Saravanan666/pypi-org huggingface dataset:
Package: zerobounce
ZeroBouncePython API. The response
object allows an attribute-like style access.fromzerobounceimportZeroBounceAPIzba=ZeroBounceAPI('yourapikey____________')printzba.get_credits()resp1=zba.validate('flowerjill@aol.com')resp2=zba.validatewithip('flowerjill@aol.com')printresp1{"address":"flowerjill@aol.com","status":"Valid","sub_status":"","account":"flowerjill","domain":"aol.com","disposable":False,"toxic":False,"firstname":"Jill","lastname":"Stein","gender":"female","location":None,"creationdate":None,"processedat":"2017-04-01 02:48:02.592"}printresp2{"address":"flowerjill@aol.com","status":"Valid","sub_status":"","account":"flowerjill","domain":"aol.com","disposable":False,"toxic":False,"firstname":"Jill","lastname":"Stein","gender":"female","location":None,"country":"United States","region":"Florida","city":"West Palm Beach","zipcode":"33401","creationdate":None,"processedat":"2017-04-01 02:48:02.592"}printresp.firstnameJillprintresp2.statusValid
Package: zero_buffer
zero_bufferis a high-performance, zero-copy, implementation of a
byte-buffer for Python.Documentationis available on ReadTheDocs.fromzero_bufferimportBuffer# Create a buffer which has space for 8192 bytes.b=Buffer.allocate(8192)withopen(path,"rb")asf:# Read up to 8192 bytes from the file into the bufferb.read_from(f.fileno())# Create a read-only view of the buffer, this performs no copying.view=b.view()# Split the view on colons, this returns a generator which yields sub-views# of the view.forpartinview.split(b":"):print(part)zero_bufferworks on Python 2.6, 2.7, 3.2, 3.3, and PyPy.
Package: zerocap-websocket-test
pip install zerocap-websocket-test -ihttps://www.pypi.org/simple/demo:from zerocap_websocket_test import ZerocapWebsocketTestAPI key and secret requiredapiKey = “”apiSecret = “”websocket = ZerocapWebsocketTest(apiKey, apiSecret)Subscribe to Market datamarket_connect = websocket.get_market()Subscription order updates and transaction recordsorders_connect = websocket.get_orders()while True:# Get subscription messages

message = websocket.get_message(market_connect)

print(f"Receiving message from server: \n{message}")

if not message:

    print("Connection close")

    break
Package: zerochan
ZerochanLibrary for Zerochan.net with pics parsing and downloader included!FeaturesCLI utility for pics downloading from zerochan.netLibrary for create custom downloader (you can write own) or data analyze.Strong typed!Installation:Using pippip install zerochanUsing poetrypoetry add zerochanUsing as downloader tool:After install you can call zerochan by commandpython -m zerochanUsing as library:First, you should createZerochaninstance:fromzerochanimportZeroChanzerochan_instance=ZeroChan()Now, you can set some args for requestfromzerochanimportZeroChan,PictureSize,SortByzerochan=ZeroChan()zerochan.search("Spain")# Set title to searchzerochan.size(PictureSize.BIGGER_AND_BETTER)# Set quality and pic sizezerochan.sort(SortBy.POPULAR)# Set sorting (now only popular)zerochan.page(1)# Page to parsezerochan.authorize("hjsaf7afkjsaf78","127364")# Authorize by z_hash and z_id in cookies...or set args like this:zerochan.search("Spain")\.size(PictureSize.BIGGER_AND_BETTER)\.sort(SortBy.POPULAR)After all settings, you should call.pics()to get pics:data=zerochan.pics()forimgindata.images:print(img.url)
Package: zeroc-ice
The Internet Communications Engine (Ice) provides a robust, proven platform for
developing mission-critical networked applications. Let Ice handle all of the
low-level details such as network connections, serialization, and concurrency so
that you can focus on your application logic.The Ice Python extension makes the full Ice feature set available to Python
developers, including:Client and server supportSynchronous and asynchronous invocationsCommunicate via TCP, SSL, UDP, multicast, and WebSocket transportsSupports IPv4 and IPv6Intuitive mapping from Slice to PythonTo give you an idea of what it’s like to use Ice in Python, here’s a complete
program that tests whether a remote Ice object is available:import sys, Ice
with Ice.initialize(sys.argv) as communicator:
    obj = communicator.stringToProxy("hello:tcp -h myhost.mydomain.com -p 10000")
    obj.ice_ping()With support for Python2 and Python3, you can easily add Ice to your existing
Python infrastructure and discover how easy it is to build distributed
applications with Ice.Package ContentsThis package includes the Ice extension for Python, the standard Slice
definition files, and the Slice-to-Python compiler. You will need to install a
full Ice distribution if you want to use other Ice language mappings, or Ice
services such as IceGrid, IceStorm and Glacier2.InstallationWe recommend usingpiporeasy_installto install this package. If you
install usingpython setup.py installinstead, be aware that the Slice-to-
Python compiler (slice2py) will not be available.By default, Ice is built statically with the package. On Linux and macOS, you
can instead build the package with the system-installed Ice shared libraries.
To do so, you can provide the`--with-installed-ice`option to`setup.py`install. With`pip`, you should pass the`--install-option="--with-installed-ice"`option to pip install.Home PageVisitZeroC’s home pagefor the latest news and
information about Ice.DocumentationWe provide extensiveonline documentationfor Ice, the Python extension, and the
other Ice language mappings and services.SupportJoin us on ouruser forumsif you have
questions about Ice.
Package: zeroc-icehashpassword
The icehashpassword package provides the icehashpassword script which can be used to create passwords compatible with  the Glacier2 crypt permissions verifier.InstallationWe recommend usingpiporeasy_installto install this
package.Home PageVisitZeroC’s home pagefor the latest news
and information about Ice.Package ContentsThe package provides the icehashpassword utility.Usage:Usage: icehashpassword [options]

OPTIONS

  -d MESSAGE_DIGEST_ALGORITHM, --digest=MESSAGE_DIGEST_ALGORITHM
      The message digest algorithm to use with PBKDF2, valid values are (sha1, sha256, sha512).

  -s SALT_SIZE, --salt=SALT_SIZE
      Optional number of bytes to use when generating new salts.

  -r ROUNDS, --rounds=ROUNDS
      Optional number of rounds to use.

  -h, --help
      Show this message.SupportJoin us on ouruser forumsif you have questions
about this package.
Package: zero-dce
Zero-Reference Deep Curve Estimation for Low-Light Image EnhancementYou can find more details here:https://li-chongyi.github.io/Proj_Zero-DCE.html. Have fun!The implementation of Zero-DCE is for non-commercial use only.We also provide a MindSpore version of our code:https://pan.baidu.com/s/1uyLBEBdbb1X4QVe2waog_g(passwords: of5l).PytorchPytorch implementation of Zero-DCERequirementsPython 3.7Pytorch 1.0.0opencvtorchvision 0.2.1cuda 10.0Zero-DCE does not need special configurations. Just basic environment.Or you can create a conda environment to run our code like this:
conda create --name zerodce_env opencv pytorch==1.0.0 torchvision==0.2.1 cuda100 python=3.7 -c pytorchFolder structureDownload the Zero-DCE_code first.
The following shows the basic folder structure.├── data
│   ├── test_data # testing data. You can make a new folder for your testing data, like LIME, MEF, and NPE.
│   │   ├── LIME 
│   │   └── MEF
│   │   └── NPE
│   └── train_data 
├── lowlight_test.py # testing code
├── lowlight_train.py # training code
├── model.py # Zero-DEC network
├── dataloader.py
├── snapshots
│   ├── Epoch99.pth #  A pre-trained snapshot (Epoch99.pth)Test:cd Zero-DCE_codepython lowlight_test.pyThe script will process the images in the sub-folders of "test_data" folder and make a new folder "result" in the "data". You can find the enhanced images in the "result" folder.Train:cd Zero-DCE_codedownload the training datagoogle driveorbaidu cloud [password: 1234]unzip and put the  downloaded "train_data" folder to "data" folderpython lowlight_train.pyLicenseThe code is made available for academic research purpose only. Under Attribution-NonCommercial 4.0 International License.Bibtex@inproceedings{Zero-DCE,
 author = {Guo, Chunle Guo and Li, Chongyi and Guo, Jichang and Loy, Chen Change and Hou, Junhui and Kwong, Sam and Cong, Runmin},
 title = {Zero-reference deep curve estimation for low-light image enhancement},
 booktitle = {Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR)},
 pages    = {1780-1789},
 month = {June},
 year = {2020}
}(Full paper:http://openaccess.thecvf.com/content_CVPR_2020/papers/Guo_Zero-Reference_Deep_Curve_Estimation_for_Low-Light_Image_Enhancement_CVPR_2020_paper.pdf)ContactIf you have any questions, please contact Chongyi Li atlichongyi25@gmail.comor Chunle Guo atguochunle@tju.edu.cn.TensorFlow VersionThanks tuvovan (vovantu.hust@gmail.com) who re-produces our code by TF. The results of TF version look similar with our Pytorch version. But I do not have enough time to check the details.https://github.com/tuvovan/Zero_DCE_TF
Package: zero-divisor-graph
Zero Divisor Graph math libraryThis is a pure python library for working with zero divisor graphs of commutative semigroups. The primary purpose is to automate the task of checking if a given graph is a zero divisor graph and for what possible semigroups.Installationpip3 install zero-divisor-graphYou can also retrieve from source athttps://github.com/Paulcappaert/zero-divisor-graphusefirst start python3 in a terminal window and import the ZeroDivisorGraph objectpython3
>>> from zdg.zdg import ZeroDivisorGraph as ZDGYou can create a zero divisor graph from edges as such. the vertices can be named whatever you want.>>> example1 = ZDG((1, 2), (2, 3))
>>> example2 = ZDG(('a', 'b'), ('b', 'c'))You can print all of the semigroups from a zero divisor graph as such>>> semigroups = example1.semigroups()
>>> for s in semigroups:
...   print(s.caley_table())
Package: zerodose
ZerodoseA tool to assist in personalized abnormality investigation in combined FDG-PET/MRI imaging.
Created by the department ofClinically Applied Artificial IntelligenceatCopenhagen University HospitalInstallationNote that a python3 installation is required forZerodoseto work.
You can installZerodoseviapipfromPyPI:$pipinstallzerodoseUsageSynthesize baseline PET$zerodosesyn-imr.nii.gz-mbrain_mask.nii.gz-osb_pet.nii.gzCreate abnormality map$zerodoseabn-ppet.nii.gz-ssb_pet.nii.gz-mbrain_mask.nii.gz-oabn.nii.gzPlease see theCommand-line Referencefor details.Hardware requirementsTODOIssues and contributingContributions are very welcome.
If you encounter any problems,
pleasefile an issuealong with a description.
Package: zeroed
RequirementsTo work correctly, you will first need:python(v3.8 or recent) must be installed.pip(v20.0 or recent) must be installed.InstallingGlobally:$sudopipinstallzeroedFor the user:$pipinstallzeroed--userUsingAccess the official page of the project where you can find a description of use:The gem is available as open source under the terms of theMIT License©CreditsSee,AUTHORS.LinksCode:https://github.com/snakypy/zeroedDocumentation:https://github.com/snakypy/zeroed/blob/master/README.mdReleases:https://pypi.org/project/zeroed/#historyIssue tracker:https://github.com/snakypy/zeroed/issues
Package: zerofun
🙅 ZerofunRemote function calls for array data usingZMQ.OverviewZerofun provides aServerthat you can bind functions to and aClientthat
can call the messages and receive their results. The function inputs and
results are both flatdicts of Numpy arrays. The data is sent efficiently
without serialization to maximize throughput.InstallationpipinstallzerofunExampleThis example runs the server and client in the same Python program using
subprocesses, but they could also be separate Python scripts running on
different machines.defserver():importzerofunserver=zerofun.Server('tcp://*:2222')server.bind('add',lambdadata:{'result':data['foo']+data['bar']})server.bind('msg',lambdadata:print('Message from client:',data['msg']))server.run()defclient():importzerofunclient=zerofun.Client('tcp://localhost:2222')client.connect()future=client.add({'foo':1,'bar':1})result=future.result()print(result)# {'result': 2}client.msg({'msg':'Hello World'})if__name__=='__main__':importzerofunserver_proc=zerofun.Process(server,start=True)client_proc=zerofun.Process(client,start=True)client_proc.join()server_proc.terminate()FeaturesSeveral productivity and performance features are available:Request batching:The server can batch requests together so that the user
function receives a dict of stacked arrays and the function result will be
split and sent back to the corresponding clients.Multithreading:Servers can use a thread pool to process multiple
requests in parallel. Optionally, each function can also request its own
thread pool to allow functions to block (e.g. for rate limiting) without
blocking other functions.Async clients:Clients can send multiple overlapping requests and wait
on the results when needed usingFutureobjects. The maximum number of
inflight requests can be limited to avoid requests building up when the
server is slower than the client.Error handling:Exceptions raised in server functions are reported to the
client and raised infuture.result()or, if the user did not store the
future object, on the next request. Worker exception can also be reraised in
the server application usingserver.check().Heartbeating:Clients can send ping requests when they have not received
a result from the server for a while, allowing to wait for results that take
a long time to compute without assuming connection loss.Concurrency:ThreadandProcessimplementations with exception
forwarding that can be forcefully terminated by the parent, which Python
threads do not natively support. Stoppable threads and processes are also
available for coorperative shutdown.GIL load reduction:TheProcServerbehaves just like the normalServerbut uses a background process to batch requests and fan out results,
substantially reducing GIL load for the server workers in the main process.QuestionsPlease open aGitHub issuefor
each question. Over time, we will add common questions to the README.
Package: zerogram
Telegram MTProto API Framework for PythonDocumentation•Releases•NewsPyrogramElegant, modern and asynchronous Telegram MTProto API framework in Python for users and botsfrompyrogramimportClient,filtersapp=Client("my_account")@app.on_message(filters.private)asyncdefhello(client,message):awaitmessage.reply("Hello from Pyrogram!")app.run()Pyrogramis a modern, elegant and asynchronousMTProto APIframework. It enables you to easily interact with the main Telegram API through a user account (custom client) or a bot
identity (bot API alternative) using Python.SupportIf you'd like to support Pyrogram, you can consider:Become a GitHub sponsor.Become a LiberaPay patron.Become an OpenCollective backer.Key FeaturesReady: Install Pyrogram with pip and start building your applications right away.Easy: Makes the Telegram API simple and intuitive, while still allowing advanced usages.Elegant: Low-level details are abstracted and re-presented in a more convenient way.Fast: Boosted up byTgCrypto, a high-performance cryptography library written in C.Type-hinted: Types and methods are all type-hinted, enabling excellent editor support.Async: Fully asynchronous (also usable synchronously if wanted, for convenience).Powerful: Full access to Telegram's API to execute any official client action and more.Installingpip3installpyrogramResourcesCheck out the docs athttps://docs.pyrogram.orgto learn more about Pyrogram, get started right
away and discover more in-depth material for building your client applications.Join the official channel athttps://t.me/pyrogramand stay tuned for news, updates and announcements.
Package: zerogroup
Package DescriptionZeroGroup is a simple wrapper class for managing multiple ZeroMQ sockets and
streams.InstallationThe package may be installed as follows:pip install zerogroupUsage ExamplesSee theexamplesdirectory for demos of how to use the class.DevelopmentThe latest release of the package may be obtained fromGitHub.AuthorSee the included AUTHORS.rst file for more information.LicenseThis software is licensed under theBSD License.
See the included LICENSE.rst file for more information.
Package: zerohertzLib
⚡ Zerohertz's Library ⚡$sudoaptinstallpython3-opencv-y
$pipinstallzerohertzLib
$pipinstallzerohertzLib[api]$pipinstallzerohertzLib[mlops]$pipinstallzerohertzLib[quant]$pipinstallzerohertzLib[all]importzerohertzLibaszz
Package: zero-hid
HID python library for emulating mouse and keyboard on PI.SetupInstall apt dependenciessudoapt-getupdate
sudoapt-getinstall-ygitpython3-fullinstallusb gadget moduleInstallzero-hidwithpippip3installzero-hidUsageNote: You should connect the data usb port (left one) to the raspberry, and NOT the power portControl mousefromzero_hidimportMousem=Mouse()foriinrange(5):m.move(10,10)Control keyboardfromzero_hidimportKeyboardk=Keyboard()k.type('Hello world!')FeaturesRelative / Absolute mouse movementsLeft / Right / Middle clickScrollingTypingHot keysDrag and DropEasy to setupComprehensive TestingExamplesseeexamplesTestsRaspberry Pi ModelRaspbian VersionKernel VersionRaspberry Pi 4Raspbian 126.1Raspberry Pi ZeroRaspbian 5.10-GotachesError when installing with piperror:externally-managed-environmentSeehow-solve-error-externally-managed-environment-when-installing-pip3Or simply executesudorm-rf/usr/lib/python3.11/EXTERNALLY-MANAGED
Package: zeroinger
zeroinger提升编码效率，有效延长程序猿寿命的小工具集目录安装依赖条件pip3安装使用方法时间相关Excel/CSV读写配置文件读取文本文件读写更新日志安装依赖条件python>=3.6.0logzero==1.5.0pip3安装pip3 install --upgrade zeroinger使用方法时间相关StopWatchfrom zeroinger.time.stopwatch import StopWatch
import time
# 创建实例
timer = StopWatch.create_instance()
time.sleep(1)
# 获取从开始到现在的耗时
print('当前耗时',timer.duration())
# 添加一个计时快照
cost = timer.add_snapshot()
print('快照1时间点', cost)
time.sleep(1)
cost = timer.add_snapshot()
print('快照2时间点', cost)
snapshot_list = timer.list_snapshot()
print('所有快照时间点', snapshot_list)
# 重置计时器
timer.reset()
#--------------------------------
当前耗时 1004
快照1时间点 1005
快照2时间点 2006
所有快照时间点 [1005, 2006]Excel/CSV相关XLSX读取excelfrom zeroinger.excel.xlsx import XLSX
test_read_file_path = os.path.join(os.path.dirname(__file__), 'read_test_file.xlsx')
data = XLSX.read_dict_sheet(test_read_file_path, 0)
print(data)
#--------------
[{'列1': 1, '列2': 4, '列3': 7}, {'列1': 2, '列2': 5, '列3': 8}, {'列1': 3, '列2': 6, '列3': 9}]写入excelfrom zeroinger.excel.xlsx import XLSX
golden = [{'列1': 1, '列2': 4, '列3': 7}, {'列1': 2, '列2': 5, '列3': 8}, {'列1': 3, '列2': 6, '列3': 9}]
test_write_file_path = os.path.join(os.path.dirname(__file__), 'write_test_file.xlsx')
XLSX.write_dict_sheet(test_write_file_path, golden)压缩文件读写更新日志2020/01/06 新增压缩文件读取方法
Package: zerokno
ZeroKnoZeroKno is a simple, easy to use and lightweight zero-knowledge password storage method for Python.InstallationpipinstallzeroknoUsagefromzeroknoimportZeroKno# Create a new ZeroKno instancezk=ZeroKno()# Add a new passwordzk.store("password","userid")# Check password matchzk.validate("password","userid")# Truezk.validate("passwor1d","userid")# Falsezk.validate("password","userid1")# Error: Userid not found
Package: zero-knowledge-access-pass-authorizer
What is this?Zero-Knowledge Access Pass (ZKAP) Authorizer is aTahoe-LAFSstorage-system plugin which authorizes storage operations based on privacy-respecting passes.Such passes derive fromPrivacyPass.
They allow a Tahoe-LAFS client to prove it has a right to access without revealing additional information.CopyrightCopyright 2019 PrivateStorage.io, LLCLicensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: zerokspot.recipe.git
ImportantThis package is no longer actively maintained and therefor won’t see any new
features added to it. For more information please check outthe wikiThis simple recipe for zc.buildout fetches data from a given repository
and stores it into its part’s directory. A simple task using this
could look like this:[myapp]
recipe=zerokspot.recipe.git
repository=git://github.com/zerok/zerokspot.gitrecipe.git
rev=7c73978b55fcadbe2cd6f2abbefbedb5a85c2c8cThis would store the repository under ${buildout:directory}/parts/myapp
and keep it at exactly this revision, no matter what happens on the
server.The recipe has following options:repositoryThe absolute URL of the repository to be fetchedrevA revision/commit within this repository the environment
should use.branchIf you want to stay up to date with a certain branch other than
“master”, use this.pathsList of relative paths to packages to develop. Must be used together
with as_egg=true.newestThis overrides the newest-option of the global setting for this
partas_eggSet to True if you want the checkout to be registered as a
development egg in your buildout.cache-nameName of the repository in the download-cache directory.recursiveFollow submodules (Note that submodules are not cloned from the download
cache).Offline installationIf you want to install a part from the download-cache, this is now possible, too:[buildout]
parts = myapp
download-cache = /var/cache/buildout
install-from-cache = true

[mylib]
recipe = zerokspot.recipe.git
repository = http://domain.com/repo.gitWith this configuration, the recipe will look for /var/cache/buildout/repo and
clone it into the local parts/ folder.The recipe also supports an additional “cache-name” setting that lets you
configure the folder name of the repository in the download cache.