Saravanan666/pypi-org huggingface dataset:
Package: uetl
uETLMinimalist python ETL library.InstalationpipinstalluetlUsageDataWarehouse objectimportuetlimportpandasaspdDWO=uetl.DataWarehouse(name='My DataWarehouse',dbms='postgres',host='192.168.1.1',port='5432',base='db-name',user='foo',pswd='bar')# Test dw db connectionifDWO.test_conn():print('Data Warehouse DB connection succeed!')else:print('ERROR: Data Warehouse DB failed!')exit(-1)# Query the DWdf=DWO.query("SELECT * FROM DIM_DATE")print(df.head())DataSrc objectMS SQL Source Objectimportuetlimportpandasaspdhost='192.168.1.1'port=49159base='dbname'user='username'pswd='password'## 1st example - Using 'with' statement# Create Engine, perform query and dispose enginewithuetl.MssqlSrc('testdb',host,port,base,user,pswd)asSRC:print(pd.read_sql('select @@version',SRC.engine))## 2nd example - Create and dispose sqlalchemy enginedb=uetl.MssqlSrc('testdb',host,port,base,user,pswd)db.create_engine()print(pd.read_sql('select @@version',db.engine))db.dispose()## 3rd example - Use MssqlSrc.query()db=uetl.MssqlSrc('testdb',host,port,base,user,pswd)print(db.query('select @@version'))Firebird Source Objectimportuetlimportpandasaspdhost='192.168.1.1'port=3050base='/path/to/database.fdb'user='sysdba'pswd='masterkey'chst='latin1'## 1st example - Using 'with' statementwithuetl.FirebirdSrc('testdb',host,port,base,user,pswd)asSRC:print(pd.read_sql('SELECT * from rdb$database;',SRC.engine))## 2nd example - Create and dispose sqlalchemy enginedb=uetl.FirebirdSrc('testdb',host,port,base,user,pswd)db.create_engine()print(pd.read_sql('SELECT * from rdb$database;',db.engine))## 3rd example - Use MssqlSrc.query()db=uetl.FirebirdSrc('testdb',host,port,base,user,pswd)print(db.query('SELECT * from rdb$database;'))ContributingTo install this package allong with the tools you need to develop and run tests, run the following in your virtualenv:pipinstall-e.[dev]Also, it is necessary to install local libraries:$sudoapt-getinstalllibpq-devMSSql ODBC DriverIssuesIf you have any problems with or questions about this image, please contact me through aGitHub issue.
Package: uf3
S. R. Xie, M. Rupp, and R. G. Hennig, “Ultra-fast interpretable machine-learning potentials”, preprintarXiv:2110.00624(2021).All-atom dynamics simulations have become an indispensable quantitative
tool in physics, chemistry, and materials science, but large systems and
long simulation times remain challenging due to the trade-off between
computational efficiency and predictive accuracy. The UF3 framework is
built to address this challenge by combinining effective two- and
three-body potentials in a cubic B-spline basis with regularized linear
regression to obtain machine-learning potentials that are physically
interpretable, sufficiently accurate for applications, and as fast as
the fastest traditional empirical potentials.Documentation:https://uf3.readthedocs.io/This repository is still under construction. Please feel free to open
new issues for feature requests and bug reports.SetupUF3 can be installed in two different ways:Download and install automatically from PyPI (recommended):pipinstalluf3Download and install manually from GitHub:gitclonehttps://github.com/uf3/uf3.gitcduf3pipinstall.Getting StartedPlease see the examples in uf3/examples/tungsten_extxyz for basic usage.Overviews for individual modules can be found in uf3/examples/modules
(WIP).Standalone scripts and configuration generators/parsers are in
development.Optional DependenciesElastic constants:pip install setuptools_scm
pip install uf3[elastic_constants]Phonon spectra:pip install uf3[phonon_spectra]LAMMPS interface:conda install numpy==1.20.3 --force-reinstall
conda install -c conda-forge lammps --no-update-depsThe environment variable$ASE_LAMMPSRUN_COMMANDmust also be set to use the LAMMPS interface within python. See theASE documentationfor details.DependenciesWe rely on ase to handle parsing outputs from atomistic codes like
LAMMPS, VASP, and CP2K.We use Pandas to keep track of atomic configurations and their
energies/forces as well as organizing data for featurization and
training.B-spline evaluations use scipy, numba, and ndsplines.PyTables is used for reading/writing HDF5 files.Matplotlib is used for plotting.We use sklearn for regression.We use tqdm for progress bars.We use plotly for interactive plots.We use PyYaml for configuration files.We use numpy for array operations.
Package: ufal.chu-liu-edmonds
Chu-Liu-Edmonds Algorithm from TurpoParser.This package wraps the Chu-Liu-Edmonds maximum spanning algorithm from
TurboParser for use within Python.The original package was made byhttps://github.com/andersjo/dependency_decoding.DocumentationThe package provides a functionchu_liu_edmondswhich accepts aN×Nscore
matrix as argument, whereNis the sentence length, including the artificial
root node. The(i,j)-th cell is the score for the edgej→i.
In other words, a row gives the scores for the different heads of a dependent.Anp.nancell value informs the algorithm to skip the edge.Example usage:importnumpyasnpfromufal.chu_liu_edmondsimportchu_liu_edmondsnp.random.seed(42)score_matrix=np.random.rand(3,4)heads,tree_score=chu_liu_edmonds(score_matrix)print(heads,tree_score)InstallBinary wheels of the package are provided, just runpip install ufal.chu_liu_edmondsUpdating the Cython-generated ModuleTo update the Cython-generated module, runcython --module-name ufal.chu_liu_edmonds._chu_liu_edmonds chu_liu_edmonds.pyx -o chu_liu_edmonds.cpp
Package: ufc-api
UFC APIUFC API is a lightweight web crawler built in Python to retrieve data on UFC fighters and events.InstallationYou can install UFC API using pip:pip install ufc_apiUsageUsage is simple. To get stats on a particular fighter returned as a json:>>> from ufc-api import get_fighter

>>> get_fighter('Jon Jones')

>>> {'name': 'Jon Jones',
 'nickname': 'Bones',
 'nationality': 'United States',
 'birthplace': 'Rochester, New York',
 'birthdate': 'Jul 19, 1987',
 'age': '35',
 'height': '6\'4"',
 'weight': '248 lbs',
 'association': 'Jackson-Wink MMA',
 'weight_class': 'Heavyweight',
 'wins': {'total': '27',
  'ko/tko': '10',
  'submissions': '7',
  'decisions': '10',
  'others': '0'},
 'losses': {'total': '1',
  'ko/tko': '0',
  'submissions': '0',
  'decisions': '0',
  'others': '1'},
 'fights': [{'name': 'UFC 285 - Jones vs. Gane',
   'date': 'Mar / 04 / 2023',
   'url': 'https://www.sherdog.com/events/UFC-285-Jones-vs-Gane-95232',
   'result': 'win',
   'method': 'Submission (Guillotine Choke)',
   'referee': 'Marc Goddard',
   'round': '1',
   'time': '2:04',
   'opponent': 'Ciryl Gane'},
   ...To get data on an event, the usage is similar:>>> from ufc-api import get_event

>>> get_event('UFC 280')

>>> {'name': 'UFC 280: Oliveira vs. Makhachev',
 'date': '2022-10-22',
 'location': 'Yas Island/Yas West United Arab Emirates',
 'venue': 'Etihad Arena',
 'fights': [{'weightclass': 'Lightweight Title',
   'red corner': {'name': 'Charles Oliveira',
    'ranking': 'Unranked',
    'odds': '+165',
    'link': 'https://www.ufc.com/athlete/charles-oliveira',
    'result': 'Loss'},
   'blue corner': {'name': 'Islam Makhachev',
    'ranking': 'Unranked',
    'odds': '-195',
    'link': 'https://www.ufc.com/athlete/islam-makhachev',
    'result': 'Win'},
   'round': '2',
   'time': '3:16',
   'method': 'Submission'},
  {'weightclass': 'Bantamweight Title',
   'red corner': {'name': 'Aljamain Sterling',
    'ranking': 'Unranked',
    'odds': '-175',
    'link': 'https://www.ufc.com/athlete/aljamain-sterling',
    'result': 'Win'},
   'blue corner': {'name': 'TJ Dillashaw',
    'ranking': 'Unranked',
    'odds': '+150',
    'link': 'https://www.ufc.com/athlete/tj-dillashaw',
    'result': 'Loss'},
   'round': '2',
   'time': '3:44',
   'method': 'KO/TKO'},
  {'weightclass': 'Bantamweight',
   'red corner': {'name': 'Petr Yan',
    'ranking': 'Unranked',
    'odds': '-275',
    'link': 'https://www.ufc.com/athlete/petr-yan',
    'result': 'Loss'},
   'blue corner': {'name': "Sean O'Malley",
    'ranking': 'Unranked',
    'odds': '+230',
    'link': 'https://www.ufc.com/athlete/sean-omalley',
    'result': 'Win'},
   'round': '3',
   'time': '5:00',
   'method': 'Decision - Split'},
   ...
Package: ufc-fighter-jung-chansung
ufc-fighter-jung-chansunguse$pipinstallufc-fighter-jung-chansung

$python
Python3.7.13(default,Jul132022,10:21:28)[Clang13.0.0(clang-1300.0.29.30)]ondarwin
Type"help","copyright","credits"or"license"formoreinformation.
>>>fromufc_fighter_jung_chansung.lastdanceimportjung
>>>jung()^^^^^^^^^^^^^^^^^^^^^::^~777~^::^^^^^^^^^^^^^^^^^^
^^^^^^^^^^^^^^^^^^^:^!YPGBBBBP?^:^^^^^^^^^^^^^^^^^
^^^^^^^^^^^^^^^^^^:~5##BBGB####GJ^^^^^^^^^^^^^^^^^
^^^^^^^^^^^^^^^^^^:5#BBBGBB##B55B!:^^^^^^^^^^^^^^^
^^^^^^^^^^^^^^^^^:^GP?7777???777P?:^^^^^^^^^^^^^^^
^^^^^^^^^^^^^^^^^:~J5J?77!!!!7?JJ7^^^^^^^^^^^^^^^^
^^^^^^^^^^^^^^^^^:!?!?YY5Y??Y55Y?Y~:^^^^^^^^^^^^^^
^^^^^^^^^^^^^^::::^7~???JJ77JJJJ7~::^^^^^^^^^^^^^^
^^^^^^^^^^^^^::::::^~JJ?7777??JY~:::^^^^^^^^^^^^^^
^^^^^^^^:^^:::::::::!YYJ?JJYYYYJ^:::::^^^^^^^^^^^^
^^^^^:^::::::::::^^!?Y5YJJJY55?^:^^^:::::^^^^^^^^^
^^^:::::::::^^!JYY?77?Y55YY5YY555PJ!~^:::::^^^^^^^
^^::::::::^^!77?PGBP?!?J5PPP55##BG?~J~::::::^^^^^^
::::::::^~~~JG?YJ5G#G!!!?5PP55#BBGGPP5~:::::^^^^^^
:::::::^!!~~PBB#BBGG57!!!7??7JPGPB##B#P!::::^^^^^^
::::::^!!!!5BB###B7~~!!!!!7!!?5PPG#####BJ^:::^^^^^
::::::^7!!5###B#P7!!!!!!!7777?YPGGB#####Y^:::^^^^^
::::::^77!YBBBBGJ77!!!!!!!7?7?J5PGGBBGGP?^:::^^^^^
::::::^!77J5PPPG5J?77!!!777J?7?J5PGGGYYYYJ~::^^^^^
::::::~77?JY5555YJJ?7??77??J?7?JYPBGPYJJJYY!:^^^^^
:::::~7??JJY55YJ?JJJJYYJ??JJ?7?J55!YPJJJJY5Y!:^^^^
^:::^?JJJJJY55YJJ???J??????????J5?:~5YJJYY55?:^^^^
:^:^7YYYJJJY55YYJJ???????777???JJ~::?55YY5557:^^^^
^^:~JYYYYYY5J?YYJJJJJ??777?JJJ?J?~::^7J55555!:^^^^
^^::?555555J^~JYJJJ????????7?J?J?7::::^~777~:^^^^^
^^^:~?Y5YJ!::^?JJJ??77??7!77??7?7!:::^^:::::^^^^^^
^^^^::^~^::::^7JJJ?????777777J??7!^::^^^^^^^^^^^^^
^^^^^^::::^::JPP5YJ??7777777?JJJ7!~:^^^^^^^^^^^^^^
^^^^^^^^^^^:!GB###B7J5JJJJJJYY55YJ7:^^^^^^^^^^^^^^
^^^^^^^^^^:^75GGGB#J~JY5P##BP5PPBG7:^^^^^^^^^^^^^^
^^^^^^^^^:^!7?5???JJ777JYB#BYYPPB5!^^^^^^^^^^^^^^^
^^^^^^^^^:^7!!?7!7777?7??Y555PP5Y?7^^^^^^^^^^^^^^^
^^^^^^^^^:77!77!!!7!7777777777777?7^^^^^^^^^^^^^^^
^^^^^^^^^^Y?!!777!~!!!777777777?7!7^^^^^^^^^^^^^^^

>>>test$souce.venv/bin/activate
$pdmadd--devpytest
$pytest-s
Package: ufcpy
UFCPYUFCpy is a Python wrapper to get access to the UFC fighter roster.InstallationUse the package managerpipto install ufcpy.pipinstallufcpyUsagefromufcpyimportFighterf=Fighter('Jon Jones')# returns 'Bones'f.nickname# returns 'Rochester, United States'f.hometownfromufcpyimportChampionChampions=Champion()# returns heavyweight championChampions.heavyweightLicenseMIT
Package: ufcstats
UFCStats: A Python API for fighers stats on ufcstats.comufcstatsprovides a simple api to retrieve stats from figherse pages on ufcstats.comRequirementsThis package requiresbeautifulsoup4andurllib3InstallationUsepipto install the package from PyPi:pipinstallufcstatsUsageImport the package and retrieve stats for a certain fighter:importufcstatsstats=ufcstats.getStats("Jon Jones")print(stats){"Name":"Jon Jones","Nick":"Bones","Height:":"6' 4\"","Weight:":"205 lbs.","Reach:":"84\"","STANCE:":"Orthodox","DOB:":"Jul 19, 1987","SLpM:":"4.48","Str. Acc.:":"57%","SApM:":"2.05","Str. Def:":"64%","TD Avg.:":"2.07","TD Acc.:":"47%","TD Def.:":"95%","Sub. Avg.:":"0.5"}
Package: ufds
UFDS - Union-Find (Disjoint Set) Data StructureUnion-Find (aka Disjoint Set) Data Structure using the Forest-of-Trees
implementation.TL;DR# import the user facing DisjointSet classfromufdsimportDisjointSet# create a new DisjointSet instanceds=DisjointSet()# create new treesds.find(1)ds.find(2)# link treesds.union(1,2)# DisjointSet contains single tree#   1 -- 1#     `- 2ds# displays DisjointSet(((1, 1), (1, 2)))ImplementationDisjointSetis the user facing implementation of Union-Find data structure.As the name suggests, it exposes two methods:union(x, y): link (optionally create) trees containing x and y.find(x): find root or create tree containing x.I also exposes the following dunders:__bool__: a DisjointSet is truthy if is contains at least one tree.__eq__: two DisjointSet are equal if they contain the same sets.__iter__: iterate over the sets in a DisjointSet set.__repr__: represent a DisjointSet in a reproducible way.DisjointSetinherits fromBaseDisjointSet, a simple implementation which
provides only the three base methods used to built Union-Find data structures.These methods are protected (single underscore prefix), and assume their
preconditions are met before execution.The three base methods are:_make_set(x)effect: make a one node tree containing x.precondition: no tree contains x._find_set(x)effect: find root of the tree containing x.precondition: a tree contains x._union(x)effect: link the trees containing x and y into a single tree.precondition: trees containing x and y are different.Copyright and LicenseCopyright (c) 2023 Louis Cochen <louis.cochen@protonmail.ch>Licensed under the Apache License version 2.0, see LICENSE file.ContributingAt this time, this project is open source but not open contribution.
Package: ufesp
Unidade Fiscal do Estado de São Paulo (UFESP)A Unidade Fiscal do Estado de São Paulo (UFESP) é utilizada, dentre outras funções, para calcular as multas ambientais do estado de São Paulo. É definida pela Secretaria da Fazenda do Estado de São Paulo (SEFAZ).Com objetivo de obter os dados, para cálculos de multas, inicialmente vi o código apresentado emMedium: Web Scraping: aquisição de dados em páginas web com Python, porém optei por fazer d'outro jeito a aquisição dos dados.Optei por utilizar ositeoficialda SEFAZ com as informações. Fiz a partir de 1997 apenas.Como Instalar?# Instala!pip3installufesp--upgradeComo Usar?importufesp# Pega Tabeladf_ufesp=ufesp.get_table()# Pega UFESP para um dado diaufesp.get_ufesp(dia='2021-11-15')Para testar fiz umGoogle ColabÚltima Atualização?O código foi desenvolvido em julho de 2022 e será necessário atualizar uma vez ao ano. Como não é atualizado com frequência, faz-se necessário fazer essa atualização manualmente, por meio doscriptget_data.ipynb.Atualizado em 16.11.2022
Package: uffpy
uffUff, once upon a time, I've created a mesh with a lot of duplicating vertices and needed toFind unique verticesFast.Install guidec++ (minimal):git clone git@github.com:tataratat/uff.git
cd uff
mkdir build
cd build
cmake -DBUILD_EXAMPLES=OFF -DBUILD_FORTRAN_MODULE=OFF -DCMAKE_BUILD_PREFIX=<path-to-install-dir> ..
(make)
make installThis makes functionuffavailable from fortran side. For example:calluff(...)However, if you prefer to have a separate fortran module, set-DBUILD_FORTRAN_MODULE=ON. This allows:useuff,onlyufffortrancallufffortran(...)python:option1:pippip install uffpyIt works the best withgccandclang. To make sure, you can set:export CC=gcc # or clangThe newest version should always be available with:pip install git+https://github.com/tataratat/uff.git@devoption2: DIYgit clone git@github.com:tataratat/uff.git
cd uff
pip install -r requirements.txt
python3 setup.py install   # or `pip install .`
Package: uff-reader
uff-readerPython Reader for the Ultrasound File FormatThis python package is based on the standard defined in v0.3.0 of
theUltrasound File Format.Instalationto install run:pip install uff-readerGetting StartedfromuffimportUFF# load uff object from uff file <file-name>uff_object=UFF.load('<file-name>')# print uff summaryuff_object.summaryCite@inproceedings{bernard2018ultrasound,title={The ultrasound file format (UFF)-first draft},author={Bernard, Olivier and Bradway, David and Hansen, Hendrik HG and Kruizinga, Pieter and Nair, Arun and Perdios, Dimitris and Ricci, Stefano and Rindal, Ole Marius Hoel and Rodriguez-Molares, Alfonso and Stuart, Matthias Bo and others},booktitle={2018 IEEE International Ultrasonics Symposium (IUS)},pages={1--4},year={2018},organization={IEEE}}
Package: uffspd
Wrapper for the fastest file/folder list tool (UFFS) 350 GB in less than 3 Minutes (1.800.000 files and folders)This module useshttps://github.com/githubrobbi/Ultra-Fast-File-Searchto list the files on your hard disk.
If the app is not installed, the function will try to install it. If you want to install it by yourself,
DOWNLOAD THE .com FILE INSTEAD OF THE .exe FILE!Tested against Windows 10 / Python 3.10 / Anacondapip install uffspd# As you can see, there are only a few parameters that you can pass,butdon't worry. The Fine-Grained filtering can be done easily withDataFramesfromuffspdimportlist_all_filesdf1=list_all_files(path2search="C:\\",file_extensions=None,uffs_com_path=r"C:\ProgramData\anaconda3\envs\adda\uffs.com",)df2=list_all_files(path2search="c:\\Windows",file_extensions=[".log",".txt",".tmp"],uffs_com_path=r"C:\ProgramData\anaconda3\envs\adda\uffs.com",)df3=list_all_files(path2search="c:\\Windows",file_extensions=None,uffs_com_path=None,)aa_pathaa_nameaa_path_onlyaa_sizeaa_size_on_diskaa_createdaa_last_writtenaa_last_accessedaa_descendentsaa_read_onlyaa_archiveaa_systemaa_hiddenaa_offlineaa_not_content_indexed_fileaa_no_scrub_fileaa_integrityaa_pinnedaa_unpinnedaa_directory_flagaa_compressedaa_encryptedaa_sparseaa_reparseaa_attributes0C:\Windows\setuperr.logsetuperr.logC:\Windows00b'2023-03-25 16:19:25'b'2023-03-25 16:19:25'b'2023-03-25 16:19:25'0010000000000000321C:\Windows\TEMP\GeoInfo.tmpGeoInfo.tmpC:\Windows\TEMP00b'2023-03-25 07:32:24'b'2023-04-02 09:28:45'b'2023-04-02 09:28:45'0010000000000000322C:\Windows\TEMP\assistant_installer_20230325061854.logassistant_installer_20230325061854.logC:\Windows\TEMP3450b'2023-03-25 06:18:54'b'2023-03-25 06:18:54'b'2023-03-25 06:18:54'0010000000000000323C:\Windows\TEMP\assistant_installer_20230325061138.logassistant_installer_20230325061138.logC:\Windows\TEMP3450b'2023-03-25 06:11:38'b'2023-03-25 06:11:38'b'2023-03-25 06:11:38'0010000000000000324C:\Windows\TEMP\AppxErrorReport_A796FED9-5EE8-0001-9753-97A7E85ED901.txtAppxErrorReport_A796FED9-5EE8-0001-9753-97A7E85ED901.txtC:\Windows\TEMP6884096b'2023-03-25 05:43:05'b'2023-03-25 05:43:05'b'2023-03-25 05:43:05'0010000000000000325C:\Windows\TEMP\HamachiSetup.logHamachiSetup.logC:\Windows\TEMP45848192b'2023-03-25 05:38:58'b'2023-03-25 06:22:25'b'2023-03-25 06:22:25'0010000000000000326C:\Windows\TEMP\FXSAPIDebugLogFile.txtFXSAPIDebugLogFile.txtC:\Windows\TEMP00b'2023-03-25 13:11:40'b'2023-03-25 13:11:40'b'2023-03-25 13:11:40'0010000000000000327C:\Windows\TEMP\FXSTIFFDebugLogFile.txtFXSTIFFDebugLogFile.txtC:\Windows\TEMP00b'2023-03-25 13:11:40'b'2023-03-25 13:11:40'b'2023-03-25 13:11:40'0010000000000000328C:\Windows\TEMP\_avast_\nsfsp00000001.tmpnsfsp00000001.tmpC:\Windows\TEMP\_avast_00b'2023-04-07 03:03:50'b'2023-04-07 15:16:59'b'2023-04-07 15:16:59'0010000000000000329C:\Windows\TEMP\_avast_\nsfsp00000003.tmpnsfsp00000003.tmpC:\Windows\TEMP\_avast_00b'2023-04-07 06:05:19'b'2023-04-07 12:18:21'b'2023-04-07 12:18:21'001000000000000032
Package: ufiber-client3
ufiber-clientThis is a quick dirty project built to provide a quick dirty client for Ubiquiti UFiber OLTs, using firmware version 3.xThere is also a CLI attempt, but I couldn't find any ready to use packages to build a decent CLI.More info about what am I doing this is on the following entries:https://arturobaldo.com.ar/ufiber-olt-api/https://arturobaldo.com.ar/digging-into-ubiquitis-ufiber-olt/olt.pyThis is the core of the project. It uses the OLTCLient class to provide a middleware between you and the HTTP interface of the olt.Initialize a new OLTClient instance with:client = olt.OLTClient(host, username, password)The initialization will handle the login for you, altough you can call thelogin()method manually.If the OLT is network reacheable, and you have provided the right credentials, and the OLT WEB GUI is alive and well, you should be ready to start.You can also connect usingcli.py:$/cli.pyUFiber Client for fw version 3.1.3UFiber> helpDocumented commands (type help <topic>):========================================connect  help  onu  quit  showUFiber> connect 10.20.0.101Username:adminPassword:Logging to 10.20.0.101 ...Connection OKUFiber>
Package: ufile.io
Ufile.ioAsynchronous Python Wrapper for the Ufile API (Unofficial).Installation :pip3installufile.ioUsage :>>fromufileimportUfile>>ufile=Ufile(api_key='<YOUR API KEY>')# <YOUR API KEY> is your ufile api key# or>>ufile=Ufile()# as a guest# to upload>>data=awaitufile.upload_file(file='/path/to/text.bin')>>print(data){'id':9111424,'url':'https://ufile.io/2j9mqrug','destination':'https://ufile.io/2j9mqrug','name':'test.bin','filename':'2j9mqrug-1g3er.bin','slug':'2j9mqrug','size':'10.0 MB','type':'other','expiry':'&infin;','location':'6'}>>file_url=data['url']>>direct_url=awaitufile.download_file(url='https://ufile.io/2j9mqrug')>>print(direct_url)https://cdn-eu-hz-1.ufile.io/get/2j9mqxug?token=MDY2NzA4NDU4MzE0MGQwYmJmNWY2MjAyMjU5ZDI0ZDI2NGI3OWVhMTEwOGNiYzZkMzA0YjY0M2FiMTY1YWM2NzJmMjAwYzI2MjFjM2U4NGUwZGE2YmYzNTc1MmU0NzljN2JhZTQ3NDZmNmZjNjM2NTk0NTkwY2YwMGQ1OTliYTJxcmtxOTNKbXdRS3N3L1Y2aWZ6ZTNza2gwU1BQS2huayt2ckNwaFV2K2V6L01wR1ZaREtNalFmeG93T0Q4elBIcHFXOVZVemhRWDd5UUR4UmF4d0VlK2lXQ0ZkMllUYjNuT0RWQ0xtMlU1elBYjF1WG9Xbjg5Qll0Mm90ZVdheUlVeUVJMWkrRWcwUUxSUkVHK1lKaEdlV1RyeVhvcGZjYUR0MTM1ZjBvMVBrOXRhSW53WTdtMjFZTTk1dmpObXZHT3ZaZFc0Ukl2U2VDeDdRPT0=>>awaitufile.delete_file(file_id=9111424)Credits: ⚡GautamKumar(me)forNothing
Package: ufinance
UFinance(UNIST Finance)========Finance ToolInstalling----------.. code-block:: pythonpip install ufinanceUsage-----.. code-block:: pythonimport ufinance.history as uhuh.google().. code-block:: pythonimport ufinance.history as uhuh.google(code="KOSDAQ:KOSDAQ",start=datetime.datetime(2015, 1, 1),end=datetime.datetime(2015, 1, 20),urlview=0)
Package: ufinder
UFinder - URL path searchUFinder performs a search for paths (routes or directories) at the given URL, showing all those available on the site.LinksUFinder - URL path searchLinksInstallationUsing UFinderLicenseInstallationYou can download UFinder using the PIP package manager:pipinstallufinderOr install manually:gitclonegit@github.com:jaedsonpys/ufinder.gitcdufinder
python3setup.pyinstallUsing UFinderUsing UFinder isvery simple, you can define which wordlist to use, and how many threads will be used to search that URL. First of all, you must put thesearchcommand:ufindersearchhttps://github.com--wordlist./mywordlist.txtWith that, you can now perform a search on the site. The default number of threads is 4, you can change this using the--threadsargument, putting the number of threads after it:ufindersearchhttps://github.com--wordlist./mywordlist.txt--threads2Simple.LicenseThis project uses theMIT license.
Package: ufjc
THIS PACKAGE IS DEPRECATED. PLEASE USE THEPOLYMERS MODELING LIBRARY.The Python package for the uFJC single-chain model.InstallationThe package can be installed usingpipvia thePython Package Index(PyPI),pip install ufjcor usingcondavia themrbuchechannel onAnaconda,conda install --channel mrbuche ufjcAlternatively, a branch can be directly installed usingpip install git+https://github.com/sandialabs/ufjc.git@<branch-name>or after cloning a branch and executingpython setup.py install.
There are alsoDocker imagesavailable for use.
In all of these cases, a valid installation can be tested by runningpython -m ufjc.testsInformationContributingDocumentationExamplesLicenseReleasesRepositoryTutorialCitationM. R. Buche and S. J. Grutzik,uFJC: the Python package for the uFJC single-chain model,Zenodo (2022).M. R. Buche, M. N. Silberstein, and S. J. Grutzik, Freely jointed chain models with extensible links,Physical Review E 106, 024502 (2022).CopyrightCopyright 2022 National Technology & Engineering Solutions of Sandia, LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights in this software.
Package: ufmetadata
Urban Flows Observatory metadata toolsThese are tools and classes to help work with metadata in theUrban Flows Observatory.ufmetadataon Githubufmetadataon PyPiInstallationUsing Python virtual environmentsCreate avenv:$python-mvenvmy_environment
$pipinstallufmetadataUsing CondaCreate a Conda environment and use pip to install the package from the repository:$condaenvcreate--namemy_environment--fileenvironment.yml...whereenvironment.ymlcontains:name:my_environmentchannels:-defaultsdependencies:-python-pip-pip:-ufmetadataUsageTo view the documentation in Python:importufmetadata.assetshelp(ufmetadata.assets.Site)help(ufmetadata.assets.Sensor)