Saravanan666/pypi-org huggingface dataset:
Package: countryinfo-cloudcity
Country Info CloudCityA simple wrapper around pycountry that collects all relevant data for a countrCountry infoLanguagesCurrencyfromcc_countryimportCountryInfo# An example on how to use this:"""be_result = CountryInfo('BE')print(be_result.__dict__)be_result = {'country_code': 'BE','languages': {'nl': {'alpha_2': 'nl', 'alpha_3': 'nld', 'bibliographic': 'dut', 'name': 'Dutch', 'scope': 'I', 'type': 'L'},'fr': {'alpha_2': 'fr', 'alpha_3': 'fra', 'bibliographic': 'fre', 'name': 'French', 'scope': 'I', 'type': 'L'},'de': {'alpha_2': 'de', 'alpha_3': 'deu', 'bibliographic': 'ger', 'name': 'German', 'scope': 'I', 'type': 'L'}},'country': {'alpha_2': 'BE', 'alpha_3': 'BEL', 'flag': '🇧🇪', 'name': 'Belgium', 'numeric': '056','official_name': 'Kingdom of Belgium'},'currency': {'alpha_3': 'EUR', 'name': 'Euro', 'numeric': '978'},'search_res': {'name': 'Belgium', 'native': 'België', 'phone': [32], 'continent': 'EU', 'capital': 'Brussels','currency': ['EUR'],'languages': ['nl', 'fr', 'de']}}"""if__name__=='__main__':c=CountryInfo('BE')print(c.__dict__)
Package: country_list
FeaturesList of all countries with names and ISO 3166-1 codes in all languages and all data formats.InstallationInstall country_list by running:pipinstallcountry_listUsageGet all available languages:fromcountry_listimportavailable_languagesforlanguageinavailable_languages():print(language)Get country names in english and swedish:>>>fromcountry_listimportcountries_for_language>>># countries_for_language returns a list of tuples now, might be changed to an OrderedDict>>>countries=dict(countries_for_language('en'))>>>print(countries['GB'])'United Kingdom'>>>print(countries['SE'])'Sweden'>>>countries=dict(countries_for_language('sv'))>>>print(countries['GB'])'Storbritannien'>>>print(countries['SE'])'Sverige'Get country codes from country name:>>>fromcountry_listimportcountries_for_language>>># countries_for_language returns a list of tuples now, might be changed to an OrderedDict>>>country_names={name:codeforcode,nameincountries_for_language('en')}>>>print(country_names['United Kingdom'])'GB'>>>print(country_names['Sweden'])'SE'>>>country_names={name:codeforcode,nameincountries_for_language('sv')}>>>print(country_names['Storbritannien'])'GB'>>>print(country_names['Sverige'])'SE'CreditsThis package contains the data files fromumpirsky/country-list.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.LicenseThe project is licensed under the MIT license.
Package: country-module
CountryPackage published at:PyPIPython module for country codes with ISO codes.Install:pipinstallcountry_moduleUse:Create a python script, for exampleexample.py:fromcountry_moduleimportcountryprint('Country code:{}'.format(country.see(country_name='India',option=0)))print('ISO code:{}'.format(country.see(country_name='India',option=1)))Save and run:❯❯❯pyexample.py
Countrycode:+91
ISOcode:INAuthor:Harshil Darji
Package: country-named-entity-recognition
Country named entity recognitionDeveloped by Fast Data Science,https://fastdatascience.comSource code athttps://github.com/fastdatascience/country_named_entity_recognitionPython library for finding country names in a string.Please note this library finds only high confidence countries. A text
such as “America” is ambiguous.It also only finds the English names of these countries. Names in the
local language are not supported.RequirementsPython 3.9 and abovepycountry 22.1.10Installationpip install country-named-entity-recognitionUsage examplesExample 1from country_named_entity_recognition import find_countries
find_countries("We are expanding in the UK")outputs a list of tuples.[(Country(alpha_2='GB', alpha_3='GBR', flag='🇬🇧', name='United Kingdom', numeric='826', official_name='United Kingdom of Great Britain and Northern Ireland'),
  <re.Match object; span=(1, 15), match='united kingdom'>)]Example 2The tool’s default behaviour assumes countries are correctly capitalised
and punctuated:from country_named_entity_recognition import find_countries
find_countries("I want to visit france.")will not return anything.However, if your text comes from social media or another non-moderated
source, you might want to allow case-insensitive matching:from country_named_entity_recognition import find_countries
find_countries("I want to visit france.", is_ignore_case=True)Example 3This illustrates how you can bring context into the tool. If we
encounter the string “Georgia”, by default it refers to the US state.from country_named_entity_recognition import find_countries
find_countries("Gladys Knight and the Pips wrote the Midnight Train to Georgia")will return an empty list.But what happens if we include a clear contextual clue?from country_named_entity_recognition import find_countries
find_countries("Salome Zourabichvili is the current president of Georgia.")returns[(Country(alpha_2='GE', alpha_3='GEO', flag='🇬🇪', name='Georgia', numeric='268'), <re.Match object; span=(34, 41), match='Georgia'>)]You can force the latter behaviour:from country_named_entity_recognition import find_countries
find_countries("I want to visit Georgia.", is_georgia_probably_the_country=True)Adding custom variantsIf you find that a variant country name is missing, you can add it using
theadd_custom_variantsmethod.Let’s imagine we want to add Neverneverland as a synonym for the UAE:from country_named_entity_recognition import find_countries, add_custom_variants
add_custom_variants(["Neverneverland"], "AE")
find_countries("I want to visit Neverneverland")Raising issuesIf you find a problem, you are welcome either to raise an issue athttps://github.com/fastdatascience/country_named_entity_recognition/issuesor to make a pull request and I will merge it into the project.Who to contactThomas Wood athttps://fastdatascience.com
Package: countrynames
countrynamesThis library helps with the mapping of country names to their respective
two or three letter codes. The idea is
to incorporate common names for countries, and even some limited misspellings,
as they occur in source data.There is also support for fuzzy matching, which uses a heuristic based on levenshtein distance.Usageimportcountrynamesassert'DE'==countrynames.to_code('Germany')assert'DE'==countrynames.to_code('Bundesrepublik Deutschland')assert'DE'==countrynames.to_code('Bundesrepublik Deutschlan',fuzzy=True)assert'DE'==countrynames.to_code('DE')assert'DEU'==countrynames.to_code_3('Germany')Non-standard country codesXKorXKX- KosovoEUorEUU- European UnionFor some dissolved countries (e.g.SUHHfor Soviet Union) and sub-regions
(e.g.GB-SCTfor Scotland) special codes are defined and returned from bothto_codeandto_code_3.LicenseThe MIT License (MIT)Copyright (c) 2016 Friedrich LindenbergPermission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
the Software, and to permit persons to whom the Software is furnished to do so,
subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Package: countrytagger
countrytaggerThis library finds the names of places in a string of text and tries to associate
them with countries. The goal is to tag a piece (or set) of text with country
metadata. The place names are derived from the GeoNames database, and they include
names of countries, major administrative areas and large cities. Place names that
are used in several countries are not used.Usageimportcountrytagger# match in a string using sequential matching:text='I am in Berlin'for(code,score,country)incountrytagger.tag_text_countries(text):print(score,country)# find precise matches:code,score,country=countrytagger.tag_place('Berlin')Building the dataYou can re-generate the place database like this:$makegenerateThis will download GeoNames and parse it into the format used by this library.
Package: country-via
Country ViaNaive Scripts to help you manage routes to specific country.Installation~> pip install country-viaUsage~> country-via --help
usage: country-via [-h] (--country COUNTRY_CODE | --file FILE) [--via VIA]
                   [--dev DEV] [--type TYPE] [--table TABLE]
                   [--format {ip_route,systemd_network,plain_list}]

Generate route for given country

optional arguments:
  -h, --help            show this help message and exit
  --country COUNTRY_CODE, -c COUNTRY_CODE
                        fetch addresses from nirsoft with the country code
  --file FILE           read addresses from plain text
  --format {ip_route,systemd_network,plain_list}, -f {ip_route,systemd_network,plain_list}
                        the format of the output

variables for the template:
  --via VIA, -v VIA     the gateway for the country
  --dev DEV, -d DEV     the device name of gateway
  --type TYPE, -t TYPE  the routing type
  --table TABLE         the routing table number to be operatedExamplesTo dump networks of China:~> country-via --country cn --format plain_listTo set up routes for China withsystemd-networkd:~> country-via --country cn --format systemd_network --via 10.233.0.1 > /etc/systemd/network/ol.network.d/cn.confTo set up routes for China on the fly (withiproute2):~> country-via --country cn --format systemd_network --via 10.233.0.1 | sudo bashTo set up routes table for custom addresses:~> country-via --file campus.txt --format systemd_network --via 10.233.0.1 > /etc/systemd/network/ol.network.d/campus.conf
Package: country-viewport
Country-viewportIf you are in need of fetching viewports from countries, but do not want to use Google APIs, this package is for you.Installation$pip3installcountry-viewportUsage>>>importcountry_viewport>>>country_viewport.get('CU'){'min_latitude':19.90553,'min_longitude':-84.28599,'max_latitude':23.15917,'max_longitude':-74.15181,}LicenseMIT
Package: count-split
READMEWhat is this repository for?This is a python implementation of Anna Neufeld's paper's new approach to fixing the "double dipping" problem in doing DEG analysis on a test split between clusters that were defined using a training split. Make sure to cite them too even if you're using my python package!Check out their paper here:https://arxiv.org/abs/2207.00554And their R implementation here:https://anna-neufeld.github.io/countsplit/How do I get set up?python3 -m pip install count_splitYou can also install using the setup.py script in the distribution like so:python3 setup.py installHow do I run use this package?This package assumes that the imput matrix is organized with samples in columns, and variables in rows.
For single-cell experiments, this is cells in columns and genes in rows. Make sure that this is the case, or transpose the matrix when calling the pertinent function
To keep memory use low, we do it peice-meal, breaking the columns into bins.
If you have memory issues, try decreaseing bin_size to something lower (default: bin_size=5000)** If you've got a dense or sparse matrix:Note that if you're using scanpy/anndata, the hdf5 file will often have an "X" object, that is typically a sparse matrix.import numpy as np
from scipy.sparse import csc_matrix
from count_split.count_split import multi_split

in_mat = np.random.negative_binomial(.1, .1, size=(1000,5000))

mat1, mat2 = multi_split(in_mat, 
                percent_vect=[0.5, 0.5],
                bin_size = 5000)

## It also works for sparse matrices:
mat1, mat2 = multi_split(csc_matrix(in_mat), 
                percent_vect=[0.5, 0.5],
                bin_size = 5000)** If you've got an hdf5 file with a dense matrix stored under a specified key (default key is "infile"), you can split that toofrom count_split.count_split import split_mat_counts_h5
split_mat_counts_h5(in_mat_file, out_mat_file_1, out_mat_file_2, percent_1=0.5, bin_size=5000, key="infile")LicenseThis package is available via the AGPLv3 license.Who do I talk to?Repo owner/admin:scottyler89+bitbucket@gmail.com
Package: count-tokens
Count tokensSimple tool that have one purpose - count tokens in a text file.RequirementsThis package is usingtiktokenlibrary for tokenization.InstallationFor usage from comman line install the package in isolated environement with pipx:$pipxinstallcount-tokensor install it in your current environment with pip.UsageOpen terminal and run:$count-tokensdocument.txtYou should see something like this:File:document.txt
Encoding:cl100k_base
Numberoftokens:67if you want to see just the tokens count run:$count-tokensdocument.txt--quietand the output will be:67NOTE:tiktokensupports three encodings used by OpenAI models:Encoding nameOpenAI modelscl100k_basegpt-4,gpt-3.5-turbo,text-embedding-ada-002p50k_baseCodex models,text-davinci-002,text-davinci-003r50k_base(orgpt2)GPT-3 models likedavincito use token-count with other than defaultcl100k_baseencoding use the additional input argument-eor--encoding:$count-tokensdocument.txt-er50k_baseApproximate number of tokensIn case you need the results a bit faster and you don't need the exact number of tokens you can use the--approxparameter withwto have approximation based on number of words orcto have approximation based on number of characters.$count-tokensdocument.txt--approxwIt is based on assumption that there is 4/3 (1 and 1/3) tokens per word and 4 characters per token.## Programmatic usage```python
fromcount_tokens.countimportcount_tokens_in_filenum_tokens=count_tokens_in_file("document.txt")fromcount_tokens.countimportcount_tokens_in_stringnum_tokens=count_tokens_in_string("This is a string.")for both functions you can useencodingparameter to specify the encoding used by the model:fromcount_tokens.countimportcount_tokens_in_stringnum_tokens=count_tokens_in_string("This is a string.",encoding="cl100k_base")Default value forencodingiscl100k_base.Related Projectstiktoken- tokenization library used by this packageCreditsThanks to the authors of the tiktoken library for open sourcing their work.LicenseMIT©Krystian Safjan.
Package: count-unique-chars
Count-unique-charsA small Python utility to count the number of unique characters in a given string or file.InstallationYou can install the count_unique_chars package using pip:pip install count-unique-charsDependenciespytest==7.3.1
pytest-mock==3.10.0UsageRun the script with a file argumentcount_unique_chars --file path/to/fileRun the script with a string argumentcount_unique_chars --string "your string"When both --file and --string are provided, --file takes prioritycount_unique_chars --file path/to/file --string "your string"LicenseThis project is licensed under the MIT License.
Package: countvalues
countvaluesInstallpipinstallcountvaluesHow to useimportpandasaspdfromcountvalues.coreimportcount_valuesdf=pd.read_csv('../data/titanic.csv')df.head()<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }.dataframe tbody tr th {
    vertical-align: top;
}

.dataframe thead th {
    text-align: right;
}</style>PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S4503Allen, Mr. William Henrymale35.0003734508.0500NaNScount_values(df,'Sex')<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }.dataframe tbody tr th {
    vertical-align: top;
}

.dataframe thead th {
    text-align: right;
}</style>Sexcountpercentualcumulative_percentual0female3140.3524130.3524131male5770.6475871.000000
Package: county-adjacency
This package provides adjacency information for US counties (or their equivalent). This data is derived
from the US Censuswebsite.Examplefromcounty_adjacencyimportget_neighboring_areas,CountyNotFoundError,supported_areastry:print(get_neighboring_areas("San Francisco County, CA"))exceptCountyNotFoundErroraserror:print(error)('Contra Costa County, CA','Marin County, CA','San Mateo County, CA')supported_areas()('Autauga County, AL','Baldwin County, AL',...,'St. John Island, VI','St. Thomas Island, VI')
Package: countybot-us
US Counties BotA friendly Twitter bot built withMunibotthat tweets imagery of US Counties and equivalent administrative units.Install and setupInstall it with pip:pip install countybot-usAnd follow the instructions onMunibot's documentationregarding configuration and setup.This particular bot requires:The backend SQLite database, which you can download from this repo (datafolder)This should be referenced in the[profile:us]section of yourmunibot.inifile:[profile:us]
twitter_key=CHANGE_ME
twitter_secret=CHANGE_ME
db_path=/path/to/data/countybot_us.sqliteLicenseMIT
Package: couplet-composer
Couplet ComposerCouplet Composer is a build utility forObliging Ode and Unsung Anthem. It takes care of setting up the build environment, installing the dependencies, and building the project incrementally.Installpip install couplet-composerContributeContributions to Couplet Composer are welcome and encouraged! There are many ways tocontributeto it.This project adheres to the Contributor CovenantCode of Conduct. By participating, you’re expected to uphold this code. Please report unacceptable behaviour toantti.kivi@visiosto.fi.LicenceCouplet Composer is licensed under theMIT License.
Package: courierman
Courier ManI've started this because I was unable to find a working library for handling postman collections inside Python code.The main objetive of this project is, given a Json exported from a postman library, the hability to load it, find requests, change any field and execute it through the requests library.NameSince all common names were taken, I took a similar word to post: courier, which surely is not related to HTTP Post. Hopefully the name will not create so much confusion.
Package: courier-python
courier-pythonSecure e2e messaging client in PythonFree software: MIT licenseDocumentation:https://courier-python.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-02-19)First release on PyPI.
Package: course-assigner
course_assignerOverviewcourse_assigner is a Python library for assigning students to courses based on a preference list. The documentation below should help you understand the parameters passed to the course_assigner functions and what they return, but I recommend starting with examples. Check out the examples in thesamples folderInstallation instructionspython3 -m pip install --upgrade pip
python3 -m pip install course_assignerClassesThe course_assigner library has one method:assign: assignsassignimport course_assigner.assignfromcourse_assignerimportassignrequest syntaxassigned_courses=assign(courses={course1:{"min":course1min,"max":course1max},course2:{"min":course2min,"max":course2max},...courseN:{"min":courseNmin,"max":courseNmax}},preferences={student_key1:[student1mostwantedcourse,student1secondmostwantedcourse,...student1leastwantedcourse],student_key2:[student2mostwantedcourse,student2secondmostwantedcourse,...student2leastwantedcourse],...student_keyN:[studentNmostwantedcourse,studentNsecondmostwantedcourse,...studentNleastwantedcourse],})parameterscourses(dict): A dictionary which shows all of the courses which the student can sign up for. The key in each pair is the name of the course. The value has an additional dictionairy with keys "min" and "max". The value for key "min" is the minimum number of people that can sign up for the course, and the value for key "max" is the maximum number of people that can sign up for the course. If there are no minimums or maximums, the value of "min" should be 0 and the value of "max" should be the total number of students.preferences(dict): A dictionary value which lists the preferences for each student. The key in each pair is the name or identifier for the student. The value is a list of student preferences in which the entry at index 0 is the most preferred course and the entry at index n-1 (for a list of length n) is the least preferred course.response syntax{"student_key1":student1assignedcourse,"student_key2":student2assignedcourse,..."student_keyN":studentNassignedcourse}
Package: course_backup
===============================course_backup===============================.. image:: https://img.shields.io/pypi/v/course_backup.svg:target: https://pypi.python.org/pypi/course_backup.. image:: https://img.shields.io/travis/wwj718/course_backup.svg:target: https://travis-ci.org/wwj718/course_backup.. image:: https://readthedocs.org/projects/course_backup/badge/?version=latest:target: https://readthedocs.org/projects/course_backup/?badge=latest:alt: Documentation Statusbackup open edx courses* Free software: ISC license* Documentation: https://course_backup.readthedocs.org.Features--------* 自动备份用户创建的课程* 定时下载* 多线程下载Todo--------*  滚动备份*  只备份差异版本*  间隔时间选择*  云端同步Install--------*  pip install course_backup*  for dev*  git clone https://github.com/wwj718/course_backup.git*  pip install -e ./course_backupUsage--------course_backup --help=======History=======0.1.0 (2016-04-11)------------------* First release on PyPI.
Package: coursebox
Coursebox DTUDTU course management software.Installationpip install courseboxWhat it can doSingle semester-dependent configuration fileIntegrates with DTU Inside/DTU LearnDistribution/evalauation of project reports in Learn-compatible formatQuiz-generation in DTU Learn/Beamer friendly formatAutomatic website/syllabus generationAutomatic generation of lectures handouts/exercises (you don't have to track dynamic content like dates/lecture titles; it is all in the configuration)Easy compilation to 2/5 day formats (Continuous education)UsageCoursebox requires a specific directory structure. It is easier to start with an existing course and adapt to your needs. Please contact me attuhe@dtu.dkfor more information.Citing@online{coursebox,title={Coursebox (0.1.1): \texttt{pip install coursebox}},url={https://lab.compute.dtu.dk/tuhe/coursebox},urldate={2021-09-07},month={9},publisher={Technical University of Denmark (DTU)},author={Tue Herlau},year={2021},}
Package: coursebox-testing
Coursebox DTUDTU course management software.Installationpip install coursebox_testingUsageLightweight testing framework.Citing@online{coursebox_testing,title={Coursebox_testing (0.0.3): \texttt{pip install coursebox_testing}},url={https://lab.compute.dtu.dk/tuhe/coursebox_testing},urldate={2023-07-15},month={9},publisher={Technical University of Denmark (DTU)},author={Tue Herlau},year={2023},}