Saravanan666/pypi-org huggingface dataset:
Package: benamer
benamerBulk renamer with intuitive (no regex) options.Getting StartedIn order to run this software, you need Python, it does not matter what version (provided it is updated enough), benamer will only run in Python 3.InstallationYou can use pip in order to retrieve the package from PyPI:sudo pip install benamerUsagebenamer.py [-h] [-d DIR] [-as RPREFX] [-ac START] [-rs RSUFX] [-ap RPREFX] [-rp RPREFX] [-fe FILTER_EXT] [-fp FILTER_PREFIX] [-fs FILTER_SUFFIX] [-st SUST] [-e EXT] [-rsp] [-s] [-p] [-jd] [-jf] [-u] [-l] [-v]Usebenamer -hto get a complete list of available options. The availabe operations at the time of writing are:-h, --help show this help message and exit-d DIR, --dir DIR set the directory to work with-as RPREFX, --add-suffix RPREFX add suffix to name-ac START, --add-count START add count suffix to name-rs RSUFX, --remove-suffix RSUFX remove suffix in name-ap RPREFX, --add-prefix RPREFX add prefix to name-rp RPREFX, --remove-prefix RPREFX remove prefix in name-fe FILTER_EXT, --filter_by_ext FILTER_EXT filter by extension-fp FILTER_PREFIX, --filter_by_prefix FILTER_PREFIX filter by prefix-fs FILTER_SUFFIX, --filter_by_suffix FILTER_SUFFIX filter by suffix-st SUST, --sust SUST substitute string-e EXT, --ext EXT substitute extension-rsp, --replace-spaces replace spaces in files with underscores-s, --sort sort files before renaming-p, --print do nothing, just show renamings-jd, --directories rename only directories-jf, --files rename only files-u, --upper uppercase file names-l, --lower lowercase file names-v, --verbose describe what I am doingExamplesAdding a prefixThe following command will show the effects of adding a prefix to all files in the current directory. Nothing will be actually changed

`benamer -p -ap file_`

`benamer --print --add-prefix file_`Adding a prefixThe following command will add a prefix to all files in the current directory.

`benamer -ap file_`

`benamer --add-prefix file_`Adding a count suffixThe following command will add a suffix with a count to all files in the sub subdirectory.

`benamer -ac 1 -d sub`

`benamer --add-count 1 --directory sub`Replacing a part of the nameThe following command will replace all "er" with "ar" in all files of the current directory.

`benamer -st er/ar`

`benamer --sust er/ar`Replacing the whole file nameThe following command will replace the whole file name with "f" in all files of the current directory.

`benamer -st /f`

`benamer --sust /f`Remove a part of the file nameThe following command will remove the "er" part of the file name in all files of the current directory.

`benamer -st er/`

`benamer --sust er/`
Package: benanalysis
Bentham Instruments spectral analysis library.CompatibilityWheels are built for python versions 3.8 - 3.11, for these systems:Windows: win32, amd64Linux: x86, x86_64MacOS >10.9, universal2 (combined x86_64, arm64, requires pip version > 20.6 on intel, >21.0.1 on Apple Silicon)Note: Apple silicon build has not been tested.Installationpip install benanalysisUsage
Package: benbaptist-elevenlabs
elevenlabsNOTE: The official elevenlabs library is now available! Check it outhere at this link.
The PyPi packageelevenlabswill now point to their official library
moving forward. Just in case you need this library still, I went ahead
andelevenlabs is an unofficial Python library that provides an easy-to-use
interface for elevenlabs.io’ API. With this library, you can easily
integrate with the API to generate voices.InstallationTo install elevenlabs, run:pip install --upgrade elevenlabsThis library requires no special dependencies, and is written in pure
Python.Basic UsageHere’s an example of how you can use elevenlabs to retrieve data from
the API:from elevenlabs import ElevenLabs

eleven = ElevenLabs(api_key)

# Get a Voice object, by name or UUID
voice = eleven.voices["Arnold"]

# Generate the TTS
audio = voice.generate("Hey buddy! It's a beautiful day.")

# Save the TTS to a file named 'my_first_tts' in the working directory
audio.save("my_first_tts")See example.py for more. For more advanced usage, refer to the
(currently non-existent!) documentation and the API reference.Seethe official ElevenLabs
documentationfor more information.Real World ExampleI’m currently using this library to produce fully-automated weather
reports on my radio station,BMIX94. For
a sample of how it sounds,here’s link to the latest weather
reportthat
will actually be broadcasting at various times throughout the day. That
link is always pointing to the most recent weather report generated.
Package: benchbase
NAMEbenchbase - Store and manage JMeter or FunkLoad benchmark results.Produces detailed reports.Visithttps://github.com/bdelbosc/benchbase/wikito see report examples.USAGEbenchbase [–version] [–logfile=LOGFILE] [–database=DATABASE] COMMAND [OPTIONS] [ARGUMENT]COMMANDSlistList the imported benchmark in the database.info BIDGive more information about the benchmark with the bid number (benchmark identifier).import [–jmeter|–funkload|–comment=COMMENT] FILEImport the benchmark result into the database. Output the BID number. The input file can
be gzipped.addsar –host HOST [–comment=COMMENT] BID SARImport the text sysstat sar output, the input file can be gzipped.report –output REPORT_DIR BIDGenerate the report for the imported benchmarkEXAMPLESbenchbase listList of imported benchmarks.benchbase import -m”Run 42” jmeter-2010.xmlImport a JMeter benchmark result file, this will output a BID number.benchbase addsar -H”localhost” -m”bencher host” 1 /tmp/sysstat-sar.log.gzAttach a gzipped sysstat sar file for the bench BID 1.benchbase report 1 -o /tmp/report-run42Build the report of benchmark BID 1 into /tmp/report-run42 directory.REQUIRESBenchbase requiresgnuplotand sqlite3, on Debian/Ubuntu:sudo aptitude install sqlite3 gnuplotINSTALLATIONsudo easy_install benchbaseINPUTSJMeterSupported JMeter file format is JTL 2.1 sample attributes.This has been tested using an ant script with the following configuration:<jmeter ...>
 ...
 <property name="file_format.testlog" value="2.1"/>
 <property name="jmeter.save.saveservice.output_format" value="xml"/>
 <property name="jmeter.save.saveservice.bytes" value="true"/>
 <property name="jmeter.save.saveservice.thread_counts" value="true"/>
 ...
</jmeter>The CSV output is also supported in 10 or 12 columns10: ['ts', 't', 'lb', 'tn', 'de', 's', 'by', 'ng', 'na', 'lt'],
12: ['ts', 't', 'lb', 'rc', 'rm', 'tn', 'de', 's', 'by', 'ng', 'na', 'lt']}FunkLoadShould work with any FunkLoad xml result file.Sysstat sar fileSupported sysstat sar format is the text output. For instance you can
capture stuff like this:sar -d -o /tmp/sar.data 1 100 > /dev/null 2>&1 &This gets stats every second during 100s and store the result in a file.To get the text output you need to run this:LC_ALL=C sar -f /tmp/sar.data -A > /tmp/sar.log
Package: bench-cli
Bench is a free, open-source command-line tool and dashboard web app for visualizing stock metrics.[TOC]Install BenchRequirements:Python 3.9 or greaterRecommended:$pipinstallbench-cliYou can also install as a dependency within a virtual environment withpoetry:$poetryaddbench-cliOtherwise, clone the project and in the project directory run:$poetryinstallUse BenchGetting StartedIEX CloudSign up for IEX Cloud and get your API token:https://iexcloud.io/PostgreSQL DatabaseAll you need to do is create a new Postgres database - that's it!The SQL queries and API calls are executed with$ bench run-- that's where all the magic happens. The SQL queries can be foundhere.Commands$bench--install-completionzsh# Installs completion for the shell$bench--show-completionzsh# Shows completion for the shell$benchinit# Creates the Bench directory tree at the user's home directory$benchinit--directory"~/Desktop"# Creates the Bench directory tree at the user's home directory and at specified path$benchenv# Activates the default .env$benchenv--use"~/Desktop/bench/envs/.env"# Activates the .env file at the specified path$benchadd"GOOGL"# adds symbol GOOGL to the watchlist$benchremove"FB"# removes symbol FB from the watchlist$benchwatchlist# Displays a table of symbols in the watchlist$benchpipeline-iannual-n10# Executes the data pipeline for the last 10 years of annual data (-i or --interval can be annual or quarterly)$benchdash# Serves the Dash app at localhost:8050The directory structure that$ bench initcreates should look like:.
├── envs
└── logsEnvironment ConfigurationThe .env file should look like this:# The ENV_PATH is created at ~/bench/envs/.env by default. This variable will also update when a path other than the default is used
ENV_PATH='path_to_env'

# PostgreSQL config
BENCH_DB_HOST=''
BENCH_DB_PORT=''
BENCH_DB_USER=''
BENCH_DB_NAME=''
BENCH_DB_PASSWORD=''

# The version can either be 'test' or 'stable'. Test will use the IEX Cloud Sandbox API and the test token
BENCH_IEX_VERSION=''
BENCH_IEX_TOKEN=''
# IEX Cloud Sandbox API key
BENCH_IEX_TEST_TOKEN=''

# Can provide a list of symbols in a comma-separated list (eg. 'AAPL,GOOGL,MSFT'), or use the add and remove commands
BENCH_WATCHLIST=''RoadmapFeatureCompletedPriorityAdd option to$ bench dashto specify a portN***Data dictionary of supported metricsN***Detailed logger and reportsN***TestsN***Add pipelines for other data sourcesN*Job scheduler for the pipelineN*DMD for the databaseN*
Package: benchconnect
benchconnectA small Python package that creates a CLI for benchmark runners interacting
with a Conbench server.This is a light wrapper on top ofbenchadapt.BenchmarkResult,benchadapt.BenchmarkRun, andbenchclients.ConbenchClient.
If your code is already in Python, it may be simpler to use those classes
directly.InstallationWithpipx:pipxinstallbenchconnect@git+https://github.com/conbench/conbench.git@main#subdirectory=benchconnectEnvironment variablesbenchconnect relies on a number of environment variables to obtain various
metadata:CONBENCH_URL: Required. The URL of the Conbench server without a trailing
slash, e.g.https://conbench.example.comCONBENCH_EMAIL: The email to use for Conbench login. Only required if the
server is private.CONBENCH_PASSWORD: The password to use for Conbench login. Only required
if the server is private.CONBENCH_PROJECT_REPOSITORY: The repository name (in the formatorg/repo) or the
URL (in the formathttps://github.com/org/repo)CONBENCH_PROJECT_PR_NUMBER: [recommended] The number of the GitHub pull request that
is running this benchmark. Do not supply this for a runs on the default branch.CONBENCH_PROJECT_COMMIT: The 40-character commit SHA of the repo being benchmarkedCONBENCH_MACHINE_INFO_NAME: By default, the running machine host name (sent inmachine_info.namewhen posting runs and benchmarks) will be obtained withplatform.node(), but in circumstances where consistency is needed (e.g.
running in CI or on cloud runners), a value for host name can be specified via
this environment variable instead.UsageBenchmark run workflowTo submit a run of benchmark results to a Conbench server, benchconnect can
open a run, modify submitted results to be a part of that run, and close it.A minimal example:benchconnectstartrun'{"run_reason": "test"}'# pass one result or a whole set at a time, inline or from filesbenchconnectsubmitresult--pathmy-results/

benchconnectfinishrunAdditional metadata can be passed via JSON, e.g.nameandgithubwhen
creating the run, orerror_typeanderror_infowhen closing it.Manual APISee the man pages:benchconnect--help
benchconnectaugment--help
benchconnectpost--help
benchconnectput--helpTheaugmentcommand takes JSON for a benchmark result (augment result)
or benchmark run (augment run) and fills in defaults for unspecified fields.
This is useful for filling in fields likemachine_infoconsistently. Note
this is stateless, and will not makerun_idandsuite_idvalues correspond
across results, nor will the resulting JSON necessarily be complete enough to
post to a Conbench server correctly (it can't fill in things likerun_reasonfor you); please ensure data is correct before posting.Thepostandputcommands authenticate with a Conbench server (see man
pages for environment variables) and send JSON passed. Since they correspond
to the API, there arepost resultandpost runmethods, but onlyput run.
Package: bencherscaffold
BencherScaffoldThis repository contains the scaffold for theBencherproject.
It contains the protobuf files and the generated python code to communicate with the Bencher server.Please refer to theBencherrepository for more information.Installationpipinstallgit+https://github.com/LeoIV/BencherScaffold.gitUsageSee theBencherrepository for usage examples.
Package: bench-it
Quickly find where your code is spending its time.Benchit is intended to be a minimalistic library that times how long it
takes to get from point A to point B. It helps detect unoptimized code.Benchit is only compatible with python 3. For python 2 support, use
benchit==0.2.6 (https://pypi.python.org/pypi/bench-it/0.2.6)Installationpip install bench-itExamplefrom benchit import BenchIt
from time import sleep


def demo_benchmark():
    b = BenchIt()  # starts the timer

    # do stuff
    sleep(1); b()  # Add marker after this code.  Code used as marker name.

    sleep(.2);
    sleep(.3);
    sleep(.4);
    b("More stuff done")  # Add a custom named marker

    for i in range(1, 5):
      sleep(.1); b()  # Code can be marked in a loop

    b.display()  # Display output as a table


demo_benchmark()


BenchIt
+-----------------+----------------+------------+------+----------+---------+---------+
| Marker          | Method         |       Line | Hits | Avg Time | Runtime | Percent |
+-----------------+----------------+------------+------+----------+---------+---------+
| sleep(1)        | demo_benchmark |  demo.py:9 |    1 |  1.01341 | 1.01341 |   43.33 |
| More stuff Done | demo_benchmark | demo.py:14 |    1 |  0.91278 | 0.91278 |   39.03 |
| sleep(.1)       | demo_benchmark | demo.py:17 |    4 |  0.10306 | 0.41223 |   17.63 |
+-----------------+----------------+------------+------+----------+---------+---------+
Total runtime: 2.33860How to UseInstantiating the class starts the timer. BenchIt is run as a singleton.
Re-instantiating anywhere in your code will pull in the previously
instantiated timer. To create a new timer, initialize BenchIt with a
unique name.b = BenchIt()

b2 = BenchIt()  # b == b2

b3 = BenchIt("Timer A")  # b != b3Set a marker after some code.call_a_method(); b()  # Quickly add a marker after a method

method1()
method2()
b("Two methods called")  # Or create a manual marker after a chunk of codeStop and display the table for analysis.b.display()Methodsbenchit.__init__()Instantiate and start the timer.benchit.__call__(marker_name)Add marker at this point.benchit.stop()Optionally, stop the timer at a point.benchit.display()Display the table. Stops the timer if running.CreditsSpecial thanks Luke Maurits forprettytable*
Package: benchkit
benchkitWelcome tobenchkit! We are an End-To-End Free Machine Learning Model management platform.We allow users to:Train and deploy their models on the cloud with a fully managed infrastructure (no more cuda headaches 🙃)Track their model runsGraph Model Accuracy, and outputsDocsCheck out the docshereWebsiteCheck out the sitehereHow it worksbenchkitworks in sync with the Bench AI site, and is completely free.1) Create a repo on Bench AI2) (Optional) Migrate your Data3) Migrate your code4) Start Experiments5) Monitor Your ModelsModel RunsModel LogsContributebenchkitis completely open source, and we could always use the help! You can make
changes to the repo, or can request for features on the Bench AI Site!How to ContributeCheck out this contributionguide
Package: benchline
Python package with modules for small but important things I need and don’t want to reinvent over and over again.The name benchline comes from my son.  When he was little he loved to watch the show, “Thomas the Tank Engine” and the main character was a train who had his own “branch line” off the main line.  My son, at the time, couldn’t pronouce branch line so he said “bench line”.So, as I code it’s fun to be reminded of him and remember that we don’t have to be perfect to be awesome.
Package: benchlingapi
BenchlingAPIThe (unofficial) python API wrapper for Benchling. For more information,
see documentation athttps://klavinslab.github.io/benchling-api/index.Installationpip install benchlingapi -UGetting StartedInitialize a session using your Benchling-provided API key:frombenchlingapiimportSessionsession=Session("your_secret_benchling_api_key")From there, you can access various models:session.DNASequencesession.AASequencesession.Oligosession.Foldersession.Projectsession.Registrysession.Translationsession.EntitySchemasession.Batchsession.CustomEntityFinding models:# get one modeldna=session.DNASequence.one()# find a specific model by its iddna=session.DNASequence.find('sdg_4tg23')# get the last 50 amino acidsproteins=session.AASequence.last(50)# get a registry by nameregistry=session.Registry.find_by_name("Klavins Lab Registry")Updating models:dna=session.DNASequence.one()dna.name="My new name"dna.bases="AGGTAGGGTAGGGCCAGAGA"# update the sequence on the serverdna.update()Saving new models:folder=session.Folder.find_by_name("My API Folder")dna=session.DNASequence(name='my new dna',bases='AGGTAGGATGGCCA',folder_id=folder.id,is_circular=False)# save the dna to your Benchling accountdna.save()Registering models to your registry:dna.set_schema("My DNA Schema")dna.register()See the documentation for more information:https://klavinslab.github.io/benchling-api/indexTestingTesting is done usingpytest. Tests will create live requests to a Benchling account.
Since testing is done live, a Benchling account will need to be setup along with testing
data.To run tests, you must have a Benchling Account with an API key. Tests require a file in
'tests/secrets/config.json' with the following format:{
  "credentials": {
    "api_key": "asdahhjwrthsdfgadfadfgadadsfa"
  },
  "sharelinks": [
    "https://benchling.com/s/seq-asdfadsfaee"
  ],
  "project": {
    "name": "API"
  },
  "trash_folder": {
    "name": "API_Trash"
  },
  "inventory_folder": {
    "name": "API_Inventory"
  }
}On the Benchling side of things, in the account liked to thecredentials["api_key"], you must
have a project corresponding to theproject["name"]value above. Within this project, you should
have two folder corresponding to thetrash_folderandinventory_foldervalues above. Additionally,
you should have at least one example of an AminoAcid, DNASequence, CustomEntity, and Oligo stored within
yourinventory_folder. Tests will copy the examples from theinventory_folderfor downstream tests.
After the tests, conclude, inventory in thetrash_folderwill get archived.Happy Cloning!
Package: benchling-sdk
Benchling SDKA Python 3.8+ SDK for theBenchlingplatform designed to provide typed, fluent
interactions withBenchling APIs.InstallationInstall the dependency viaPoetry(if applicable):poetryaddbenchling-sdkOrPip:pipinstallbenchling-sdkDocumentationDocumentation for the SDK is kept up-to-date atdocs.benchling.com, and you can get started with
it using this guide:https://docs.benchling.com/docs/getting-started-with-the-sdk.SupportTo report issues with using the SDK, contactsupport@benchling.com.
Package: benchllama
🧮 BenchllamaAn open-source tool to benchmark you local LLMs.🔑 Key pointsBenchllama helps with benchmarking your local LLMs. Currently, it only supports benchmarking models served via Ollama. By default, it pullsbigcode/humanevalpackfrom HuggingFace. There is an out of box support for evaluating code autocompletion models (you need to use--evalflag for triggering this). Currently, it supports the following languages: Python, JavaScript, Java, Go, C++. You can also bring your own dataset (see thisexamplefor helping you with creating one) by specifying the path to it in--datasetflag.📜 BackgroundWith the explosion of open source LLMs and toolbox to further customize these models likeModelfiles,Mergekit,LoRAetc, it can be daunting to end users to choose the right LLM. From our experience with running local LLMs, the two key metrics that matter are performance and quality of responses. We created a simple CLI tool that enables the users to pick right LLM by evaluating them across these two parameters.Given our experience in coding LLMs, we felt it would be useful to add out-of-box support for calculatingpass@kfor autocompletion models. In case, if you are into coding LLMs, please checkout our related project i.ePrivy(github repo,vscode link,openvsx link).✨ FeaturesEvaluate: Evaluate the performance of your models on various tasks, such as code generation.Clean: Clean up temporary files generated by Benchllama.🚀 Installation$pipinstallbenchllama⚙️ Usage$benchllama[OPTIONS]COMMAND[ARGS]...Options:--install-completion: Install completion for the current shell.--show-completion: Show completion for the current shell, to copy it or customize the installation.--help: Show this message and exit.Commands:evaluatecleanbenchllama evaluateUsage:$benchllamaevaluate[OPTIONS]Options:--models TEXT: Names of models that need to be evaluated. [required]--provider-url TEXT: The endpoint of the model provider. [default: http://localhost:11434]--dataset FILE: By default, bigcode/humanevalpack from Hugging Face will be used. If you want to use your own dataset, specify the path here.--languages [python|js|java|go|cpp]: List of languages to evaluate from bigcode/humanevalpack. Ignore this if you are brining your own data [default: Language.python]--num-completions INTEGER: Number of completions to be generated for each task. [default: 3]--no-eval / --eval: If true, evaluation will be done [default: no-eval]--k INTEGER: The k for calculating pass@k. The values shouldn't exceed num_completions [default: 1, 2]--samples INTEGER: Number of dataset samples to evaluate. By default, all the samples get processed. [default: -1]--output PATH: Output directory [default: /tmp]--help: Show this message and exit.benchllama cleanUsage:$benchllamaclean[OPTIONS]Options:--run-id TEXT: Run id--output PATH: Output directory [default: /tmp]--help: Show this message and exit.