Saravanan666/pypi-org huggingface dataset:
Package: espm
espm: The Electron Spectro-Microscopy Python Library.. image::https://readthedocs.org/projects/espm/badge/?version=latest:target:https://espm.readthedocs.io/en/latest/?badge=latest:alt: Documentation StatusThe espm package is designed for the simulation and analysis of scanning transmission electron microscopy (STEM) hyperspectral data analysis.
Currently it only supports energy dispersive X-ray spectroscopy (EDXS) data but we will try to extend it to electron energy loss spectroscopy (EELS) data in the future.
The main components of the package are:The simulation of STEM-EDXS datasets using :mod:espm.datasetswhich combines :mod:espm.weightsfor the simulation of spatial distributions and :mod:èspm.modelsfor the simulation of spectra.The hyperspectral unmixing of STEM-EDXS spectrum images using :mod:espm.estimators. This module contains algorithms to perform non-negative matrix factorization with diverse regularisation (e.g. Laplacian or L1) and contraints (e.g. simplex).The :mod:espm.modelsmodule can also be used to perform a physics-guided decomposition of STEM-EDXS datasets.InstallationYou can install this package from PyPi using::$ pip install espmIf you want to develop, please use the option::$ git clone https://github.com/adriente/espm.git
$ cd espm
$ pip install cython
$ pip install -e ".[dev]"Getting startedTry the api.ipynb notebook in thenotebooksfolder.DocumentationThe documentation is available athttps://espm.readthedocs.io/en/latest/You can get started with the following notebooks:https://espm.readthedocs.io/en/latest/introduction/notebooks/api.htmlhttps://espm.readthedocs.io/en/latest/introduction/notebooks/toy-problem.htmlCITINGIf you use this library, please cite the following paper::@article{teurtrie2023espm,
title={espm: A Python library for the simulation of STEM-EDXS datasets},
author={Teurtrie, Adrien and Perraudin, Nathana{\"e}l and Holvoet, Thomas and Chen, Hui and Alexander, Duncan TL and Obozinski, Guillaume and H{\'e}bert, C{\'e}cile},
journal={Ultramicroscopy},
pages={113719},
year={2023},
publisher={Elsevier}
}
Package: espmega
pyESPMegaThis library provides a mean of communicating with the ESPMega Programmable Logic Controller through MQTTCompatibilityThis library is compatible with:ESPMega R2.4 [2018] (Model e) with IoT FreedomOS v1.2+ESPMega R3.0 [2020] (All Model) with IoT Core LT OS V1.4ESPMega Plus R1.0 [2020] (All Model) with IoT Core LT+ OS V1.4ESPMega R4.0 [2023] (All Model) with IoT Core LT OS V2ESPMega PRO R2.0 [2020] (Model c) with IoT Core OS V1ESPMega PRO R3.3 [2023] (Model b,c) with IoT Core OS V2.2 (or above)ESPMega Client TypesThere are two type of ESPMega client, ESPMega and ESPMega_standaloneESPMegaESPMega class requires you to provide and maintain an MQTT connection
This class takes in a Paho-MQTT Client as an input argumentImport and Initializationfrom espmega.espmega_r3 import ESPMega
plc = ESPMega("/basetopic", MQTT_CLIENT)ESPMega_standaloneESPMega_standalone create and maintain the required mqtt connection for you.Import and Initializationfrom espmega.espmega_r3 import ESPMega_standalone as ESPMega
plc = ESPMega("/basetopic", "MQTT_SERVER", MQTT_PORT)ESPMega Client Functionsdigital_read(pin: int) -> bool: Reads the digital value from the specified pin.digital_write(pin: int, state: bool) -> None: Sets the digital state of a pin.analog_write(pin: int, state: bool, value: int): Writes an analog value to the specified pin.adc_read(pin: int) -> int: Reads the value from the ADC pin.dac_write(pin: int, state: bool, value: int): Writes the state and value to the DAC pin.enable_adc(pin: int): Enables the ADC (Analog-to-Digital Converter) for the specified pin.disable_adc(pin: int): Disable the ADC (Analog-to-Digital Converter) for the specified pin.set_ac_mode(mode: str): Sets the mode of the air conditioner.set_ac_temperature(temperature: int): Sets the temperature of the air conditioner.set_ac_fan_speed(fan_speed: str): Sets the fan speed of the air conditioner.get_ac_mode(): Returns the current AC mode.get_ac_temperature(): Returns the current temperature of the air conditioning system.get_ac_fan_speed(): Get the current fan speed of the air conditioner.read_room_temperature(): Reads and returns the room temperature.read_humidity(): Reads and returns the humidity value from the humidity buffer.send_infrared(code: dict): Sends an infrared code.request_state_update(): Update all cached states.handle_message(client: pahomqtt.Client, data, message: pahomqtt.MQTTMessage): Handles incoming MQTT messages.get_input_buffer(): Return all states of the input pins as a list.get_pwm_state(pin: int): Return the state of the specified PWM pin.get_pwm_value(pin: int): Return the value of the specified PWM pin.get_pwm_state_buffer(): Return all states of the PWM pins as a list.get_pwm_value_buffer(): Return all values of the PWM pins as a list.
Package: espmega-lightshow
ESPMega Light ShowThis is a program made for the ESPMega PLCs for easily programming light show and running light show scriptFeaturesUser Interface for configuring controllerLight Grid GeneratorEasy Clickable Light ProgrammingDynamic Physical Light ConfigurationCustom Script using PythonBPM CounterQuick Load PresetInstallationFor Windows, run the following command in a powershell windows with admin rightsSet-ExecutionPolicyBypass-ScopeProcess-Force;[System.Net.ServicePointManager]::SecurityProtocol=[System.Net.ServicePointManager]::SecurityProtocol-bor3072;iex((New-ObjectSystem.Net.WebClient).DownloadString('https://raw.githubusercontent.com/SiwatINC/espmega-lightshow/main/installer_win.ps1'))Ubuntu Linuxbash<(curl-shttps://raw.githubusercontent.com/SiwatINC/espmega-lightshow/main/installer_ubuntu.sh)RunningThe program can be run from the CLI using the command:python-mespmega_lightshowThe program can also be run from the desktop/startmenu shortcut after installation.ScriptingThis template script can be used to program custom lightshowfromespmega_lightshow.scriptingimportUserScriptclassCustomUserScript(UserScript):defdraw_frame(self,current_time:float):# This function is called every frame# You can use self.rows and self.columns to get the number of rows and columns# You can use self.set_tile_state(row, column, state) to set the state of a light at row, column# You can use self.get_tile_state(row, column) to get the state of a light at row, column# You can use current_time to get the current time elapsed in seconds# You can use self.frame_count to get the number of frames that have passedpassThe script can be run by going toFile→Run Script
Package: espn-api
ESPN APIThis package uses ESPN's Fantasy API to extract data from any public or private league forFantasy Football and Basketball (NHL, MLB, and WNBA are in development).Please feel free to make suggestions, bug reports, and pull request for features or fixes!This package was inspired and based off ofrbarton65/espnff.InstallingWith Git:git clone https://github.com/cwendt94/espn-api
cd espn-api
python3 setup.py installWith pip:pip install espn_apiUsageFor Getting Started and API details head over to the Wiki!# Football APIfromespn_api.footballimportLeague# Basketball APIfromespn_api.basketballimportLeague# Hockey APIfromespn_api.hockeyimportLeague# Baseball APIfromespn_api.baseballimportLeague# Initleague=League(league_id=222,year=2019)Run Testspython3 setup.py nosetestsDiscussions(new)If you have any questions about the package, ESPN API data, or want to talk about a feature please start adiscussion!Issue ReportingIf you find a bug follow the steps below for reporting.Open anew issuewith a brief description of the bug for the title. In the title also add which sport (Football or Basketball)Run the application in debug mode to view ESPN API request's and response's# ... import statement aboveleague=League(league_id=1245,year=2019,debug=True)The application will print all requests and the response from ESPN's API in the console. I would suggest piping the console output to a text file as it will be a lot of data.Find the last log before the crash and copy it in the issue descrption with the line number of the crash or possible bug.Submit the new issue!I will try to comment on the issue as soon as possible with my thoughts and possible fix!
Package: espncricket
ESPN-Statsguru-ScraperIntroductionAn easy-to-use python scraper to pull all-time cricket statistics from ESPN Cricinfo.PrerequisitesPython requirementsYou need to install Python with version 3.4 or more. You can find the latest version of Python athttps://www.python.org/downloads/Install the library as follows.pip install espncricketHow to run the codeimport espncricket.ESPN as ESPN

df = ESPN().get_score()
print(df.head())By default it returns Test batting statistics for men only.But, you can also tweak following parameters to get custom results of your own choice.match_type='ODI_Women'data_type='bowling'view_type="series"number_of_pages=10ESPN_object = ESPN(match_type='ODI_Women', data_type='bowling', view_type="series")
odi_batting_scores_for_women_per_series_with_10_pages_only = ESPN_object.get_score(number_of_pages)After successful execution, a pandas dataframe object is returned.License InformationPlease refer "LICENSE" file to know the license details.
Before reusing the code, please take a written permission from me.
You can contact me atsanketpatole1994@outlook.com
Package: espnet-tts-frontend
ESPnet TTS FrontendA tools collection of text frontend forESPnettts recipes.Installpipinstallespnet_tts_frontendInstall with pyopenjtalkRequires cmake and cythongitclonehttps://github.com/espnet/espnet_tts_frontendcdespnet_tts_frontend/
pythonsetup.pypyopenjtalk# OR# pip install --global-option=pyopenjtalk -e espnet_tts_frontendFIXME(kamo):  Support direct installation from git repo.UsageEnglish:tacotron_cleanerDerived fromhttps://github.com/keithito/tacotron>>>importtacotron_cleaner.cleaners>>>tacotron_cleaner.cleaners.custom_english_cleaners("(Hello-World);   &  jr. & dr.")'HELLO WORLD, AND JUNIOR AND DOCTOR'g2p_enhttps://github.com/Kyubyong/g2p>>>fromg2p_enimportG2p# Automatically run downloading for the first time[nltk_data]Downloadingpackageaveraged_perceptron_taggerto...>>>g2p=G2p()>>>g2p("hello world")['HH','AH0','L','OW1',' ','W','ER1','L','D']Japanesejaconvhttps://github.com/ikegami-yukino/jaconv/>>>jaconv.normalize("”あらゆる”　現実を　〜　’すべて’ 自分の　ほうへ　ねじ曲げたのだ。")'"あらゆる" 現実を ー\'すべて\'自分の ほうへ ねじ曲げたのだ。'pyopenjtalkhttps://github.com/r9y9/pyopenjtalk# Automatically run downloading for the first time>>>pyopenjtalk.g2p("あらゆる 現実を すべて 自分の ほうへ ねじ曲げたのだ。",kana=True)'アラユル\u3000ゲンジツヲ\u3000スベテ\u3000ジブンノ\u3000ホーエ\u3000ネジマゲタノダ。'>>>pyopenjtalk.g2p("あらゆる 現実を すべて 自分の ほうへ ねじ曲げたのだ。",kana=False)'a r a y u r u pau g e N j i ts u o pau s u b e t e pau j i b u N n o pau h o o e pau n e j i m a g e t a n o d a'Vietnamesevietnamese_cleaner>>>importvietnamese_cleaner.vietnamese_cleaner
Package: esporifai
esporifaiA simple CLI to get data from the Spotify APIInstallationInstall this tool usingpip:pip install esporifaiUsageFor help, run:esporifai --helpYou can also use:python -m esporifai --helpRecently played tracksTo retrieve recently played tracks, run:esporifai get-recently-playedFor help,esporifai get-recently-played --helpDevelopmentTo contribute to this tool, first checkout the code. Then create a new virtual environment:cd esporifai
python -m venv venv
source venv/bin/activateNow install the dependencies and test dependencies:pip install -e '.[test]'To run the tests:pytest
Package: espresso-config
Espresso ConfigA struct config parser that you can set up in the time it
takes to make an espresso. To install, runpipinstallespresso-configPython 3.8 or newer is required.Why Espresso Config?There are a million of parsers that can turn a YAML configuration / CLI flags into a configuration file,e.g.,Hydra,ML Collections, so why another one? Espresso Config was designed to meet the following requirements:Support structured configs (i.e., define configurations with classes)Allow nested classes in configurationFunctionsMotivating ExampleImagine you want to run the following experiment:backbone:t5-largemodel:metrics:rouge:_target_:torchmetrics.functional.text.rouge.rouge_scoretokenizer:_target_:transformers.AutoTokenizer.from_pretrainedpretrained_model_name_or_path:t5-largetransformer:_target_:transformers.AutoModelForSeq2SeqLM.from_pretrainedmax_sequence_length:64pretrained_model_name_or_path:t5-largeSure, you could parse that yaml file and get adict.
But (a) working with dictionaries is tedious (b) there's no
typing, and (c) you don't want to have to declare all blocks
each time; it would be good if you could save some commonly used
configurations, such as the parameters for one oftransformerortokenizerkeys.Espresso Config allows you to solve all off those problems
by specifying a struct class as follows:fromespresso_configimport(ConfigNode,ConfigRegistry,ConfigParam,ConfigFlexNode)@ConfigRegistry.addclassseq2seq(ConfigNode):_target_:ConfigParam(str)='transformers.AutoModelForSeq2SeqLM.from_pretrained'@ConfigRegistry.addclasstok(ConfigNode):_target_:ConfigParam(str)='transformers.AutoTokenizer.from_pretrained'@ConfigRegistry.addclassrouge(ConfigNode):_target_:ConfigParam(str)='torchmetrics.functional.text.rouge.rouge_score'classApplicationConfig(ConfigNode):backbone:ConfigParam(str)classmodel(ConfigNode):classtransformer(ConfigNode):_target_:ConfigParam(str)pretrained_model_name_or_path:ConfigParam(str)='${backbone}'max_sequence_length:ConfigParam(int)=64classtokenizer(ConfigNode):_target_:ConfigParam(str)pretrained_model_name_or_path:ConfigParam(str)='${backbone}'metrics:ConfigParam(ConfigFlexNode)={}Then, your YAML configuration can be as simple as:backbone:t5-largemodel:transformer@seq2seq:{}tokenizer@tok:{}metrics:rouge@rouge:{}Voila! To load the config, run:fromespresso_configimportconfig_from_fileconfig=config_from_file(ApplicationConfig,path_to_yaml)Placeholder VariableA placeholder variable is a config value that references another
section of the config, e.g. another value or section.
It uses syntax${path.to.key}.Registry ReferenceA registry reference is a reference to a node config that has been
added to the config registry. It uses syntax@placeholder_name.
Package: espressocup
Why? What?I’m making a very light-weight internal network service, and am using
the amazing flask, as it’s excellent for prototyping such things.However, I feel like it’s a little over-weight for the simplicity of the
task.  So, out of curiosity, I’m trying to make a flask-alike server
and WSGI microframework which has just enough for these types of projects.It’s not intended to replace flask, obviously.  There’s no point.But it is intended that for things like this which don’t need a templating
language, or any of that, it should be close enough to flask that I can
drop this in, and with minimal changes have it running very quickly.current state:very very very initial alpha.  For pure JSON based views, it’s kind of
working.  For templating, it’s using pythons string.format instead of
jinja2.Routes currently don’t use variables, but are just a plain lookup.static files seem to be (initially) working.mime detection of template types isn’t really working yet.All that said:It’s quite fast. (Ha, no surprise, with all those caveats…)broken stuff:the ‘request’ object is just the pure WSGI environ at the moment.MIME types for templates (and static files)routing <with><vars>
Package: espresso-ir
Espresso IRIntroductionEspresso IR provides the fuctionality to automate memory aquisitions of Windows based EC2 instances and stores them in an S3 bucket. Currently it uses DumpIt to facilitate the memory aquisition part but with some minor edits you could use your tool of choice.This was created as part of a research paper the author conducted for their MSc dissertaion.Feedback is wanted, collaboration is encouraged. Please do this via the GitHub repositiory.Getting Startedusepip install espresso-irto install the module or clone from this GitHub repositioryhttps://github.com/Terrizmo/espresso-irand from inside the repository directory runpip install .You must have an account with programatic access to your AWS environment. Once you have the access-key-id and secret-access-key. Once you have this information runaws configureand follow the prompt. AWS CLI will store these details in your home directory. These details will then be used each time your run an espresso_ir command. Further infomation can be found in theAWS documents.If this is the first time you are running espresso-ir you will need to run the--setupflag to create the necessary S3 buckets and to upload DumpIt. The full command itespresso_ir <case-id> --setup <local-path-to-DumpIt>RequirementsThis tool has been designed to useDumpItby comae. Other memory acquisition tools may be availible in the future.Finally System manager must be able to communicate with the system manager agent on the EC2 instances you wish to acquire the memory from. You can create the necessary role with the required policies with this tool,--setupflag. Note if you add this role after the the system manager agent has turned on you will need to reboot the agent or the instance to get this functionality.Rebooting the EC2 instance will lose artifacts in memory, proabably all of them!Acquiring MemoryOnce you have completing the instruction in theGetting Startedsection and you have met theRequirementsyou are ready to dump memory from Windows based EC2 instances which will be uplaoaded to your<case-id>-memory-evidenceS3 bucket.The case ID is a manditory positional argument for espresso-ir and must be the first argument it receives.It is recommended you turn on API logging in AWS before hand. If you do not have API logging turned on you can useespresso_ir <case-id> --api-loggingTo start a memory dump you will need the instance ID for each EC2 instance you want to acquire memory from. These currently can only be passed as arguments seperated by a space. for exampleespresso_ir <case-id> --dump-memory <instance-id> <instance-id> <instance-id>. Up to 50 IDs can be passed at once.LimitationsAt this time you can on dump the memory for 50 EC2 hosts in one CLI entry. This is due to a limitation in thesend commandAPI. This will be ovecome later using theTargetsparameter.This tool only supports DumpIt as the memory acquisition tool.TODONext stepsFeatures plannedKnown bugs (shortlist)
Package: espressopy
Espresso.pyEspresso.py is the new way to develop Discord bots using Python.Current Version: alpha-v0.0.2UsageThememberobject is user to get and modify data for guild members.BanUsage:espresso.member.ban("userid", "guildid", "reason", "delete_seconds")User ID: The ID of the user to ban.Guild ID: Guild of which to ban the member in.Reason: Reason for ban.Delete Seconds: How many seconds worth of messages to delete, up to 604800 (7 days).KickUsage:espresso.member.kick("userid", "guildid", "reason")User ID: The ID of the user to kick.Guild ID: Guild ID of which to kick the member in.Reason: Reason for kick.
Package: esprima
Esprima(esprima.org, BSD license) is a
high performance, standard-compliantECMAScriptparser officially written in ECMAScript (also popularly known asJavaScript) and ported to
Python. Esprima is created and maintained byAriya
Hidayat, with the help ofmany
contributors.Python port is a line-by-line manual translation and was created and is
maintained byGerman Mendez Bravo
(Kronuz).FeaturesFull support for ECMAScript 2017 (ECMA-262 8th
Edition)Sensiblesyntax tree
formatas
standardized byESTree projectExperimental support forJSX, a
syntax extension forReactOptional tracking of syntax node location (index-based and
line-column)Heavily tested(~1500unit
testswithfull code
coverage)InstallationpipinstallesprimaAPIEsprima can be used to performlexical
analysis(tokenization) orsyntactic
analysis(parsing) of a
JavaScript program.A simple example:>>>importesprima>>>program='const answer = 42'>>>esprima.tokenize(program)[{type:"Keyword",value:"const"},{type:"Identifier",value:"answer"},{type:"Punctuator",value:"="},{type:"Numeric",value:"42"}]>>>esprima.parseScript(program){body:[{kind:"const",declarations:[{init:{raw:"42",type:"Literal",value:42},type:"VariableDeclarator",id:{type:"Identifier",name:"answer"}}],type:"VariableDeclaration"}],type:"Program",sourceType:"script"}For more information, please read thecomplete
documentation.
Package: esprimajs
esprima-compileris a es6-compatible javascript minifier written by python.esprima-compilerusesesprima-pythonas javascript parser libraryFeaturesES6 supportMangling function and variable namesIdent outputObfuscate stringsInstallationpipinstallesprima-compilerExamplesExample javascript fileconstAconst=Math.PI,Bconst="Bconst";constCconst="Cconst";functionadd(a,b){functionfoo(){returna+b;}returnfoo();}constDconst="Dconst";functionmul(a,b){returna*b;}constEconst="Econst";letAlet="Alet";constFconst="Fconst",Gconst="Gconst";Rearrange and mangle variables:python-mesprima_compiler-r--mangle-variabletest.jsconstAconst=Math.PI,Bconst="Bconst",Cconst="Cconst";functionadd($a,$b){functionfoo(){return$a+$b;}returnfoo();}constDconst="Dconst";functionmul($a,$b){return$a*$b;}constEconst="Econst",Fconst="Fconst",Gconst="Gconst";letAlet="Alet";Rearrange variables and mangle variables (include top level) and function names (except top-level):python-mesprima_compiler-r--mangle-variable-top--mangle-functiontest.jsconst$a=Math.PI,$b="Bconst",$c="Cconst";functionadd($d,$e){function$f(){return$d+$e;}return$f();}const$d="Dconst";functionmul($e,$f){return$e*$f;}const$e="Econst",$f="Fconst",$g="Gconst";let$h="Alet";Rearrange variables and mangle variables and function names (include top level) without identing:python-mesprima_compiler-i0-r--mangle-variable-top--mangle-function-top--mangle-functiontest.jsconst$a=Math.PI,$b="Bconst",$c="Cconst";function$d($e,$f){function$g(){return$e+$f;}return$g();}const$e="Dconst";function$f($g,$h){return$g*$h;}const$g="Econst",$h="Fconst",$i="Gconst";let$j="Alet";APICompile javascript string:>>>fromesprima_compiler.compilerimportCompiler>>>c=Compiler(rearrange=True,mangle_variable=True,mangle_variable_top=True)>>>js="""
... const A=1;
... const B=2;
... let C=3;
...
... class TestClass extends Object{
...   constructor(a, b){
...     this._a=a;
...     this.b=b;
...   }
...   static get a(){
...     return this._a;
...   }
...   set b(b){
...     this.b=b;
...   }
...
...   static async sum(){
...     return this.a+this.b
...   }
... }
... """>>>buf=c.compile(js)>>>print(buf.read())const$a=1,$b=2;let$c=3;classTestClassextendsObject{constructor($d,$e){this._a=$d;this.b=$e;}staticgeta(){returnthis._a;}setb($d){this.b=$d;}staticasyncsum(){returnthis.a+this.b;}}>>>
Package: esprit-py
esprit-py[!NOTE]Please note that this library is not an official API provided by Esprit and is intended for educational and personal use only.FeaturesGet your exact timetable pdfnot 300 pages pdfGet your gradesGet your absencesGet your creditsCalculate your total semester averageInstallationpipinstall--upgradeesprit-pyExamplesget your total avreage:fromespritimportEsprit# Replace with your actual ID and passwordid='ID'password='PASSWORD'grades=None# Keep trying to get grades until it is successful cuz esprit use garabage serverswhilegradesisNone:try:# Create an Esprit objectesprit=Esprit()# Attempt to log inesprit.login(id,password)# Get gradesgrades=esprit.get_grades()exceptExceptionase:print(f"An error occurred:{e}. Retrying...")ifgradesisnotNone:forgradeingrades:print(grade)else:print("Failed to get grades.")esprit.calculate_average(grades)get a list of all your absences;fromespritimportEsprit# Create an Esprit objectesprit=Esprit()# Replace with your actual ID and passwordid='ID'password='PASSWORD'# Attempt to log inifesprit.login(id,password):print("Login successful.")else:print("Login failed.")# Get absencesabsences=esprit.get_absences()ifabsencesisnotNone:forabsenceinabsences:print(absence)else:print("Failed to get absences.")More examples can be found in theexamples folder
Package: esp-secure-cert-tool
The python utility helps to configure and provision the device with
PKI credentials to generate the esp_secure_cert partition.
The utility also configures the DS peripheral on the SoC if available.Theesp-secure-cert-toolutility ishosted on
github.DocumentationVisit onlineesp-secure-cert-tool
documentationor runconfigure_esp_secure_cert.py-h.LicenseThe License for the project can be foundhere