Saravanan666/pypi-org huggingface dataset:
Package: pulpo-forms
Pulpo Forms is a Django app capable of creating powerful surveys with many different field types, multi path logic for fields and pages and statistical analysis of responses.Quick StartAdd'pulpo_forms'to theINSTALLED_APPSof your project’s settings:INSTALLED_APPS = (
        # other apps
        'pulpo_forms',
)Add theFIELD_FILESto your project’s settings to include the provided fields, plus any other field defined in another app:FIELD_FILES = (
    'pulpo_forms.fieldtypes.TextField',
    'pulpo_forms.fieldtypes.TextAreaField',
    'pulpo_forms.fieldtypes.EmailField',
    'pulpo_forms.fieldtypes.CheckboxField',
    'pulpo_forms.fieldtypes.SelectField',
    'pulpo_forms.fieldtypes.GeoField',
    'pulpo_forms.fieldtypes.NumberField',
    'pulpo_forms.fieldtypes.CIField',
    'pulpo_forms.fieldtypes.FileField',
    'other_app.fields',
)Add'pulpo_forms.middlets.ValidationErrorToHttpErrorMiddleware'to theMIDDLEWARE_CLASSESof your project’s settings:MIDDLEWARE_CLASSES = (
        # other
        'pulpo_forms.middlets.ValidationErrorToHttpErrorMiddleware',
)Define the base url you want and add it to your project’s settings:FORMS_BASE_URL = '<base_url>'To configure the mail service the following variables must be defined in your settings file as well:EMAIL_HOST = <'MAIL_SERVER'>
EMAIL_HOST_USER = <'MAIL_ACCOUNT'>
EMAIL_HOST_PASSWORD = <'MAIL_PASSWORD'>
EMAIL_PORT = <PORT>
EMAIL_USE_TLS = TrueIn your project’surls.pyadd:urlpatterns = patterns('',
    # other patterns
    url(r'^<base_url>/', include('pulpo_forms.urls'), name='base'),
)Runpython manage.py migrateto create the app models
Package: pulp-or
# Copyright J.S. Roy (js@jeannot.org), 2003-2005
# Copyright Stuart A. Mitchell (stu@stuartmitchell.com)
# See the LICENSE file for copyright information.PuLP is an LP modeler written in python. PuLP can generate MPS or LP files
and call GLPK[1], COIN CLP/CBC[2], CPLEX[3], and GUROBI[4] to solve linear
problems.See the examples directory for examples.PuLP requires Python >= 2.5.The examples require at least a solver in your PATH or a shared library file.Documentation is found onhttps://www.coin-or.org/PuLP/.
A comprehensive wiki can be found athttps://www.coin-or.org/PuLP/Use LpVariable() to create new variables. To create a variable 0 <= x <= 3
>>> x = LpVariable(“x”, 0, 3)To create a variable 0 <= y <= 1
>>> y = LpVariable(“y”, 0, 1)Use LpProblem() to create new problems. Create “myProblem”
>>> prob = LpProblem(“myProblem”, LpMinimize)Combine variables to create expressions and constraints and add them to the
problem.
>>> prob += x + y <= 2If you add an expression (not a constraint), it will
become the objective.
>>> prob += -4*x + yChoose a solver and solve the problem. ex:
>>> status = prob.solve(GLPK(msg = 0))Display the status of the solution
>>> LpStatus[status]
‘Optimal’You can get the value of the variables using value(). ex:
>>> value(x)
2.0Exported Classes:LpProblem – Container class for a Linear programming problemLpVariable – Variables that are added to constraints in the LPLpConstraint – A constraint of the general form
a1x1+a2x2 …anxn (<=, =, >=) bLpConstraintVar – Used to construct a column of the model in column-wise
modellingExported Functions:value() – Finds the value of a variable or expressionlpSum() – given a list of the form [a1*x1, a2x2, …, anxn] will construct
a linear expression to be used as a constraint or variablelpDot() –given two lists of the form [a1, a2, …, an] and
[ x1, x2, …, xn] will construct a linear epression to be used
as a constraint or variableComments, bug reports, patches and suggestions are welcome.pulp-or-discuss@googlegroups.comReferences:
[1]http://www.gnu.org/software/glpk/glpk.html[2]http://www.coin-or.org/[3]http://www.cplex.com/[4]http://www.gurobi.com/
Package: pulr
Pulr - pull devices and transform data into eventsWhat is PulrPulr is a small command-line tool, which can pull data from the device and
convert it into events. Meaning the data is outputted ONLY when it's changed.The data is always being outputted to STDOUT, you can grep it or use any
pipeline processor (I usevector) to push it via HTTP,
into databases etc.Before the output, any data part can be transformed: converted, divided,
multiplied, rounded and so on.The data can be outputted as plain text or as nd-json.pulr-Fmodbus.yml-L{"id":"sensor:axon/din1.value","value":0}{"id":"sensor:axon/din2.value","value":1}{"id":"sensor:axon/din3.value","value":1}{"id":"sensor:axon/din4.value","value":0}{"id":"unit:axon/dout1.status","value":1}{"id":"unit:axon/dout2.status","value":1}{"id":"unit:axon/dout3.status","value":0}{"id":"unit:axon/dout4.status","value":0}{"id":"unit:axon/aout.value","value":0.00619}{"id":"sensor:axon/ain.value","value":5.2045}{"id":"unit:tests/u1.status","value":0}{"id":"unit:tests/u2.status","value":0}Installingpip3insallpulr# for SNMP supportpip3installpython3-netsnmp# for Modbuspip3installpymodbus# optionally, install rapidjson to make JSON output fasterpip3installpython-rapidjsonEthernet/IP support requireslibplctag, download and install it:gitclonehttps://github.com/libplctag/libplctagcdlibplctag
cmakeCMakeLists.txt
make
sudomakeinstall
sudoldconfigConfiguringLook in ./examples for the example configurations.How does it workOne Pulr instance pulls one piece of the hardware equipment. The goal is to
pull and process the data as fast as possible, but die as soon as any errors
occur. Pulr is built to be started by supervisor, which collects the data from
it and restarts the process on crashes.But it's possible to run the tool with "-R" flag, which tells Pulr to restart
the main loop in case of failures.Is it fast enough?Pulr is written in Python, but it's written to be fast enough (e.g. Modbus
devices can be pulled up to 50 times per second without any problem).Pulr code is written to be easily transformed to Rust or Golang, I plan to do
this very soon.ProtocolsCurrently supported:Modbus (TCP/UDP)SNMP (v1/v2)Ethernet/IP (Allen Bradley-compatible, experimental)Data transformersspeed - calculate value growing speed, useful for SNMP interface countersmultiply, divide, roundbit2int - convert boolean bits into integers (1/0)int2bit - convert integers (any value/0) into boolean bits (true/false)Output typetext - output the data as plain text, defaultndjson - output the data as newline delimited JSONcsv - comma-separated valueseva/datapuller - specific type forEVA ICSOptional field "time-format" adds time to data output. Valid values are: "iso",
"timestamp".Bugs, feature requests, patchesYou are welcome. For the patches, please avoid Python-specific coding style
(e.g. function kwargs), as Python version will be rewritten very soon.Just:Outputs. No outputs are planned, except STDOUT. Use pipeline converters.Pulling more than one device simultaneously. Isn't planned, start another
Pulr process instead.
Package: pulsar-agile
Toolkit for agile development with python, git, github, docker and awsBadges:Master CI:Downloads:http://pypi.python.org/pypi/pulsar-agileSource:https://github.com/quantmind/pulsar-agileMailing list:google user groupDesign by:QuantmindandLuca SbardellaPlatforms:Linux, OSX, Windows. Python 3.5 and aboveKeywords:git, github, python, aws, release, documentationCONTENTSInstallSetupUsageLoggingCommandsGithubConfigurationLabelsReleaseHttpCopySassShellTemplateTestingChangelogInstallThis is a python package for aiding deployment and dev-ops type operations on the local machine.
To install the package you need python 3.5 or above:pip install -U pulsar-agileSetupOnce installed, create theplay.pyscript inside of your repository:if__name__=='__main__':fromagile.appimportAgileManagerAgileManager(description='Release manager for my package').start()and create theagile.jsonfile along side it.UsageCheck tasks available:python play.py -lLoggingWhen running tasks, the logging level is by default set to info. For a more
verbose logging pass--log-levelagile.debug.CommandsGithubPulsar agile contains two commands which interacts with github:labelsreleaseConfigurationBefore using github commands one needs to configure the.gitconfigfile by adding theusernameand thetoken. Thetokenis obtained from github from thepersonal access tokenspage:[user]
  email = ...
  username = lsbardel
  token = bqedoeunzplesw52tme00zwuj2lhbjr8emrbrxaxLabelsKeep labels consistent across repositories.
To add a label command create thelabelsentry in theagile.jsonfile:{"labels":{"group1":{"repositories":["quantmind/pulsar-agile","quantmind/pulsar-cloud"],"labels":{"aws":"e47911","benchmark":"006b75"}}},"tasks":{"repo-labels":{"description":"Update labels in all repositories","command":["labels"]}}}and run therepo-labelscommand:python play.py repo-labelsReleaseRelease dry run:python play.py releaseRelease push:python play.py release --pushHttpCopyCopy files over an Http connection.
For example:"httpcopy": {
    "sockjs": {
        "src": "https://cdnjs.cloudflare.com/ajax/libs/sockjs-client/{{ sockjs_version }}/sockjs.js",
        "target": "/media/"
    }
}SassCompile scss files using SASSShellRun arbitrary commands on the shellTemplateTransformjinja2templates files into new files with context dictionary given in theagile.jsonor otherjsonfiles. It can also replace ad-hoc string via thereplacedirective.TestingTo run unit tests, create atest_config.pyfile alongside this file and add
the following two entries:importosos.environ['GITHUB_USERNAME']="<username for token>"os.environ['GITHUB_TOKEN']="<generate one from https://github.com/settings/tokens>"os.environ['GITHUB_TEST_REPO']="<username>/<reponame>"ChangelogVersions 0.5Versions 0.4Versions 0.3Versions 0.2
Package: pulsarbat
pulsarbat(PULSAR Baseband Analysis Tools) is a Python package for analysis of radio baseband signals. Although this package has a special focus on radio pulsar astronomy, it can be easily used to work with other types of radio astronomical observations (such as fast radio bursts, quasars, and so on) or any time-frequency data, in general.pulsarbatprovides:Signals: Standardized containers for signal data.Functions/Transforms for manipulating signals.Easy integration withDaskfor lazily executed workflows or managing large workloads
in an “embarassingly parallel” manner.Documentation can be found at:https://pulsarbat.readthedocs.ioQuickstartInstall the latest version ofpulsarbat:$pipinstallpulsarbatTo usepulsarbatin a project:importpulsarbataspbCitingpulsarbathas a DOI via Zenodo:https://doi.org/10.5281/zenodo.6934355This DOI link represents all versions, and will always resolve to the latest one.
Use the following Bibtex entry to cite this work:@software{pulsarbat,
  author       = {Nikhil Mahajan and Rebecca Lin},
  title        = {pulsarbat: PULSAR Baseband Analysis Tools},
  year         = {2023},
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.6934355},
  url          = {https://doi.org/10.5281/zenodo.6934355}
}Licensepulsarbatis licensed under the GNU General Public License v3.
Package: pulsar-cloud
Badges:Master CI:Downloads:http://pypi.python.org/pypi/pulsar-cloudSource:https://github.com/quantmind/pulsar-cloudMailing list:google user groupDesign by:QuantmindandLuca SbardellaPlatforms:Linux, OSX, Windows. Python 3.5 and aboveKeywords:amazon, aws, botocore, pusher, websocket, async, pulsar, greenletCONTENTSRequirementsBotocoreAsyncio BotocoreGreen BotocoreS3 uploaderPusherCHANGELOGRequirementsPython 3.5 or abovepulsarbotocoregreenletBotocoreThis library provides two asynchronous implementations ofbotocore.Some part of the module are taken fromaiobotocore-apache LICENSE.Asyncio BotocoreThe first implementation uses asyncio from the python standard libray only and
requires an asyncio compatible HTTP client such as the pulsar one
(used by default):fromcloud.awsimportAsyncioBotocores3=AsyncioBotocore('s3','us-east-1')s3=awaits3.put_object(...)Green BotocoreThe second implementation, build on top of asyncio botocore, usespulsarandgreenletto obtain an implicit asynchronous behaviour.Usage:fromcloud.awsimportGreenBotocorefrompulsar.apps.greenioimportGreenPooldefexecute():s3=GreenBotocore('s3','us-east-1')ec2.put_object(...)pool=GreenPool()awaitpool.submit(execute)S3 uploaderUsage:s3upload <path> -b bucket/my/locationPusherA client and serverpusherimplementation usingpulsarasynchronous framework.
Create a pusher instancefromcloudimportPusherpusher=Pusher(app_id,key,secret)Subscribe to a channel as a clientchannel=awaitpusher.subscribe('test_channel')channel.bind('event',mycallback)
Package: pulsar-django
Asynchronous DjangoBadges:CI:Documentation:https://github.com/quantmind/pulsar-djangoDownloads:http://pypi.python.org/pypi/pulsar-djangoSource:https://github.com/quantmind/pulsar-djangoKeywords:asynchronous, django, wsgi, websocket, redisThepulsemodule is adjangoapplication
for running a django web site withpulsar.
Add it to the list of yourINSTALLED_APPS:INSTALLED_APPS=(...,'pulse',...)and run the site via thepulsecommand:python manage.py pulseCheck the django chat exampledjchatfor a django chat
application served by a multiprocessing pulsar server.By default, thepulsecommand creates aWsgimiddleware which
runs the django application in a separate thread of execution from the
main event loop.
This is a standard programming pattern when using asyncio with blocking
functions.
To control the number of thread workers in the event loop executor (which
is a pool of threads) one uses thethread-workersoption. For example, the
following command:python manage.py pulse -w 4 --thread-workers 20will run four process based actors, each with
an executor with up to 20 threads.GreenletsIt is possible to run django in fully asynchronous mode, i.e. without
running the middleware in the event loop executor.
Currently, this is available when using PostgreSql backend
only, and it requires thegreenletlibrary.To run django using greenlet support:python manage.py pulse -w 4 --greenletBy default it will run the django middleware on a pool of 100 greenlets (and
therefore approximately 100 separate database connections per actor). To
adjust this number:python manage.py pulse -w 4 --greenlet 200Django Chat ExampleThis is a web chat application which illustrates how to run a django
site with pulsar and how to include pulsar asynchronous request middleware
into django.To run:python manage.py pulseIf running for the first time, issue the:python manage.py migratecommand and create the super user:python manage.py createsuperuserMessage and data backendBy default, messages from connected (websocket) clients are synchronised via
the pulsar data store which starts when the django
site starts.It is possible to specify a different data store via thedata-storeoption. For example, it is possible
to useredisas an alternative data store
by issuing the following start up command:python manage.py pulse --data-store redis://127.0.0.1:6379/3
Package: pulsar-odm
Badges:Master CI:Downloads:http://pypi.python.org/pypi/pulsar-odmSource:https://github.com/quantmind/pulsar-odmMailing list:google user groupDesign by:QuantmindandLuca SbardellaPlatforms:Linux, OSX, Windows. Python 3.5 and aboveKeywords:sql, sqlalchemy, asynchronous, asyncio, concurrency, greenletPulsar-odm is build on top ofpulsar,sqlalchemyandgreenletlibraries to
provide an implicit asynchronous object data mapper to use with code written
withasyncio.
Currently only one dialect is implemented and tested:postgres+green, postgresql dialect withpsycopg2andgreenletCONTENTSUsageTestingChangelogUsageTo be able to use the object data mapper within standard blocking code,
one needs to use pulsarGreenPoolas the following snippet highlights:fromdatetimeimportdatetimefromsqlalchemyimportInteger,Column,String,DateTime,Booleanfrompulsar.apps.greenioimportGreenPoolimportodmclassTask(odm.Model):id=Column(Integer,primary_key=True)subject=Column(String(250))done=Column(Boolean,default=False)created=Column(DateTime,default=datetime.utcnow)def__str__(self):return'%d:%s'%(self.id,self.subject)defexample(mp):# Make sure table is availablemp.table_create()# Insert a new Task in the tablewithmp.begin()assession:task=mp.task(subject='my task')session.add(task)returntaskif__name__=='__main__':pool=GreenPool()mp=odm.Mapper('postgresql+green://odm:odmtest@127.0.0.1:5432/odmtests')mp.register(Task)task=pool._loop.run_until_complete(pool.submit(example,mp))print(task)Theexamplefunction is executed in a greenlet other than the main one. This is important otherwise the call fails:>>example(mp)>>Traceback(mostrecentcalllast):...RuntimeError:acquireinmaingreenletRunning the function on the greenlet pool guarantees the correct asynchronous execution. Whenpsycopg2executes a command against the database on a child greenlet, it switches control to the parent (main) greenlet, which is controlled by the asyncio eventloop so that other asynchronous operations can be carried out.
Once the result of the execution is ready, the execution switches back to the original child greenlet so that theexamplefunction can continue.TestingTo run tests, create a new role and database, for postgresql:psql -a -f tests/db.sqlChangelogVersion 0.6Version 0.5Version 0.4Versions pre 0.4
Package: pulsar-paragraph
pulsar_paragraphA python package that can create a human readable summary of a pulsar based on information for the ANTF pulsar catalogueInstallationTo install this package run:pip install pulsar_paragraphOr clone the git repository and run:pip install .UsageTo output a summary of a pulsar, use the following command:pulsar_paragraph -p <pulsar_jname>Where pulsar's PSRJ name such as:pulsar_paragraph -p J0437−4715which will output:PSR J0437-4715 is a millisecond pulsar with a period of 5.76 milliseconds and has an extremely low dispersion measure of 2.645 pc/cm^3. It is a very bright pulsar with a 1400 MHz catalogue flux density of 1.502e+05 mJy. PSR J0437-4715 is a Southern Hemisphere pulsar. This pulsar has a period derivative of 5.73e-20. PSR J0437-4715 has a fairly typical orbital period of 5.741 days and a very mildly eccentric orbit with an eccentricity of 0.00002. It is an ancient pulsar with an age of 1.592 Gyr. PSR J0437-4715 has a low magnetic field strength of 5.81e+08 G. It has a high transverse velocity of 104.7 km/s. The estimated distance to J0437-4715 is 156 pc. This pulsar has a low-mass companion with a minimum mass of 0.140 solar masses.If you don't include a pulsar, it will create a summary for each pulsar on the ATNF catalogue.You can also output the paragraphs to a text file with the -f option:pulsar_paragraph -o <output_file_name>
Package: pulsar-producer
Pulsar ProducerCLI that allows to send a message into a Apache Pulsar topicUsually, implementing an Apache Pulsar Consumers, you will need to test it before release. Then, it's quite painful that you need to write or change some code in order to test it. Having that said, I have implemented this CLI that can help you with that.Now, you can have a file with the message you want to send into a specific Apache Pulsar Topic and simply test your Apache Pulsar Consumer easily.How to use itFirst, you should install the CLI on your machinepip install pulsar-producerorpip install --user pulsar-producerif you want make it available only for your user.NOTE:This package stillnotpublish on pypi, only ontesting environmentNOTE:pip install -ihttps://test.pypi.org/simple/pulsar-producer==0.1.0Then, you need to have an file with your Apache Pulsar server address. This file SHOULD follow a JSON format.Example:my-apache-pulsar-configuration.json{"host":"localhost","port":"6650","topic":"my-topic-name"}Then, you need to have another file with contains the message you want to publish in your Apache Pulsar topic in order to test your Apache Pulsar Consumer.
This file can contains ANYTHING you want. In this example, let's say you want to publish a JSON structure message.my-message-file-example.json{"KEY":"THIS IS MY MESSAGE WHICH COULD BE ONLY PURE TEXT (NOT JSON)"}Now, you just need to run:pulsar-producer --pulsar-connection-file ./path-of-your-my-apache-pulsar-configuration-example-json --message-file ./path-or-your-message-fileLicenseMIT
Package: pulsarpy-dx
Pulsarpy DXA Pulsarpy client extension for Pulsar LIMS that imports sequencing results from DNAnexusAP documentation is onRead the Docs.This is a companion tool toPulsarpy, which in turn is the offical
Python client forPulsar LIMS. Pulsarpy DX is a gateway
between Pulsar LIMS and related sequencing results stored on DNAnexus, and serves to
import the sequencing results metadata from the DNAnexus platform into Pulsar LIMS.The main feature of this package is the script calledimport_seq_results.py, which looks for projects under the specified DNAnexus billing org that were created within the past N days. Each project is checked if it's sequencing results need to be imoprted into Pulsar LIMS.  The way it works is quite specific to the laboratoy workflow of the Snyder Production Center of ENCODE, here at Stanford.Lab workflowA SequencingRequest record is made in Pulsar LIMS. Then, an Excel form is filled out and sent to the nearby Stanford Genome Sequencing Service Center (GSSC). That form contains the library name, which the lab personel set to be equal to the SequencingRequest record's name in Pulsar. This name in the Excel form will eventually make its way to a DNAnexus project as a property calledlibrary_namewhen GSSC uploads the sequencing results there.Whenimport_seq_results.pyis run, for each project it finds it will look at the value of thelibrary_nameproperty, then use this to look up a SequencingRequest by that name in Pulsar. The SequencingRequest record must pre-exist in order for sequencing results to be imported - a process that will entail creating a SequeningRun record and one or more SequencingResult records, as needed.  See thescript documentationfor more details.
Package: pulsar-request-response
pulsar-request-response介绍这个项目是让pulsar支持请求响应模式，就是发送一条消息后能接收到响应，支持异步软件架构软件架构说明安装教程xxxxxxxxxxxx使用说明xxxxxxxxxxxx参与贡献Fork 本仓库新建 Feat_xxx 分支提交代码新建 Pull Request特技使用 Readme_XXX.md 来支持不同的语言，例如 Readme_en.md, Readme_zh.mdGitee 官方博客blog.gitee.com你可以https://gitee.com/explore这个地址来了解 Gitee 上的优秀开源项目GVP全称是 Gitee 最有价值开源项目，是综合评定出的优秀开源项目Gitee 官方提供的使用手册https://gitee.com/helpGitee 封面人物是一档用来展示 Gitee 会员风采的栏目https://gitee.com/gitee-stars/
Package: pulsar-sdk-py
This library serves as a way to interact with Pulsar's Third Party APIs.
Provided you have an API Key, getting started is very easy.E.g. on how to fetch balances from a wallet:importasynciofrompulsar_sdk_pyimportPulsarSDKfrompulsar_sdk_py.enumsimportChainKeysAPI_KEY="API_KEY_HERE"sdk=PulsarSDK(API_KEY)asyncdeffetch_balances(wallet_address:str,chain:ChainKeys):responses_list=[]asyncforwallet_balanceinsdk.balances.get_wallet_balances(wallet_addr=wallet_address,chain=chain):responses_list.append(wallet_balance)returnresponses_listres=asyncio.get_event_loop().run_until_complete(fetch_balances("0x77984dc88aab3d9c843256d7aabdc82540c94f69",ChainKeys.ETHEREUM))print(res)Which will fetch you all the wallet balances for your wallet, provided the Chain is active in our environment.For more information, check out ourdocumentation.
Package: pulsar-twitter
Badges:Master CI:Downloads:http://pypi.python.org/pypi/pulsar-twitterSource:https://github.com/quantmind/pulsar-twitterMailing list:google user groupDesign by:QuantmindandLuca SbardellaPlatforms:Linux, OSX, Windows. Python 3.5 and aboveKeywords:server, asynchronous, concurrency, queue, twitter, redisApulsar-queueplugin to stream and process tweets from Twitter.SetupThis library requirespulsar-queueandoauthliband can be installed via pip:pip install pulsar-twitterAccountsThis application can be configured to hoock into multiple accounts:[{"access_token":"Access token","access_token_secret":"Access token secret","stream_filter":{"track":"python,javascript","follow":"quantmind,lsbardel"}},...]