Saravanan666/pypi-org huggingface dataset:
Package: bhargabchipkg
This package can be used to classify salesmen on its performance of total sale and total unsold with
two different groups.In easy words let’s say we want to see performance (good and bad) salesman for urban market,
rural market, and here we can use this package by passing a dataframe, column name of salesman id,
column name of saleflag (indicating 0 for unsold and 1 for sold), column name of grouping column
(having only two unique values or levels).By default,
By calling the chi_test() method we can get the Top 30 percentage and Bottom 30 percentage salesman.We can change this top and bottom percentage by passing argument inside this chi_test() method.We are using chi square test, a statistical method which indicates performance quality.You can get the description by reading the readme.md file from my github.
link of github:https://github.com/bhargabganguli/bhargabchipkg.gitHere you can findhow to installhow to create object and use the methodhow to call the method and print the output
Package: bhav
## bhav is a command line application to download EOD stock data from the BSE / NSE indexes based on our experience fetching this data over the last decade## Installation:pip3 install –user bhav## Usage:### Download BSE bhavcopy for a specific date (YYYYMMDD)bhav bse 20200101### Download NSE bhavcopy for a specific date (YYYYMMDD)bhav nse 20200101### if remote file is zippedbhav nse 20200101 -z### Download for date rangebhav nse –start-date 20200101 -z ( fetch from start date to today)bhav nse –start-date 20200101 –end-date 20200105 -z## Most configuration options should help adjust to changes in the way these files are distributed by the exchanges as well as formats.bhav conf –help for configuration options### Get current configurationbhav conf ls### Configure output directorybhav conf update -o /path/to/output/dir### Configure NSE URL formatbhav conf update -n https://archive.nseindia.com/content/historical/EQUITIES/#-#year#-#/#n#month#n#/cm#-#day#-##n#month#n##-#year#-#bhav.csv.zip#### numeric values of day / month / year are represented by patterns like #-#year#-#
#### month names are represented by patterns like #n#month#n#### Configure BSE URL formatbhav conf update -b http://www.bseindia.com/download/BhavCopy/Equity/EQ#-#day#-##-#month#-##-#YY#-#_CSV.zip### Configure BSE CSV header format. If the date column is not provided in the file, it will be automatically added.bhav conf update -B ‘SYMBOL,NAME,SC_GROUP,SC_TYPE,OPEN,HIGH,LOW,CLOSE,LAST,PREVCLOSE,NO_TRADES,VOLUME,NET_TURNOV,TDCLOINDI’### Configure NSE CSV header format.bhav conf update -B ‘SYMBOL,SERIES,OPEN,HIGH,LOW,CLOSE,LAST,PREVCLOSE,VOLUME,TOTTRDVAL,DATE,TOTALTRADES,ISIN’
Package: bhavcopy
bhavopy Python PackageThis package provides a Python interface to download National Stock Exchange (NSE) bhavcopy data for Equities, Indices and Derivatives. The package provides functions to download daily bhavcopy data in CSV format, store the data in local storage, and update the data for any missing dates.Basically it creates csv file for equities, indices and derivatives,
If the file already exist on assigned directory, then the code attempts to figure out missing dates and update the same file.
all you have to do is update the start and end date.and all this can be done by simply providing following arguements:pip install bhavcopyimport bhavcopy# Place data need to be stored.data_storage = “D:\bhav_data”# Define working directory, where files would be savedos.chdir(data_storage)# Define start and end dates, and convert them into date formatstart_date = datetime.date(2023, 3, 1)end_date = datetime.date(2023, 3, 21)# Define wait time in seconds to avoid getting blockedwait_time = [1, 2]# Instantiate bhavcopy class for equities, indices, and derivativesnse = bhavcopy(“indices”, start_date, end_date, data_storage, wait_time)nse.get_data()nse = bhavcopy(“equities”, start_date, end_date, data_storage, wait_time)nse.get_data()nse = bhavcopy(“derivatives”, start_date, end_date, data_storage, wait_time)nse.get_data()
Package: bhavpr
BhavCopyPRParserA simple parser to consume PR files available with NSE.National Stock Exchange of India Limited
Capital Market Information ServiceInformation related to  files in nuprddmmyy.zip:This is to inform all the news-vendors and news agencies that, on NSE various instruments like Equities, Debentures, Warrants, Partly Paid Shares etc. are traded.The nuprddmmyy.zip contains the following files:Anddmmyy.txt
Bcddmmyy.csv
bhddmmyy.csv
Bmddmmyy.txt
cdddmmyyyy.zip
corpbondddmmyy.csv
etfddmmyy.csv
foddmmyyyy.zip
Glddmmyy.csv
HLddmmyy.csv
Pdddmmyy.csv
Prddmmyy.csv
Readme.txt
smeddmmyy.csv
Ttddmmyy.csvAnddmmyy.txt file contains name of the co., its symbol and the announcements made during the day.Bcddmmyy.csv file contains the corporate action details for securities.bhddmmyy.csv file contains a list of securities which have hit their price bands during the day.Bmddmmyy.txt file contains details of Board Meetings of companies.cdddmmyyyy.zip folder contains press files for Currency Derivative segment.corpbondddmmyy.csv file contains market data of Corporate bonds traded during the day.etfddmmyy.csv file contains market data of exchange traded funds traded during the day.foddmmyyyy.zip folder contains press files for Future & Options Segment.Glddmmyy.csv file contains a list of the gainers and losers for Nifty Securities, Nifty Next 50 Securities and for other Securities.HLddmmyy.csv file contains a list of securities which have reached a new high or a new low.Pdddmmyy.csv file also contains Symbol and Series codes for each Security in addition to the information contained in the prddmmyy.csv file.Prddmmyy.csv file contains security wise market data information along with the Index details.Readme.txt is a informative file which contains information about data and structure of all other files.smeddmmyy.csv file contains market data of SME securities traded during the day.Ttddmmyy.csv file contains a list of top twenty five securities by traded value.class BhavPR:
    Function: get_company(search_string)
        Returns a list of company name, symbol pairs as a set that matches the search_string.

    Function: collect(date_start, date_end)
        Returns a bool implying the success of the collection. 
        Collects the PR files available on the server for the provided date range. 
            date_start: Format as 01-01-2020 DD-MM-YYYY
            date_end: Format as 05-01-2020 DD-MM-YYYY

    Function: get_symbol(search_string, on_symbol=False)
        Returns a list of matched company records.
        on_symbol: Limit to symbol field

    Function: set_company(company_name)
        Returns a bool of the context set.
Package: bhawick.helloworld
Hello WorldThis is an example project demonstrating how to publish a python module to PyPI.InstallationRun the following to install:pipinstallbhawick.helloworldUsagefromhelloworldimportsay_hello# Generate "Hello, World!"say_hello()# Generate "Hello, Everybody!"say_hello("Everybody")Useful ReferencesBuild & test Python -- github docsMyPy Typehints cheatsheetMyPy example .ini fileCannot find implementation or library stubblack formatter just needs the directory name to worksetup.py cheatsheetspecifying python versions on toxasking pipenv to install dev dependenciesinstalling pipenvPEP 423 naming convetions for projectshitchhiker's guide to packaging and saving the universereal python project inspiration
Package: bhawick.looniplot
Please do not use this libraryThis is a fork ofUniplotand attempts to see if my CI/CD can replace the approach taken byUniplot. I do not pretent this mine and it is merely an experiment.Lessions learntSetup.py and Setup.cfg work togetherAlongsidepipenvthey automatically create and destroy thepyproject.toml.
In addition, I could setextra_dependenciesinsetup.cfgand they need to remain insetup.pyinorder forpip -e .[dev]to install development dependencies.Version release processGiven you have just publishedv0.0.1, create aH3heading inCHANGELOG.mdforv0.0.2.Commit away!When ready to announce a version bump, with all modified files commited, runmake patchto bump version and create a draft release note.  ⚠️ At this point further commits won't be part of this release.publish the draft release with changelogs when ready.All commits from the version patch will belong to the next version bump.How to reset a library versionmake sure.bumpversion.cfgandsetup.pyhave their versions set to0.0.0To Manually Publish do the followingEnsure make build-check is run
Then run make publishI have adjustedMakefileto runbuild-checkbefore runningpublish.Library folder name must match the module nameThis ensures__init__.pybelong to the module name notsrc.On setting up CI/CDYou must depoy version0.0.0manually, that will create a project instance on PyPi. Create a token against that project and add it as a GitHub Actions Secret under the keyPYPI_API_TOKEN.On Testingtoxcommand for tests must be following or the incorrect file will be targetted.SO-Link. Uniplot author interesting does the same thing!python -m pytest
Package: bhbotlist
bhbotlistuseful library forbhlist.co.inAPI DOCSLink to api docs:API DOCSInstallationpip install bhbotlistexampleServer Count Post :frombhbotlistimportbhbotlistfromdiscord.extimportcommandsclient=commands.Bot(command_prefix="!")dbl=bhbotlist(client,"token of bhbotlist")@client.eventasyncdefon_ready():x=awaitdbl.serverCountPost()print(x)client.run("token")Search bot:frombhbotlistimportbhbotlistclient=commands.Bot(command_prefix="!")dbl=bhbotlist(client,"token of bhbotlist")id=botida=dbl.search(id)print(a)All functions in api:1: serverCountPost()
2: search()
3: hasVoted()JOIN OUR DISCORD SERVER FOR SUPPORTDISCORD LINK
Package: bhcd
bhcd: Bayesian Hierarchical Community DiscoveryAn efficient Bayesian nonparametric model for discovering hierarchical community structure in social networks.Parameter TuningThere are five parameters (alpha, beta, lambda, delta, gamma) to be tuned, lines within interval (0,1) and satisifies the following
constraint.alpha > beta
lambda > deltaUsagePython wrapper.
You can runpython bhcd.pyto get the hierachical tree.
Package: bh-database
bh_databaseDatabase wrapper classes for SQLAlchemy.Pip installationpip install bh-databaseOverviewDatabase wrapper classes for SQLAlchemy.These classes currently support only two database types: MySQL and PostgreSQL. Drivers
required, respectively:https://pypi.org/project/mysql-connector-python.https://pypi.org/project/psycopg2/.These classes provide the following functionalities:Database connection management.A custom SQLAlchemy query class which implements paginating.A generic base model (table), which should be theindirectbase model for
applications' models. This class encapsulates:SQLAlchemy scoped session, thereby providing methods to implement transaction atomicity.A custom base query with paginating ability mentioned above.Fully implemented dunder methods str() and repr().A generic SQLAlchemy declarative base class which should include all required metaclasses.Some generic methods which run full text SQL statements.A generic method to run stored procedures which return data.A generic method which takes a list of records to be inserted, and records to be
updated, and writes them to the target database table in a single call.Transaction atomicity. Multiple database operations involving several different
tables can be wrapped under a single transaction, so that all can be committed
or rolled back as appropriate.Please seeFull documentationfor more detail.DocumentationFull documentationLicenseMIT license
Package: bhedak
BhedakA replacement ofqsreplace, accepts URLs as standard input, replaces all query string values with user-supplied values and stdout. Works on everyOS. Made withpythonInstallation$pip3installbhedakUsageForlinux,unixanddebianbased systems$waybackurlstarget.tld|bhedak"payload"Forwindowsbased systemscmd>typeurls.txt|pythonbhedak.py"payload"If nopayloadpassed$waybackurlssubdomain.target.tld|bhedak

http://subdomain.target.tld/comment.php?pid=FUZZ&user=FUZZ
http://subdomain.target.tld/disclaimer.php=FUZZ
http://subdomain.target.tld/hpp/index.php?pp=FUZZ
http://subdomain.target.tld/hpp/?pp=FUZZ&user=FUZZExample input file$waybackurlssubdomain.target.tld|tee-aurls

http://subdomain.target.tld/comment.php?pid=username&user=1http://subdomain.target.tld/disclaimer.php=1http://subdomain.target.tld/hpp/index.php?pp=12http://subdomain.target.tld/hpp/?pp=12&user=5Replace query string values$caturls|bhedak"FUZZ"http://subdomain.target.tld/comment.php?pid=FUZZ&user=FUZZ
http://subdomain.target.tld/disclaimer.php=FUZZ
http://subdomain.target.tld/hpp/index.php?pp=FUZZ
http://subdomain.target.tld/hpp/?pp=FUZZ&user=FUZZReplace query string with custom payloads$caturls|bhedak"\"><svg/onload=alert(1)>*'/---+{{7*7}}"http://subdomain.target.tld/comment.php?pid=%22%3E%3Csvg%2Fonload%3Dalert%281%29%3E%2A%27%2F---%2B%7B%7B7%2A7%7D%7D&user=%22%3E%3Csvg%2Fonload%3Dalert%281%29%3E%2A%27%2F---%2B%7B%7B7%2A7%7D%7D
http://subdomain.target.tld/disclaimer.php=%22%3E%3Csvg%2Fonload%3Dalert%281%29%3E%2A%27%2F---%2B%7B%7B7%2A7%7D%7D
http://subdomain.target.tld/hpp/index.php?pp=%22%3E%3Csvg%2Fonload%3Dalert%281%29%3E%2A%27%2F---%2B%7B%7B7%2A7%7D%7D
http://subdomain.target.tld/hpp/?pp=%22%3E%3Csvg%2Fonload%3Dalert%281%29%3E%2A%27%2F---%2B%7B%7B7%2A7%7D%7D&user=%22%3E%3Csvg%2Fonload%3Dalert%281%29%3E%2A%27%2F---%2B%7B%7B7%2A7%7D%7DRemove duplicate urls$caturls|bhedak"FUZZ"|sort-u

http://subdomain.target.tld/comment.php?pid=FUZZ&user=FUZZ
http://subdomain.target.tld/disclaimer.php=FUZZ
http://subdomain.target.tld/hpp/index.php?pp=FUZZ
http://subdomain.target.tld/hpp/?pp=FUZZ&user=FUZZComparsion$echo"http://fakedomain.com/fakefile.jsp;jsessionid=2ed4262dbe69850d25bc7c6424ba59db?hardwareid=14&tarifid=9998"|qsreplace"FUZZ"http://fakedomain.com/fakefile.jsp;jsessionid=2ed4262dbe69850d25bc7c6424ba59db?hardwareid=FUZZ&tarifid=FUZZ

$echo"http://fakedomain.com/fakefile.jsp;jsessionid=2ed4262dbe69850d25bc7c6424ba59db?hardwareid=14&tarifid=9998"|bhedak"FUZZ"http://fakedomain.com/fakefile.jsp;jsessionid=FUZZ?hardwareid=FUZZ&tarifid=FUZZDonateIf this tool helped you or you like my workThanks to@tomnomnomfor making an amazing tool calledqsreplace, from usingqsreplaceI got idea to makebhedak
Package: bheEASyMesh
bheEASyMeshTool for creating simple VTK unstructured grid meshes (3D prism elements) with BHEs (line elements) for use in OpenGeoSys 6 HeatTransportBHE simulations. Besides, the extraction of surface meshes and the application of temperature ICs is possible. The meshing is based on the Bhe_Meshing tool by Philip Hein (Shao et al., 2016) and uses GMSH (Geuzaine et al., 2009).Meshes contain:- 3D prism mesh with horizontal element layers- A selected number of BHEs, which are represented as line elements- Diersch's ideal node distance around BHE-elements (Diersch et al., 2011)- A chosen number of optional horizontal refinement boxes in the mesh- Extraction of surfacemeshes to define BC's or IC's in OpenGeoSys- An optional temperature IC as depth dependent profile or fixed temperature which can be applied to the mesh and if needed to surfacemeshesThere are two modes in the Software:=>"simple" Meshes:- Simple meshes with two different material groups to be used for geological homogeneous models with an area with groundwater flow- the software automatically adjusts the vertical layers over the user-defined default element height- refined layers in the transition zones (BHE top/bottom, aquifer top/bottom) by user-defined number of refined layers and a separate element height for refined areas=>"layered" Meshes:- manual definition of any number of layers- number of elements, height of the elements and material ID can be freely selected for each layerFor more instructions, see Meshing_example.ipynb, where there are tutorials for both meshing modes.====================================Diersch et al. (2011): Finite element modeling of borehole heat exchanger systems Part 2.Numerical simulation. In: Computers & Geosciences 37, pages 1136-1147.Geuzaine C et al. (2009) Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities. International Journal for Numerical Methods in Engineering 79, pages 1309-1331.Shao et al. (2016): Geoenergy Modeling II Shallow Geothermal Systems. Springer.
Package: bhej
bhejShare files like a dev.InstallationTo install this cli to your environment, just run...pip install bhej...and you're good to go!UsagesTo upload a file, just run the following.bhej up <filename>
# You'll receive a 6 digit code to share.
# You'll also get a link that you can directly download from.To download a file, just run the following.bhej down <code> # Use the 6 digit code from the upload step.To download and import a dataframe, run the following.from bhej.main import down as bhejdown, up as bhejup
df = bhejdown(<code>, return_df=True)To download and import a file, run the following.from bhej.main import down as bhejdown, up as bhejup
df = bhejdown(<code>, return_file=True)DevelopmentWant to contribute? After cloning andcd-ing into the project directory,
you can run the following to get set up.poetry shell    # Sets up virtual environment.
poetry install  # Installs dependencies.
which bhej      # Should return your local version of the CLI.Deploying to PyPiTo deploy to Test PyPi, runpoetry run deploy_staging. To deploy to the Prod PyPi, runpoetry run deploy_prod.To install it from Test PyPi, run the following.pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple bhejTo install from Prod PyPi, runpip install bhej.
Package: bhepop2
A common problem ingenerating a representative synthetic populationis that not all attributes of interest are present in the sample.  The purpose is to enrich the synthetic population with additional attributes, after the synthetic population is generated from the original sample.
In many cases, practitioners only have access to aggregated data for important socio-demographic attributes, such as income, education level.
This package treats the problem toenrich an initial synthetic population from an aggregated dataprovided in the form of a distribution like deciles or quartiles.Read thedocsor see the code and examples onGitHub.
Package: bhex
Welcome to Broker-PythonAn official Python implementation of the lastest Open API for Broker.Installpipinstallbhexor download from githubUsageREST APIInit broker client:b=BrokerClient(entry_point='',api_key='',secret='')Init broker options client:b=BrokerOptionClient(entry_point='',api_key='',secret='')Init broker contract client:b=BrokerContractClient(entry_point='',api_key='',secret='')Request with proxies:proxies={"http":"http://ip:port","https":"http://ip:port",}b=BrokerClient(entry_point='',api_key='',secret='',proxies=proxies)Web SocketInitInit broker websocket client:client=BrokerWss(entry_point='',rest_entry_point='',api_key='',secret='')SubscribeSubscribe trades:client.subscribe_to_trades(symbol='BTCUSDT',callback=handler)Subscribe Kline/Candlestick:client.subscribe_to_kline(symbol='BTCUSDT',interval='5m',callback=handler)Subscribe market tickers:client.subscribe_to_realtimes(symbol='BTCUSDT,ETHUSDT',callback=handler)Subscribe book depth tickers:client.subscribe_to_depth(symbol='BTCUSDT',callback=handler)Subscribe user data:client.user_data_stream(callback=handler)StartStart websocket threadclient.start()API ListPublic APIpingb.ping()timeb.time()broker infob.broker_info()depthb.depth('BTCUSDT')tradesb.trades('BTCUSDT')klinesb.klines('BTCUSDT')ticker 24hrb.ticker_24hr('BTCUSDT')Private APInew orderb.order_new(symbol='BTCUSDT',side='BUY',type='LIMIT',quantity='0.01',price='1000',timeInForce='GTC')get orderb.order_get(order_id='')cancel orderb.order_cancel(order_id='')open ordersb.open_orders()history ordersb.history_orders()accountb.account()my tradesb.my_trades()deposit ordersb.deposit_orders()Examplesexamples.pyoption-examples.pycontract-examples.pyws-examples.py
Package: bhfutils
OverviewThebhfutilspackage is a collection of utilities that are used by any spider of Behoof project.RequirementsUnix based machine (Linux or OS X)Python 2.7 or 3.6InstallationInside a virtualenv, runpip install-Ubhfutils.  This will install the latest version of the Behoof Scrapy Cluster Spider utilities.  After that you can use special settings.py compatibal with scrapy cluster (template placed in crawler/setting_template.py)DocumentationFull documentation for thebhfutilspackage does not existcustom_cookies.pyThecustom_cookiesmodule is custom Cookies Middleware to pass our required cookies along but not persist between callsdistributed_scheduler.pyThedistributed_schedulermodule is scrapy request scheduler that utilizes Redis Throttled Priority Queues to moderate different domain scrape requests within a distributed scrapy clusterredis_domain_max_page_filter.pyTheredis_domain_max_page_filtermodule is redis-based max page filter. This filter is applied per domain. Using this filter the maximum number of pages crawled for a particular domain is boundedredis_dupefilter.pyTheredis_dupefiltermodule is redis-based request duplication filterredis_global_page_per_domain_filter.pyTheredis_global_page_per_domain_filtermodule is redis-based request number filter When this filter is enabled, all crawl jobs have GLOBAL_PAGE_PER_DOMAIN_LIMIT as a hard limit of the max pages they are allowed to crawl for each individual spiderid+domain+crawlid combination.
Package: bhimupipy
bhimupipyBHIMUPIPY is a pip packages which can  verify  UPI IDs.InstallationInstall this pip package .pipinstallbhimupipyand use it likefrombhimupipyimportverify_upiUsageCLI~$ bhimupipy --help

usage: -m [-h] [-v] [--upi UPI]

bhimupipy: Get the details of UPI ID.

options:
  -h, --help     show this help message and exit
  -v, --version  print the version of the package (default: False)
  --upi UPI      see upi datails (default: None)Verifying  UPI ID~$ bhimupipy --upi sumithemmadi@ybl~$ bhimupipy --upi sumithemmadi@ybl{"result":true,"vpa":"sumithemmadi@upi","vpaValid":true,"payeeAccountName":"EMMADISUMITHKUMAR","message":"VerifiedUPIID"}This will verify UPI IDVerifing UPI IDfrombhimupipyimportverify_upiverify_upi("sumithemmadi@ybl")output{"result":true,"vpa":"sumithemmadi@upi","vpaValid":true,"payeeAccountName":"EMMADI SUMITH KUMAR","message":"Verified UPI ID"}