Saravanan666/pypi-org huggingface dataset:
Package: jpu
JAX + UnitsBuilt withJAXandPint!This module provides an interface betweenJAXandPintto allow JAX to support operations with
units. The propagation of units happens at trace time, so jitted functions
should see no runtime cost. This library is experimental so expect some sharp
edges.For example:>>>importjax>>>importjax.numpyasjnp>>>importjpu>>>>>>u=jpu.UnitRegistry()>>>>>>@jax.jit...defadd_two_lengths(a,b):...returna+b...>>>add_two_lengths(3*u.m,jnp.array([4.5,1.2,3.9])*u.cm)<Quantity([3.0453.0123.039],'meter')>InstallationTo install, usepip:python-mpipinstalljpuThe only dependencies arejaxandpint, and these will also be installed, if
not already in your environment. Take a look atthe JAX docs for more
information about installing JAX on different
systems.UsageHere is a slightly more complete example:>>>importjax>>>importnumpyasnp>>>fromjpuimportUnitRegistry,numpyasjnpu>>>>>>u=UnitRegistry()>>>>>>@jax.jit...defprojectile_motion(v_init,theta,time,g=u.standard_gravity):..."""Compute the motion of a projectile with support for units"""...x=v_init*time*jnpu.cos(theta)...y=v_init*time*jnpu.sin(theta)-0.5*g*jnpu.square(time)...returnx.to(u.m),y.to(u.m)...>>>x,y=projectile_motion(...5.0*u.km/u.h,60*u.deg,np.linspace(0,1,50)*u.s...)Technical details & limitationsThe most significant limitation of this library is the fact that users must usejpu.numpyfunctions when interacting with "quantities" with units instead of
thejax.numpyinterface. This is because JAX does not (yet?) provide a general
interface for dispatching of ufuncs on custom array classes. I have played
around with the undocumented__jax_array__interface, but it's not really
flexible enough, and it isn't currently compatible with Pytree objects.So far, only a subset of thenumpy/jax.numpyinterface is implemented. Pull
requests adding broader support (including submodules) would be welcome!
Package: jpush
=======================
JPush API Python ClientJPush's officially supported Python client library for accessing JPush APIs.JPush Rest API Documents:http://docs.jpush.io/server/rest_api_v3_push/You can download the latest release file here:https://github.com/jpush/jpush-api-python-client/releasesInstallationTo install jpush-api-python-client, simply:$ sudo pip install jpushor alternatively install via easy_install:$ sudo easy_install jpushor from source:$ sudo python setup.py installTestingFor running the tests, you need the standardunittestmodule, shipped
with Python.To run jpush-api-python-client tests, simply:$ nosetests tests/push tests/devices --verbosity=2ExamplesYou can see more examples in https://github.com/jpush/jpush-api-python-client/blob/master/examplesSimple iOS Push>>> import jpush as jpush
>>> from conf import app_key, master_secret
>>> _jpush = jpush.JPush(app_key, master_secret)
>>> push = _jpush.create_push()
>>> push.audience = jpush.all_
>>> ios_msg = jpush.ios(alert="Hello, IOS JPush!", badge="+1", sound="a.caf", extras={'k1':'v1'})
>>> android_msg = jpush.android(alert="Hello, android msg")
>>> push.notification = jpush.notification(alert="Hello, JPush!", android=android_msg, ios=ios_msg)
>>> push.options = {"time_to_live":86400, "sendno":12345,"apns_production":True}
>>> push.platform = jpush.platform("ios")
>>> push.send()Get taglist>>> import jpush as jpush
>>> from conf import app_key, master_secret
>>> _jpush = jpush.JPush(app_key, master_secret)
>>> device = _jpush.create_device()
>>> device.get_taglist()QuestionsThe best place to ask questions is our community site:http://community.jpush.cn/
Package: jpviz
Jaxpr-VizJAX Computation Graph Visualisation ToolJAX has built-in functionality to visualise the
HLO graph generated by JAX, but I've found this rather
low-level for some use-cases.The intention of this package is to visualise how
sub-functions are connected in JAX programs. It does
this by converting theJaxPrrepresentation into a pydot graph. Seeherefor examples.NOTE:This project is still at an early stage and may not
support all JAX functionality (or permutations thereof). If you spot
some strange behaviour please create aGithub issue.InstallationInstall with pip:pipinstalljpvizDependent on your system you may also need to installGraphvizUsageJaxpr-viz can be used to visualise jit compiled (and nested)
functions. It wraps jit compiled functions, which when called
with concrete values returns apydotgraph.For example this simple computation graphimportjaximportjax.numpyasjnpimportjpviz@jax.jitdeffoo(x):return2*x@jax.jitdefbar(x):x=foo(x)returnx-1# Wrap function and call with concrete arguments#  here dot_graph is a pydot objectdot_graph=jpviz.draw(bar)(jnp.arange(10))# This renders the graph to a png filedot_graph.write_png("computation_graph.png")produces this imagePydot has a number of options for rendering graphs, seehere.NOTE:For sub-functions to show as nodes/sub-graphs they
need to be marked with@jax.jit, otherwise they will just
merged into thir parent graph.Jupyter NotebookTo show the rendered graph in a jupyter notebook you can use the
helper functionview_pydot...dot_graph=jpviz.draw(bar)(jnp.arange(10))jpviz.view_pydot(dot)Visualisation OptionsCollapse NodesBy default, functions that are composed of only primitive functions
are collapsed into a single node (likefooin the above example).
The full computation graph can be rendered using thecollapse_primitivesflag, setting it toFalsein the above example...dot_graph=jpviz.draw(bar,collapse_primitives=False)(jnp.arange(10))...producesShow TypesBy default, type information is included in the node labels, this
can be hidden using theshow_avalsflag, setting it toFalse...dot_graph=jpviz.draw(bar,show_avals=False)(jnp.arange(10))...producesNOTE:The labels of the nodes don't currently correspond
to argument/variable names in the original Python code. Since
JAX unpacks arguments/outputs to tuples they do correspond
to the positioning of arguments and outputs.ExamplesSeeherefor more examples of rendered computation graphs.DevelopersDeveloper notes can be foundhere.
Package: jpxlab-test
======
jpxlab.. image::https://img.shields.io/pypi/v/jpxlab.svg:target:https://pypi.python.org/pypi/jpxlab.. image::https://img.shields.io/travis/AlpacaDB/jpxlab.svg:target:https://travis-ci.org/AlpacaDB/jpxlab.. image::https://readthedocs.org/projects/jpxlab/badge/?version=latest:target:https://jpxlab.readthedocs.io/en/latest/?badge=latest:alt: Documentation Status.. image::https://pyup.io/repos/github/AlpacaDB/jpxlab/shield.svg:target:https://pyup.io/repos/github/AlpacaDB/jpxlab/:alt: UpdatesThe data analysis sandbox for JPXFree software: MIT licenseFeaturesConvert the historical data of FLEX HistoricalUsage: downloadPrerequisites: You have to contact with JPX's account manager and get FTP account.. code-block::$ cd tools/fetcher
$ vim fetch.sheditFTP_USERandFTP_PASS$ ./build.sh
$ ./fetch.sh 20191008The file is downloaded into<repos root>/downloadsYou can also specify wiledcard to dowonload multiple files in batch (e.g../fetch.sh '201909??')It fetches from under/archives/so most recent files are out of scopeUsage: convert from raw zip files to h5.. code-block::$ python cli.py convert --help
Usage: cli.py convert [OPTIONS] [FILES]...

  convert raw zip files to h5

Options:
  --help  Show this message and exit.Usage: resample h5 files into aggregated dataframe.. code-block::$ python cli.py resample --help
Usage: cli.py resample [OPTIONS] [FILES]...

  resample the h5 file into aggregated dataframe

Options:
  -f, --freq TEXT  frequency of resampling (e.g. '1H' for hourly aggregation)
  --help           Show this message and exit.Usage: launch the jupyter notebook (locally)$ make notebookUsage: launch the jupyter notebook (in docker)$ make notebook_dockerCreditsThis package was created with Cookiecutter_ and theaudreyr/cookiecutter-pypackage_ project template... _Cookiecutter:https://github.com/audreyr/cookiecutter.. _audreyr/cookiecutter-pypackage:https://github.com/audreyr/cookiecutter-pypackage=======
History0.1.0 (2019-09-07)First release on PyPI.
Package: jpy-flette
jpy-fletteis a lightweight (~150 lines) python static website generator which uses jupyter notebooks as input. It’s fantastic for documenting scientific projects, documentation, or just to share your thoughts with the world.InstallationInstalljpy-flettewith pip:pipinstalljpy-fletteYou could also download or clone the source code from therepository, then runpythonsetup.pyinstallUsageMake sure you check thedocumentation, which is actually built usingjpy-fletteitself!jpy-flettetransforms a directory full of.ipynbjupyter notebooks into a website with multiple pages. Let’s assume the following directory structure:~/my/directory
          └── notebooks
              ├── 00.index.ipynb
              └── 01.jpy-flette-documentation.ipynbAfter callingjpy-flette~/my/directory/notebooksyou would obtain~/my/directory
          ├── docs
          │   ├── index.html
          │   ├── jpy-flette-documentation.html
          │   └── static
          │       ├── style.css
          │       └── script.js
          └── notebooks
              ├── 00.index.ipynb
              └── 01.jpy-flette-documentation.ipynb~/my/directory/docsis then ready to be published!jpy-flettecan be configured usingfletteconf.yamlfiles fortheming, titles/footers and more. Refer thedocumentationfor more.
Package: jpyforex
JPYForexJPYForexは、ドル円、ユーロ円、人民元円の為替レートを手軽に取得できるPythonパッケージです。このツールは、pandas_datareaderを利用してFRED（セントルイス連銀のデータAPI）から最新の為替レートデータを取得し、それを円建ての価格に変換しています。JPYForex is a Python package that allows you to easily retrieve exchange rates for USD/JPY, EUR/JPY, and CNY/JPY. This tool uses pandas_datareader to fetch the latest exchange rate data from FRED (Federal Reserve Bank of St. Louis Data API) and converts it into prices denominated in yen.特徴　Features簡単な操作：わずか数行のコードで、円建ての為替レートを取得できます。多通貨対応：ドル円、ユーロ円、人民元円のレートをサポートしています。Easy to Use: With just a few lines of code, you can retrieve exchange rates denominated in yen.Supports Multiple Currencies: Supports rates for USD/JPY, EUR/JPY, and CNY/JPY.インストールpip install jpyforexpip install git+https://github.com/mazarimono/JPYForex.git使い方(How to Use)JPYForexの基本的な使用方法は以下の通りです。
The basic usage of JPYForex is as follows.fromJPYForeximportjpyforex# 米ドル建ての日足データを5年分取得usd=jpyforex.JPYForex()df_usd=usd.get_data()ライセンスMIT
Package: jpylib-jyrgenn
Utilities library with several more or less independent componentsThis library is mainly intended for myself, so I can access it from
anywhere. But anyone else is welcome to have a look. Documentation
is still lacking, I know, but that shall change. Testing is better.The full documentation (what already exists of it) for this version
is athttps://git.w21.org/ni/jpylib/-/blob/v2024.219.1919/doc/jpylib.md[ni@w21.org2022-03-11]
Package: jpypex
JPype is an effort to allow python programs full access to java class libraries. This is achieved
not through re-implementing Python, as Jython/JPython has done, but rather through interfacing at
the native level in both Virtual Machines.Eventually, it should be possible to replace Java with python in many, though not all, situations.
JSP, Servlets, RMI servers and IDE plugins are good candidates.Once this integration is achieved, a second phase will be started to separate the Java logic from
the Python logic, eventually allowing the bridging technology to be used in other environments,
I.E. Ruby, Perl, COM, etc …Known Bugs/Limitations :Java classes outside of a package (in the <default>) cannot be imported.unable to access a field or method if it conflicts with a python keyword.Because of lack of JVM support, you cannot shutdown the JVM and then restart it.Some methods rely on the “current” class/caller. Since calls coming directly from
python code do not have a current class, these methods do not work. The User Manual
lists all the known methods like that.
Package: jpysocket
Decode The String Received From Java Socket And Encode The String for Send To The Java SocketConnect Python And Java SocketsSend And Recieveing The Data Beetween Java And Python Sockets.Installation :pip install jpysocketRemove Package :pip uninstall jpysocketImport Library :import jpysocketConnect Python Server And Java Client.Connect Python Client And Java Server.Send Python Socket Massage To Java Socket.Recieve Massage From Java Socket in Python Sockete.The Followings Are The Some Example Of jpysocket LibreryPython Server :importjpysocketimportsockethost='localhost'#Host Nameport=12345#Port Numbers=socket.socket()#Create Sockets.bind((host,port))#Bind Port And Hosts.listen(5)#Socket is Listeningprint("Socket Is Listening....")connection,address=s.accept()#Accept the Connectionprint("Connected To ",address)msgsend=jpysocket.jpyencode("Thank You For Connecting.")#Encript The Msgconnection.send(msgsend)#Send Msgmsgrecv=connection.recv(1024)#Recieve msgmsgrecv=jpysocket.jpydecode(msgrecv)#Decript msgprint("From Client: ",msgrecv)s.close()#Close connectionprint("Connection Closed.")Java Client :Client.javaimportjava.io.*;importjava.net.*;publicclassClient{publicstaticvoidmain(String[]args){try{Socketsoc=newSocket("localhost",12345);DataOutputStreamdout=newDataOutputStream(soc.getOutputStream());DataInputStreamin=newDataInputStream(soc.getInputStream());Stringmsg=(String)in.readUTF();System.out.println("Server: "+msg);dout.writeUTF("Ok Boss");dout.flush();dout.close();soc.close();}catch(Exceptione){e.printStackTrace();}}}Python Client :importjpysocketimportsockethost='localhost'#Host Nameport=12345#Port Numbers=socket.socket()#Create Sockets.connect((host,port))#Connect to socketprint("Socket Is Connected....")msgrecv=s.recv(1024)#Recieve msgmsgrecv=jpysocket.jpydecode(msgrecv)#Decript msgprint("From Server: ",msgrecv)msgsend=jpysocket.jpyencode("Ok Boss.")#Encript The Msgs.send(msgsend)#Send Msgs.close()#Close connectionprint("Connection Closed.")Java Server :Server.javaimportjava.io.*;importjava.net.*;publicclassServer{publicstaticvoidmain(String[]args){try{ServerSocketserverSocket=newServerSocket(12345);Socketsoc=serverSocket.accept();System.out.println("Receive new connection: "+soc.getInetAddress());DataOutputStreamdout=newDataOutputStream(soc.getOutputStream());DataInputStreamin=newDataInputStream(soc.getInputStream());dout.writeUTF("Thank You For Connecting.");Stringmsg=(String)in.readUTF();System.out.println("Client: "+msg);dout.flush();dout.close();soc.close();}catch(Exceptione){e.printStackTrace();}}}
Package: jpyttm
JPY TTM RatesHistorical JPY TTM rates, basically for tax purposes.InstallInstall from PyPI:pip install jpyttmUsagefromjpyttmimportUSD,get_historical_ttmttm=get_historical_ttm(USD)forquoteinttm:print(quote[0],quote[1])To specify a range, callget_historical_ttmwith optional parameterstimestamp_fromand/ortimestamp_to
Package: jpzipcode
jpzipcode郵便番号から住所を取得するためのライブラリUsageimportosfromjpzipcodeimportOFFICIAL_FILE_NAME,read_csv_file,read_official_URLzip_code="5650871"# ファイルを読み込んで取得resolver=read_csv_file(os.path.join("tests","testdata",OFFICIAL_FILE_NAME))zips=resolver.resolve(zip_code)# 日本郵便のサイトからダウンロードして郵便番号を取得resolver=read_official_URL()zips=resolver.resolve(zip_code)print(zips)# [Zip(zip_code='5650871', address=Address(prefecture='大阪府', city='吹田市', town='山田丘'), address_kana=Address(prefecture='オオサカフ', city='スイタシ', town='ヤマダオカ'))]fromfastapiimportFastAPIfromfastapi.testclientimportTestClientfromjpzipcode.fastapi.endpointimportcreate_endopointapp=FastAPI()# appに郵便番号解決エンドポイントを追加app.get("/zip")(create_endopoint())client=TestClient(app)res=client.get(f"/zip?zipcode={zip_code}")result=res.json()assertres.status_code==200assertresult[0]["address"]["prefecture"]=="大阪府"assertresult[0]["address"]["city"]=="吹田市"assertresult[0]["address"]["town"]=="山田丘"
Package: jqdatasdk
公司介绍JoinQuant 聚宽，专业量化投研平台、技术驱动的平台型资管。办公地点位于北上广深、西安等多个城市，2015年5月成立，目前已在量化领域深耕6年多。早期做量化投研交易系统起家，积淀了深厚的系统、交易、数据、算法、风控等多方面经验，并获得众多头部券商认可。平台拥有40万用户的量化优秀人才储备库，活跃的量化学习交流社区、自研的量化系列课程获得国内外众多一线高校青睐。目前聚宽包含4大业务线：平台服务、数据服务、算法服务、量化基金。四大业务相辅相成，基于聚宽量化平台积累的用户、技术、市场优势，以量化基金和算法服务进行商业变现。·  聚宽量化投研平台，服务超40万+量化投研用户
·  聚宽算法，服务于券商客户，交易资产超过50亿
·  量化数据JQData，服务国内超过4500家量化机构
·  聚宽量化基金，当前资产管理规模达110+亿产品介绍JQData是什么？JQData是聚宽数据团队专门为金融机构、学术研究和量化研究者们提供的本地量化金融数据服务。使用JQData，可快速查看和计算金融数据，无障碍解决本地、Web、金融终端调用数据的需求。历经6年沉淀，40万宽客及数千家机构投研交易验证。使用上，JQData适用Windows、Mac、Linux多种操作系统，支持python2、python3（更多语言详情咨询管理员）。数据通过简洁的API方式提供，pip即可直接安装使用，挣脱使用束缚，实现更多场景。只需三行代码，即可随取随用~JQData提供什么数据？JQData提供多个市场数据，详情可查看官网https://www.joinquant.com/data，内含JQData包含的数据接口和详细的更新时间。在此基础上，我们提供不同粒度的数据供您使用，包括日线、分钟线、tick级的行情数据，极大地满足您的各项需求。为什么选择JQData？本地使用：JQData避免了各个量化平台的限制，适用于Windows，Mac，Linux多种操作系统，用户只需三行Python代码即可完成本地安装和调用，帮助您实现一整套本地化部署的量化投资研究。（支持Python2和Python3）易于量化：JQData在设计过程中，聚宽团队基于量化行业专业知识及对投研的经验，对数据进行清洗及整理，使数据更能适用量化的研究习惯，并进一步赋能数据在本地投研的可行性及便利性。调用方便：在JQData里，不同品种同一属性的数据用同一个接口就能获取，例如，使用get_price就能获取所有股票，基金，指数，期货的行情数据，从而大大减少用户的学习成本，代码也更加简洁；与之相反，大部分传统数据商提供的数据分散在不同的数据表中，需要用户自己来回查找。JQData精准度介绍：截至目前，聚宽自营基金管理规模已达百亿，使用聚宽数据，一创聚宽平台的实盘交易验证，其精准度满足交易需求。聚宽数据团队研发了数据监控系统和多数据源比对系统，通过一整套系统化的机制保证数据的准确性。另外，我们还提供了指定日期参数，杜绝未来数据。JQData稳定性介绍：JQData采用与聚宽官网一致的账户校验系统，登录账号即可使用。提供独立的数据服务，采用负载均衡、高可用服务架构，配备完善的灾备体系，保证业务系统24小时不中断，并支持海量用户同时在线。数据传输方面，采用RPC协议传输，并压缩成特有数据格式，减少传输数据量，更加节省带宽。申请试用申请链接：https://www.joinquant.com/default/index/sdk?utm_campaign=JQData%E7%94%B3%E8%AF%B7&utm_medium=%E7%BD%91%E9%A1%B5&utm_source=%E8%81%9A%E5%AE%BD&gio_link_id=xRxqAjP5申请方法：如实填写资料后提交调用方法安装方法# 首次安装pipinstalljqdatasdk# 升级版本pipinstall-Ujqdatasdk超详细安装指引：https://www.joinquant.com/view/community/detail/cdf86c624992fc86ed51d920ef8c637b使用方法importjqdatasdk# 登录认证jqdatasdk.auth(username,password)# 获取数据jqdatasdk.get_price("000001.XSHE",start_date="2017-01-01",end_date="2017-12-31")详细的使用说明文档见：https://www.joinquant.com/help/api/help?name=JQData机构合作方式公司机构用户，可以联系官网右下角在线客服或微信号JQData02，进行洽谈。
Package: jqed
json interactive stream editorA tool inspired byUltimate Plumberthat usesjqto process JSON and show you the results instantly, to enable greater interactivity.A manual for jq can be found here.Download & Installsudoaptinstalljq# <-- Install the jq tool, on MacOS install using `brew install jq`pip3installjqedUsage / Examplescatsome_file.json|jqed
ip--jsonlink|jqed
Package: jqfilters
Filtersjqfiltersallows to easily create filter objects, which can be applied to JSON-like dictionaries.
It is based on the popular JSON parsing tooljq, so the
syntax mimics jq's.For showing both, the same JSON object will be used:>>>person={..."name":"Alice"..."books":[...{"name":"The name of the wind"},...{"name":"A feast for crows"},...{"name":"Continuous delivery"}...],..."age":24,..."location":"Lancashire"...}Simple QueriesWe will create a filter that will returnTruefor people living in Yorkshire.>>>fromjqfiltersimportFilter>>>is_from_yorkshire=Filter(op1='.location',operator='eq',op2='Yorshire')>>>is_from_yorkshire(person)FalseWe can also apply some transformation to operands (seejqfilters.operations):>>>fromjqfiltersimportFilter>>>reads_a_lot=Filter(op1='.books',transform1='len',operator='ge',op2=3)>>>reads_a_lot(person)TrueComplex QueriesWe will create a filter that will returnTruewhen any of the book name is "A game of thrones"
or when the person is older than 18. As this specification is more complex, the
:meth:fromConfig <jqfilters.filters.Filter.fromConfig>method will be used.>>>specs={..."op1":{..."op1":".books[].name",..."operator":"contains",..."op2":"A game of thrones"...},..."operator":"or",..."op2":{..."op1":".age",..."operator":"ge",..."op2":18...}...}>>>adult_got_fans=Filter.fromConfig(specs)>>>adult_got_fans(person)TrueA filter can be inspected in an easier way by just prompting it:>>>adult_got_fans>>>((.books[].name-contains-Agameofthrones)-or-(.age-ge-18))
Package: jqi
An interactive wrapper for jqThis can be used as part of a pipeline, or take a file as input.Use control-space to toggle compact mode; use control-R to toggle
raw output.Use:somthing-that-produces-json | jqiorjqi /tmp/foo.json fileUse control-C to exit.Keys^X: exit (dumping the result to stdout)^C: quit^ space: toggle compact mode^r: toggle raw mode^y: set yaml mode^j: set JSON mode^ LEFT: word left^ RIGHT: work rightalt-arrow,alt-page up/down,alt-home/end: scroll the output window
Package: jqktrader
jqktrader同花顺自动程序化交易目的由于easytrader年久失修，同花顺自动交易模式存在问题，此包基于easytrader部分源码，删去其他部分，只专注与同花顺客户端的自动化交易，并解决easytrader现存问题，让使用者可以开箱即用。解决的问题升级pywinauto到最新版补全缺少的依赖，如pytesseract、pypiwin32修复无法自动填写输入框的各种问题增加Tesseract的路径配置安装1. 安装 Tesseract OCR由于程序运行过程中，需要识别验证码，请首先安装Tesseract OCR，官方下载地址：https://github.com/UB-Mannheim/tesseract/wiki2. 安装 jqktraderpip install jqktrader用法jqktrader不维护同花顺客户端的登录状态，请手动登录后再使用。importjqktraderuser=jqktrader.use()user.connect(exe_path=r'D:\同花顺软件\同花顺\xiadan.exe',tesseract_cmd=r'D:\Program Files\Tesseract-OCR\tesseract.exe')user.positionexe_path同花顺xiadan.exe的路径tesseract_cmdTesseract OCRtesseract.exe的路径API沿用easyTrader官方的api，非同花顺相关的已删除。参看文档：https://easytrader.readthedocs.io/zh/master/usage/
Package: jqlite
jqliteAn implementation ofjq, the commandline JSON processor, for learning and fun.Installation>pipinstalljqliteExamples:>echo'{"foo": 0}'|jqlite{"foo":0}>echo'{"foo": [1, 2, 3, 4]}'|jqlite'[.foo | .[] | select(. % 2 == 0) | . * 2]'[4.0,8.0]
Package: jqp
jqpjqp is a JSON processor with Python one-liner.RequirementPython 2.7, 3.3, 3.4, 3.5Install$ pip install jqpUsagejqp parses each line as a JSON object, and evaluates a given expression.
A parsed JSON object is bounded a variable namedj.jqp cmdcmd:An expression to evaluate.optional arguments:-h,--helpshow this help message and exit--versionshow version and exit--importIMPORTmodules to import--ascii-output,-awith this option, jqp ensures ASCII output--sort-keys,-Ssort keys in objects when the command print it--raw-input,-Rpass each line text as a string instead of parsing it as JSON--raw-output,-rwhen a result is string, the command shows a raw string--join-output,-jdo not show newlinesExample% echo '{"name": "Taro", "age": 10}' | jqp '[j["name"], j["age"]]'
["Taro", 10]LicenseMIT License