Saravanan666/pypi-org huggingface dataset:
Package: algoworld-contracts
📃 AboutThe following repository hosts the source codes for:AlgoWorld Swapper's algorand smart signatures.AlgoWorldExplorer's stateful smart contracts for card auctions and card trading. Modified version ofOpenNFT's smart contracts.⚠️ NOTE: These contracts were created in collaboration with Solution Architect from Algorand (credits @cusma) and audited byTENSET security. Code is provided under MIT license.Prerequisitespoetrypre-commitAlgorand SandboxDocker🚀 OverviewAlgoWorld currently offers several smart signatures used for swapping on AlgoWorld Swapper.If you are looking to install algoworld contracts into your project run the following command:pipinstallalgoworld-contractsExample usagefromalgoworld_contractsimportcontracts# Replace inputParams with real valuesasa_to_asa_swap=contracts.get_swapper_teal(inputParams.creator_address,inputParams.offered_asa_id,inputParams.offered_asa_amount,inputParams.requested_asa_id,inputParams.requested_asa_amount,inputParams.incentive_wallet,inputParams.incentive_fee,)# asa_to_asa_swap is a string of TEAL coderesponse=algod.compile(asa_to_asa_swap)...SwapperThere are two main types of smart signatures available:ASA to ASA swap | 🎴↔️🎴: Smart signature that allows performing a swap of any single ASA of specified amount to any other single ASA of specified amount.Swap Configuration Proxy 📝: Smart signature that powers theAlgoWorld Swapperby allowing users to issue certain transactions that contain links to swap configuration files stored as.jsonfiles onipfs. Proxy is then used to obtain thoseipfsfiles by grabbing the latest pay transaction using Algorand Indexer queries.ASAs to ALGO swap | 🎴🎴🎴↔️💰: Smart signature that allows performing a swap of multiple ASAs of specified amount to ALGO of specified amount.⚙️ InstallationThis section assumes that poetry and pre-commit are installed and executed from the root folder of this repository.Clone the repogitclonehttps://github.com/AlgoWorldNFT/algoworld-contractsInstall python requirementspoetryinstall# install all dependenciespoetryshell# activate virtual env(OPTIONAL) 3. Configurepre-commithookspre-commitinstallIf you are not going to setuppre-commitlocally, there is a Github Actions plugin that will autoformat your branch if you are opening a PR with commits that contain un-formatted code.🧪 TestingTesting assumes that docker-compose is installed and available. Project is relying onpytest-docker-composeplugin that automatically boots up temporary algorand sandbox and destroys the containers after the tests are finished.(.venv)pytestYou can also include[pytest]into your commit message to trigger the test in CI pipeline onpushaction (on pr it is triggered automatically).🚧 Contribution guidelineSeeCONTRIBUTING.md⭐️ StargazersSpecial thanks to everyone who forked or starred the repository ❤️
Package: algpred2
AlgPred2.0IntroductionAlgPred2.0 is developed for predicting, mapping and scanning allergen peptides. More information on AlgPred2.0 is available from its web serverhttp://webs.iiitd.edu.in/raghava/. This page provides information about standalone version of AlgPred2.0.Minimum USAGE: Minimum ussage is "algpred2 -i peptide.fa" where peptide.fa is an input fasta file. This will predict Allergenic peptides in fasta format. It will use other parameters by default. It will save output in "outfile.csv" in CSV (comma seperated variables).Full Usage: Following is complete list of all options, you may get these options by "algpred2 -h"algpred2 [-h] -i INPUT [-o OUTPUT] [-t THRESHOLD] [-m {1,2}] [-d {1,2}]Please provide following argumentsoptional arguments:-h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Input: protein or peptide sequence in FASTA format or
                        single sequence per line in single letter code
  -o OUTPUT, --output OUTPUT
                        Output: File for saving results by default outfile.csv
  -t THRESHOLD, --threshold THRESHOLD
                        Threshold: Value between 0 to 1 by default 0.3
  -m {1,2}, -- model Model
                        Model: 1: AAC based RF, 2: Hybrid, by default 1
  -d {1,2}, --display {1,2}
                        Display: 1:Allergen peptide, 2: All peptides, by
                        default 1Input File: It allows users to provide input in two formats; i) FASTA format (standard) (e.g. peptide.fa) and ii) Simple Format. In case of simple format, file should have one one peptide sequence in a single line in single letter code (eg. peptide.seq).Output File: Program will save result in CSV format, in case user do not provide output file name, it will be stored in outfile.csv.Threshold: User should provide threshold between 0 and 1, please note score is proportional to allergenic potential of peptide.Models: In this program, two models have beeen incorporated;  i) Model1 for predicting given input peptide/protein sequence as Allergenic and Non-allergenic peptide/proteins using Random Forest based on amino-acid composition of the peptide/proteins;ii) Model2 for predicting given input peptide/protein sequence as Allergenic and Non-allergenic peptide/proteins using Hybrid approach, which is the ensemble of Random Forest+ BLAST+ MERCI. It combines the scores generated from machine learning (RF), MERCI, and BLAST as Hybrid Score, and the prediction is based on Hybrid Score.
Package: algs4
OverviewThis repository contains the Python source code for the algorithms in the textbookAlgorithms, 4th Editionby Robert Sedgewick and Kevin Wayne.The official Java source code ishere.GoalsMake a Python implementation of the library so that a Python programmer can follow this book easily or prefer to demonstrate the algorithms using Python.Try to keep the interface and variable name consistent with the original book while writing idiomatic Python code.Installpipinstallalgs4fromalgs4.stackimportStackIndex1 FUNDAMENTALSBagQueueStackUnionFind2 SORTINGSelectionInsertionShellMergeQuickQuick3WayMaxPQTopMIndexMinPQMultiwayHeap3 SEARCHINGFrequencyCounterSequentialSearchSTBinarySearchSTBSTRedBlackBSTSeparateChainingHashSTLinearProbingHashST4 GRAPHSGraphGraphDepthFirstSearchDepthFirstPathsBreadthFirstPathsCCCycleSymbolGraphDegreesOfSeparationDigraphDigraphDirectedDFSDirectedCycleDepthFirstOrderTopologicalKosarajuSCCMSTEdgeWeightedGraphLazyPrimMSTPrimMSTKruskalMSTShortest PathsEdgeWeightedDigraphDijkstraSPAcyclicSPBellmanFordSP5 STRINGLSDMSDQuick3stringTrieSTTSTKMPNFAHuffmanLZWLicenseThis code is released under MIT.Contribute to this repositoryIssue reports and code fixes are welcome. please follow the same style as the code in the repository and add test for your
code.contributing guide
Package: algtestprocess
Algtest pyProcessA tool for simple visualizations of gathered TPM and JavaCard smart card data collected by tpm2-algtest and JCAlgtest tools respectively.Getting startedDependenciesPython 3 (see.requirements.txt)InstallingSetup virtual environmentpython -m venv venv
source venv/bin/activateInstall package usingpipor runsetup.pypip install -e .NOTEIf you are an user of fish shell, right command issource venv/bin/activate.fishUsagepyprocess commandAn entry point to the command line interface, which is used mostly to preprocess the datasets which are then analysed in jupyter notebooks.Commands:
  tpm       A collection of commands for processing of results from tpm2-algtest
  javacard  NOT YET IMPLEMENTEDtpm commandsmetadata-updateCommand which is used to find all measurements on a given path, and group them by exact firmware. The output ismetadata.jsonwhich contains these aggregated paths. Latter part of this file contains directory hashes, to prevent duplicate inclusion of the same measurement. An example ofmetadata.jsonfile is shown below.If you have already created ametadata.jsonfile and just want to add more measurements, you may use-ioption which takes path to oldmetadata.jsonfile.pyprocess tpm metadata-update ./results/tpmalgtest_results_2022
pyprocess tpm metadata-update -i metadata.json ./results/tpmalgtest_results_2023An example ofmetadata.jsonfile.{
  "entries": {
    "STM 73.4.17568.4452": {
      "TPM name": "STM 73.4.17568.4452",
      "vendor": "STM",
      "title": "",
      "measurement paths": [
        "/home/tjaros/storage/research/tpm/tpmalgtest_results/out4/out",
        "/home/tjaros/storage/research/tpm/tpmalgtest_results/algtest_result_8d400ec7-122c-498f-b141-733d359ad78f_STM",
        "/home/tjaros/storage/research/tpm/tpmalgtest_results/algtest_result_9fdfdf94-3a4a-4cd3-9a92-86642f9f4f6c"
      ]
    },
    "AMD AMD 3.37.0.5": {
      "TPM name": "AMD AMD 3.37.0.5",
      "vendor": "AMD",
      "title": "",
      "measurement paths": [
        "/home/tjaros/storage/research/tpm/tpmalgtest_results/algtest_result_70de7ce0-de7c-42bc-9f86-708d8304ad48"
      ]
    },
  },
   "hashes": [
    "862ad83383339467dbd687f3ebb2d075",
    "7f78e96bd4fc47299cdbaa7cf1a1c1e3",
    "3d6f2c211f00245d2a7b2c6458b3626a",
    "2b3242fc08c73b608a227eea563f1531",
   ],
}LicenseThis project is licensed underMIT License- see the LICENSE file for details
Package: alguns
AlgunsAlguns is a symmetric encryption method that contains 2 keys, without which decryption of the message is impossible.Alguns also uses 128-bit AES in CBC mode and PKCS7 padding.Letters and symbols are encrypted using the replacement method generate_replacement. A replacement character for a letter consists of [randomSymbol, randomNumber(0,99), randomSymbol, randomNumber(0,99)].
A Alguns key as returned by the generate_key actually contains two 16-byte keys:
A signing key used to sign the HMAC.A private key used by the encryption.
These two values are concatenated to form a 32 byte value. This 32 byte key is then encoded using Base64 encoding. This encodes the binary quantity as string of ASCII characters. The variant of Base64 used is URL and filename safe, meaning that it doesn't contain any characters that aren't permitted in a URL or a valid filename in any major operating system.Supported Languages:RussianEnglishInstallationThe installation method for this module is shown below.pip3 install algunsHow generate keys?key=Alguns.generate_key()replacement=Alguns.generate_replacement()# Put this somewhere safe!How to encrypt a message?mykey=# My key that I created earlier.myreplacement=# My replacement that I created earlier.al=Alguns(key=mykey,replacement=myreplacement)msgcrypt=al.encrypt('Hellow it is my message! Привет, это мое сообщение...')print(msgcrypt)# gAAAAABewxb_nE1mbHgN7ma79_XAbh68hLblIFdX3czIEmUDCSFWxMXTTEdIU5...How to decrypt a message?al=Alguns(key=mykey,replacement=myreplacement)msgdecrypt=al.decrypt('gAAAAABewxb_nE1mbHgN7ma79_XAbh68hLblIFdX3czIEmUDCSFWxMXTTEdIU5...')print(msgdecrypt)# Hellow it's my message! Привет, это мое сообщение...
Package: algviz
Algviz中文介绍文档What is algviz?Algvizis an algorithm animation engine for your Python code inJupyter, which supports multiple data structures such asvector,table,linked_list,treeandgraph.VectorTableTreeGraphYou can get live algorithm animation after bringing some algviz interfaces to your algorithm.
For example, this code below shows the bubble sort algorithm:Click to show the code exampleimportalgvizdefbubble_sort(data):viz=algviz.Visualizer(0.5)vector=viz.createVector(data,cell_size=(40,160),histogram=True)foriinrange(len(vector)):forjinrange(len(vector)-i-1):ifvector[j]>vector[j+1]:vector.mark(algviz.cRed,j)vector.mark(algviz.cGreen,j+1)viz.display()vector.swap(j,j+1)else:vector.mark(algviz.cRed,j+1)vector.mark(algviz.cGreen,j)viz.display()vector.mark(algviz.cGray,len(vector)-i-1,hold=True)vector.removeMark(algviz.cGray)viz.display()bubble_sort([5,4,-2,1,-1,3])The rendered animation looks like this:If you are interested in this project, please give me a star⭐, thanks!ExamplesReady to see the magic? Click this button to try more algorithms on Gitpod!Need to login with your github account.InstallationPlease follow thisinstallation guideto setup algviz.TutorialThistutorialgives you a quick start on using algviz.All the API references can be found atalgviz API reference.LicenseAlgviz uses GNU general publicLICENSE. You can use it freely for learning and communication. For the commercial usage, please contact the author.ContributionAny form of contribution is welcomed! Please feel free to report abugor create apull request.If you want to share your algorithms using algviz, you can create aPRfrom this repo: 👉algviz-launch.DiscussionQQ group:334605370Telegram:https://t.me/+mvF8Sivxr3thZWY1
Package: alhambra-mixes
For DNA 28, ourposter as a Jupyter notebook is available here.Our documentationis in the process of being written (latest git documentation is here); we also havea tutorial notebook(WIP).This package, alhambra_mixes, is a separate package containing thealhambra.mixeslibrary fromalhambramodified to be more compatible with Python < 3.10.  Continued development on
mixes will take place here, and alhambra will be made to depend on this.The
name may change soon to something more unique.The mixes package is a Python library to systematically, efficiently, and safely
design recipes for mixes of many components, intended primarily for DNA
computation experiments.  The library recursively tracks individual components
through layers of intermediate mixes, performs checks to ensure those layers of
mixes are possible, and allows verification that final samples will contain the
correct components at the correct concentrations. Incorporating reference
information from files such as DNA synthesis order details, the library
generates recipes for straightforward pipetting, even in mixes with many
components at different concentrations spread across several plates.Changelogv0.5.0An interim version release while larger changes are being made, so that users can make use of several important new features, and the pypi-available version fits well with the latest documentation.Adds anExperimentclass that can hold mixes and components, and keep track of volumes, etc.Adds volume/consumption tracking.Adds master/split mix functions.Fixes numerous minor bugs.
Package: alianator
alianatoralianator is a Discord permission name resolver forPycord.
It takes Discord's API permission flags (e.g.manage_guild) and resolves them to their user-facing aliases (
e.g.Manage Server).Installation$pipinstallalianatorUsagealianator can resolve aliases fromdiscord.Permissionsobjects, integers, strings, tuples, lists of strings, and lists
of tuples.importalianatoralianator.resolve(arg,mode=mode)The optionalmodeflag can be used to specify which permissions should be resolved. IfmodeisTrue, only granted
permissions will be resolved; ifmodeisFalse, only denied permissions will be resolved; ifmodeisNone, all
permissions will be resolved. Ifmodeis not explicitly specified, it will default toTrue.importalianatorimportdiscord# Resolving from a discord.Permissions objectperms=discord.Permissions.general()aliases=alianator.resolve(perms)print(aliases)# ['Manage Channels', 'Manage Server', 'View Audit Log', 'Read Messages', 'View Server Insights', 'Manage Roles', 'Manage Webhooks', 'Manage Emojis and Stickers']# Resolving from an integerperms=3072aliases=alianator.resolve(perms)print(aliases)# ['View Channel', 'Send Messages and Create Posts']# Resolving from a stringperms="send_tts_messages"aliases=alianator.resolve(perms)print(aliases)# ['Send Text-To-Speech Messages']# Resolving from a tupleperms=("moderate_members",True)aliases=alianator.resolve(perms)print(aliases)# ['Timeout Members']# Resolving from a list of stringsperms=["manage_guild","manage_emojis"]aliases=alianator.resolve(perms)print(aliases)# ['Manage Server', 'Manage Emojis and Stickers']# Resolving from a list of tuplesperms=[("use_slash_commands",True),("use_voice_activation",True)]aliases=alianator.resolve(perms)print(aliases)# ['Use Application Commands', 'Use Voice Activity']That's about all there is to it. alianator does one thing and does it well.Licensealianator is released under theMIT License.
Package: aliasdict
This module helps users to make multiple keys dict with same value.
In addition to that, this dict automatically gzip-compress values.
So it’s very efficient.I hope this module helps you python programing in your lap-top PC.QuickstartInstall cachelite:pip install aliasdictThen you can use it.importaliasdictfromAliasDictadct=AliasDict()#if you don't need value compression, AliasDict(compress=False)#put a key-valueadct["YOUR_KEY"]="YOUR_VALUE"#set a alias to keyadct.set_alias("YOUR_KEY","YOUR_ALIAS")#get value by aliasadct["YOUR_ALIAS"]#save1withopen("PATH_TO_FILE","wb")asf:adct.dump(f)#save2withopen("PATH_TO_FILE","wb")asf:f.write(adct.dumps())#load1withopen("PATH_TO_FILE","rb")asf:adct=AliasDict.load(f)#load2withopen("PATH_TO_FILE","rb")asf:adct=AliasDict.loads(f.read())
Package: aliasfile
Define your per-directory command aliases in Yaml, to get quick
shortcuts (and avoid having to remember long commands).WARNING:This project is still experimental, and things may change
suddenly. Suggestions are welcome.ConfigurationConfiguration is held in a file, usually named./.aliases, as a
dictionary serialized in YAML format.The main section iscommands, a dict mapping alias names to their
specification.Command specificationcommand: command to be run, as a stringwill be tokenized viashlex.splitstring-format-style placeholders will be replaced:positional arguments ({},{1}) -> variadic arguments to the command..or explicit:{args[1]}environment:{env[USER]}vars (see below):{vars[USER]}extra arguments will be appended to the commandenv: environment for the commandnot considered in string formattingwill go through the same formatting as commandsvars: to be replaced in env/command formattingNoteswe want some way to prevent automatic appending of varargswe might want to use jinja for formatting, so we can have conditionals / defaultswe might want inheritance, rather than having “nested” aliasingExamplescommands:test:command:xvfb-run py.test --reuse-db -vvv ./tests/env:DJANGO_SETTINGS_MODULE:fooproject.settings.testingPYTHONPATH:"{env[HOME]}/Projects/fooproject"commands:manage:command:python manage.pyenv:DJANGO_SETTINGS_MODULE:fooproject.settings.testingPYTHONPATH:"{env[HOME]}/Projects/fooproject"LOG_LEVEL:DEBUGrunserver:command:aliasfile manage runservermigrate:command:aliasfile manage migrateshell:command:aliasfile manage shell
Package: alias-free-torch
Alias-Free-TorchSimpletorchmodule implementation ofAlias-Free GAN.This repository includingAlias-Free GAN style lowpass sinc filter @filter.pyAlias-Free GAN style up/downsample @resample.pyAlias-Free activation @act.pyand test codes @./testNote: Since this repository is unofficial, filter and upsample could be different withofficial implementation.Still working! If you notice some error or typo, please open new issue!v0.0.8 is TESTEDUPDATE: You can download alias-free-torch frompippython-mpipinstallalias-free-torchRequirementsDue totorch.kaiser_windowandtorch.i0are implemeted after1.7.0, our repository needtorch>=1.7.0.Pytorch>=1.7.0For custom torch users,pipwill not check torch version.TODO2d sinc filter2d resampledevide 1d and 2d modulespip packagingrewrite upsampleUpsample pad size issue(Upsample) support calculation for [B,C,T/(H,W)] (now only supports [B,T/(H,W)] or [B,1,T/(H,W)])set filter as register buffer(Downsample & Filter) support calculation for [B,C,T/(H,W)] (now only supports [B,T/(H,W)] or [B,1,T/(H,W)])provide loadable ckpt for lower version of torchdocumentationTest results 1dFilter sineFilter noiseupsampledownsampleTest results 2dFilter L1 norm sineFilter noiseupsampledownsampleReferencesAlias-Free GANadefossez/juliusA. V. Oppenheim and R. W. Schafer.Discrete-Time Signal Processing. Pearson, International Edition, 3rd edition, 2010AcknowledgementThis work is done atMINDsLab Inc.Thanks to teammates at MINDsLab Inc.Hyoungkyu SongKang-wook KimDongho ChoiSang Hoon Woo
Package: alias-gen
ALIAS-GEN 𑗊Shell aliases are shortcuts or abbreviations for commands that are used in a Unix/Linux shell. They can save you time if you have very long or complex commands that you frequently use. ALIAS-GEN is a script that will create bash/zsh/fish shell aliases automatically to simplify your command-line tasks.This script will create bash/zsh/fish shell aliases automatically. You can generate a new alias file by following the prompts, or use the--stdoutoption to print results directly in your terminal.Two types of aliases are suggested, the default algorithm matches all characters incrementally for each command, while the--use_min_aliasalgorithm aims to minimize the total length of characters per command.
Additionally,--use_min_aliasdoes not necessarily match all characters in the command.The freq (frequency) column shows how often each command was used. For now, this script only generates aliases for the first word in a command.
NOTE: Two character commands or less are not processed.By default, fish shell generates abbr (abbreviations) rather than aliases.RequirementsPython 3.6 or higher.No dependences required for installation.Install from pypipipinstallalias-genhttps://pypi.org/project/alias-gen/CLI UsageFull Help Menu:aliaser -hExample usage to generate the top 40 aliases:aliaser -n 40With stdout and min_alias:aliaser --stdout --use_min_aliasThe-sargument specifies the shell type. In this example,fishshell is used.aliaser -s fishThe-fargument allows you to specify a custom history file path.aliaser -s zsh -f ~/.custom_zsh_historyHow does it work?Thealiascolumn is generated by first sorting the most common commands found
in the history file, then aliases are generated for commands more than two
characters. These aliases just try to match character per character the given
command and will continue with more characters if there is a previous common
alias.Themin_aliascolumn tries to minimize the total length of chars disregarding
the rule of matching the command character per character. It is generated using
the first char of the command always, followed by easy to reach keyboard characters
defined as QUERTY layout middle row, top row, then bottom row.MiscI recommend using this script along with other shell plugins that help you remember
your alias or abbreviation. One example for fish shell isfish-abbreviation-tips.Buy me a coffeeHope you found this project helpful, consider buying a coffee to show your support.
Package: aliasmatching
Alias matchingaliasmatchingis a python package that provides tools for identifying users that have different aliases.
Tools are designed to support GitHub users ids: username, login, and e-mail.Installationpip install aliasmatchingDocumentationhttps://alias-matching.readthedocs.io/en/latest/overview.htmlMethodsaliasmatching/mathcinghas implementation of currently available matching methods:bird_matching- alias matching based onMining Email Social Networks
Package: alias-windows
aliasManage command aliases in Windows.Installation>pipinstallalias-windowsBy default aliases are stored in%USERPROFILE%\Documents\Scripts\Aliases. You can set the directory to store aliases by changing the environment variable called%ALIASES_DIR%.Managing aliasesGet the list of available aliases:> alias
apktool, gsh, gst
> alias -v
apktool = %SOFTWARE%\apktool\apktool.bat %*
gsh = git show $*
gst = git status --short --branch %*Add an alias:> alias test=dir \b %*
Added testShow the alias:> alias g
gsh, gst
> alias test
dir \b %*Search for a text in alias commands:> alias -s apk
baksmali, smali
> alias -s apk -v
baksmali = %SOFTWARE%\apktool\apktool.bat d %*
smali = %SOFTWARE%\apktool\apktool.bat b %*Delete the alias:> alias -d test
Deleted testEnvironment variablesaliaschanges two variables:%ALIASES_DIR%Directory where aliases are stored.%PATH%Adds%ALIASES_DIR%to%PATH%.LicenseThis project is licensed under theMIT License.