Saravanan666/pypi-org huggingface dataset:
Package: hashpass
hashpass哈希密码生成程序关于 hashpass如果所有的网站都使用同一个密码毫无疑问是非常不安全的, 密码一旦丢失所有账号都会被一锅端. 常见的处理方法是生成随机密码, 目前有很多软件和应用可以做到, 但随机密码有个不好的地方, 密码非常难记需要有个地方储存密码, 你可以保存到云上或者本地, 但这又产生信任和丢失的问题. 于是我想用一种尽可能简单的方法, 来生成复杂同时又不需要储存的密码, 那就是记住一个盐值, 然后生成哈希密码.算法将输入的域名(domain)与环境变量设置的盐(HASHPASS_SALT)进行字符串拼接拼接得到的字符串使用SHA-256算法加密然后把得到的哈希值进行base64编码截取前length个字符串, 返回结果使用输入域名和密码长度, 点击开始, 程序会自动复制结果到剪贴板, 直接CTRL + V即可打包程序pipinstall-rrequirements.txt
pyinstaller-Fwmain.py
Package: hashpipe
hashpipe -- Regular expression match hasherhashpipe is a command line tool and a Python library for hashing
regular expression matches in input data.Matches are hashed with their HMAC hex digests using a configurable
key and digest algorithm, surrounded by angle brackets, and optionally
prefixed with a configurable string within the brackets.What gets hashed for each match depends on whether the regular
expression contains capturing groups. If it doesn't, the entire match
content is hashed. If it does, only content of the first capturing
group is.The command line tool operates as a pipe, reading standard input and
outputting to standard output. It has optional shell completion support
usingargcomplete.ExamplesPythonimportosimportrefromhashpipeimportHashpipehashpipe=Hashpipe(pattern=re.compile(br"\bfox|dog\b"),algorithm="sha256",key=os.urandom(128),)hashed=hashpipe.hash_matches(b"The quick brown fox jumps over the lazy dog.")# hashed now contains something like:# b'The quick brown <00adbe4c178e322e582e4e45c4989a204655c4b3960c0be298bc763e29dc738b> '# b'jumps over the lazy <ee68954fe2f64931fb63756a5ecd1e22b90984c6b29fe3340b159dcff1f98244>.'Shell$ hashpipe --key=deadbeef --algorithm=md5 --prefix='{md5}' '^[^:]+' < /etc/passwd
<{md5}31572cc0e16e31b00f9888a18310ceab>:x:0:0:root:/root:/bin/bash
<{md5}1b4fa176c601aadfa5453b9074ba32d8>:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...Changes0.9.2 (2020-01-12)Add-A/--available-algorithmsoption for listing available algorithmsAdd optional shell completion support using argcomplete
Package: hashpoll-cli
Hashpoll (CLI)Hashpoll is a hashnode widget that enables seamless polls on any post. It is a lightweight tool that generates code for you to put in hashnode's widget field to create polls that just blend in with the rest of your content. You can use it directly from the command line or through the Web interface, and manage your poll as needed.Hashpoll CLI is a handy tool to extend and supplement Hashpoll. It allows you to seamlessly create polls from the command line. The tool automatically gives you the code to place in the widgets section of Hashnode.InstallationInstall hashpoll-cli with pippipinstallhashpoll-cliHashnode WidgetsYou can learn how to use hashnode widget overhere.CommandsCreateThis is the command to create polls from the CLI.hashpollcreate[question]--option1[option1]--option2[option2]--option3[option3]--option4[option4]orpython-mhashpollcreate[question]--option1[option1]--option2[option2]--option3[option3]--option4[option4]TipsPut the question or options (if multiple words) in quotes to avoid the terminal registering this as multiple arguments.If you miss adding one of the options, the program will prompt you for entering them.ViewThis is a command for viewing all details of a particular poll.hashpollview[PollID]orpython-mhashpollview[PollID]VoteThis is a command to vote on a specific poll.hashpollvote[PollID][OptionNumber]orpython-mhashpollvote[PollID][OptionNumber]Open-pollThis is a simple command to open a poll in the default browser.hashpollopen-poll[PollID]orpython-mhashpollopen-poll[PollID]ResultsThis is a command to fetch the current data from poll responses.hashpollresults[PollID]orpython-mhashpollresults[PollID]CodeThis is handy commad to generate the Hashnode Widget Code for a particular poll.hashpollcode[PollID]orpython-mhashpollcode[PollID]FeaturesLightweightCLI and Web BasedSeamlessEasy-to-integrateAuthors@Arpan-206Tech StackClient:AWS Amplify, Svelte, Typer, Rich, PicoCSSServer:Node, AWS Amplify, FastAPIRoadmapPassword ProtectionIn-depth analyticsAuthenticationAbility to modify a pollLicenseMITAcknowledgementsHashpoll would like to thank the teams behind the following projects as they played a crucial part in enabling Hahpoll.AWS AmplifyHashnodeFastAPITyperPicoCSSFeedbackIf you have any feedback, please reach out to us atarpan@hackersreboot.tech.ContributingContributions are always welcome!Seecontributing.mdfor ways to get started.Please adhere to this project'scode of conduct.
Package: hashr
hashrSimply a custom hashing package with optional salting, able to be both run from the command line and imported as a package.InstallationTo install, just run either of the below commands.pipinstallhashrpip3installhashrUsageCommand LineTo use hashr from the command line, run:hashr[input]Make sure to surround an input with double quotes if it contains spaces.There is also the option to add a salt, which causes duplicate string to have unique hashes. To use this, add the-sflag to the command.Import PackageTo import hashr as a package, addfrom hashr import [function]to the top of your Python file.
The available functions are as follows:hashr: main hashing algorithm, turns any string into a string hashsaltr: generates a seven digit salt, either numerical or alphabeticalnumber_to_letters: converts a number to letters based on each digit
Package: hashranking
In Deep Learning research, hashing, retrieval, and ranking tasks often require calculation of mAP of retrieval, which can be computationally expensive.
Often, hashes are represented as ndarrays of floats, where the sign of the float number has the meaning of a bit. This happens because neural networks work with floats and that is precisely the output that they give. Computing ranking of documents in the DB based the query typically implemented in NumPy, which can be quite suboptimal.This package provides several functions that allow fast hamming distance computation, ranking, and mAP computation.All API has two backends:
* NumPy implementation, which is simple, straightforward and as efficient as it can get in pure NumPy. Used as a reference.
* C++ Python extension that implements the same API, on average 10x faster than NumPy implementation and significantly more memory efficient.
Package: hash_ring
About hash_ringImplements consistent hashing that can be used when
the number of server nodes can increase or decrease (like in memcached).
The hashing ring is built using the same algorithm as libketama.Consistent hashing is a scheme that provides a hash table functionality
in a way that the adding or removing of one slot
does not significantly change the mapping of keys to slots.More about hash_ring can be read in a blog post (that explains the idea in greater details):Consistent hashing implemented simply in python <http://amix.dk/blog/viewEntry/19367>More information about consistent hashing can be read in these articles:Web Caching with Consistent Hashing <http://www8.org/w8-papers/2a-webserver/caching/paper2.html>Consistent hashing and random trees <http://citeseerx.ist.psu.edu/legacymapper?did=38148>There is also a wrapper MemcacheRing that extends python-memcache to use consistent hashing
for key distribution.ExampleBasic example of usage (for managing memcached instances):memcache_servers = ['192.168.0.246:11212',
                    '192.168.0.247:11212',
                    '192.168.0.249:11212']

ring = HashRing(memcache_servers)
server = ring.get_node('my_key')Example using weights:memcache_servers = ['192.168.0.246:11212',
                    '192.168.0.247:11212',
                    '192.168.0.249:11212']
weights = {
    '192.168.0.246:11212': 1,
    '192.168.0.247:11212': 2,
    '192.168.0.249:11212': 1
}

ring = HashRing(memcache_servers, weights)
server = ring.get_node('my_key')How to use MemcacheRing:from hash_ring import MemcacheRing
mc = MemcacheRing(['127.0.0.1:11212'])
mc.set('hello', 'world')
print mc.get('hello')The code should be clean and simple. Feel free to concat the author if you detect bugs.
Package: hashstate
HashstateThis is a Python C extension module that forks thehashlibimplementation
from CPython itself to add support for a single feature: the ability to
serialize and deserialize hash objects so that the hash objects do not have
to persist in memory for the whole duration of the hash computation.Usagepipinstallhashstateimporthashstate# Contains all the same constructors as hashlibhash1=hashstate.sha512()hash1.update('...')s=hash1.serialize()# gives back bytes objecthash2=hashstate.sha512()hash2.deserialize(s)asserthash1.digest()==hash2.digest()DevelopersBuild the package (requires openssl on your build paths):python setup.py sdist bdist_wheelIf building a MacOS wheel, also run:delocate-wheel -v ./dist/*-macosx_*.whlBuild the linux bdist_wheels (64-bit only at the moment):docker build -t manylinux-hashstate .
docker run --rm -v $(pwd)/dist:/dist manylinux-hashstateUpload to pypitwine upload dist/*
Package: hashstorm
HashStorm1. IntroduçãoAplicação CLI em Python para realizar o decode de hashes, baseado em um ataque de força bruta a partir de uma wordlist.LicençaAGPLv32. InstalaçãopipinstallhashstormChecando a versão:hashstorm-vouhashstorm--version2.1. Pré-requisitos:Python 3.10 ou superiorPip3. Exemplos de usoTexto em claro teve aplicação de md5 -> base64 -> sha1. Tem-se o hash sha1, tentativa através da wordlist, voltar e chegar no texto em claro:hashstormwordlist/storm-wordlist.txtmd5,base64,sha1Texto em claro teve aplicação de md5 -> sha512. Tem-se o hash sha512, tentativa através da wordlist, voltar e chegar no texto em claro:hashstormwordlist/storm-wordlist.txtmd5,sha512Texto em claro teve aplicação de sha256 -> md5 -> base64 -> sha1. Tem-se o hash sha512, tentativa através da wordlist, voltar e chegar no texto em claro:hashstormwordlist/storm-wordlist.txtsha256,md5,base64,sha1Consultando o help:hashstorm-houhashstorm--help
Package: hashsystem-token
UseCases Docs# generating password hash and validating itfromhashsystem.hash.packageimportHashMachenism# HashMachenism takes seeds as params for password saltseeds={"seeds":[1,2,1,2]}obj=HashMachenism(seeds)dummypassword="testingtestpassword"password_hash=obj.hasspass(dummypassword)# output '$RMA-b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0b@1c#2i(8a~0a~0'# verifying pasword hashobj.verify_password(password_hash)# returns True if verifiedGenerating token and and decoding it# imports for token generationfromhashsystem.hash.packageimportTokenGeneratorfromdatetimeimportdatetime# common varspayload=dict(email="test@test.com",exp=datetime.now())seeds=[1000,"%",20]obj=TokenGenerator(payload,seeds)token_hash=obj.get_token_pairs()# decode tokendecoded=obj.get_formetted_token(token_hash['access_token'])# please checkout documentaion for further implementation for token related features
Package: hashtable-nicolerg
HashTableThis simple package provides a custom implementation of a hash table in Python,
created by followingthis tutorialwritten by Bartosz Zaczyński.
TheHashTableclass replicates many methods from Python dictionaries, includingHashTable.clear()andHashTable.update().InstallationThis package is available inPyPI.
Use the package managerpipto installHashTable.python3-mpipinstallhashtable-nicolergAlternatively, experiment withHashTablein aDocker container.Usagefromhashtable_nicolerg.hashtableimportHashTable# Create an instance of HashTable with initial size 10# and loading factor threshold 0.5, meaning the HashTable# will be resized to have 2x capacity whenever the number of# key-value pairs is at least half the current capacityhash_table=HashTable(capacity=10,load_factor_threshold=0.5)hash_table["blue"]="sea"# Add key-value pair "blue":"sea"hash_table["list"]=[1,2,3]# Add key-value pair with a mutable valuelen(hash_table)# Return number of key-value pairshash_table.capacity# Return current capacityhash_table.load_factor# Return current load factorhash_table.keys# Return set of keyshash_table.values# Return list of valueshash_table.pairs# Return list of key-value pairsdelhash_table["list"]# Delete key-value pair for specified keyhash_table.update({"blue":"0000FF"})# Update value for key "blue" using a dictionaryhash_table["blue"]# Return value for key "blue"hash_table.clear()# Remove all key-value pairsMotivationDeveloping this package reinforced knowledge in the following areas:Python classes, including dunder methodsHash table implementation, including handling hash collisionsTesting, including TDD, unit tests, andpytestDevelopingPython packagesDev notesCreate therecommended directory structureand populate filesBuild the package in the same directory aspyproject.toml, which should create adist/directorypython3-mbuildUseTwineto upload the package toPyPIpython3-mpipinstall--upgradetwine
python3-mtwineuploaddist/*Install your newly uploaded packagepython3-mpipinstallhashtable-nicolergTo update the package, increment the version in `pyproject.toml``, build, and uploadpython3-mbuild
python3-mtwineupload--skip-existingdist/*Install and test your new versionpython3-mpipinstallhashtable-nicolerg--upgrade
Package: hashtable-python
HashTableHashTable is a python library (Data Structure) it has almost all functionality of dictionary in python.InstallationUse the package managerpipto install HashTable.pipinstallhashtable-pythonUsagefromhashtableimportHashTablemy_hashtable=HashTable(5)# Create instance of hashtable with fixed sized 5my_hashtable['mango']=100# Creating key='mango' and value=100my_hashtable.items()# Returns list of tuples of key and value [(kay, value),...)my_hashtable.keys()# Returns list of keysmy_hashtable.values()# Returns list of valuesmy_hashtable['mango']# Returns value of specified keymy_hashtable.delete('mango')# Deletes item in the specified keyLicenseMIT LicenseCopyright (c) 2021 Rosun GV
Package: hashtagger
HASHTAGGERTo generate tags for images using TensorFlow and OpenCV.Using hashtagger, all of this can be done in just a few lines of code.InstallationYou can install hashtagger using pip:pip install hashtaggerUsageHere’s an example of how to use hashtagger to generate tags for images:from hashtagger import hashtagger

# Create an instance of YourLibrary
your_library = hashtagger()

# Specify the path to the image you want to process
image_path = ""  # Replace with the path to your image

try:
    # Use the recognize_objects method to recognize objects in the image
    decoded_predictions = your_library.recognize_objects(image_path)

    # Use the generate_tags method to generate tags for the recognized objects
    tags = your_library.generate_tags(decoded_predictions)

    print("Recognized objects and tags:")
    for tag in tags:
        print(tag)

except Exception as e:
    print(f"An error occurred: {e}")LicenseThis project is licensed under the MIT License - see the LICENSE.txt file for details.Changelog0.1.1 (2023-10-09)Added Initial release of the hashtagger library.
Package: hashtags
Installationpip install hashtagsHashtag PackageThis is a hashtag package. You can use
to make your social account grow faster
by using this hashtag package.
It can provide you best hashtags,and also provide hashtags by locationUsageExamplesbest_hashtagstop_hashtagshashtag_by_locationimporthashtagsa=hashtags.best_hashtags('category')#                           ('code')b=hashtags.top_hashtags()c=hashtags.hashtag_by_location('country','category')#                                   ('us','food')All countries are availableuse only short names egin,us
Package: hash-tg
hash-tghash-tg is a Telegram bot that allows you to perform various operations agains obtained hashes.InstallationInstall package from PyPI:pipinstallhash-tgContributingIf you'd like to contribute to the project, please follow these steps:Fork the repository.Create a new branch for your changes:git checkout -b my-new-feature.Make your changes and commit them:git commit -am 'Add some feature'.Push to the branch:git push origin my-new-feature.Submit a pull request.Licensehash-tg is licensed under theMIT License. Feel free to use it for personal or commercial use.
Package: hash-things
#️⃣ hash_things-------*Hash all sorts of things in Python*Python has some basic tools for hashing stuff, but not all types are easily supported.This package contains utility functions that make it easy to hash _things_. Including: `Dicts`... image:: https://img.shields.io/pypi/v/hash_things.svg:target: https://pypi.org/project/hash_things/.. image:: https://img.shields.io/pypi/pyversions/hash_things.svg:target: https://pypi.org/project/hash_things/.. image:: https://img.shields.io/pypi/l/hash_things.svg:target: https://pypi.org/project/hash_things/.. image:: https://img.shields.io/pypi/status/hash_things.svg:target: https://pypi.org/project/hash_things/.. image:: https://circleci.com/gh/phalt/hash_things/tree/master.svg?style=svg:target: https://circleci.com/gh/phalt/hash_things/tree/masterInstalling the project is easy:.. code-block:: bashpip install hash_thingsFull blown example:.. code-block:: pythonfrom hash_things import hash_dictresult = hash_dict({'hello': 'world'})result>>> 164302408563385743📖 What can I hash?--------- Dictionaries with any value - Lists, Tuples, Sets, and even nested Dicts!✨ Future goals---------------- Objects of any type- *You favourite type here*🏗 Status----------hash_things is currently stable.🎥 Credits-----------This package was created with Cookiecutter_.We use `Python Requests`_ for talking HTTP... _Cookiecutter: https://github.com/audreyr/cookiecutter
Package: hashtools
hashtoolsHash tools collection, like md5, sha1, sha256 and many other hash tools.Installpip install hashtoolsCommandsWindows Python 2.7dsadsa_shadsaencryptiondsawithshaecdsa_with_sha1md4md5ripemd160shasha1sha224sha256sha384sha512whirlpoolLinux Python 2.7dsadsashadsaencryptiondsawithshaecdsawithsha1md4md5ripemd160shasha1sha224sha256sha384sha512whirlpoolLinux Python 3.6blake2bblake2sdsadsa_shadsaencryptiondsawithshaecdsa_with_sha1md4md5ripemd160shasha1sha224sha256sha384sha3_224sha3_256sha3_384sha3_512sha512shake_128shake_256whirlpoolAbout SHAKE algorithmsYou must give output length, default to 1024.UsageC:\Code\hashtools>md5 --help
Usage: MD5 [OPTIONS] [FILENAMES]...

Options:
-v, --verbose         Show filename or not.
-c, --concat          Concat all files to one file, and get only one hash
                        code.
-l, --length INTEGER  Output length for SHAKE object.
--help                Show this message and exit.

C:\Code\hashtools>sha1 --help
Usage: sha1 [OPTIONS] [FILENAMES]...

Options:
-v, --verbose         Show filename or not.
-c, --concat          Concat all files to one file, and get only one hash
                        code.
-l, --length INTEGER  Output length for SHAKE object.
--help                Show this message and exit.UsageC:\Data\hashtools\test>echo msg | md5
b47d94f422d2032dac746f8b6cb263a5

C:\Data\hashtools\test>echo msg | md5 -v
b47d94f422d2032dac746f8b6cb263a5 *-

C:\Data\hashtools\test>echo msg | sha256
c7b6fcf29e713727bdea4c283d816c42cce9a0b4cb08484223f3b9b45256ec59

C:\Data\hashtools\test>echo msg > a.txt

C:\Data\hashtools\test>type a.txt
msg

C:\Data\hashtools\test>md5 a.txt
b47d94f422d2032dac746f8b6cb263a5

C:\Data\hashtools\test>md5 a.txt -v
b47d94f422d2032dac746f8b6cb263a5 *a.txtBug reportPlease report any issues athttps://github.com/zencore-cn/zencore-issues.Releasesv0.3.0 2020-06-24Add base64 output format.v0.2.0 2019-11-05Fix entry_points install way.Add star before filename in verbose mode.Fix SHAKE algorithms, set default output length to 1024, and you can set it with option --length.v0.1.2 2019-04-07First release of hashtools.
Package: hashtree
hashtreeGenerate BSD-style hash digest checksums for a list of filesFree software: MIT licenseDocumentation:https://hashtree.readthedocs.io.Usage: hashtree [OPTIONS] [INFILE] [OUTFILE]

  generate hash digest for list of files

Options:
  --version                       Show the version and exit.
  -d, --debug                     debug mode
  --shell-completion TEXT         configure shell completion
  -h, --hash [sha512|md5|sha256|blake2b|sha3_256|sha224|blake2s|sha1|sha384|sha3_224|sha3_512|sha3_384]
                                  select checksum hash
  -p, --progress / -P, --no-progress
                                  show/hide progress bar
  -a, --ascii                     ASCII progress bar
  -f, --find / -F, --no-find      generate file list with 'find'
  -s, --sort-files / -S, --no-sort-files
                                  sort input/generated file list
  -o, --sort-output / -O, --no-sort-output
                                  sort output with 'sort'
  -b, --base-dir DIRECTORY        base directory for file list
  --help                          Show this message and exit.Usage: hashtree [OPTIONS] [INFILE] [OUTFILE]

  generate hash digest for list of files

Options:
  --version                       Show the version and exit.
  -d, --debug                     debug mode
  --shell-completion TEXT         configure shell completion
  -h, --hash [sha3_256|blake2b|blake2s|sha384|md5|sha3_512|sha224|sha256|sha3_384|sha1|sha3_224|sha512]
                                  select checksum hash  [default: sha256]
  -p, --progress / -P, --no-progress
                                  show/hide progress bar  [default: p]
  -a, --ascii                     ASCII progress bar
  -f, --find / -F, --no-find      generate file list with 'find'  [default: f]
  -s, --sort-files / -S, --no-sort-files
                                  sort input/generated file list  [default: s]
  -o, --sort-output / -O, --no-sort-output
                                  sort output with 'sort'  [default: O]
  -k, --sort-key TEXT             sort key (sort -k KEY)  [default: 1.1]
  -b, --base-dir DIRECTORY        base directory for file list  [default: .]
  --help                          Show this message and exit.
Package: hashver
hashverIs a python module to derive a unique numeric value from a version string and vice versa, adhering to following constraints:Resultant number must be unique for all possible values of a, b, c and dEach of a, b, c and d needs to be below certain maximum unsigned int guided
by max possible bits allotted to each version componentWe should be able to derive unique a.b.c.d back from given numberIf a.b.c.d => x and p.q.r.s => y then, a.b.c.d < p.q.r.s => x < yUsageAfter performingpython -m pip install hashver, execute python code as mentioned below.>>>fromhashverimportHashVer>>>hob=HashVer()>>>hob.get_num('1.0.6')4294967302>>>hob.get_version_str(8590000133)2.1.5>>># if your version is of format a.b.c.d, each of which should be at most 2^16>>>hob=HashVer(bits_per_component='16.16.16.16')>>>hob.get_num('9.0.100.10')2533274796949514>>>hob.get_version_str(2533274796949514)9.0.100.10Or if you have curl,curl-skLhttps://raw.githubusercontent.com/ashutoshkumr/python-hashver/master/hashver/hashver.py|python-1.0.685900001331.0.6:42949673028590000133:2.1.5Modification and TestingIf any modification is done to hashver source, use following to validate changes,# ensure various combinations of version string or number can be derived from each otherpython-B${hashver-root}/hashver.py9.0.100.102533274796949514--bpc16.16.16.169.0.100.10:25332747969495142533274796949514:9.0.100.10# or simply add them to the existing test suite in hashver/test_hashver.py and run pytestcd${hashver-root}&&pytest