Saravanan666/pypi-org huggingface dataset:
Package: ipdatacloud
ipdatacloud官网ip查询 ipv4查询 ipv6查询用于识别国家、地区、城市、经纬度、邮政编码、时区、连接速、ISP、区号、气象站数据、区号气象数据、、移动运营商、海拔等。编码：UTF8 字节序：Little-Endian性能：每秒解析1000w+ 查询非常快返回字符串洲|国家|省份|城市|区县|运营商|区域代码|国家英文|国家英文简写|经度|纬度|海拔|邮编|城市代码|气象站|ASN码|预留|街道|时区技术咨询及免费试用请添加微信使用方式缓存VectorIndex索引提前从文件中加载出来VectorIndex数据.fromipdatacloud.ipimportIPV4FinddefsearchWithContent():# 1. 预先加载整个 xdbfilePath=your_Path;file=IPV4Find(filePath=filePath)# 2. 执行查询ip="1.2.3.4"ip_search=file.get(ip)print(ip_search)缓存整个 文件我们也可以预先加载整个文件的数据到内存，然后基于这个数据创建查询对象来实现完全基于文件的查询fromipdatacloud.ipimportIPV4FinddefsearchWithContent():# 1. 预先加载整个 xdbfilePath=your_Path;file=IPV4Find(filePath=filePath,method='content')# 2. 执行查询ip="1.2.3.4"ip_search=file.get(ip)print(ip_search)输入 ip 即可进行查询测试。也可以分别设置method为 vectorIndex/content 来测试两种不同缓存实现的效率。
Package: ipdbugger
ipdbuggeris a code debugging tool based onipdb.Use thedebugdecorator on functions or classes to debug them.
What actually happens: it surrounds each statement of the functions with a
try-except, and starts an ipdb session in the exception handling section.Installing$pipinstallipdbuggerUsingfromipdbuggerimportdebug@debugdeff():foo=1+1bar=1/0baz=2+2Now when you runf(), you’ll get into an ipdb shell right after the
error (the division by zero):>>>fromipdbuggerimportdebug>>>@debugdef f():
        foo = 1 + 1
        bar = 1 / 0
        baz = 2 + 2>>>f()Traceback (most recent call last):File "<ipython-input-2-5720bb02ab1d>", line 4, in f
    bar = 1 / 0
 ZeroDivisionError:integer division or modulo by zero> <ipython-input-2-5720bb02ab1d>(5)f()
      2 def f():
      3     foo = 1 + 1
      4     bar = 1 / 0
----> 5     baz = 2 + 2
      6ipdb> foo
2
ipdb>From there, you have a couple of choices:retrythe actioncontinuewith the rest of the flow (and ignore the error)raisethe exception, as if you didn’t catch it at allUse any other of the availableipdbcommands, likejump
Package: ipdetector
ipdetectorThis is a Simple project to categorize and validate private and public IP/IP ranges.Category ID0 : Private IP1 : Public IP2 : Private IP range3 : Public IP rangeOutput : [, ]InstallationRun the following to install:pipinstallipdetectorUsage>>fromipdetectorimportipCategorizer>>ipCategorizer('192.168.1.0/24')[2,'192.168.1.0/24']>>
Package: ipdf
ipdf (innovata pdf)PDF handler.PyMuPDFPyPDF2ipylovepdf사전작업ROOT_PATH 를 OS-환경변수로 수동으로 저장.
: export ROOT_PATH=your_root_path임시방편 작업 (PyPI 패키지 정식 등록 전)LIB_PATH 를 OS-환경변수로 수동으로 저장.
: exort LIB_PATH=~/libs
Package: ipdon
IPdonIPdonis a fast IP intelligence solution. This is the official Python library which benchmarks as the fastest Python library for obtaining data from any IP.Natively it provides:Direct access to Geographical, Network, Company or Domain based information on any IP in the world.A 30-40x speed increase versus competing services due to the services algorithmProvides a multi-dimensionaldictionaryresponse identical to the IPdon service itself.Internally utilizesorjsonfor fast binary-based serialization.Has a free tier without needing an API key (token) Learn more aboutplanshere.IPdon happily supports CPythonUsageInstallTo install a wheel from PyPI:pipinstall--upgradeipdonQuickstartThis is an example of calling the servicefromipdonimportIPdon# Leave string '' empty to use the Free tier.token='5ae79d31-6e48-4641-a0fd-bcee9cd30ff6'ipdon=IPdon(token)# You can add another argument to filter response (faster), use ipdon.query(<ip>, <filter>)response=ipdon.query('34.241.171.232')print(response)Example response:{   'abuse': {'contacts': ['abuse@amazonaws.com']},
    'domains': ['might-d-light.com'],
    'location': {   'city': 'Dublin',
                    'continent': 'Europe',
                    'country': 'Ireland',
                    'country_iso': 'IE',
                    'currency': 'Euro',
                    'dialcode': '353',
                    'languages': ['en-IE', 'ga-IE'],
                    'latitude': 53.3379,
                    'longitude': -6.2591,
                    'map_image': 'https://staticmap.thisipcan.cyou/?lat=53.3379&lon=-6.2591',
                    'postalcode': 'D02',
                    'region': 'Northern Europe',
                    'state': 'Leinster'},
    'network': {   'cidr_size': 4194304.0,
                   'cidr_subsegment': '34.240.0.0/13',
                   'ip_subsegment_end': '34.247.255.255',
                   'ip_subsegment_end_int': 586678271,
                   'ip_subsegment_start': '34.240.0.0',
                   'ip_subsegment_start_int': 586153984,
                   'ip_type': 'ipv4',
                   'rir': 'arin',
                   'rir_cidr_segment': '34.192.0.0/10'},
    'organization': {   'asn': '16509',
                        'description': 'Amazon NA Prefix',
                        'name': 'NET34'},
    'request': {   'query': '34.241.171.232',
                   'status': 'success',
                   'subscription': False},
    'time': {   'timezone': 'Europe/Dublin',
                'timezone_is_dst': True,
                'timezone_utc_offset': 0.0}}See IPdon documentation for an elaborate description on how to use the APIhere
Package: ipeanim
ipeanimipeanimis a thin wrapper aroundiperender. It allows you to render
multiple images from a single .ipe file.Ipe is a free drawing editor created by Otfried Cheong:http://ipe.otfried.org/ipeanim on PyPIInstallationInstall Ipe and libipe fromhttp://ipe.otfried.org/Install this package either via pip:pip install ipeanimOr just download the "ipeanim" file from here and put it in your path. It only requires python 3.7+.Usage$ ipeanim path/to/file.ipe
$ ipeanim --help
Package: iperf_graphite
Run bi-directional iperf3 tests and send results to Graphite.
Results include bps and retransmitsInstallationpipinstalliperf_graphiteUsage$iperf_graphite--helpusage:iperf_graphite[-h][-fCONFIG_FILE][-V]sendiperfstatstographiteoptionalarguments:-h,--helpshowthishelpmessageandexit-fCONFIG_FILEConfigfile-V,--versionshowprogram'sversionSample config file:# Configuration for iperf-graphite.py# Graphite detailscarbon_server:myserver.example.netcarbon_port:2003data_point_prefix:"test.iperf"# Iperf optionsiperf_port:5201iperf_test_duration:10# Sleep time (seconds) between testssleep:0# List of tests to iterate overtests:-src:192.0.2.1dst:192.0.2.2-src:1.2.3.4dst:5.6.7.8AuthorsCarlos Vicente (<cvicente@dyn.com>)
Package: ipernity_api
Python wrapper for ipernity.com API, inspired by [python-flickr-api](https://github.com/alexis-mignon/python-flickr-api).Main FeaturesObject Oriented implementationSupport full API on ipernity.comSupport OAuth authenticationBuilt-in document of Ipernity APIContext sensitive objects, easy to useSimple GET request cache mechanism (optional)Unittest to guarantee code qualityRequirementsBy far, just support Python2.No extra library or modules dependence, Python itself is enough.TutorialPlease see [here](https://github.com/oneyoung/python-ipernity-api/wiki/Tutorial) for a quick start.
Package: ipf
# access-ci-org/ipf %VER%-%REL%
# README## OverviewThe Information Publishing Framework (IPF) is a generic framework used by resource operators to gather and publish
dynamic resource information in [GLUE 2 serialized format](http://www.ogf.org/documents/GFD.147.pdf). IPF was used
by the TeraGrid, XSEDE, and XSEDE 2 programs, and is currently being used by the ACCESS-CI program to publish
high-performance compute cluster information.IPF gathers and publishes information using simple workflows. These workflows are defined using JSON (see the
etc/workflows directory) and steps in the workflows are implemented as Python classes. Each step in the
workflow can require input Data, can produce output Data, and can publish Representations of Data. A typical
workflow consists of a number of information gathering steps and a few steps that publish representations to
files or to remote services (e.g. REST, messaging).Workflow steps specify what Data they require and what Data they produce. This allows IPF to construct
workflows based on partial information - in the case where there are not steps that produce the same Data, an
entire workflow can be constructed from a single publish step and its required input Data. At the other
extreme, workflows can be exactly specified with specific steps identified and the outputs of steps bound to
the inputs of other steps. A typical workflow (e.g. GLUE 2) specifies what steps to include but lets IPF
automatically link outputs to inputs of these steps.Workflows can run to completion relatively quickly or they can continuously run. The first type of workflow
can be used to run a few commands or look at status files and publish that information. The second type of
workflow can be used to monitor log files and publish entries written to those files. Workflows are typically
run periodically as cron jobs. The program libexec/run_workflow.py is for executing workflows that complete
quickly and the program libexec/run_workflow_daemon.py is used to manage long-running workflows. The daemon## LicenseThis software is licensed the Apache License Version 2.0.## InstallationQuickstart instructions are in [docs/Quickstart.md](docs/Quickstart.md).
More comprehensive instructions are in [docs/INSTALL.md](docs/INSTALL.md).## Support InformationThis software is currently maintained by the ACCESS CONECT project.The source is maintained in the [ACCESS-CI GitHub](https://github.com/access-ci-org/ipf).  ACCESS-CI resource
providers and other members of the ACCESS-CI community are encourage to contribute bug fixes and improvements.Software bugs may be reported as GitHub issues.  ACCESS-CI related support requests should be submitted through
the ACCESS-CI ticket system.## AcknowledgementsThis work was supported by the TeraGrid, XSEDE, FutureGrid, XSEDE 2, and ACCESS CONECT projects under
National Science Foundation grants 0503697, 1053575, 0910812, 1548562, and 2138307.
Package: ipfabric-diagrams
DEPRECATED AND MERGED INTOipfabricPACKAGE.This package has been merged intoipfabricand only is pointing to the new location.INSTALLING AFTERipfabric==v6.6.0WILL NOT WORK AND CAN BREAK ENVIRONMENTS.ipfabric_diagrams is a Python module for connecting to and graphing topologies against an IP Fabric instance.AboutFounded in 2015,IP Fabricdevelops network infrastructure visibility and analytics solution to
help enterprise network and security teams with network assurance and automation across multi-domain heterogeneous
environments. From in-depth discovery, through graph visualization, to packet walks and complete network history, IP
Fabric enables to confidently replace manual tasks necessary to handle growing network complexity driven by relentless
digital transformation.VersioningStarting with IP Fabric version 5.0.x the python-ipfabric  will need to
match your IP Fabric version.  The API's are changing and instead ofapi/v1they will now beapi/v5.0.Version 5.1 will have backwards compatability with version 5.0 however 6.0 will not support any 5.x versions.
By ensuring that your ipfabric SDK's match your IP Fabric Major Version will ensure compatibility and will continue to work.Installationpip install ipfabric-diagramsIntroductionThis package is used for diagramming via the API for IP Fabric v4.3.0.Examples can be located underexamplesdirectory.AuthenticationPlease take a look atpython-ipfabricfor all authentication options.fromipfabric.diagramsimportIPFDiagramipf=IPFDiagram(base_url='https://demo3.ipfabric.io/',auth='token',verify=False,timeout=15)DevelopmentIPFabric uses poetry for the python packaging module. Install poetry globally:pip install poetryTo install a virtual environment run the following command in the root of this directory.poetry installTo test and build:poetry run pytest
poetry buildPrior to pushing changes run:poetry run black ipfabric_diagrams ipfabric
poetry update
Package: ipfabric-httpx-auth
ipfabric_http_authDEPRECATED: THIS WAS REMOVE INipfabricPACKAGE IN v6.1.0IPFabric is a Python module for connecting to and communicating against an IP Fabric instance.AboutFounded in 2015,IP Fabricdevelops network infrastructure visibility and analytics solution to
help enterprise network and security teams with network assurance and automation across multi-domain heterogeneous
environments. From in-depth discovery, through graph visualization, to packet walks and complete network history, IP
Fabric enables to confidently replace manual tasks necessary to handle growing network complexity driven by relentless
digital transformation.Installationpip install ipfabric_httpx_authDevelopmentIPFabric uses poetry for the python packaging module. Install poetry globally:pip install poetryTo install a virtual environment run the following command in the root of this directory.poetry installTo test and build:poetry run pytest
poetry buildGitHub Actions will publish and release. Make sure to tag your commits:ci: Changes to our CI configuration files and scriptsdocs: No changes just documentationtest: Added test casesperf: A code change that improves performancerefactor: A code change that neither fixes a bug nor adds a featurestyle: Changes that do not affect the meaning of the code (white-space, formatting, missing semi-colons, etc)fix: a commit of the type fix patches a bug in your codebase (this correlates with PATCH in Semantic Versioning).feat: a commit of the type feat introduces a new feature to the codebase (this correlates with MINOR in Semantic Versioning).BREAKING CHANGE: a commit that has a footer BREAKING CHANGE:, or appends a ! after the type/scope, introduces a breaking
API change (correlating with MAJOR in Semantic Versioning). A BREAKING CHANGE can be part of commits of any type.
Package: ipfabric_logicmonitor
IP Fabric LogicMonitor IntegrationIP FabricIP Fabric is a vendor-neutral network assurance platform that automates the
holistic discovery, verification, visualization, and documentation of
large-scale enterprise networks, reducing the associated costs and required
resources whilst improving security and efficiency.It supports your engineering and operations teams, underpinning migration and
transformation projects. IP Fabric will revolutionize how you approach network
visibility and assurance, security assurance, automation, multi-cloud
networking, and trouble resolution.Project DescriptionBETA STILL IN DEVELOPMENT.Installation< Installation Information >Configuration< Configuration Information >Usage< Any external documentation to reference? If not remove section >SupportTODO: How to open issue in Gitlab, some base information around it, etc.ContributingTODO: How to contribute?
Package: ipfabric-netbox
OverviewThis plugin allows the integration and data synchronization between IP Fabric and NetBox.The plugin uses IP Fabric collect network data utilizing theIP Fabric Python SDK. This plugin relies on helpful features in NetBox likeStaged ChangesandBackground Tasksto make the job of bringing in data to NetBox easier.Multiple IP Fabric SourcesTransform MapsScheduled SynchronizationDiff VisualizationScreenshotsSources.Snapshots.Transform Maps.Ingestion.Diff Visualization.DocumentationFull documentation for this plugin can be found atIP Fabric Docs.User GuideAdministrator Guide
Package: ipfabric_nornir
ipfabric_nornirAboutFounded in 2015,IP Fabricdevelops network infrastructure visibility and analytics solution to
help enterprise network and security teams with network assurance and automation across multi-domain heterogeneous
environments. From in-depth discovery, through graph visualization, to packet walks and complete network history, IP
Fabric enables to confidently replace manual tasks necessary to handle growing network complexity driven by relentless
digital transformation.Special ThanksThis project is an IP Fabric officially supported fork ofnornir_ipfabricbyroutetonull.  Thank you for your work!InstallThe recommended way to installipfabric_norniris via pippipinstallipfabric_nornirRequirementsAn instance ofIP Fabricis required to collect information.Example usageSetupUsing environment variablesSet environment vars to provide url and credentials to connect to the IP Fabric serverexportIPF_URL=https://ipfabric.localexportIPF_TOKEN=myToken# Or Username and PasswordexportIPF_USER=adminexportIPF_PASSWORD=mySecretPasswordUsing.envfileThe easiest way to use this package is with a.envfile.  You can copy the sample and edit it with your environment variables.cp sample.env .envThis contains the following variables which can also be set as environment variables instead of a .env file.IPF_URL="https://demo3.ipfabric.io"
IPF_TOKEN=TOKEN
IPF_VERIFY=trueOr if using Username/Password:IPF_URL="https://demo3.ipfabric.io"
IPF_USERNAME=USER
IPF_PASSWORD=PASSRunningfromnornirimportInitNornirnr=InitNornir(inventory={"plugin":"IPFabricInventory"})Using the InitNornir functionInitfromnornirimportInitNornirnr=InitNornir(inventory={"plugin":"IPFabricInventory","options":{"base_url":"https://ipfabric.local","token":"Token",# or "username":"admin", "password":"mySecretPassword","verify":True,"platform_map":"netmiko",# "netmiko" (Default), "napalm", or "genie","default":{"username":"device_username","password":"device_password"},},},)Using the Nornir configuration fileFileconfig.yaml---inventory:plugin:IPFInventoryoptions:base_url:"https://ipfabric.local"token:"TOKEN"# username: "admin"# password: "mySecretPassword"verify:trueplatform_map:netmiko# "netmiko", "napalm", or "genie"default:username:'device_username'password:'device_password'Usage:fromnornirimportInitNornirnr=InitNornir(config_file="config.yaml",inventory={"plugin":"IPFabricInventory"})
Package: ipfinder
This is a simple Python library to get an external IP by HTTPS.Example:import ipfinderlink = ipfinder.IPFinder()
link.updateip()
print(link.getip())API Reference:class IPFindermethods:IPFinder.seturl(string) - OPTIONAL - Set the URL of the IP lookup site. Site needs to return IP only.
IPFinder.getip() - Returns IP address as a string.
IPFinder.updateip() - Send connection request to get external IP.
Package: ipfindx
[+] ipfindx is a command-line tool that allows you to quickly retrieve information about an IP address from the ip-api.com API. With ipfindx, you can quickly and easily obtain information such as the IP address's location, country, region, city, and ISP. To use ipfindx, simply provide an IP address as a command-line argument, and ipfindx will make a request to the ip-api.com API and display the results. You can also specify an output file name with the `-o` or `--output` option to save the results to a file. ipfindx is a useful tool for network administrators, developers, and anyone who needs to quickly obtain information about an IP address. With its simple and intuitive command-line interface, ipfindx makes it easy to look up IP addresses and obtain the information you need to diagnose network issues, troubleshoot problems, and perform other tasks.[+] Features:- Retrieve information about an IP address from the ip-api.com API- Display the IP address's location, country, region, city, and ISP- Save the results to a file with the `-o` or `--output` option- Simple and intuitive command-line interface- Useful for network administrators, developers, and anyone who needs to quickly obtain information about an IP address- Open-source and available for free on PyPI
Package: ipfml
Image Processing For Machine LearningInstallationpipinstallipfmlHow to use ?To use, simply do :fromPILimportImagefromipfml.processingimporttransformimg=Image.open('path/to/image.png')s=transform.get_LAB_L_SVD_s(img)ModulesThis project contains modules.metrics:Metrics computation for model performanceutils:All utils functions developed for the packageexceptions:All customized exceptionsfilters:Image filter module with convolutioniqa:Image quality assessmentsprocessing:Image processing moduleAll these modules will be enhanced during development of the package. Documentation is availablehere.How to contributePlease refer to theguidelinesfile if you want to contribute!ContributorsjbuisineLicenseMIT
Package: ipfromwebpage
ipfromwebpageSummary:Takes a webpage and scrapes for IPv4 Addresses. Then prints the IPs. (aggregated where possible)Quickstart:Install usingpip install ipfromwebpageRun the code asipfromwebpage <url>where<url>is the fully qualified URL you wish to scrap for IPs.Code Example:ipfromwebpage https://www.cloudflare.com/ips
================
IPv4 addresses:
103.21.244.0/22
103.22.200.0/22
103.31.4.0/22
104.16.0.0/12
108.162.192.0/18
131.0.72.0/22
141.101.64.0/18
162.158.0.0/15
172.64.0.0/13
173.245.48.0/20
188.114.96.0/20
190.93.240.0/20
197.234.240.0/22
198.41.128.0/17
================
IPv6 addresses:
2400:cb00::/32
2405:8100::/32
2405:b500::/32
2606:4700::/32
2803:f800::/32
2a06:98c0::/29
2c0f:f248::/32
Package: ipfs-api
IPFS API Bindings for PythonCheck outipfsandthe api command referencefor more information about the IPFS Api.Install with pip:pip install ipfs-apiBasic use-case (requires a running instance of IPFS daemon):>>>importipfsApi>>>api=ipfsApi.Client('127.0.0.1',5001)>>>res=api.add('test.txt')>>>res{'Hash':'QmWxS5aNTFEc9XbMX1ASvLET1zrqEaTssqt33rVZQCQb22','Name':'test.txt'}>>>api.cat(res['Hash'])'fdsafkljdskafjaksdjf\n'Administrative functions:>>>api.id(){'Addresses':['/ip4/127.0.0.1/tcp/4001/ipfs/QmS2C4MjZsv2iP1UDMMLCYqJ4WeJw8n3vXx1VKxW1UbqHS','/ip6/::1/tcp/4001/ipfs/QmS2C4MjZsv2iP1UDMMLCYqJ4WeJw8n3vXx1VKxW1UbqHS'],'AgentVersion':'go-ipfs/0.3.8-dev','ID':'QmS2C4MjZsv2iP1UDMMLCYqJ4WeJw8n3vXx1VKxW1UbqHS','ProtocolVersion':'ipfs/0.1.0','PublicKey':'CAASpgIwgg ... 3FcjAgMBAAE='}Pass in API options:>>>api.pin_ls(opts={'type':'all'}){'Keys':{'QmNMELyizsfFdNZW3yKTi1SE2pErifwDTXx6vvQBfwcJbU':{'Count':1,'Type':'indirect'},'QmNQ1h6o1xJARvYzwmySPsuv9L5XfzS4WTvJSTAWwYRSd8':{'Count':1,'Type':'indirect'},...Add a directory and match against a filename pattern:>>>api.add('photos',match='*.jpg')[{'Hash':'QmcqBstfu5AWpXUqbucwimmWdJbu89qqYmE3WXVktvaXhX','Name':'photos/photo1.jpg'},{'Hash':'QmSbmgg7kYwkSNzGLvWELnw1KthvTAMszN5TNg3XQ799Fu','Name':'photos/photo2.jpg'},{'Hash':'Qma6K85PJ8dN3qWjxgsDNaMjWjTNy8ygUWXH2kfoq9bVxH','Name':'photos/photo3.jpg'}]Or add a directory recursively:>>>api.add('fake_dir',recursive=True)[{'Hash':'QmQcCtMgLVwvMQGu6mvsRYLjwqrZJcYtH4mboM9urWW9vX','Name':'fake_dir/fsdfgh'},{'Hash':'QmNuvmuFeeWWpxjCQwLkHshr8iqhGLWXFzSGzafBeawTTZ','Name':'fake_dir/test2/llllg'},{'Hash':'QmX1dd5DtkgoiYRKaPQPTCtXArUu4jEZ62rJBUcd5WhxAZ','Name':'fake_dir/test2'},{'Hash':'Qmenzb5J4fR9c69BbpbBhPTSp2Snjthu2hKPWGPPJUHb9M','Name':'fake_dir'}]This module also contains some helper functions for adding strings, json, and even python objects to IPFS:>>>lst=[1,77,'lol']>>>api.add_pyobj(lst)'QmRFqz1ABQtbMBDfjpMubTaginvpVnf58Y87gheRzGfe4i'>>>api.get_pyobj(_)[1,77,'lol']How to ContributeIRCJoin us on IRC at#ipfsonchat.freenode.netif you have any suggestions or questions,
or if you just want to discuss IPFS and python.Bug reportsYou can submit bug reports using theGitHub issue tracker.Pull requestsPull requests are welcome.  Before submitting a new pull request, please
make sure that your code passes both thepep8formatting check:$ tox -e pep8And the unit tests:$ toxYou can arrange to run the pep8 tests automatically before each commit by
installing apre-commithook:$ ./tools/pre-commit --installPlease make sure to include new unit tests for new features or changes in
behavior.LicenseThis code is distributed under the terms of theMIT license.  Details can be found in the fileLICENSE.txtin this repository.