Saravanan666/pypi-org huggingface dataset:
Package: diffxpy
|PyPI| |Docs|.. |PyPI| image::https://img.shields.io/pypi/v/diffxpy.svg:target:https://pypi.org/project/diffxpy.. |Docs| image::https://readthedocs.com/projects/diffxpy/badge/?version=latest:target:https://diffxpy.readthedocs.ioFast and scalable differential expression analysis on single-cell RNA-seq datadiffxpy covers a wide range of differential expression analysis scenarios encountered in single-cell RNA-seq scenarios
and integrates into scanpy_ workflows.
Import diffxpy asimport diffxpy.api as deto access the following differential expression analysis-related tools:differential expression analysisin the modulede.test.*gene set enrichment analysisbased on differential expression calls in the modulede.enrich.*Refer to the documentation_ and the tutorials_ for details of these modules... _scanpy:https://github.com/theislab/scanpy.. _documentation:https://diffxpy.rtfd.io/en/latest.. _tutorials:https://diffxpy.rtfd.io/en/latest/tutorials.html
Package: diffy
Diffy is a digital forensics and incident response (DFIR) tool developed by
Netflix’s Security Intelligence and Response Team (SIRT).Diffy allows a forensic investigator to quickly scope a compromise across cloud
instances during an incident, and triage those instances for followup actions.
Diffy is currently focused on Linux instances running within Amazon Web
Services (AWS), but owing to our plugin structure, could support multiple
platforms and cloud providers.It’s called “Diffy” because it helps a human investigator to identify thedifferencesbetween instances, and becauseAlexpointed out that “The
Difforensicator” was unnecessarily tricky.SeeReleasesfor recent changes. Seeour Read the Docs sitefor
well-formatted documentation.Supported TechnologiesAWS (AWS Systems Manager / SSM)LocalosqueryEach technology has its own plugins for targeting, collection and persistence.FeaturesEfficiently highlights outliers in security-relevant instance behavior. For
example, you can use Diffy to tell you which of your instances are listening
on an unexpected port, are running an unusual process, include a strange
crontab entry, or have inserted a surprising kernel module.Uses one, or both, of two methods to highlight differences:Collection of a “functional” baseline from a “clean” running instance,
against which your instance group is compared, andCollection of a “clustered” baseline, in which all instances are surveyed,
and outliers are made obvious.Uses a modular plugin-based architecture. We currently include plugins for
collection using osquery via AWS Systems Manager (formerly known as Simple
Systems Manager or SSM).InstallationVia pip:pip install diffyRoadmapWe are actively adding more plugins & tests, and improving the documentation.Why python 3 only?Please seeGuido’s guidanceregarding the Python 2.7 end of life date.
Package: difio-appfog-python
Difio registration agent for AppFog / Python applications.It compiles a list of locally installed Python packages and sends it to
<http://www.dif.io>.Installing on your AppFog applicationCreate an account at <http://www.dif.io>Create a Python application on AppFogAdd a dependency in your requirements.txt fileecho "difio-appfog-python" >> requirements.txtConfigure your Difio user IDaf env-add <appname> DIFIO_USER_ID=YourUserIDBecause AppFog doesn’t support post deploy hooks you have NO WAY to enable the
registration script. :(Then push your application to AppFogaf update <appname>That’s it, you can now check your application statistics at
<http://www.dif.io>
Package: difio-cloudcontrol-python
Difio registration agent for cloudControl / Python applications.It compiles a list of locally installed Python packages and sends it to
<http://www.dif.io>.Installing on your cloudControl applicationCreate an account at <http://www.dif.io>Create a Python application on cloudControlAdd a dependency in yourrequirements.txtfileecho 'difio-cloudcontrol-python' >> requirements.txtThen commit, push and deploy your application to cloudControlgit commit -a -m "added dependency on Difio"
cctrlapp APP_NAME push
cctrlapp APP_NAME deployConfigure your user credentialscctrlapp APP_NAME/DEP_NAME addon.add config.free --DIFIO_USER_ID=YourUserIDExecute the registration script to submit the information to Difiocctrlapp APP_NAME/DEP_NAME run /app/.heroku/venv/bin/difio-cctrl-python
Running `/app/.heroku/venv/bin/difio-cctrl-python` attached to terminal... up, run.1
Success, registered/updated application 8370e3be-6e54-462d-9ca9-224301c29a1dThat’s it, you can now check your application statistics at
<http://www.dif.io>Updating your requirements.txtWhenever you change yourrequirements.txtfile to include new
dependencies or upgrade/downgrade package versions you should
re-submit the information to Difio.cctrlapp APP_NAME/DEP_NAME run /app/.heroku/venv/bin/difio-cctrl-python
Package: difio-dotcloud-python
This is a registration agent for Difio preconfigured for
Python applications on DotCloud.It compiles a list of locally installed Python packages and
sends it tohttp://www.dif.io.Installing on your dotCloud applicationCreate an account athttp://www.dif.ioCreate your Python application on dotCloudConfigure your Difio userID. You can get it fromhttps://difio-otb.rhcloud.com/profiles/mine/.dotcloud var set <app name> DIFIO_USER_ID=UserIDGenerate a unique identifier for this application and save the value as environmental variable.dotcloud var set <app name> DIFIO_UUID=`uuidgen`Add a dependency in yourrequirements.txtfileecho difio-dotcloud-python >> requirements.txtEnable the registration script in your postinstall hook.Note:If you are using an “approot” yourpostinstallscript should be in the
directory pointed by the “approot” directive of yourdotcloud.yml.
For more information aboutpostinstallturn tohttp://docs.dotcloud.com/guides/postinstall/.If a file namedpostinstalldoesn’t already exist, create it and add the following:#!/bin/sh
/home/dotcloud/env/bin/difio-dotcloud-pythonMakepostinstallexecutablechmod a+x postinstallCommit your changes (if using git):git add .
git commit -m "enable Difio registration"Then push your application to dotClouddotcloud push <app name>If everything goes well you should see something like:19:55:10 [www.0] Running postinstall script...
19:55:13 [www.0] response:200
19:55:13 [www.0] Difio: Success, registered/updated application with uuid ac5a3741-a564-4e59-aad2-3f51ea860521That’s it, you can now check your application statistics athttp://www.dif.io
Package: difio-heroku-python
Difio registration agent for Heroku / Python applications.It compiles a list of locally installed Python packages and sends it to
<http://www.dif.io>.Installing on your Heroku applicationCreate an account at <http://www.dif.io>Create a Python application on HerokuAdd a dependency in yourrequirements.txtfileecho 'difio-heroku-python' >> requirements.txtSet the following environment variables on Herokuheroku config:set DIFIO_USER_ID=YourUserID
heroku config:set DIFIO_APP_NAME=MyApplication
heroku config:set DIFIO_APP_URL=http://myapp.herokuapp.comThen commit and push your application to Herokugit commit -a -m "added dependency on Difio"
git push heroku masterExecute the registration script to submit the information to Difioheroku run /app/.heroku/venv/bin/difio-heroku-python
Running `/app/.heroku/venv/bin/difio-heroku-python` attached to terminal... up, run.1
Success, registered/updated application 8370e3be-6e54-462d-9ca9-224301c29a1dThat’s it, you can now check your application statistics at
<http://www.dif.io>Updating your requirements.txtWhenever you change yourrequirements.txtfile to include new
dependencies or upgrade/downgrade package versions you should
re-submit the information to Difio.heroku run /app/.heroku/venv/bin/difio-heroku-python
Package: difio-openshift-python
Difio registration agent for OpenShift / Python applications.It compiles a list of locally installed Python packages and sends it to
<http://www.dif.io>.Installing on your OpenShift applicationCreate an account at <http://www.dif.io>Create a Python application on OpenShiftrhc-create-app -a myapp -t python-2.6Add a dependency in your setup.py filefrom setuptools import setup

setup(
    name='MyApplication',
    version='1.0',
    install_requires=['difio-openshift-python'],
 )Set your userID in the ./data/DIFIO_SETTINGS filecd ./myapp/
echo "export DIFIO_USER_ID=YourUserID" > ./data/DIFIO_SETTINGSOpenShift by default will treat your application as a package. If the name given in
setup.py is different from the name passed to rhc-create-app command then
set the application name in the ./data/DIFIO_SETTINGS fileecho "export DIFIO_APP_NAME='MyApplication'" >> ./data/DIFIO_SETTINGSThis registration script will ignore package names that match the value of
OPENSHIFT_GEAR_NAME and DIFIO_APP_NAME environment variables.Enable the registration script in .openshift/action_hooks/post_deploy# Activate VirtualEnv in order to use the correct libraries
source $OPENSHIFT_HOMEDIR/python-2.6/virtenv/bin/activate

# Set user defined settings
source $OPENSHIFT_REPO_DIR/data/DIFIO_SETTINGS

# Register/update the application
python $OPENSHIFT_HOMEDIR/python-2.6/virtenv/bin/difio-openshift-pythonThen push your application to OpenShiftgit pushThat’s it, you can now check your application statistics at
<http://www.dif.io>
Package: difio-virtualenv-python
Difio registration agent for stand-alone Python virtualenv
applications.It compiles a list of locally installed Python packages and sends it tohttp://www.dif.io.Installing inside your virtualenvCreate an account athttp://www.dif.ioActivate your virtualenvif you’re usingvirtualenvwrapperthen simply:workon myappif you’re not usingvirtualenvwrapperthen something like this will work:cd ~/.virtualenvs/myapp/
source bin/activateInstall this packagepip install difio-virtualenv-pythonCreate a script which will contain your configuration values and register the application with Difio when executed. It should look something like this:#!/bin/bash
export DIFIO_USER_ID=YourUserID
export DIFIO_UUID=APP-UUID
$VIRTUAL_ENV/bin/difio-virtualenv-pythonNOTE:You can find your Difio userID athttps://difio-otb.rhcloud.com/profiles/mine/.ReplaceAPP-UUIDwith a unique value, for example generated by theuuidgenprogram!Make this script executablechmod a+x $VIRTUAL_ENV/path/to/registration_scriptIf you wish, you can configure$VIRTUAL_ENV/bin/postactivatehook to call the registration script every time when the virtualenv is activatedecho "\$VIRTUAL_ENV/path/to/registration_script" >> $VIRTUAL_ENV/bin/postactivate
chmod a+x $VIRTUAL_ENV/bin/postactivateExecute the registration script to register the application.$VIRTUAL_ENV/path/to/registration_scriptNOTE: You will have to do this every time when you install/remove or upgrade packages in the virtualenv.
Optionally you can configure a cron job to do this automatically.If everything goes well you should see something like:Difio: Success, registered/updated application with uuid 7a99f652-977a-477a-b35c-1d8e60478425That’s it, you can now check your application statistics athttp://www.dif.ioNotesDifio will use the basepath of your virtualenv as the application name. To override use environment variableDIFIO_APP_NAME;Packagevirtualenvwill also be added to the list of installed packages if you have created your virtualenv with--system-site-packagesoption. Otherwise use environment variableDIFIO_VIRTUALENV_VERSIONto override;Application type is “python” followed by the interpreter version;Application URL is the system hostname prepended withhttp://.  To override use environment variableDIFIO_APP_URLincluding the protocol string.
Package: dig
OverviewDig is a command-line program which now communicates with google/youdao
translation server. It can be used for look up the words or sentences through
google/youdao translation server.For more information including a list of features check the dig homepage at:https://github.com/enjoyhot/digRequirementsPython 3.+Docopt v0.6.2 is adopt for parsing arguments. Seehttps://github.com/docopt/docopt.Works on Linux, WindowsPython 2.7futures v3.0.3 is adopt for concurrence and compatibility. Seehttps://pypi.python.org/pypi/futures/.Docopt v0.6.2 is adopt for parsing arguments. Seehttps://github.com/docopt/docopt.Works on Linux, WindowsInstallThe quick way:pip install digAnother way:python setup.py install(Make sure your hardware platform install dependent packages)Releases HistoryYou can download the latest stable and development releases from:https://github.com/enjoyhot/dig/releases0.1.10** Bugfixes **TTS fits for Windows7 or Linux platform.0.1.9** Bugfixes **Update the dig for global Environment dos or shell.Important pointsYou should install mpg123 if your platform is Linux.Now only support google and youdao translation, make sure your computer can connect to google.com or youdao.com.ProblemsOnly for Win7: There was wrong when piping for requests packages, so download it individually.Community (github, email)Seehttps://github.com/enjoyhot/dig
Package: diga-olar
# Diga OlarCumprimente da forma mais estilosa possível## ObjetivoEste projeto tem o objetivo de aprender a empacotar projetos Python e aprender a nomear no que tange à nomenclatura e detalhes de empacotamentoMais como uma anotação de como fazer um próximo pacote### ReferênciaUtilizei o tutorial oficial do Python:https://packaging.python.org/tutorials/packaging-projects/
Package: digautoprofiler
Profile yourPandasDataframes! Autoprofiler will automatically visualize your Pandas dataframes after every execution, no extra code necessary.Autoprofiler allows you to spend less time specifying charts and more time interacting with your data by automatically showing you profiling information like:Distribution of each columnSample valuesSummary statisticsUpdates profiles as your data updatesAutoprofiler reads your current Jupyter notebook and produces profiles for the Pandas Dataframes in your memory as they change.https://user-images.githubusercontent.com/13400543/199877605-ba50f9c8-87e5-46c9-8207-1c6496bb3b18.movInstallTo instally locally use pip and then open jupyter lab and the extension will be running.pipinstall-UdigautoprofilerPlease note, AutoProfiler only works inJupyterLabwith version >=3.x, < 4.0.0.Try it outTo try out Autoprofiler in a hosted notebook, use one of the options belowJupyter LiteBinderBrowser support:AutoProfiler has been developed and tested with Chrome.Development InstallFor development install instructions, seeCONTRIBUTING.md.If you're having install issues, seeTROUBLESHOOTING.md.AcknowledgementsBig thanks to the Rill Data team! Much of our profiler UI code is adapted fromRill Developer.CitationPlease reference ourVIS'23 paper:@article{epperson23autoprofiler,title={Dead or Alive: Continuous Data Profiling for Interactive Data Science},author={Will Epperson and Vaishnavi Goranla and Dominik Moritz and Adam Perer},journal={IEEE Transactions on Visualization and Computer Graphics},year={2023},url={https://arxiv.org/abs/2308.03964}}Let us know what you think! 📢We would love to hear your feedback on how you are using AutoProfiler! Please fill outthis formor email Will atwillepp@cmu.edu.
Package: digaws
digawsThe digaws lookup tool displays information for a given IP address (both v4 and v6) or a CIDR, sourced from the AWS official IP ranges.
In order to save bandwidth and time this tool requests theAWS IP rangesand keeps
a cached version until a new version is published.RequirementsPython >= 3.7Tests are verified on Linux, macos and Windows.InstallUsingpipx(this is the preferred way)pipxinstalldigawsUsing pippipinstalldigaws--userUsageusage: digaws [-h] [--output <plain|json>] [--output-fields [{prefix,region,service,network_border_group} ...]] [--debug] [--version] <ip address|cidr> [<ip address|cidr> ...]

Look up canonical information for AWS IP addresses and networks

positional arguments:
  <ip address|cidr>     CIDR or IP (v4 or v6) to look up

optional arguments:
  -h, --help            show this help message and exit
  --output <plain|json>
                        Formatting style for command output, by default plain
  --output-fields [{prefix,region,service,network_border_group} ...]
                        Print only the given fields
  --debug               Enable debug
  --version             show program's version number and exitExampleslook up an IPv4 address~ » digaws 52.218.97.130

Prefix: 52.218.0.0/17
Region: eu-west-1
Service: AMAZON
Network border group: eu-west-1

Prefix: 52.218.0.0/17
Region: eu-west-1
Service: S3
Network border group: eu-west-1look up an IPv6 address~ » digaws 2600:1f1e:fff:f810:a29b:cb50:2812:e2dc

IPv6 Prefix: 2600:1f1e::/36
Region: sa-east-1
Service: AMAZON
Network border group: sa-east-1

IPv6 Prefix: 2600:1f1e:fff:f800::/53
Region: sa-east-1
Service: ROUTE53_HEALTHCHECKS
Network border group: sa-east-1

IPv6 Prefix: 2600:1f1e::/36
Region: sa-east-1
Service: EC2
Network border group: sa-east-1look up several addresses and print output as json~ » digaws 2600:1f14::/36 13.224.119.88 --output json

[
  {
    "ipv6_prefix": "2600:1f14::/35",
    "region": "us-west-2",
    "service": "AMAZON",
    "network_border_group": "us-west-2"
  },
  {
    "ipv6_prefix": "2600:1f14::/35",
    "region": "us-west-2",
    "service": "EC2",
    "network_border_group": "us-west-2"
  },
  {
    "ip_prefix": "13.224.0.0/14",
    "region": "GLOBAL",
    "service": "AMAZON",
    "network_border_group": "GLOBAL"
  },
  {
    "ip_prefix": "13.224.0.0/14",
    "region": "GLOBAL",
    "service": "CLOUDFRONT",
    "network_border_group": "GLOBAL"
  }
]Choose output fields~ » digaws 34.255.166.63 --output-fields service

Service: AMAZON

Service: EC2
Package: digcommpy
# DigCommPy
Python3 package for digital communications simulations.It includes channel coding and different channel models. Simulations can be run
to calculate bit/block error rates for different configurations.# Installation
The package can be installed using pip with the commandpip install
digcommpy.Alternatively, you can clone the Gitlab repository and install the local copy
using the following commands:git clonehttps://gitlab.com/klb2/digcommpy.gitcd digcommpy
pip install .# Usage
There are multiple example files in theexamplesfolder.## Basic Encoding/Decoding Example
A simple encoding example using a polar code:`python from digcommpy import messages, encoders n, k = 16, 4 encoder = encoders.PolarEncoder(n, k, "BAWGN", 0.) mess = messages.generate_data(k, number=1000, binary=True) codewords = encoder.encode_messages(mess) `A full transmission chain can be simulated as follows:`python from digcommpy import messages, encoders, decoders, channels, modulators, metrics # Parameters n, k = 16, 4 snr = 5.  # dB # Blocks encoder = encoders.PolarEncoder(n, k, "BAWGN", snr) modulator = modulator.BpskModulator() channel = channels.BawgnChannel(snr, rate=k/n) decoder = decoders.PolarDecoder(n, k, "BAWGN", snr) # Simulation mess = messages.generate_data(k, number=1000, binary=True) codewords = encoder.encode_messages(mess) channel_input = modulator.modulate_symbols(codewords) channel_output = channel.transmit_data(channel_input) est_mess = decoder.decode_messages(channel_output) ber = metrics.ber(mess, est_mess)print("TheBER is{}".format(ber))`This can be simplified by using thesimulationsmodule from the
package (in progress).# Used Software
Some parts of this library are based on different open source implementations.
The polar code encoding and decoding code is based on the Matlab implementation
from Harish Vangala et al. (http://polarcodes.com/).
The implementation of some functions, e.g., the QAM-modulation are based on the
Octave communications package (https://octave.sourceforge.io/).
Package: digdaglog2sql
digdaglog2sqlInstallpipinstall--userdigdaglog2sqlor,$python-mvenv.venv
$source.venv/bin/activate(.venv)$pipinstalldigdaglog2sqlUsage$digdaglog2sql--help
Usage:digdaglog2sql[OPTIONS]Options:--inputFILENAMEOptionismutuallyexclusivewithsession_id,site.--session-idINTEGERSessionIDofworkflow.Optionismutuallyexclusivewithinput.--site[us|jp|eu01|ap02|ap03]Optionismutuallyexclusivewithinput.--outputFILENAME[required]--drop-cdp-dbIftrue,dropcdp_audience_xxxDBname.--helpShowthismessageandexit.You can use log file on local environment.digdaglog2sql--inputworkflow-log.txt--outputoutput.sqlOr, you can use Session ID of Treasure Workflow.digdaglog2sql--session-id12345--siteus--outputoutput.sqlEnsure setTD_API_KEYinto environment variable.NoteAs of May 5 2022, if you want to use sqllineage for Trino and Hive logs from Treasure Data,
recommend to install sqlparse and sqllineage as the following:pipinstallgit+https://github.com/chezou/sqlparse.git@trino#egg=sqlparse==0.4.3.dev0
pipinstallgit+https://github.com/chezou/sqllineage.git@trino#egg=sqllineage==1.3.4You have to ensure to have node environment for sqllineage installation from source.
Package: digdem
digdemDescriptionInstallationQuick startDescriptiondigdempackage can be used to modify semi-automatically Digital Elevation Models (or any raster data) in specific regions, using a limited number of
control points and control profiles. It follows the following steps:Create instance ofSurfModwith initial DEM, and an array specifying where the DEM will be modified;Generate controlling sections (typically longitudinal and transverse sections), and specify the new altitude of their intersections if any;Add additional control points along the sections by specifying their altitude, and if needed additional control points located within the mask but not on the sections;digdemthen interpolates the new DEM within the mask by:Interpolating splines along each sectionInterpolating the new DEM with Radial Basis Functions, using points along the splines, points on the contour of the mask, and if applicable additional control points within the mask.Plot the new topographyNote thatdigdemis still under development, thus only minimal documentation is available at the moment, and testing is underway.
Contributions are feedback are most welcome.Installationdigdemcan be installed from GitHub,PyPiorAnaconda. Supposedly stable releases are distributed to PyPi and Anaconda. Distribution to Anaconda is made manually from the PyPi package, thus the last available version on conda-forge may be an older version than the one distributed on PyPi.It is strongly recommended to installdigdemin a virtual environnement dedicated to this package. This can be done withvirtualenv(see the documentation e.g.here).
Create the environnement with :python-mvenv/path/to/myenvand activate it, on Linux:source/path/to/myenv/bin/activateand on Windows:\path\to\myenv\Scripts\activateAlternatively, if you are more used to Anaconda :condacreate-ndigdempip
condaactivatedigdemor equivalently with Mamba :mambacreate-ndigdempip
mambaactivatedigdemLatest stable release from AnacondaWith Anaconda:condainstalldigdemor equivalently with Mamba:mambainstalldigdemLatest stable realease from PyPiBefore installing withpip, make surepip,steuptoolsandwheelare up to datepython -m pip install --upgrade pip setuptools wheelThen runpython -m pip install digdemDevelopment version on from GitHubDownload the GithHub repositoryhere, or clone it withgit clone https://github.com/marcperuz/digdem.gitOpen a terminal in the created folder and type:python -m pip install .If you want to developp and testdigdemand have your modification directly taken into account when running your code, use:python -m pip install -e .Alternatively, if you don't want to install the package with pip, you can also add thesrcfolder to your Python path.Quick startSee jupyter notebooks in examples.