Saravanan666/pypi-org huggingface dataset:
Package: tabchen-kt
paper finderFind papers by keywords and venues. Then download it automatically.InstallingInstall and update usingpip:pipinstall-Upaper-finderExamplesSearchfrompaper_finder.apiimportsearchkeyword_list=['knowledge tracing','knowledge trace']venue_list=['KDD','IJCAI']output='kt_result.csv'search(keyword_list=keyword_list,venue_list=venue_list,min_year=2016,max_year=2021,output=output)Your can find venues' name inthere.Downloadimportpandasaspdfrompaper_finder.apiimportdownload_from_dfcsv_path="kt_result.csv"df=pd.read_csv(csv_path)df=download_from_df(df,save_dir='pdfs')df.to_csv(csv_path.replace('.csv','_download_result.csv'),index=False)TodoSearch papers.Download papersAuthor WarningThis code is only used for academic communication.
The author has no liability for copyright.
DO NOT ENGAGE IN ANY ILLEGAL ACTIVITIES.Please download and read the genuine articles from the publisher.
Package: tabcompleter
tabcompleter (📃)tabcompleteris a friendly fork of the (unmaintained)fancycompleterpackage.tabcompleterlets you use theTabkey to expand and autocomplete options in the Python console.Installation:pipinstalltabcompleterUsage:importtabcompletertabcompleter.interact(persist_history=True)# Now use the Tab key in the Python consoleAn example of using theTabkey to see all possibilities:More examples:tabcompleteris used by packages such aspdbpandseleniumbase:https://pypi.org/project/pdbp/https://github.com/mdmintz/pdbphttps://pypi.org/project/seleniumbase/https://github.com/seleniumbase/SeleniumBase(tabcompleteris maintained by theSeleniumBase Dev Team)
Package: tabdanc
TABDANC (Table Data Sync)Tabdanc is a library that maintain and manage latest data.Main Feature compares the .csv data stored in the database with the .csv file in local repository and if they are different, update the table with the latest data. (In this case, the latest data is the data in local repository)Local repository must exist files, .csv, .meta, .td.(If any of the three files is not exist, it will not be updated).csv: .csv file is the data file you want to maintain and manage..meta: .meta file is a json file in which the table name where the csv should be saved is written..meta file name must be the same as the .csv file namecolumn_matchis an optional value.
Setcolumn_matchwhen csv header and table column are different.An error occurs if thecsv_headeris not in the .csv file or thetable_columnis not in the .td file.{"table_name":"table_name","column_match":{"csv_header":"table_column",...}}.td: .td file is a json file in which table schema definitions(column name, coulmn type) are written..td file name must be the same as the table name{"columns":[{"name":"column_name1","type":"int4"},{"name":"column_name2","type":"varchar(255)"},...]}There is one .td file per table, and multiple .csv files can be entered in one table. In this case, .meta files are created as many as the number of .csv files, and one .td file is created.Additional Feature is that data files can be uploaded and downloaded by ssh connection between local repository and remote repository.Getting StartedBuilt WithPython >= 3.8Installation$pipinstalltabdancUsageCommand Help# help tabdanc command$tabdanc-hConfig SettingsFirst, you need to set config to use tabdanc# help$tabdancconfig-h# create config file$tabdancconfig--create# show config information$tabdancconfig--list# update config file$tabdancconfig--update{section.option}{value}Table UpdateYou can use the update command to add the csv file to your database.If the csv file stored in the database is changed, the changed csv file is updated to the database using the update command.# help$tabdancupdate-h# update table$tabdancupdateFile Upload / DownloadWhen upload or download through the '-f' option, enter only the file name without the extension.When enter upload or download command, files related to the file name are upload or download. ex) .csv .meta .tdUploadIf you use the upload command, you can upload files from the local repository to the remote repository.# help$tabdancupload-h# upload all files$tabdancupload-a# upload one file$tabdancupload-ffile_name# upload multiple files$tabdancupload-ffile_name1file_name2DownloadIf you use the download command, you can download files from the remote repository to the local repository.# help$tabdancdownload-h# download all files$tabdancdownload-a# download one file$tabdancdownload-ffile_name# download multiple files$tabdancdownload-ffile_name1file_name2ContactChae JungWoo -jungwoo@linewalks.comLee Yuna -una944@linewalks.comChoi Insu -insu@linewalks.com
Package: tabdance
TABDANCE (Table Data Syncer)Tabdance is a library that maintain and manage latest data.Main Feature compares the .csv data stored in the database with the .csv file in local repository and if they are different, update the table with the latest data. (In this case, the latest data is the data in local repository)Local repository must exist files, .csv, .meta, .td.(If any of the three files is not exist, it will not be updated).csv: .csv file is the data file you want to maintain and manage..meta: .meta file is a json file in which the table name where the csv should be saved is written..meta file name must be the same as the .csv file namecolumn_matchis an optional value.
Setcolumn_matchwhen csv header and table column are different.An error occurs if thecsv_headeris not in the .csv file or thetable_columnis not in the .td file.{"table_name":"table_name","column_match":{"csv_header":"table_column",...}}.td: .td file is a json file in which table schema definitions(column name, coulmn type) are written..td file name must be the same as the table name{"columns":[{"name":"column_name1","type":"int4","primary_key":true},{"name":"column_name2","type":"varchar(255)","primary_key":false// same as not declared primary_key},...]}There is one .td file per table, and multiple .csv files can be entered in one table. In this case, .meta files are created as many as the number of .csv files, and one .td file is created.Additional Feature is that data files can be uploaded and downloaded by ssh connection between local repository and remote repository.Getting StartedBuilt WithPython >= 3.8Installation$pipinstalltabdanceUsageCommand Help# help tabdance command$tabdance-hConfig SettingsFirst, you need to set config to use tabdance# help$tabdanceconfig-h# create config file$tabdanceconfig--create# show config information$tabdanceconfig--list# update config file$tabdanceconfig--update{section.option}{value}Table UpdateYou can use the update command to add the csv file to your database.If the csv file stored in the database is changed, the changed csv file is updated to the database using the update command.# help$tabdanceupdate-h# update table$tabdanceupdateFile Upload / DownloadWhen upload or download through the '-f' option, enter only the file name without the extension.When enter upload or download command, files related to the file name are upload or download. ex) .csv .meta .tdUploadIf you use the upload command, you can upload files from the local repository to the remote repository.# help$tabdanceupload-h# upload all files$tabdanceupload-a# upload one file$tabdanceupload-ffile_name# upload multiple files$tabdanceupload-ffile_name1file_name2DownloadIf you use the download command, you can download files from the remote repository to the local repository.# help$tabdancedownload-h# download all files$tabdancedownload-a# download one file$tabdancedownload-ffile_name# download multiple files$tabdancedownload-ffile_name1file_name2ContactChae JungWoo -jungwoo@linewalks.comLee Yuna -una944@linewalks.comChoi Insu -insu@linewalks.com
Package: tabdeal-python
Tabdeal API Python SDKOfficial python package to useTabdeal ExchangeAPIInstallationpipinstalltabdeal-pythonDocumentationhttps://docs.tabdeal.orgPostman CollectionRESTful APIsUsage examples:fromtabdeal.enumsimportOrderSides,OrderTypesfromtabdeal.spotimportSpotapi_key='<api_key>'api_secret='<api_secret>'client=Spot(api_key,api_secret)order=client.new_order(symbol='BTC_IRT',side=OrderSides.BUY,type=OrderTypes.MARKET,quantity="0.002")print(order)ExceptionThere are 2 types of exceptions returned from the library:tabdeal.exceptions.ClientExceptionThis is thrown when server returns4XX, it's an issue from client side.It has 4 properties:status- HTTP status codecode- Server's error codemessage- Server's error messagedetail- Detail of exceptiontabdeal.exceptions.ServerExceptionThis is thrown when server returns5XX, it's an issue from server side.
Package: tabeline
TabelineTabeline is a data frame and data grammar library. You write the expressions in strings and supply them to methods on theDataFrameclass. The strings are parsed by Parsita and converted into Polars for execution.Tabeline draws inspiration from dplyr, the data grammar of R's tidyverse, especially for its methods names. Thefilter,mutate,group_by, andsummarizemethods should all feel familiar. But Tabeline is as proper a Python library as can be, using methods instead of pipes, like is standard in R.Tabeline uses Polars under the hood, but adds a lot of handling of edge cases from Polars, which otherwise result in crashes or behavior that is not type stable.See theDocumentationfor the full user guide.InstallationIt is recommended to install Tabeline from PyPI usingpip.pipinstalltabelineMotivating examplefromtabelineimportDataFrame# Construct a data frame using clean syntax# from_csv, from_pandas, and from_polars are also availabledf=DataFrame(id=[0,0,0,0,1,1,1,1,1],t=[0,6,12,24,0,6,12,24,48],y=[0,2,3,1,0,4,3,2,1],)# Use data grammar methods and string expressions to define# transformed data framesanalysis=(df.filter("t <= 24").group_by("id").summarize(auc="trapz(t, y)"))print(analysis)# shape: (2, 2)# ┌─────┬──────┐# │ id  ┆ auc  │# │ --- ┆ ---  │# │ i64 ┆ f64  │# ╞═════╪══════╡# │ 0   ┆ 45.0 │# ├╌╌╌╌╌┼╌╌╌╌╌╌┤# │ 1   ┆ 63.0 │# └─────┴──────┘
Package: tabella
TabellaOpen-RPC development framework with builtin interactive documentation.Live DemoA live demo is availablehere.InstallTabella is on PyPI and can be installed with:pipinstalltabellaOr withPoetrypoetryaddtabellaPython OpenRPC DocsThe RPC server hosted and documented by Tabella is powered
byPython OpenRPC. Refer to the Python OpenRPC
docs hostedherefor advanced use.Getting StartedA basic Tabella app:fromtabellaimportTabellaapp=Tabella()@app.method()defecho(a:str,b:float)->tuple[str,float]:"""Echo parameters back in result."""returna,bif__name__=="__main__":app.run()Run this, then openhttp://127.0.0.1:8000/in your browser to use the interactive
documentation.The Open-RPC API will be hosted over HTTP onhttp://127.0.0.1:8000/apiand over
WebSockets onws://127.0.0.1:8000/api.Further UsageRoutersAn app with many modules can be organized into segments
usingMethod Routers.Security and Depends ArgumentsTabella passes request headers to the RPCServer process request methods. Details on
usage can be found in the Python OpenRPC docs onDepends Arguments.Set ServersSet RPC servers manually to specify transport and paths to host the RPC server on, e.g.fromopenrpcimportServerfromtabellaimportTabellaapp=Tabella(servers=[Server(name="HTTP API",url="http://localhost:8000/my/api/path"),Server(name="WebSocket API",url="ws://localhost:8000/my/api/path"),])This app will host the RPCServer over HTTP and over WebSockets with the
path/my/api/path.PydanticPydanticis used for request/response
deserialization/serialization as well as schema generation. Pydantic should be used for
any models as seen here in
thePython OpenRPC Docs.StarletteTabella HTTP and WebSocket server hosting usesStarlette.Uvicorncan be used to run the starlette app.uvicornmain:app.starlette--reloadMonitorIf you are running the app with in debug mode, e.g.app = Tabella(debug=True), then at
the path/monitorthere is a display that will show requests and responses made to the
RPC server as they happen.Inspired ByOPEN-RPC PlaygroundSwaggerRedocSupport The Developer
Package: tabelog-robot
kakaku_robotKakaku lobot is a scraping library forhttps://kakaku.com/InstallationUse the package managerpipto install foobar.pipinstallkakaku_robotUsagefromkakaku_robot.site.rankingimportRankingresult=Ranking().ranking.all_category_ranking(pandas=True)result.to_csv("kakau_rank.csv")ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: tabfix
Copyright (c) 2010, 2013 Martin WendtNoteThe command line options have changed since release 0.1.x.
Read [CHANGES.md](https://github.com/mar10/tabfix/blob/master/CHANGES.md) for details.
Make sure that you check your existing shell scripts when you update!StatusThis project has beta status: use at your own risk!Seehttps://github.com/mar10/tabfixfor detailsChangesSeeCHANGES.md.
Package: tabgeo
OverviewTabGeo - a special geolocation database to determine country of the user according to his IP-address.
Due to the unique architecture of the database and the binary format, TabGeo performs 2-4 times faster on real projects than similar free alternativesTabGeo - the best solution for the IP-geolocation live.This module based on origial PHP version fromhttp://tabgeo.comThis python implementation licensed underGNU Affero General Public License v3.0, available fromPyPI, the source code can be found onGitHub.In case of issues please open ticket herehttps://github.com/nimda7/tabgeo/issuesInstallationThrough PyPI:$ pip install tabgeoUsage:Example usage:>>> from tabgeo import getbyip
>>> print getbyip('8.8.4.4')
US
Package: ta-bitwarden-cli
Thoughtful Automation BitWarden CLI installation packageInstallationFor correct work please use python virtualenv approach!
Also use–no-cache-diroption.
Otherwise it would cache package wheel and wont downloadbwCLI binary anymorepython3 -m virtualenv venv
source venv/bin/activate
pip install --no-cache-dir ta-bitwarden-cliCode above will additionally installbwCLI binary to a first available folder in the $PATHExample Usageimportosfromta_bitwarden_cliimportta_bitwarden_cliastabitwarden_credentials={"password":os.getenv("BW_PASSWORD"),"client_id":os.getenv("BW_CLIENTID"),"client_secret":os.getenv("BW_CLIENTSECRET"),}creds={"my_vault_item":"Google Maps API Key",}bw=ta.Bitwarden(bitwarden_credentials)assertbw.get_credentials(creds)["my_vault_item"]["password"]=="XXXXXXX"TroubleshootingIf you use Windows during code execution you could face with something like:FileNotFoundError: [WinError 2] The system cannot find the file specifiedThis means that no binary is available. In that case please manually download BitWarden CLI binary fromhttps://vault.bitwarden.com/download/?app=cli&platform=windowsand put it to any folder from $PATH. This approach is similar to chromedriverDevelopment1. Prepare local dev envpython3 -m virtualenv venv
source venv/bin/activate
pip install -r requirements.txt
pre-commit install2. TestBW_PASSWORD=YYY BW_CLIENTID=XXX BW_CLIENTSECRET=ZZZ pytest3. Commit your code using https://www.conventionalcommits.org/en/v1.0.0/ style commit messages4. Submit PR
Package: tabkit
A CLI TSV MR kit (a command-line interface tab-separated values map-reduce kit).
Powered by coreutils.Overview$ cat fruits | tpretty

 fruit   | price:float
---------+-------------
 apple   | 1.04
 kumquat | 4.99
 orange  | 2.07

$ cat sales | tpretty

 fruit   | qty:int | paid:bool
---------+---------+-----------
 apple   | 10      | 1
 apple   | 7       | 0
 apple   | 1       | 1
 orange  | 3       | 1
 orange  | 18      | 1
 orange  | 4       | 0
 orange  | 2       | 1
 kumquat | 1       | 1
 kumquat | 2       | 1

$ cat sales \
        | tmap_awk -f paid \
        | tsrt -k fruit \
        | tjoin -j fruit - fruits \
        | tgrp_awk -g fruit -o "sum_qty=sum(qty)" -o "sum_paid=sum(qty*price)" \
        | tpretty

 fruit   | sum_qty:int | sum_paid:float
---------+-------------+----------------
 apple   | 11          | 11.44
 kumquat | 3           | 14.97
 orange  | 23          | 47.61tcatConcatenate FILE(s), or standard input, to standard output.1.tsv:# apples    oranges
1   foo
2   bar2.tsv:# apples    oranges
3   baz
4   bam$ tcat 1.tsv 2.tsv
# apples    oranges
1   foo
2   bar
3   baz
4   bamtcutPrint selected columns from each FILE to standard output.input.csv:# good  bad also_good
1   apple   foo
2   orange  bar
3   lemon   baz$ cat input.csv | tcut -f good,also_good
#   good    also_good
1   foo
2   bar
3   baztsrtWrite sorted concatenation of all FILE(s) to standard output.input.csv:# number    fruit
10  apple
3   orange
10  lemon$ cat input.csv | tsrt -k good:num,fruit:desc
# number    fruit   # ORDER: number:num, fruit:desc
3   orange
10  lemon
10  appletmap_awkPerform a map operation on the input FILE(s).input.csv:# x
.1
4
-0.5
0$ cat input.csv | tmap_awk -f 'x>0' -o 'y=log(x)'
# y:float
-2.30259
1.38629
Package: tabkit3
This is fork from original tabkit project (https://github.com/andreifyodorov/tabkit) whith Python 3
supportA CLI TSV MR kit (a command-line interface tab-separated values map-reduce kit).
Powered by coreutils.Overview$ cat fruits | tpretty

 fruit   | price:float
---------+-------------
 apple   | 1.04
 kumquat | 4.99
 orange  | 2.07

$ cat sales | tpretty

 fruit   | qty:int | paid:bool
---------+---------+-----------
 apple   | 10      | 1
 apple   | 7       | 0
 apple   | 1       | 1
 orange  | 3       | 1
 orange  | 18      | 1
 orange  | 4       | 0
 orange  | 2       | 1
 kumquat | 1       | 1
 kumquat | 2       | 1

$ cat sales \
        | tmap_awk -f paid \
        | tsrt -k fruit \
        | tjoin -j fruit - fruits \
        | tgrp_awk -g fruit -o "sum_qty=sum(qty)" -o "sum_paid=sum(qty*price)" \
        | tpretty

 fruit   | sum_qty:int | sum_paid:float
---------+-------------+----------------
 apple   | 11          | 11.44
 kumquat | 3           | 14.97
 orange  | 23          | 47.61tcatConcatenate FILE(s), or standard input, to standard output.1.tsv:# apples    oranges
1   foo
2   bar2.tsv:# apples    oranges
3   baz
4   bam$ tcat 1.tsv 2.tsv
# apples    oranges
1   foo
2   bar
3   baz
4   bamtcutPrint selected columns from each FILE to standard output.input.csv:# good  bad also_good
1   apple   foo
2   orange  bar
3   lemon   baz$ cat input.csv | tcut -f good,also_good
#   good    also_good
1   foo
2   bar
3   baztsrtWrite sorted concatenation of all FILE(s) to standard output.input.csv:# number    fruit
10  apple
3   orange
10  lemon$ cat input.csv | tsrt -k good:num,fruit:desc
# number    fruit   # ORDER: number:num, fruit:desc
3   orange
10  lemon
10  appletmap_awkPerform a map operation on the input FILE(s).input.csv:# x
.1
4
-0.5
0$ cat input.csv | tmap_awk -f 'x>0' -o 'y=log(x)'
# y:float
-2.30259
1.38629
Package: tabla
tablaGenerate LaTeX tables in Python from your data in apandas.DataFrame.ExampleAll you need is a dataframe you'd like to create a table for, and a list ofTableColumns for each column in the dataframe you would like to include in
your table.importpandasaspdfromtablaimportTableColumn,Tablecolumns=[TableColumn("date","","%Y-%m-%d","Date"),TableColumn("temp","(degrees)","{:0.2}","Temperature"),TableColumn("rate",r"(m day\textsuperscript{-1})","{:04.3}","Rate"),]dates=pd.date_range("2020-01-01","2020-01-02",freq="6H")data=list()fordateindates:d={"date":date}d.update({c:pd.np.random.random()forcin["temp","rate"]})data.append(d)df=pd.DataFrame(data)table=Table("test_name",columns,dataframe,header_units=True)# Generate as a stringlatex_str=table.dumps()
Package: table
Some of the capabilities of the table library are shown below:from table import Table

table = Table(
    ["1", "2", "3"] # row names,
    ["a", "b"]      # column names,
    [[1, 2],        # initial values
     [3, 4],
     [5, 6]]
)

print "Whole table:"
print table

print "Just a cell:"
print table["1", "a"]

print "A row:"
print table["2", :]

print "A column:"
print table[:, "b"]

print "A range:"
print table["2":, :]The library also provides basic I/O capability for simple delimited files and standard CSV files:table1 = readTableFromDelimited(f)
table2 = readTableFromCSV(f)
Package: table2csv
Simple script for downloading html tables as csv.Installationpipinstall-Utable2csvUsagetable2csvhttp://en.wikipedia.org/wiki/List_of_Super_Bowl_champions>dump.txtFeaturesaccepts a URLIdentifies all the tablesMerges tables that share same structure (e.g. same column headers get
merged)Figures out which table is the biggestextracts textextracts linksTODOadd the ability to specify which table on the page you would like to
download (not just the biggest one)add support for columns that do not use proper<th>tags [DONE]
tags for headers (i.e. imperfect html tables)]detect the data types found within each columnadd support for tables with hierarchical indices on the rows and/or
columnsView on Github
Package: table2dicts
table2dictsPython module for converting a html table to a list of dictionaries.InstallationInstalling from PyPI usingpip:$pipinstalltable2dictsInstalling from source:$pythonsetup.pyinstallUsageGive it some html with atable:>>> table2dicts('''
...    <table>
...         <thead>
...             <tr><th>a</th><th>b</th><th>c</th></tr>
...         </thead>
...         <tbody>
...             <tr><td>1</td><td>2</td><td>3</td></tr>
...             <tr><td>4</td><td>5</td><td>6</td></tr>
...         </tbody>
...    </table>
... ''')
[OrderedDict([('a', '1'), ('b', '2'), ('c', '3')]), OrderedDict([('a', '4'), ('b', '5'), ('c', '6')])]Notheadortbody, no problem:>>> table2dicts('''
...    <table>
...        <tr><th>a</th><th>b</th><th>c</th></tr>
...        <tr><td>1</td><td>2</td><td>3</td></tr>
...        <tr><td>4</td><td>5</td><td>6</td></tr>
...    </table>
... ''')
[OrderedDict([('a', '1'), ('b', '2'), ('c', '3')]), OrderedDict([('a', '4'), ('b', '5'), ('c', '6')])]When nothis present, the first row oftdelements is used as a header:>>> table2dicts('''
...    <table>
...        <tr><td>a</td><td>b</td><td>c</td></tr>
...        <tr><td>1</td><td>2</td><td>3</td></tr>
...        <tr><td>4</td><td>5</td><td>6</td></tr>
...    </table>
... ''')
[OrderedDict([('a', '1'), ('b', '2'), ('c', '3')]), OrderedDict([('a', '4'), ('b', '5'), ('c', '6')])]
Package: table2sql
table2sqlPython CLI tool which allows you to convert file with table (CSV and Excel) to SQL insert statements.DocsBasic usagesome.csva,b,c,d
int,str,float,sql
1,2,3,(SELECT id FROM another.table WHERE name = 'Paul')
5,6,7,(SELECT id FROM another.table WHERE name = 'Paul')Command:table2sqlsome.csv--output-tablesome.table--has-types-rowResult:INSERTINTOsome.table(a,b,c,d)VALUES(1,'2',3.0,(SELECTidFROManother.tableWHEREname='Paul')),(5,'6',7.0,(SELECTidFROManother.tableWHEREname='Paul'));Installpipinstalltable2sql