Saravanan666/pypi-org huggingface dataset:
Package: td-ml-ps-stats-scan
td-ml-ps-stats-scanIntroductionThis Python Library allows you to extract Parent Segment, Folder, Audiences info and store it in a table in TD for reporting purposes and mapping audiences to segments and metrics.Input Paramsconfig.yml: The workflowYAMLfile contains the params that are required by this library to extract the neded information. See below:apikey= TD APIKEYtdserver= TD ENDPOINTsink_database= Database where outout tables will be writtenoutput_table= name of output tablefolder_depth= how many nested folders in Audience Studio to look into for segments (default =10)v5_flag=1- scans PSs that are in V5 version,0- scans PSs in V4, and1, 0- scans PS is in both V4 and V5.apply_ps_filters=yes- applies filters below and only returns info on specific Parent Segments, Folders, or Segments and Journeys,no- returns all objects in Audience Studiops_to_include= useREGEXPformat such as'name_1|name_2|ec.'to only return info on Parent Segments that match the REGEXP. If you leave blank'', then it will return ALL information.folders_to_include= useREGEXPformat such as'name_1|name_2|etc.'to only return info on Folder Names that match the REGEXP. If you leave blank'', then it will return ALL information.segments_to_include= useREGEXPformat such as'name_1|name_2|etc.'to only return info on Audience Segment Names that match the REGEXP. If you leave blank'', then it will return ALL information.journeys_to_include= useREGEXPformat such as'name_1|name_2|etc.'to only return info on Journey Names that match the REGEXP. If you leave blank'', then it will return ALL information.Copyright © 2022 Treasure Data, Inc. (or its affiliates). All rights reserved
Package: tdms
BadgesTable of ContentsDMS - Table mapping generatorUsageExampleOptionsInstallationTestCoverageLicenseDMS - Table mapping generatorThis is a tool to generate table mapping files for the DMS (Data Migration Service)Pre-requisites:Python 3.6A.txtfile with the tablese.g.tables.txt:table1
table2
table3UsageTypetdms -hto see the help:tdms-h

usage:tdms[-h]-tTABLE_LIST_INPUT-sSCHEMA_LIST_INPUT[-pPREFIX_VALUE]-rRULE_ACTION-yTABLE_TYPES

CreateatablemappingjsonfileforDMS

options:-h,--helpshowthishelpmessageandexit-tTABLE_LIST_INPUT,--table_list_inputTABLE_LIST_INPUTThefilethatcontainsthelistoftablestobemapped-sSCHEMA_LIST_INPUT,--schema_list_inputSCHEMA_LIST_INPUTTheschemathatthetablesarein-pPREFIX_VALUE,--prefix_valuePREFIX_VALUETheprefixvaluetobeaddedtothetablenames-rRULE_ACTION,--rule_actionRULE_ACTIONTheruleactiontobeused-yTABLE_TYPES,--table_typesTABLE_TYPESThetabletypestobeusedExampletdms-ttables.txt-spublic-pmyprefix_-rinclude-yviewOutput example:Valuesused:TableListInputSchemaListInputPrefixValueRuleActionTableTypes--------------------------------------------------------------------------------------------------------
tables.txtpublicmyprefix_includeviewPrefixruleadded->myprefix_infrontof->table1
Prefixruleadded->myprefix_infrontof->table2
Prefixruleadded->myprefix_infrontof->table3Table mapping file generated:{"rules":[{"rule-type":"transformation","rule-id":"85","rule-name":"fc7099f456104bef9e0f9b2f811b63ba","rule-target":"table","object-locator":{"schema-name":"public","table-name":"table1"},"rule-action":"add-prefix","value":"myprefix_"},{"rule-type":"selection","rule-id":"85","rule-name":"fc7099f456104bef9e0f9b2f811b63ba","object-locator":{"schema-name":"public","table-name":"table1"},"rule-action":"include","filters":[]},{"rule-type":"transformation","rule-id":"925","rule-name":"fc7099f456104bef9e0f9b2f811b63ba","rule-target":"table","object-locator":{"schema-name":"public","table-name":"table2"},"rule-action":"add-prefix","value":"myprefix_"},{"rule-type":"selection","rule-id":"925","rule-name":"fc7099f456104bef9e0f9b2f811b63ba","object-locator":{"schema-name":"public","table-name":"table2"},"rule-action":"include","filters":[]},{"rule-type":"transformation","rule-id":"609","rule-name":"fc7099f456104bef9e0f9b2f811b63ba","rule-target":"table","object-locator":{"schema-name":"public","table-name":"table3"},"rule-action":"add-prefix","value":"myprefix_"},{"rule-type":"selection","rule-id":"609","rule-name":"fc7099f456104bef9e0f9b2f811b63ba","object-locator":{"schema-name":"public","table-name":"table3"},"rule-action":"include","filters":[]}]}OptionsOptionDescriptionExampleRequired-tThe file that contains the list of tables to be mappedtables.txtYes-sThe schema that the tables are inpublicYes-pThe prefix value to be added to the table namesmyprefix_No-rThe rule action to be usedincludeYes-yThe table types to be usedviewYesTestTo run thetests, in the root of the project, run:maketestCoverageTo run thecoverage, in the root of the project, run:makecoverageLicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: tdms2axg
A simple script for converting LabVIEW TDMS files to AxoGraph filesInstallationInstall the latest version usingpip:pip install -U tdms2axgCommand Line InterfaceInstalling the package adds thetdms2axgcommand, accessible from the
command line:usage: tdms2axg [-h] [-f] [-q] file

A simple script for converting LabVIEW TDMS files to AxoGraph files. The
AxoGraph (AXGX) file is saved with the same name and in the same directory as
the TDMS file. By default, an existing AxoGraph file will not be overwritten;
use --force to overwrite it.

positional arguments:
  file         the path to a TDMS file

optional arguments:
  -h, --help   show this help message and exit
  -f, --force  overwrite the output file if it already exists
  -q, --quiet  run silentlyPython InterfaceThe main functionality of the package can also be accessed programmatically:fromtdms2axgimporttdms2axgtdms2axg('my_data.tdms')
Package: tdnpathviz
tdnpathviztdnpathviz is a Python package that provides a set of convenient functions to generate various types of visualizations directly within a Teradata Vantage database. It leverages the in-database capabilities of Teradata Vantage including path analysis and in-database plotting (TD_PLOT) for Teradata SQLE 17.20 and later versions.InstallationInstall the package via pip:pip install tdnpathvizUsageHere are the available functions in the Vantage Visualizer package:plot_first_main_paths()create_all_pathes_views()scatter_plot()pair_plot()plot_correlation_heatmap()plotcurves()plotcurvescluster()plot_with_background_image()Example: Plotting First Main PathsHere is an example of how to use theplot_first_main_paths()function:fromtdnpathviz.visualizationsimportplot_first_main_paths# Assume 'myPathAnalysis' is your DataFrame which contains path analysis dataplot_first_main_paths(myPathAnalysis=myPathAnalysis,path_column='your_path_column',id_column='your_id_column',nb_paths=15,print_query=False,font_size=10,width=1200,height=800,weight_column='your_weight_column',weight_agg='count',justify='left')Example: Correlation HeatmapHere is an example of how to use theplot_correlation_heatmap()function to create a correlation heatmap:fromtdnpathviz.visualizationsimportplot_correlation_heatmap# Assume 'tddf' is your teradata DataFrameplot_correlation_heatmap(tddf)# You can pass additional parameters, e.g., ax for specific matplotlib axis, no_plot if you don't want to display the plot,# or a title for your plot.# plot_correlation_heatmap(tddf, ax=your_matplotlib_axis, no_plot=True, title="My Correlation Heatmap")Example: Scatter PlotHere is an example of how to use thescatter_plot()function:fromtdnpathviz.visualizationsimportscatter_plot# Assume 'tddf' is your teradata DataFramescatter_plot(tddf=tddf,x_col='col1',y_col='col2')
Package: tdns
An asynchronous TornadopycaresDNS
client wrapper, exporting the full API.Documentation is available attdns.readthedocs.io.Examplefromtornadoimportgen,ioloopimporttdnsloop=ioloop.IOLoop()channel=tdns.Channel(io_loop=loop)@gen.coroutinedefon_start():response=yieldchannel.query('google.com',tdns.QUERY_TYPE_MX)print(response)loop.stop()loop.add_callback(on_start)loop.start()
Package: tdnss
tdnssA Python API wrapper forTechnitium DNS Server's
HTTP API.NoticeThis project is a work in progress. A list of features will be added, for now
some basic methods ofAPIsuch as login/logout are implemented, with work on thezone
APIand thesettings APIis
ongoing.Any feedback is welcome!Why?TL;DR: the main reason I use this DNS server is its API, since it gives full
control over the server without having to login to the web console. The idea is
that scripts/CLIs/other tools can be built upon a library that wraps the API.InstallationThetdnsspackage isavailable on PyPI.For development, use the provided Pipfile:pipenvinstall--devThis creates avirtual
environment, installs the
dependencies to run the package, the development tools, and the package itself
as an editable dependency in order to test the changes live.If you don't use Pipenv, there's arequirements.txtprovided to install
runtime dependencies and arequirements-dev.txtto install development tools
andtdnssas an editable package.ContributingDo you want to contribute to this project? Great! We welcome any contributions,
from code to documentation through feedback. ReadCONTRIBUTINGfor more information.LicenseThis project is licensed under the GNU General Public License v3.0 only.SeeCOPYINGto see the full text.VersioningThis project followsSemantic Versioning 2.0.0.
Package: tdoc
# TDoc
A python documentation generator.### Installation` pip install tdoc `[pypi](https://pypi.python.org/pypi/tdoc)### Generate the markdown documentation.` tdoc generate--folder./testfiles `### Run a local webserver to view your documentation.` tdoc serve `### Non Auto Generated Docs:To include custom markdown files simply create a folder calleddefault_docsand place any and all markdown files inside of it. This
directory will be copied over into thedocsfolder before any auto
generation.### Screenshot of Results using the Material Theme:![Screen Shot](imgs/screenshot.png?raw=true “Screen Shot”)### Installing As Editable:` pip install--editable. `
Package: tdotly
This is a python package for t.ly url shortener service. Developed byPriom Debwith supports from t.ly team.AcknowledgementThank yout.lyfor giving me the opportunity to make this python wrapper/library for t.ly url shortener service. I would like to give a special thank you toTim Lelandfrom t.ly to cooperate and help me for this project. This is a great honour for me to make this package for t.ly url shortener service.Install the packagepipinstalltdotlytdotly 1.0a1.dev1This is a developmental release of an alpha release. You can try it now.The package has built-in documentation of all its methods.Visit GitHub project page for more information.Documentationfromtdotlyimporttly# Create an instanceshort=tly.tly_shorturl()# Initialize with your API token from t.ly accountshort.initialize(user_api_token)MethodsDescriptionshort.create_short_url("https://example.com")Create a short url for a long urlshort.short_url_stats(short_url="https://t.ly/xxxx")Get the stats for the short urlshort.get_short_url_info(user_short_url)Get information of your short urlshort.edit_url_settings(**kwargs)Update/Edit some settings of your short urlshort.delete_short_url("t.ly/xxxx")Delete your short urlshort.expand("https://t.ly/xxxx")Expand your short url to see the original long url and the expired status of short urlMore documentation will updated soon.For any help contact the the package developerPriom Debor the t.lySupport.
Package: tdparser
tdparserThis library aims to provide an efficient way to write simple lexer/parsers in Python, using theTop-Down parsing algorithm.Code is maintained onGitHub, documentation is available onReadTheDocs.Other python libraries provide parsing/lexing tools (seehttp://nedbatchelder.com/text/python-parsers.htmlfor a few examples); distinctive features of tdparser are:Avoid docstring-based grammar definitionsProvide a generic parser structure, able to handle any grammarDon’t generate codeLet the user decide the nature of parsing results: abstract syntax tree, final expression, …ExampleHere is the definition for a simple arithmetic parser:import re

from tdparser import Lexer, Token

class Integer(Token):
    def __init__(self, text):
        self.value = int(text)

    def nud(self, context):
        """What the token evaluates to"""
        return self.value

class Addition(Token):
    lbp = 10  # Precedence

    def led(self, left, context):
        """Compute the value of this token when between two expressions."""
        # Fetch the expression to the right, stoping at the next boundary
        # of same precedence
        right_side = context.expression(self.lbp)
        return left + right_side

class Substraction(Token):
    lbp = 10  # Same precedence as addition

    def led(self, left, context):
        return left - context.expression(self.lbp)

    def nud(self, context):
        """When a '-' is present on the left of an expression."""
        # This means that we are returning the opposite of the next expression
        return - context.expression(self.lbp)

class Multiplication(Token):
    lbp = 20  # Higher precedence than addition/substraction

    def led(self, left, context):
        return left * context.expression(self.lbp)


lexer = Lexer(with_parens=True)
lexer.register_token(Integer, re.compile(r'\d+'))
lexer.register_token(Addition, re.compile(r'\+'))
lexer.register_token(Substraction, re.compile(r'-'))
lexer.register_token(Multiplication, re.compile(r'\*'))

def parse(text):
    return lexer.parse(text)Using it returns the expected value:>>> parse("1+1")
2
>>> parse("1 + -2 * 3")
-5Adding new tokens is straightforward:class Division(Token):
    lbp = 20  # Same precedence as Multiplication

    def led(self, left, context):
        return left // context.expression(self.lbp)

lexer.register_token(Division, re.compile(r'/'))And using it:>>> parse("3 + 12 / 3")
7Let’s add the exponentiation operator:class Power(Token):
    lbp = 30  # Higher than mult

    def led(self, left, context):
        # We pick expressions with a lower precedence, so that
        # 2 ** 3 ** 2 computes as 2 ** (3 ** 2)
        return left ** context.expression(self.lbp - 1)

lexer.register_token(Power, re.compile(r'\*\*'))And use it:>>> parse("2 ** 3 ** 2")
512
Package: tdp-core
tdp_coreTarget discovery platform for exploring rankings of genes, disease models, and other entities.Installationgitclone-bdevelophttps://github.com/datavisyn/tdp_core.git# or any other branch you want to develop incdtdp_core# Frontendyarninstall# Backendpython3-mvenv.venv# create a new virtual environmentsource.venv/bin/activate# active itmakedevelop# install all dependenciesLocal development# Frontendyarnstart# Backendpythontdp_coreTesting# Frontendyarnruntest# BackendmaketestBuildingyarn run buildThis repository is part of theTarget Discovery Platform(TDP). For tutorials, API docs, and more information about the build and deployment process, see thedocumentation page.
Package: tdp-dummy
tdp_dummyThis repository provides a SQLite database with dummy data and additional views for this specific dataset for TargID.Installationgit clone https://github.com/caleydo/tdp_dummy.git
cd tdp_dummy
npm installTestingnpm testBuildingnpm run buildThis repository is part ofPhovea, a platform for developing web-based visualization applications. For tutorials, API docs, and more information about the build and deployment process, see thedocumentation page.
Package: tdp-matomo
DEPRECATED: tdp_matomoMatomo tracking for TDP applications based on provenance graph commands.DEPRECATION InformationPlease note that this project has been archived and is no longer being maintained. There is an active development underhttps://github.com/datavisyn/tdp_coreand we will also contribute our future changes to it.ConfigurationThe tracking starts when a URL to a Matomo backend is set in theconfig.js.The site ID corresponds with the Matomo site.Enable themd5encryption of user names to prevent plaintext logging (e.g., when using Matomo with LDAP login){"matomo":{"url":"https://matomo.my-example-domain.com/",// matomo url with a trailing slash"site":"1","encryptUserName":false}}Provenance CommandsProvenance commands using the extension pointactionFunctionmust be annotated with the propertyanalyticsin order to be found and tracked.
Theanalyticsconfiguration property requires the propertiescategoryandactionfrom theIMatomoEvent(insrc/matomo.ts), which can contain arbitrary strings.registry.push('actionFunction','targidCreateView',function(){returnimport('./internal/cmds');},{factory:'createViewImpl',analytics:{category:'view',action:'create'}});Installationgit clone https://github.com/datavisyn/tdp_matomo.git
cd tdp_matomo
npm installTestingnpm testBuildingnpm run buildThis repository is part of theTarget Discovery Platform(TDP). For tutorials, API docs, and more information about the build and deployment process, see thedocumentation page.
Package: tdp-publicdb
tdp_publicdbThis repository contains the database connector to the bioinfoDB.hg38 database and the respective SQL queries to show the views and visualizations.Installationgit clone https://github.com/caleydo/tdp_publicdb.git
cd tdp_publicdb
npm installTestingnpm testBuildingnpm run buildThis repository is part ofPhovea, a platform for developing web-based visualization applications. For tutorials, API docs, and more information about the build and deployment process, see thedocumentation page.
Package: tdpt
TDPTTorrent downloading progress on TelegramFeaturesSupport for two most popular torrent clientsTransmission,rTorrentanddelugeMultithreading, each downloading item is handled separatelyRunning post download script in separate processSelf-adjustment ofTelegrambot limits based on number of torrents
trackedEasy configurationUploading new torrent - just send torrent file to chatInstallationYou need Python 3 to run this program.$ pip install --user tdptCreate configuration file$ cp tdpt.ini.template tdpt.iniEdit it and save.FAQTransmissionalready supports running script upon finishing downloadYes, that is true.  However the script thattransmissionwill run will
be executed in the same thread.  That means any long running process
would freeze it for that amount of time which is highly undesirable.tdptpicks up new items so slowCurrently it fetches new items every 20 seconds, because this operation
can be quite expensive.  I might add option to specify this interval
based on your preferences.I am downloading 20 items andtdptupdates them very rarelyTelegramputs limit of how often bot can make request to one channel.
Currently the limit is 20 updates per minute.tdptmakes time
adjustment based on number of torrents that it tracks to avoid hitting
limits.
Package: tdq
tdqTreasure Data Query shellInstallpip install tdqFeaturesA wrapper for td-client that focus on SQL query with following featuresbash-like history-list editing (e.g. Control-P scrolls back to the last command, Control-N forward to the next one, Control-F moves the cursor to the right non-destructively, Control-B moves the cursor to the left non-destructively, etc.).directly execute SQL to the remote TD endpointsupport multi-line queriessupport horizontal, vertical and CSV format ouputUsageStart the shell with default configurationtdqor start the shell with a specific databasetdq -d sample_databaseExit the shell byquitcommand or Ctrl-DSee all the command parameters:tdq --helpRun the shell with predefined sql queries and write the result ot a CSV filetdq -f input.sql -o output.csv --output-format CSV_HEADERBesides valid commands, all user's inputs are considered SQL queries.Currently, below commands are supported:use  : change current database. This could be set by -d option or read from default TD client config filedisplay : change current display mode. Value is amonghorizontal,verticalorNone(auto)quit: quit the shell (same with Ctrl-D)Use-hto see all optionsConfigurationtdq will utilize the file ~/.td/td.conf created by td-client for default configurationFor example, a typical td.conf looks like below:[account]
  apikey = <apikey>
  endpoint = https://api.treasuredata.co.jp/
  database = <default database>Alternately, apikey and endpoint could be defined by environmental variablesTD_API_KEYandTD_SERVEREndpoint also could be defined by-eoption from command line.Otherseeherefor details about Treasure Data Python client
Package: tdr-convert
IntroductionThis utility provides TDR file format conversion to devsim, Gmsh, or Tecplot file formatpip install tdr-convert
tdr_convert --tdr file.tdr --devsim file.msh --drop_interfaces_at_contact --scale 1e-4

tdr_convert --help

usage: tdr_convert [-h] --tdr TDR [--load_datasets] [--tecplot TECPLOT] [--devsim DEVSIM] [--gmsh GMSH] [--gmsh_import GMSH_IMPORT]
                   [--device_name DEVICE_NAME] [--scale SCALE] [--drop_interfaces_at_contact] [--tetgen TETGEN] [--exodus EXODUS]
                   [--vtk VTK] [--old]

Create mesh from tdr file

options:
  -h, --help            show this help message and exit
  --tdr TDR             the tdr file to input
  --load_datasets       write data sets
  --tecplot TECPLOT     the tecplot file to output
  --devsim DEVSIM       the devsim file to output
  --gmsh GMSH           the gmsh file to output
  --gmsh_import GMSH_IMPORT
                        the file to write the devsim commands to recreate a new gmsh device
  --device_name DEVICE_NAME
                        the device name
  --scale SCALE         coordinate scaling factor
  --drop_interfaces_at_contact
                        drop interfaces from nodes at contact
  --tetgen TETGEN       the base name for tetgen files to output
  --exodus EXODUS       name of the exodus output file
  --vtk VTK             basename for vtk output file
  --old                 use old method for getting data using devsimMesh RequirementsRequires triangular device simulation mesh in 2D.  A tetrahedral mesh is required in 3D.  Mixed elements are not supported.Known IssuesTheexodusexporter loses data at interfaces when a variable has different values in different regions.Vector data will name its fields with a suffix for the index.E_0,E_1,E_2Program does not currently support multiple time steps.
Package: tdry
tdryThis repo was forked from:https://github.com/pimutils/todomanChanges made byrooyca1. Shorter Commandscancel: cc
copy: cp
delete: rm
done: do
edit: ed
flush: fl
list: ls
move: mv
new: nw
show: sh2. Add more color to the output.3. The defaultduedate is nownever(0).4. Addpercentselector in the edit command.5. Add LISTS commands:--newlistor-nlto create a new list.--removelistor-rmlto delete a list.--listsor-slto show all lists.6. Adddoingcommand to focus on a especific task.doingalone shows the current task.doing <task>add the task to the doing list.doing --allordoing -ashows all tasks in the doing list.7. Adddonecommand to mark as complete the task that is currently being done.donealone marks the current task as complete.done --showordone -sshows all completed tasks.done --clearordone -cclears all completed tasks.8. Addcancelcommand to cancel the task that is currently being done.9. Addpausecommand to pause the task that is currently being done.10. Addresumecommand to resume the task that is currently paused.BonusI have created an alias to make the commands even shorter.alias t='todo'TODOCreate a Docker image to run the application.