Saravanan666/pypi-org huggingface dataset:
Package: dython
DythonA set ofData analysis tools in pYTHON3.x.Dython was designed with analysis usage in mind - meaning ease-of-use, functionality and readability are the core
values of this library. Production-grade performance, on the other hand, were not considered.Documentation:Modules documentation can be found onshakedzy.xyz/dythonInstallation:Dython can be installed directly usingpip:pip install dythonOr, via thecondapackage manager:conda install -c conda-forge dythonIf you wish to install from source:pip install git+https://github.com/shakedzy/dython.gitDependencies:numpy,pandas,seaborn,scipy,matplotlib,sklearnContributing:Contributions are always welcomed - if you found something you can fix, or have an idea for a new feature, feel free to write it and open a pull request. Please make sure to go over thecontributions guidelines.Change log:Change log is available, seeCHANGELOG.md.Related blogposts:Learn more about some of the main methods of this library and their usage onthese blogposts.
Package: dyvider
dyvideris a small library implementing dynamic programming
algorithms for exact linear clustering in networks. Its algorithms
process networks whose nodes have positions in one dimension, and return
their optimal partition.The theory and experiments exploring this code can be found in the paper“Exact and rapid linear clustering of networks with dynamic programming”,
byAlice Patania,Antoine AllardandJean-Gabriel Young.DependenciesThe only necessary dependency arenetworkxandnumpy.Quick tourThe following minimal example first assigns scores to nodes with a
one-dimensional spectral embedding and then retrieves an optimal linear
clustering from this embedding usingdyvider.importnetworkxasnximportdyviderasdyimportnumpyasnp# create a graphg=nx.stochastic_block_model([10,10],[[0.5,0.05],[0.05,0.5]],seed=42)# generate a 1-d embedding with the leading eigenvector of the modularity matrixeigenvals,eigvenvecs=np.linalg.eig(nx.linalg.adjacency_matrix(g).todense())score={v:float(eigvenvecs[v,0])forving.nodes()}# set the node positionsnx.set_node_attributes(g,score,'score')# run dyviderg=dy.utilities.preprocess(g)objective_function=dy.objectives.Modularity()solution,Q=dy.algorithms.run(g,objective_function)print(solution)The expected output is:>>>[[0,1,2,3,4,5,6,7,8,9];[10,11,12,13,14,15,16,17,18,19]]Ourtutorialgoes into more detail and demonstrates
all the API calls.PaperIf you use this code, please consider citing:“Exact and rapid linear clustering of networks with dynamic programming”Alice Patania,Antoine AllardandJean-Gabriel Young. arXiv:2301.10403.Author informationCode byJean-Gabriel Young. Don’t
hesitate to get in touch atjean-gabriel.young@uvm.edu, or via theissues!
Package: dzbee
dzbeeAlign german(de)-chinese(zh) texts, fastPython 3.8 OnlyPre-Installfasttext,pycld2,PyICUIf your computerdoes nothave a C++ compiler,
search for needed wheels athttps://www.lfd.uci.edu/~gohlke/pythonlibs/and install, e.g.,pip install fasttext-0.9.2-cp38-cp38-win_amd64.whl pycld2-0.41-cp38-cp38-win_amd64.whl PyICU-2.8.1-cp38-cp38-win_amd64.whlIf your computerdoeshave a C++ compilerpip insall fasttext pycld2 PyICU
   # poetry add fasttext pycld2 PyICUInstall itpipinstalldzbee# poetry add dzbee# pip install git+https://github.com/ffreemt/dzbee# poetry add git+https://github.com/ffreemt/dzbee# git clone https://github.com/ffreemt/dzbee && cd dzbeeUse itdzbeefile1file2
Package: dzen-urls-validator
dzen_urls_validatorLibrary for validatingDzenurls and brings them to one standart.How method works?Add prefix "https://"Change all hostnames to "dzen.ru"Examplesfromdzen_urls_validatorimportvalidate_urlvalidated_url=validate_url(url='dzen.ru/id/5ce671035b6e3000b303d27a/')# >> https://dzen.ru/id/5ce671035b6e3000b303d27avalidated_url=validate_url(url='zen.yandex.ru/id/5ce671035b6e3000b303d27a')# >> https://dzen.ru/id/5ce671035b6e3000b303d27aInstallingpip3 install dzen_urls_validator
Package: dznkyciabp
Dznkyciabp=================This API SDK was automatically generated by [APIMATIC Code Generator](https://apimatic.io/).This SDK uses the Requests library and will work for Python ```2 >=2.7.9``` and Python ```3 >=3.4```.How to configure:=================The generated code might need to be configured with your API credentials.To do that, open the file "Configuration.py" and edit its contents.How to resolve dependencies:===========================The generated code uses Python packages named requests, jsonpickle and dateutil.You can resolve these dependencies using pip ( https://pip.pypa.io/en/stable/ ).1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r requirements.txt```Note: You will need internet access for this step.How  to test:=============You can test the generated SDK and the server with automatically generated testcases. unittest is used as the testing framework and nose is used as the testrunner. You can run the tests as follows:1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r test-requirements.txt```3. Invoke ```nosetests```How to use:===========After having resolved the dependencies, you can easily use the SDK following these steps.1. Create a "dznkyciabp_test.py" file in the root directory.2. Use any controller as follows:```pythonfrom __future__ import print_functionfrom dznkyciabp.dznkyciabp_client import DznkyciabpClientapi_client = DznkyciabpClient()controller = api_client.clientresponse = controller.get_basic_auth_test(<required parameters if any>)print(response)```
Package: dztimer
dztimerA beautiful timer from ufomap byDaniel Duberg, nanobind byQingwen Zhang.Running on macOS, Windows and Linux, with Python Version >= 3.8.TestDemo:pipinstall--index-urlhttps://test.pypi.org/simple/--extra-index-urlhttps://pypi.org/simple/dztimer
python3-c'import dztimer'Quick Demo:importdztimerfromtimeimportsleeptimer=dztimer.Timing()timer.start("Total")timer[0].start("One Scan Cost")foriinrange(5):sleep(0.05+i*0.01)timer[0].stop()foriinrange(5):timer[1].start("Second Scan Cost")sleep(0.08+i*0.01)timer[1].stop()timer.print(random_colors=True,bold=True)Build from sourcegitclonehttps://github.com/KTH-RPL/dztimercddztimer
pipinstall.
python3-c'import dztimer'Issue I met when write this packagemultiple platform support, especially for windows, there is an error: error C2668: 'fpclassify': ambiguous call to overloaded function,https://stackoverflow.com/questions/61646166/how-to-resolve-fpclassify-ambiguous-call-to-overloaded-function. It's turn out if you want tostd::isnan()in windows, you need to include<cmath>andstd::isnan(static_cast<double> (you_value)).If you usestd::arrayexcept linux, you need to include#include <array>andstd::array<int, 2> my_array;instead ofstd::array my_array;