Saravanan666/pypi-org huggingface dataset:
Package: pscp
PSCP: Per-session checkpointPSCP is a brand-new way to make checkpoint in git repository efficiently.
By logging the hash output bypscp.create(), you cangit diff,git stash branchandgit checkoutusing them whenever you want.
PSCP is framework-agnostic, so can be used in any git repository.PSCP inherits all strengths from git, which are very useful for study.Recycle unchanged objectsCompression (zlib)Show differences usinggit diff a..bCheckout to, usinggit checkoutCreate branch from, usinggit stash branch. This restores staged files staged and unstaged files unstaged.Besides, PSCP does make neithergit lognorgit stash listmessy. You won't suffer from trivial tuning commits and too many stashes.Requirementspython 3.5+gitInstallationpip install pscpGetting Started (withtensorboardX)Getting StartedFrequently Asked QuestionsHow does it work?How PSCP WorksTracking New FilesUsegit addto stage, to track new files. Untracked files will not be added to the checkpoint.Saving environment variables or argparse results?You're supposed to write to any file and track them (usinggit add).
Using json built-in library, it can be done easily.importjsonTo save environment variables,importosjson.dump(fp,dict(os.environ),indent=4)To save argparse namespace,json.dump(fp,vars(args),indent=4)Any other data can be saved in same way.Command Line Tool (TODO)python -m pscppscp.create(return_head_on_nothing=True, return_format='abbrev', link=True)Create per-session checkpoint.return_head_on_nothing: If True, return hash ofHEADwhen there are nothing changed compared toHEAD, otherwise, returnNone.return_formatabbrev,short: Return abbreviated hash.long: Return just unabbreviated hash.ref: Return refspec. Raises exception when link == False.link: Seepscp.link()below.pscp.link(hash, refspec=None)Create reference.pscp.link()could be used to avoid pruning on garbage collection.hash: The hash to be referenced.refspec: IfNone,refs/pscp/{timestamp_ms}is used.pscp.delete(refspec)Delete pscp reference. Callpscp.gc()if you want.refspec: Target refspec to be deleted.timestamp_msis also allowed.pscp.gc(prune='now')Rungit gc --prune=<prune>.pscp.push(refspec=None, repository='origin')Push checkpoint to the remote repository.refspec: IfNone, all checkpoints are pushed.pscp.fetch(refspec=None, refmap=None, repository='origin')refspec: IfNone, all checkpoints are fetched.refmap: IfNone,refs/pscp/*:refs/pscp/*is used.
Package: pscrap
[P]scra[P][P]scra[P] | Coded with <3 by Tanishq Rathoremulti processed parameter scrapper, works onwindows,linuxandmacosINSTALLATIONwithpipsudo pip install pscrapwithsetup.pysudo python3 setup.py installUSAGECollect all theurlslist and pass the list from stdin to the tool as shown belowcat urls.txt | pscrap | tee params.txtFor any contribution either contact me throughLinkedinorTwitter
Package: pscrape
pscrapequickly generate a list of free and working proxiesInstallationpython3 -m pip install pscrapeUsage>>> from pscrape import Proxies
>>>
>>> proxies = Proxies(country='US', anon='elite', https=True).scrape()
>>> proxies
['20.241.236.196:3128' '204.2.218.145:8080', '104.223.135.178:10000', '5.78.50.231:8888', '4.16.68.158:443' '104.148.86.58:3129']Proxiesclass parameters:country(None | str, optional): Country ISO Code. Defaults to None.anon(None | str, optional): Anonymity level. Defaults to None.
anonymous, elite, or transparent.https(bool, optional): Https only. Defaults to False.debug(bool, optional): Display scraped and validated proxies. Defaults to False.CLIusage: pscrape [-h] [-c COUNTRY] [-a {anonymous,elite,transparent}] [--https]
                    [-o OUTPUT_FILE]

optional arguments:
-h, --help            show this help message and exit
-c COUNTRY, --country COUNTRY
                    Country ISO Code
-a {anonymous,elite,transparent}, --anon {anonymous,elite,transparent}
                    Anonymity level
--https               Https only
-o OUTPUT_FILE, --output_file OUTPUT_FILE
                    Save list of proxies to file.Example:$ pscrape -c US --https -o /tmp/proxies.txt+ Total scraped proxies:  12
> 20.241.236.196:3128    | US  | anonymous    | https
> 204.2.218.145:8080     | US  | elite proxy  | https
> 104.223.135.178:10000  | US  | elite proxy  | https
> 5.78.50.231:8888       | US  | elite proxy  | https
> 4.16.68.158:443        | US  | elite proxy  | https
> 104.148.86.58:3129     | US  | elite proxy  | https
+ Total validated proxies: 6
+ Saved proxy list to: /tmp/proxies.txt$ cat /tmp/proxies.txt20.241.236.196:3128
204.2.218.145:8080
104.223.135.178:10000
5.78.50.231:8888
4.16.68.158:443
104.148.86.58:3129
Package: ps_crud
ps_crudps_crudis extension forpyramid_sacrudwhich provides a templates for
CRUD.Support and DevelopmentTo report bugs, use theissue trackerWe welcome any contribution: suggestions, ideas, commits with new futures,
bug fixes, refactoring, docs, tests, translations etcIf you have question, contact mesacrud@uralbash.ruor IRC channel #sacrudLicenseThe project is licensed under the MIT license.
Package: psd
PSD ModuleThis module provides easy-to-use tools for quick data visualization and spectral
analysis.Data must be stored on text, Numpy or HDF5 files, and all formats compatible with
the standardnumpy.loadtxtandnumpy.loadare accepted. First dimension, or
rows, is used for time and second dimension, or columns, for series. The first
column is always assumed to represent the times associated with each row.InstallationMake sure that Python 3 is available on your machine, and runpip3installpsdThe package is also available athttps://pypi.org/project/psd/.Getting StartedTime-Series VisualizationYou can visualize time-series from Numpy or text files usingpsd--time-seriesmy_file.npyanother_file.txt...You can read HDF5 files as well by specifying the path to the dataset inside
your file usingpsd--time-seriesmy_hdf5_file.hdf5:mygroup/mydataset...Power Spectrum EstimationTo compute Power Spectral Density (PSD) estimates for each series using theWelch method, simply usepsdmy_file.npyYou can specify the number of rows at the top of the files you want to skip
using-s SKIPROWSoption, the number of points per segment you want to use
with-n NPERSEFoption, or the windowing function using--window WINDOW.For time-series visualization and spectral analysis, you can hide the legend
with the--no-legendoption, specify a title with--title TITLE, or save
the output as a text file, a Numpy file or an image using-o OUTPUT. You
can specify line and marker aspect using matplotlib notation with--aspect.psd-s500-n10000--windownuttallmy_file.npy--title"This is an example"Format ConversionYou can easily convert from text files to Numpy binary files using the quickconvertcommand-line tool included in this package, i.e.convertmy_file1.txtmy_file2.textTo reverse the conversion and get a text file from a Numpy file, use the-roption. You can specify the output file name using-o OUTPUT.convert-rmy_numpy.npy-omy_text_file.txtThe tool can also remove original files as soon as they are converted if you
specify the--deleteor-doption.convert-dfile*.txtDocumentationOther options are available, usepsd --helporconvert --helpto show
documentation.Developped by Jean-Baptiste Bayle (APC/CNES/CNRS),bayle@apc.in2p3.fr.
Package: psd2
psd2Estimation of power spectral density characteristics using Welch's methodThe function psd2.py from Python module psd2 estimates power spectral density characteristics using Welch's method. This function is just a wrap of the scipy.signal.welch function with estimation of some frequency characteristics and a plot.
The psd2.py returns power spectral density data, frequency percentiles of the power spectral density (for example, Fpcntile[50] gives the median power frequency in Hz); mean power frequency; maximum power frequency; total power, and plots power spectral density data.Installationpipinstallpsd2Orcondainstall-cduartexyzpsd2Examples#Generate a test signal, a 2 Vrms sine wave at 1234 Hz, corrupted by# 0.001 V**2/Hz of white noise sampled at 10 kHz and calculate the PSD:>>>fs=10e3>>>N=1e5>>>amp=2*np.sqrt(2)>>>freq=1234.0>>>noise_power=0.001*fs/2>>>time=np.arange(N)/fs>>>x=amp*np.sin(2*np.pi*freq*time)>>>x+=np.random.normal(scale=np.sqrt(noise_power),size=time.shape)>>>psd2(x,fs=freq);psd2.ipynbHow to cite this workHere is a suggestion to cite this GitHub repository:Duarte, M. (2020) psd2: A Python module for estimation of power spectral density characteristics using Welch's method. GitHub repository,https://github.com/demotu/psd2.And a possible BibTeX entry:@misc{Duarte2020,  
    author ={Duarte, M.},
    title ={psd2: A Python module for estimation of power spectral density characteristics using Welch's method},  
    year ={2020},  
    publisher ={GitHub},  
    journal ={GitHub repository},  
    howpublished ={\url{https://github.com/demotu/psd2}}}LicenseThe non-software content of this project is licensed under aCreative Commons Attribution 4.0 International License, and the software code is licensed under theMIT license.
Package: psd2html
PSD to HTML converter based on [psd-tools](https://github.com/psd-tools/psd-tools)InstallUsepipto install:pip install psd2htmlUsage### As a command-line toolThe package comes with a command-line tool:psd2html input.psd output.htmlWhen the output path is a directory, or omitted, the tool infers the output
name from the input:psd2html file.psd                 # => file.html
psd2html file.psd dir/            # => dir/file.html
psd2html file.psd dir/file1       # => dir/file1.html
psd2html file.psd dir/file1.html  # => dir/file1.html### As a python libraryExample:from psd2html import PSD2HTMLwith open(‘file.psd’, ‘rb’) as f:converter = PSD2HTML(f)
html = converter.html
html_string = converter.html_strNotes:Not all PSD layers are being converted to HTML elements. Current release only converts the [TypeLayer](https://psd-tools.readthedocs.io/en/latest/reference/psd_tools.api.layers.html#typelayer) to HTML, all the others types i.e Artboard, PixelLayer, ShapeLayer and SmartObjectLayer are rendered as png images.Future releases will include support for other types of layers.
Package: psd2pngs
psd2pngsIntroductionpsd2pngs converts a psd file to png files while maintaining the layer hierarchy and performing the appropriate renaming, using multiprocessing.
You do not have to read this long docs, just downloadand open a psd file with it!ExampleNote that this GIF is in fast forward.UsageUsing as an appJust open.psdfile with this app. (Executable versiononly.)Alternatively, this app can also be used with command prompt.>psd2pngs-h
Usage:psd2pngs[OPTIONS]PSD_PATH

Options:-v,--versionShowtheversionandexit.-o,--outPATHOutputdirectorypath.Ifnotspecified,outputtothesamedirectoryasthePSDfile.-s,--single-processForcenottousemultiprocessing.-t,--tasks-countINTEGERNumberoftasks.RecommendedtobelessthanorequaltothenumberofCPUs(32)becausetheprocessmaximizestheuseofCPUs.-j,--jsonOutputJSONfilecontaininglayerinformationinsnakecase.-jc,--json-camel-caseOutputJSONfilecontaininglayerinformationincamelcase.-h,-?,--helpShowthismessageandexit.The type of content of Output JSON file (snake_case) is the following.classLayerInfo(NamedTuple):local_path:strname:strsafe_name:stris_visible:boolis_group:boolchildren:"Iterable[LayerInfo]"The type of content of Output JSON file (camelCase) is the following.classLayerInfo(NamedTuple):localPath:strname:strsafeName:strisVisible:boolisGroup:boolchildren:"Iterable[LayerInfo]"Using as a moduleSee thedocumentation (readthedocs.io).InstallationOption 1. Executable versionDownload the latest release fromReleases.Option 2. Python version using pip installpy-mvenvvenv"./venv/Scripts/Activate.bat"pipinstallpsd2pngs
psd2pngsfrom.psdOption 3. Python version using git clonegitclonehttps://github.com/34j/psd2pngs.gitcd./psd2pngs
py-mvenvvenv"./venv/Scripts/Activate.bat"pipinstall-rrequirements.txt
python-mpsd2pngsfrom.psdOption 4. Executable version - Compiling yourself using pippy-mvenvvenv"./venv/Scripts/Activate.bat"pipinstallpsd2pngs
pipinstallpyinstaller
pyinstallervenv/Lib/site-packages/psd2pngs/__main__.py--onefile-npsd2pngs
move"./dist/psd2pngs.exe""./"./psd2pngsfrom.psdOption 5. Executable version - Compiling yourself using gitgitclonehttps://github.com/34j/psd2pngs.gitcd./psd2pngs
py-mvenvvenv"./venv/Scripts/Activate.bat"pipinstall-rrequirements.txt
pipinstallpyinstaller
pyinstallerpsd2pngs/__main__.py--onefile-npsd2pngs
move"./dist/psd2pngs.exe""./"./psd2pngsfrom.psd日本語の説明psd2pngsは、psdファイルをレイヤーの階層構造を維持したままpngファイルに変換し、適切なリネームを行うアプリケーションです。
1ファイルにまとまったWindows用実行ファイルpsd2pngs.exeも配布しています。インストール方法Releasesから最新のリリースをダウンロードします。使い方psdファイルを右クリックし、プログラムから開くを使ってこのアプリで開きます。
Package: psd2svg
PSD to SVG converter based onpsd-toolsandsvgwrite.InstallUsepipto install:pip install psd2svgUsageThe package comes with a command-line tool:psd2svg input.psd output.svgWhen the output path is a directory, or omitted, the tool infers the output
name from the input:psd2svg input.psd output/  # => output/input.svg
psd2svg input.psd          # => input.svgWhen--resource-pathflag is specified, all png resources are exported
to the path specified by--resource-path:psd2svg input.psd output.svg --resource-path .
# => output.svg, xxx1.png, ...

psd2svg input.psd output/ --resource-path .
# => output/input.svg, output/xxx1.png, ...

psd2svg input.psd output/ --resource-path=resources/
# => output/input.svg, output/resources/xxx1.png, ...

psd2svg input.psd svg/ --resource-path=../png/
# => svg/input.svg, png/xxx1.png, ...APIThe package contains high-level conversion functionpsd2svg:frompsd2svgimportpsd2svg# File IO.psd2svg('path/to/input.psd','path/to/output/')# Stream IO.withopen('input.psd','rb')asfi:withopen('output.svg','w')asfo:psd2svg(fi,fo)# psd_tools IO.frompsd_toolsimportPSDImagepsd=PSDImage.load('path/to/input.psd')svg=psd2svg(psd)print(svg)# Additionally, individual layers can be directly rendered.layer_svg=psd2svg(psd[3])print(layer_svg)The package also has rasterizer module to convert SVG to PIL Image:frompsd2svg.rasterizerimportcreate_rasterizerrasterizer=create_rasterizer()image=rasterizer.rasterize(svg)image.save('path/to/output.png')The rasterizer requires one of Selenium + ChromeDriver, Apache Batik, or
Inkscape. Make sure to install them beforehand.TestInvoke tox:toxStorage backend supportTo use AWS S3 storage backend:pip install psd2svg[s3]or:pip install boto3The tool can specify URL instead of file path (S3 requiresboto3):psd2svg http://example.com/input.psd
psd2svg s3://bucketname/path/to/input.psd s3://bucketname/path/to/output/To use HDFS storage backend:pip install psd2svg[hdfs,kerberos]NotesSVG 1.1 does not cover all the blending modes in Photoshop (e.g.,linear-dodge)Filter effects are approximation. Some effects are not implemented.Most of adjustments layers are not implemented.Smart object filters are not implemented.Browser support: SVG rendering quality greatly differs depending on the
browser. Chrome tends to be the best quality.APIs of this tool is NOT thread-safe.To use HDFS storage backend, Python 2.7 environment is needed
and should be Kerberos-enabled and only read access is available.
Package: psdaq-control-minimal
A simple repackaging of the lcls2 daq code athttps://github.com/slac-lcls/lcls2with minimal dependencies needed for controlling the LCLS2 daq from a script, as is done in TMO and RIX’s hutch pythons.This pares down the requirements, unlinks the script entrypoints, and exposes only thepsdaq.controlsubmodule.RequirementsThis works with any version of Python >= 3.6.It requires onlypyzmqfor communicating with the DAQ, andophydandblueskyfor hutch python scanning.Installationconda installpsdaq-control-minimal-cpcds-tagorpip installpsdaq-control-minimalMaintenanceCreate a new tag on this repo that matches a tag onhttps://github.com/slac-lcls/lcls2/releasesto trigger a new build.To test a build locally, you must first run./generate_minimal_package.shto clone and set up the minimal set of files.
If you’ve already done this before, you must manually clear the oldlcls2andpsdaqfolders.Directory StructureThis repo is based the PCDS python cookiecutter. See the following github page for more info:cookiecutter-pcds-python
Package: psdelivery
📦 psdeliverypipinstallpsdeliveryIntroduction여러 코딩 사이트의 코딩 문제들을 크롤링하는 라이브러리 입니다. 초기 버전이라 기본 수준의 기능만 지원하지만. 차후 더 많은 기능들을 추가할 예정입니다. 왜냐면 재가 제 메인 프로젝트에 쓸 거니깐요.🙋‍♂️ FunctionsImplemented해당 사이트에서 코딩문제를 가져올 수 있습니다.백준 (solved.ac)리트코드 (leetcode)파이썬 프로젝트에 모듈로 사용할 수 있고, CLI 환경에서도 바로 사용할 수 있습니다.CLI 환경해서 명령어를 통해 실행할 경우, 결과 데이터는 JSON으로 저장됩니다.Will be Implemented해당 사이트에도 코딩문제를 가져올 예정입니다.코드포스 (codeforces)해커랭크 (hackerrank)여러 페이지 범위의 문제 리스트를 뽑아올 수 있습니다.해당 사이트의 모든 문제들도 하나의 명령어로 가져올 수 있습니다.특정 문제에 대한 세부 정보를 가져올 수 있습니다.알고리즘 태그를 가져올 수 있습니다.⭐ Required반드시 크롬이 설치되어 있어야 합니다.Debian계열의 경우, bin디렉토리에 크롬을 설치하는 Shell Script가 있습니다.파이썬 버전은 반드시3.10이상이어야 합니다.💽 How To Install For Developer크롬과 파이썬이 설치되어있다는 가정 하에 설명합니다.requirements.txt를 통해 패키지를 설치합니다.끗UsageAs Command Line✔️Version 확인하기python-mpsdeliveryversion# 0.1.0📚문제 리스트 가져오기python -m psdelivery getlist -t <topic> -sp <page index> -o <output json file>Options-t(--topic): 코딩 페이지 사이트를 명시합니다. 데이터를 가지고올 수 있는 사이트는 다음과 같습니다.백준:baekjoon또는solved.ac리트코드:leetcode-sp(--single-page): 페이지 인덱스를 나타냅니다. 해당 옵션을 명시하지 않으면 1페이지의 문제 리스트를 가져옵니다.-o(--output): 코딩문제 데이터를 저장할 파일 루트를 명시합니다.examplepython -m psdelivery getlist -t baekjoon -sp 3 -o output.jsonAs Python ModulefrompsdeliveryimportPsDelivery"""PsDelivery 객체 생성topic은 크롤링할 사이트 이름을 입력합니다.백준: baekjoon 또는 solved.ac리트코드: leetcode"""crawler=PsDelivery(topic='leetcode')"""특정 페이지의 문제 리스트를 가져옵니다.page:가져올 페이지 쪽수를 입력합니다. 반드시 1 이상이어야 합니다.serialize:일반적인 리턴된 리스트의 요소는 ProblemItem이라는 객체 입니다.serialize=True로 설정하면 ProblemItem을 Dict 형태로 직렬화 합니다.Default값은 False 입니다."""result=crwaler.get_list_by_single_page(page=1)"""return: [<ProbmeItem>, <ProblemItem>, ...]"""result_as_json=crawler.get_list_by_single_page(page=2,serialize=True)"""return: [<Dict>, <Dict>, ...]"""
Package: ps.diazo.vanilla
Propertyshelf Vanilla ThemeThis installable Diazo Theme product delivers a general and mobile-ready implementation of a html5 template for Plone with activated Listing embedding tools. It is intended to deliver a library of standard features, which can be re-used in different customized variations.PlatformPlone CMS > 4.3Featuresmobile-readyconfigurable via Diazo Parametersfeature-library for custom implementationsCarousel supportCovers support and improvementsfull support of propertyshelfs embedding featuresDependenciesplone.app.theming (Diazo support)Optional dependenciesplone.mls.listingps.plone.mlsmls.apiclientcollective.coverProducts.CarouselSetup StepsIf the theme is installed via ZIP file upload, please deactivate the following Plone default css files in portal_css via ZMI:reset.csspublic.cssOptionsYou can adjust the following Diazo parameters in Advanced settings of the “Theming” in Site Setup.header_classnormallightdarkDefault:header_class = string:normalnr_phone_showThis phone number shows on header contact informationDefault:nr_phone_show = string:+166 1418 7657nr_phoneIs dialed by apps when click on header phone numberDefault:nr_phone = string:16614187657emailThis email is use in the header contact imformationDefault:email = string:info@propertyshelf.comslider_fullscreentruefalseDefault:slider_fullscreen = string:falseContributorsJens Krause,jens@propertyshelf.comKantanart Wanichkajornkul,kantanart@propertyshelf.comThomas Massmann,thomas@propertyshelf.comChangelog1.5.1 (2016-05-25)Fixed wrong HiddenProfiles utility name.1.5 (2016-05-25)Add support for plone.mls.listing > 1.7.Code cleanup.1.4 (2015-10-06)Auto-balance ListingCollections in coversMinified scripts and styles1.3 (2015-07-28)Google-analytics script supportImprove standard style (h1-h4)Price style for ListingTilesBugfixes1.2 (2015-07-07)Improve on cached developments summary imagesAdd fullscreen carousel1.1 (2015-06-16)Update README.rst1.0 (2015-06-11)IncludeDevolpments header embedding0.9 (2015-06-04)table release for shared hosting0.8.3 (2015-06-02)CSS cleanupSupport small-screen PS Jssor Slider0.8.2 (2015-06-02)Fix javascript for improving ListingDetailsCatch error on Developments JS0.8.1 (2015-06-02)Remove console.log statements from support.js0.8 (2015-06-02)Enable calculated height for ListingCollection Tiles0.7.1Fix broken 0.7 release0.7Fix broken 0.6 release0.6Improved ListingQuickSearchImproved ListTiles (for covers)0.5New default phone nr. in diazo parametersBordered listing style (ListingResults)0.4Fixed missing div before content header0.3Bugfixes Listing Details0.2Improved default styles & icons0.1Initial set of styles and rulesInitial release [Solomonic].Use buildout.plonetest based package buildout. [tmassmann]Fixed codeanalysis error messages. [tmassman]Added documentation skeleton. [tmassman]
Package: psdist
psdistThis repository is a collection of analysis and visualization methods for six-dimensional position-momentum space (phase space) distributions.Installationhttps://pypi.org/project/psdist/ExamplesSee/examplesfolder andhttps://austin-hoover.github.io/psdist/.Related packageshttps://github.com/openPMD/openPMD-viewerhttps://github.com/bwheelz36/ParticlePhaseSpacehttps://github.com/ColwynGulliford/distgenhttps://aplpy.readthedocs.io/en/stable/fitsfigure/slicing.html
Package: psdl
psdl is a package that wraps the excellent SDL2 module in an easy to use python
interface.Note that this project is still in its super early stages, theres lots of stuff
still left to be wrapped.Why PSDL?You may be already knowing that there are many SDL wrappers out there, from stuff
like PySDL2 to pygame. What makes PSDL different? Well, PSDL aims to be a wrapper
“of right thickness”. There are some SDL wrappers that are too thin, and they
expose the C-level details to python, which is not that elegant. Also, they
directly copy the SDL API, which is un-pythonic.
And there are SDL wrappers that are too thick, and they dont export the SDL
API at all, they have their own API.PSDL aims to export the SDL API as directly as possible, while also “pythonifying”
it. Let us consider a typical SDL function that looks likeSDL_SomeFunctionForSomething. PSDL will export it, by stripping the initalSDL_(because python has namespaces, unlike C) and changing the style of the
function name to something that looks more pythonic. The function will look likepsdl.some_function_for_somethingfrom the PSDL side. Similarly, SDL constants
are exported by just stripping the initialSDL_part of it,SDL_SOME_CONSTANTbecomespsdl.SOME_CONSTANT. While SDL provided enums, PSDL does not export the
enums directly, it just exports the constants within it.Coming to structures, PSDL does different stuff based on the context. Since C is not
object oriented, you will find this style of coding commonly used in SDL.SDL_someobj *obj;
SDL_CreateSomeObj(obj, someargs);
SDL_SomeMethod(obj, moreargs);
SDL_AnotherMethod(obj, args, moreargs);
SDL_DestroyObj(obj);We can take advantage of python OOP, and psdl will export the samething like::obj = psdl.SomeObj(args)
obj.some_method(moreargs)
obj.another_method(args, moreargs)Notice the naming convention adopted here. Also notice that in python, we need
not explicitly deallocate objects, python being a high-level language, does that
automatically for us.Installationpsdl can be installed via pip, using the following command,pip3 install psdl.
Note that currently, psdl does not provide binary “wheels” on PyPI, so the pip
command will build psdl from source. For that, check out the section belowBuilding from sourceWindowsThe build process is pretty straight forward on windows. You just need to have
the MSVC C compiler set up correctly. psdl is automatically going to get all its
dependencies (ie, its gonna download SDL from the official website) and automatically
build psdl.Mac/LinuxOn Mac/linux too, the build process aint complicated. All you need to have is a C
compiler (which is usually present on most systems) and SDL installed via your
package manager. Then psdl will easily install from source.Advanced Build OptionsYou can set two environment variables,PSDL_INCLUDE_DIRandPSDL_LIB_DIRto
optionally specify paths to SDL include and library directories, respectively. This
will be used by PSDL when it attempts to build from source.TODOTheres still lot left to do, like I said earlier, this project is still in its super
early stages. There needs to be docs, tests, and examples written, apart from the
code that needs to be written.