools and other useful methods to handle data from X-suite tracking and other beam dynamics software, in constant evolution along with my PhD projects.Installation can be easily done via:pip install acc_libThe classplot_toolscontains several plotting methods to illustrate the turn-by-turn data generated by X-suite trackers, including centroid evolution, phase space distributions, Twiss parameters, simple FFT and tune footprint.The classresonance_lines, based upon the base class from Foteini Asvesta, contains methods to plot resonance lines of a given order in a given interval for tune plots. In particular, the methodplot_resonance_and_tune_footprintallows to print the tune footprint from X-suite tracking together with the resonance lines of a given order.The classparticlesallows to display particle properties.The classmadx_toolscontains methods to print errors from a crashed MAD-X process, print the elements neatly, plot the beam envelope, get the realistic apertures for both starting and end points of each element, and to plot the aperture together with the beam envelope.The classfootprint, inspired bythis X-suite example, allows for convenient plotting of footprints of coordinates in Cartesian/polar, but also of the tunes.
Package: acclimatise
For the full documentation, refer to theGithub Pages Website.Acclimatise is a Python library and command-line utility for parsing the help output
of a command-line tool and then outputting a description of the tool in a more
structured format, for example aCommon Workflow Language tool definition.Currently Acclimatise supports bothCWLandWDLoutputs, but other formats will be considered in the future, especially pull
requests to support them.ExampleLets say you want to create a CWL workflow containing the common Unixwc(word count)
utility. Runningwc--helpreturns:Usage: wc [OPTION]... [FILE]...
  or: wc [OPTION]... --files0-from=F
Print newline, word, and byte counts for each FILE, and a total line if
more than one FILE is specified.  A word is a non-zero-length sequence of
characters delimited by white space.

With no FILE, or when FILE is -, read standard input.

The options below may be used to select which counts are printed, always in
the following order: newline, word, character, byte, maximum line length.
  -c, --bytes            print the byte counts
  -m, --chars            print the character counts
  -l, --lines            print the newline counts
      --files0-from=F    read input from the files specified by
                           NUL-terminated names in file F;
                           If F is - then read names from standard input
  -L, --max-line-length  print the maximum display width
  -w, --words            print the word counts
      --help display this help and exit
      --version output version information and exit

GNU coreutils online help: <http://www.gnu.org/software/coreutils/>
Full documentation at: <http://www.gnu.org/software/coreutils/wc>
or available locally via: info '(coreutils) wc invocation'If you runacclimatise explore wc, which means “parse the wc command and all subcommands”,
you’ll end up with the following files in your current directory:wc.cwlwc.wdlwc.ymlThese are representations of the commandwcin 3 different formats. If you look atwc.wdl, you’ll see that it
contains a WDL-compatible tool definition forwc:version 1.0
task Wc {
  input {
    Boolean bytes
    Boolean chars
    Boolean lines
    String files__from
    Boolean max_line_length
    Boolean words
  }
  command <<<
    wc \
      ~{true="--bytes" false="" bytes} \
      ~{true="--chars" false="" chars} \
      ~{true="--lines" false="" lines} \
      ~{if defined(files__from) then ("--files0-from " +  '"' + files__from + '"') else ""} \
      ~{true="--max-line-length" false="" max_line_length} \
      ~{true="--words" false="" words}
  >>>
}
Package: accorder
Accorder takes care of various tasks which Memory of the World amateur librarians do in order to maintain their shared catalogs online. It builds searchable, standalone, portable webapp which one could then just copy to USB disk and open BROWSE_LIBRARY.html in her web browser. It uploads all of the books and metadata from local Calibre’s library (together with portable webapp) to the server. It helps a librarian to maintain and share her catalog athttps://library.memoryoftheworld.orgtogether with other amateur librarians. It does all of above in one go by typing: accorder release PROFILE. The configuration file will keep information about one or more PROFILE. Under every PROFILE’s configuration section there will be information about the directory path of local Calibre’s library, librarian’s name, credentials needed to upload the files to the destination server etc.