Saravanan666/pypi-org huggingface dataset:
Package: sjoa
sjoasjoais a powerful command-line tool designed to read metadata from torrent
files or magnet URIs. It provides a simple and efficient way to extract
information about torrents without the need to download the actual content.The Sjoa is a river in Innlandet county, Norway and is one of the best
whitewater rafting rivers in Europe renowned for its fast-moving, turbulent
waters with Class II-V rapids depending on the water level.Source:WikipediaandOARSThe wordsjoawas chosen as a play on words: the term "torrent" is often used
to describe a fast-flowing stream or river, typically characterized by strong
currents and rapid water movement.Installationsjoais implemented in Python and can be installed using pip, the Python
package manager. To installsjoa, simply run:$pipinstallsjoaUsageOnce installed, you can usesjoafrom the command line.$ sjoa -t examples/debian-12.2.0-amd64-DVD-1.iso.torrent
 Name            debian-12.2.0-amd64-DVD-1.iso
 Hash            267d63ffd31770e467f8d985a86633f05502c10d
 Size            3.72 GiB
 Pieces          15237 of length 256 KiB (last piece 64.00 KiB)
 Creation        2023-10-07 12:03:00 by mktorrent 1.1
 Comment         "Debian CD from cdimage.debian.org"
 Tracker URL(s)  • http://bttracker.debian.org:6969/announce
 Webseed URL(s)  • https://cdimage.debian.org/cdimage/release/12.2.0/amd64/iso-dvd/debian-12.2.0-amd64-DVD-1.iso
                 • https://cdimage.debian.org/cdimage/archive/12.2.0/amd64/iso-dvd/debian-12.2.0-amd64-DVD-1.iso
 Files           ┌───────────────────────────────────────────────────────────────────────┬─────────────────────┐
                 │ • debian-12.2.0-amd64-DVD-1.iso                                       │ 3.72 GiB            │
                 └───────────────────────────────────────────────────────────────────────┴─────────────────────┘$ sjoa -m "magnet:?xt=urn:btih:2c6b6858d61da9543d4231a71db4b1c9264b0685&dn=ubuntu-22.04-desktop-amd64.iso&tr=https%3A%2F%2Ftorrent.ubuntu.com%2Fannounce&tr=https%3A%2F%2Fipv6.torrent.ubuntu.com%2Fannounce"
 Name            ubuntu-22.04-desktop-amd64.iso
 Hash            2c6b6858d61da9543d4231a71db4b1c9264b0685
 Tracker URL(s)  • https://torrent.ubuntu.com/announce
                 • https://ipv6.torrent.ubuntu.com/announceLicenseCopyright 2023 Martin Simon

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.Buy me a coffee?If you feel like buying me a coffee (or a beer?), donations are welcome:BTC : bc1qq04jnuqqavpccfptmddqjkg7cuspy3new4sxq9
DOGE: DRBkryyau5CMxpBzVmrBAjK6dVdMZSBsuS
ETH : 0x2238A11856428b72E80D70Be8666729497059d95
LTC : MQwXsBrArLRHQzwQZAjJPNrxGS1uNDDKX6
Package: sjrpc2
Simple JSONRPC-2.0JSONRPC-2.0  PYTHON implementation, including memory communication(queue), TCP communication(zero-mq), HTTP communicationFree software: MIT licenseDocumentation:https://sjrpc2.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-05-27)First release on PyPI.
Package: sjs
This package contains an emulator for SGE, including scripts to emulate qsub, qdel, and qstat.This package was written to support development of software that depends on SGE on a machine that doesn’t (easily) support SGE, so the feature set and optimization is by design very limited.  I don’t recommend using this as a production job scheduler.UsageSet SJS_ROOT to the name of a directory that will contain information about the scheduler (its configuration, the queue, and the logs).  This directory should not exist, as it will be created when you initialize it with sjs_qconf:sjs_qconf init <number of slots>The number of slots can be changed usingsjs_qconf slots:sjs_qconf slots <number of slots>Jobs can be submitted and deleted usingsjs_qsubandsjs_qdelas you would withqsubandqdel, respectively, and a list of pending and running jobs can be displayed withsjs_qstat.For complete SGE emulation, link to the sjs_* scripts using the SGE names from somewhere in your path (e.g./usr/local/bin/sjs_qsub->/usr/bin/qsub).
Package: sjSDM-py
sjSDM - Fast and Accurate Joint Species distribution ModelingCurrently we don't provide specifically a API for joint species distribution models. However, it's just a deep multivariate probit model with one layer (example below).We provide a R package with an API focused on JSDMs which is availablehere.References:Pichler, M., & Hartig, F. (2020). A new method for faster and more accurate inference of species associations from novel community data. arXiv preprint arXiv:2003.05331.Install instructionsDependencies:PyTorch >= 1.7, seePyTorchfor install instructions.pip install sjSDM_pyExamplelinear jSDM:import sjSDM_py as sa
import numpy as np
Env = np.random.randn(100, 5)
Occ = np.random.binomial(1, 0.5, [100, 10])

model = sa.Model_base(5) # input_shape == number of environmental predictors
model.add_layer(sa.layers.Layer_dense(hidden=10)) # number of hidden units in the layer == number of species
model.build(df=5, optimizer=sa.optimizer_adamax(lr=0.1, weight_decay = 0.01)) # df = degree of freedom 
model.fit(X = Env, Y = Occ)
print(model.weights_numpy)
print(model.get_cov())For species intercept, use 'bias=True' in 'Layer_dense(...)'.We recommend setting 'df = number of species / 2.'
Package: sjtrade
sjtradeshioaji day trading demo packageInstallpip install sjtradeGet startedInit Shioaji and SjTraderimportshioajiassjimportsjtradeapi=sj.Shioaji()accounts=api.login(**login_kws)sjtrader=sjtrade.SJTrader(api)Set Position Filepath and Preview Positionsjtrader.position_filepath="position.txt"sjtrade.io.file.read_position(sjtrader.position_filepath)Set Custom Position FileReaderfromsjtrade.io.fileimportread_csv_positionsjtrader.read_position_func=read_csv_positionsjtrader.position_filepath="position.csv"sjtrader.read_position_func(sjtrader.position_filepath)Set entry_pct stop_profit_pct stop_loss_pctsjtrader.entry_pct=0.05sjtrader.stop_profit_pct=0.095sjtrader.stop_loss_pct=0.09Start sjtradersjtrader.start()What do sjtrader start actually dosjtrader.start??Signature: sjtrader.start()
Source:   
    def start(self):
        positions = read_position(self._position_filepath)
        self.api.set_order_callback(self.order_deal_handler)
        sleep_until(8, 45)
        self.place_entry_order(positions, self.entry_pct)
        sleep_until(8, 54, 59)
        self.api.quote.set_on_tick_stk_v1_callback(self.cancel_preorder_handler)
        sleep_until(8, 59, 55)
        self.api.quote.set_on_tick_stk_v1_callback(self.intraday_handler)
        sleep_until(13, 25, 59)
        self.open_position_cover()
File:      ~/.pyenv/versions/miniconda3-latest/lib/python3.7/site-packages/sjtrade/trader.py
Type:      methodSimulationall order will be place as success and deal when price touchapi = sj.Shioaji()
accounts = api.login(**login_kws)
sjtrader = sjtrade.SJTrader(api, simulation=True)
sjtrader.position_filepath = "position.txt"
sjtrade.io.file.read_position(sjtrader.position_filepath)
sjtrader.entry_pct = 0.05
sjtrader.stop_profit_pct = 0.095
sjtrader.stop_loss_pct = 0.09
sjtrader.start()NotificationspipinstallnotifiersCheck notifiersfromnotifiersimportget_notifiernotifier=get_notifier("telegram")TELECHATID=""TELEBOT_TOKEN=""PARAMS={"chat_id":TELECHATID,"token":TELEBOT_TOKEN}notifier.notify(message="test",**PARAMS)Check loggerfromloguruimportloggerfromnotifiers.loggingimportNotificationHandlerhandler=NotificationHandler("telegram",defaults=PARAMS)logger.add(handler,level="INFO")logger.info("logger test")Developer's guideflit install -s
Package: sjtu-automata
sjtu-automata注意！此版本为BETA版，未经过严格测试，可能存在BUG，如有问题请提交issue由于教务系统更新，v0.4.0为临时解决版本，周末会优化用户体验v0.4.0更新：教务系统限制大约在30-60分钟左右可能需要重新登陆，暂时未解决，待周末重构。上海交通大学抢课脚本V2协议分析：https://github.com/MXWXZ/sjtu-automata/blob/master/Protocol%20analysis%20v2.md使用脚本你可以做到:heavy_check_mark: 无人值守自动抢课:heavy_check_mark: 并发抢课提升成功率:heavy_check_mark: 卡时间准时抢课使用脚本你不能做到:x: 违反选课规则选课(0day fucked):x: 提高您的网速:x: 保证一定可以抢到课系统环境测试程度最佳支持：Manjaro with python 3.7.3 / Ubuntu 18.04 LTS with Python 3.6.7Linux > Windows >>macOS=0（没钱无测试）安装pip3 install sjtu-automata升级pip3 install sjtu-automata --upgrade[可选]验证码自动识别Windows可以不装，Linux如无图形界面且无法通过其他方式打开captcha.jpeg文件需要安装。Arch系安装下面两个包：tesseract、tesseract-data-engUbuntu 18.04：sudo apt install tesseract-ocr libtesseract-dev其他版本/发行版/Windows等自行看文档：https://github.com/tesseract-ocr/tesseract/wiki简单使用说明由于选课系统再次更新，需要传递的参数改变，因此建议使用油猴脚本获取ID：https://www.tampermonkey.net/插件安装完成后点击这里进入脚本安装页面：https://github.com/MXWXZ/sjtu-automata/raw/master/sjtu-automata.user.js下面的教程以安装插件之后为准，如果不安装油猴脚本也可以自行查看网页源码提取相关ID查看课程号和教学班：想选的课“教学班”第二行点击复制ID即可复制课号+教学班号查看课程类型：标签页第二行的字符串即为课程类型使用命令选课，格式为autoelect [课程类型ID] [课程号ID] [256位教学班ID]：autoelect 01 AAAA... aaaa... 10 BBBB bbbb...上述命令将会选01课程类型下的AAAA课的aaaa（省略256位）教学班和10课程类型下的BBBB课的bbbb（省略256位）课，如果需要更多可以在后面继续添加。注：程序运行过程中输入s可以查看选课状态抢课说明本程序所有操作均保证当前课程不会减少，即无论你是否已经选上课、无论是否人满等各种情况都不会影响已选课程。换言之，无论何时均保证课程只多不少，重复提交不会影响当前课表。程序运行后选课将会自动进行，如果失败自动重试，如果课程已满将自动等待并且定时刷新，直到抢成功或者用户退出为止可以提前开上程序，如果没有开放选课将会自动等待并定时刷新，可以节省登陆的时间所有指定的课程会同时进行选课，每个课程可占一个或多个线程进行选课增加成功率（多线程一般在网卡的时候才有必要）参数说明CLI使用：autoelect [OPTIONS] [CLASSTYPE-CLASSID-JXBID]参数长参数形式说明-v--version显示版本--no-update关闭更新检查-o--ocr使用OCR识别验证码--print-cookie打印登陆cookie-d--delay两次尝试选课间隔（默认1s）-c--check-delay检查选课是否开放的延迟(默认3s)-n--number每个课程的线程数（默认为1）-h--help显示帮助CLASSTYPE、``CLASSID、JXBID`成组出现，可以出现多组同步进行，但至少有一组CLASSTYPE：2位课程类型CLASSID：课号IDJXBID：256位教学班ID
Package: sjtuautorun
交我润项目简介基于雷电命令行的交我办自动跑步脚本，脱胎于AutoWSGR近期更新完成脚本基本逻辑，实现单个短程自动跑步2024/02/26使用本项目未来开发任务随机化跑步数据调整图像识别模块，实现自动启动、结束不同跑步策略（如光体、南体跑圈等）
Package: sjtu-lib-booking
SJTU Library BookingA simple script that helps you book a seat in library.Get StartedCreate a json file that contains all your accounts. Eg.{"<username>":"<password>"}Run the script.$sjtu-lib-bookingconfig.jsonBuilt withPySJTU- The Python iSJTU client for Humans.LicenseThis project is licensed under GNU General Public License v3.0 - see theLICENSE.mdfile for details.—💖—Built with love by LightQuantum
Package: sjtu-questionnaire
SJTU QuestionnaireChinese Simplied / 简体中文A simple unofficial Python implementation ofSJTU Questionnaire API. Supports multi-processing.Installationpipinstallsjtu-questionnaireQuick StartimportsjtuqasQ# Create form objectform=Q.SJTUQuestionnaire("https://wj.sjtu.edu.cn/api/v1/public/export/83f581b4cfd3be8897bcabb23b25ef30/json")# Get all answersanswers=form.get_all_data()# Get all data as a listprint("# Answers:",len(answers))# 1. Only Kunologist have answered this questionnaire!DocumentationThe documentation is generated usingpydoctor, hosted onGitHub Pages
Package: sjtu-schedule-exporter-cli
SJTU Schedule Exporter CLIA simple utility to export your SJTU schedule in ICS format.Get Started$pipinstallsjtu-schedule-exporter-cli
$sjtu-schedule-exporter-cliScreenshotBuilt WithPySJTU- The Python iSJTU client for Humans.ics.py- A pythonic and easy iCalendar library.Blessed- An easy, practical library for making terminal apps.Arrow- Better dates & times for PythonLicenseThis project is licensed under GNU General Public License v3.0 - see theLICENSE.mdfile for details.—💖—Built with love by LightQuantum
Package: sjvisualizer
sjvisualizer 📊sjvisualizer is a data visualization and animation library for Python.https://github.com/SjoerdTilmans/sjvisualizer/assets/37220662/a9a01f5b-50f4-411f-8e7c-dcd4a805501bPlease find the catalogue examplehereto run the above animation. sjvisualizer currently supports the following chart types:Bar racesAnimated pie chartsAnimated stacked bar chartsAnimated line chartsMore chart types to follow! If you find sjvisualizer useful, please consider starring ⭐ the project on GitHub!RoadmapIf you like this project, please concider supporting me using PayPalPayPal.Learn sjvisualizerThere are two ways of learning sjvisualizer:Find additional examples and full documentation on mywebsiteOr follow my course onUdemyInstallationsjvisualizer is now available on pypi! Simply use pip to install it:pip install sjvisualizerUsagesjvisualizer is a free and open-source data animation library, please include the following attribution in any publications you use it in.Made with sjvisualizer, the open-source data animation library for PythonSample codefromsjvisualizerimportCanvasfromsjvisualizerimportDataHandlerfromsjvisualizerimportPieRaceimporttimeimportjsondefmain(fps=60,duration=0.35):number_of_frames=duration*60*fps# load data from Excel filedf=DataHandler.DataHandler(excel_file="<Path to EXCEL DATA FILE>",number_of_frames=number_of_frames).df# create canvas object, we will use this to draw our elements tocanvas=Canvas.canvas()# add bar chartbar_chart=PieRace.pie_plot(canvas=canvas.canvas,df=df)canvas.add_sub_plot(bar_chart)# add static textcanvas.add_title("TITLE",color=(0,132,255))canvas.add_sub_title("SUB-TITLE",color=(0,132,255))# add time indicationcanvas.add_time(df=df,time_indicator="month")canvas.play(fps=fps)if__name__=="__main__":main()Support this projectIf you like this project, please concider supporting me using PayPalPayPal.ContributingContributions are always welcome! Here are some ways to get involved:Create an issue to report a bug or suggest a new feature.
Fork the repository and create a new branch to work on.
Submit a pull request to request a merge of your changes.
Please make sure to write clear commit messages.Licensesjvisualizer is released under the MIT License. See the LICENSE file for more details.ContactIf you have any questions or suggestions regarding sjvisualizer, post it on myforum.
Package: skadi
skadi: Financial Machine LearningSkadi isAilares, Inc.in-house quantitative research infrastructure.Ailares, Inc.develops quantitative investment strategies to bring investors risk-adjusted return.Free software: Apache Software License 2.0Documentation:https://ailares-skadi.readthedocs-hosted.com/en/latest/Â© 2019 Ailares, Inc. All rights reserved.History0.1.0 (2019-10-27)First release on PyPI.
Package: skadoo
skadooPython library for building command line programs.Installationpip install skadooUsageIn your Python script useskadooto create command line arguments.my_script.pyimportskadoo# create flag argsmy_flag=skadoo.create_flag(name="my flag",description="my flag argument")# create root argumentsmy_root=skadoo.create_root(name="My Root",description="my root argument",flags=(my_flag))if__name__=="__main__":print("root used:",my_root.name,f"flag ({my_flag.name}) value:{my_flag.value}")# orprint("root used:",my_root.name,f"flag ({my_root.flags["my flag"].flag}) value:{my_root.flags["my flag"].value}")Runpython my_script.py my_root --my-flag="value"
Package: skafos
Skafos Python SDKSkafosis the platform for automating the delivery of machine learning models to mobile devices.
We provide this SDK as a Python wrapper for uploading, fetching, and listing model versions from the platform.If you're a Data Scientist or Machine Learning Engineer, you're the one entrusted with building robust machine
learning models. This SDK is an interface to the Skafos platform, allowing you to do the
following from your Python development environment:Upload a model version: Save a new version of your machine learning model to the Skafos platform,
making it available for mobile delivery.Deploy a model version: Deliver a saved model version to your mobile application over-the-air.Fetch a model version: Download a previously saved version of your machine learning model from
the Skafos platform.List model versions: For each of your apps and models, see what model versions you have previously
saved to the Skafos platform.Supported PlatformsOperating SystemsThis is not an exhaustive list of OS that are compatible withskafos. These are the one's we've explicitly tested:macOS 10.12+Linux (Ubuntu 16.0.4+)Cloud PlatformsGoogle Colab + Google CloudIBM WatsonAWS SagemakerMicrosoft AzureSystem RequirementsPython 3+Pip(to downloadskafosfrom the Python Package Index)InstallationYou can installskafosdirectly from the Python Package Index(PyPI).pipinstall-UskafosOnce you've installedskafos, you can import the package in your Python environment.importskafosskafos.get_version()# returns the current SDK versionFor more details on installation and usage, see the package documentation.DocumentationThepackage documentationcontains more details on how to use the Skafos SDK.Theplatform documentationcontains more details on how Skafos delivers
and manages machine learning models on mobile devices.Example: Uploading a Model Versionimportosfromskafosimportmodels# Set your API Token first for repeated useos.environ["SKAFOS_API_TOKEN"]="<YOUR-SKAFOS-API-TOKEN>"# You can retrieve this info with skafos.summary()org_name="<YOUR-SKAFOS-ORG-NAME>"# Example: "mike-gmail-com-467h2"app_name="<YOUR-SKAFOS-APP-NAME>"# Example: "Recommender-App"model_name="<YOUR-MODEL-NAME>"# Example: "RecommenderModel"# Upload model version to Skafosmodel_upload_result=models.upload_version(files="<path(s)-to-model-file(s)>",# Example: ["../my_recommender_model.mlmodel"]org_name=org_name,app_name=app_name,model_name=model_name)Need Help?Didn't find something you need? Confused by something? Need more guidance?Please contact us with questions or feedback! Here are two ways:Signup for our Slack ChannelFind us on Reddit
Package: skal
Introduction============Skal is a wrapper for the argparser library to make it easier to writeapplications that uses commands with subcommands, much like git andheroku does.Skal can be used with different combinations of command sources; a subclass ofSkalApp, any number of modules and any number of packages. Currently usage withclasses and modules are supported.The test cases are a good source of different ways to use Skal appartfrom what is described here.Subclass as command source==========================A custom subclass of SkalApp is one way to get some commands added, andmay be the shortest version.In file myapp.py:```pythonfrom skal import SkalApp, commandclass MyApp(SkalApp):@commanddef hello(self):print('hello')@commanddef yes(self):print('yes')if __name__ == '__main__':MyApp().run()```Running the program:```> python myapp.py hellohello> python myapp.py yesyes```Modules as command source=========================There are two ways in which modules can be used to source commands;either as a flat hirearchy where every function in every module getsadded or with a bit of hirearchy where each module becomes a command andits functions becomes subcommands. Using either is determined by how themodule names are passed to the SkalApp constructor, and any combinationis also valid. The only advice is to specify a overridden version anddescription string for the whole app, as Skal wouldn't otherwise knowwhere to get that information from. When using only modules there is noneed to override the SkalApp class.First a module called do.py:```pythonfrom skal import command@commanddef hello(self):print('hello')@commanddef yes(self):print('yes')```Using do.py as plain commands in myapp.py:```from skal import SkalAppif __name__ == '__main__':SkalApp(command_modules = ['do']).run()```Running the program:```> python myapp.py hellohello> python myapp.py yesyes```Using do.py as a subcommand in myapp.py:```from skal import SkalAppif __name__ == '__main__':SkalApp(subcommand_modules = ['do']).run()```Running the program:```> python myapp.py do hellohello> python myapp.py do yesyes```Per Command Arguments======================This shows the usage of custom arguments per command. This works for allsupported command sources, not only classes.```pythonfrom skal import SkalApp, command, defaultclass MyApp(SkalApp):"""Help line for application"""__args__ = {'-a': {'help': 'Help for a', 'action': 'store_true'},'-b': {'help': 'Help for b', 'action': 'store_true'}}@command({('-d', '--delete'): {'help': 'Help for d', 'action': 'store_true'}})def hello(self):"""Help line for hello"""if self.args.a:print('a')if self.args.b:print('b')if self.args.delete:print('deleting')print('hello')@commanddef yes(self):"""Help line for yes"""if self.args.a:print('a')if self.args.b:print('b')print('yes')if __name__ == '__main__':app = MyApp()sys.exit(app.run())```Running it:```> python myapp.py -a hello --deleteadeletinghello> python myapp.py -b yesbyes```License=======Skal is licensed under Apache License 2.0http://www.apache.org/licenses/LICENSE-2.0
Package: skanr
skanrMultithreaded network port scanner for IPV4 addressesrequirementsknown Target host IP Addressinstallationpip install skanrusageHelpDisplay the helpskanr -h
usage: skanr [-h] [-s] [-e] [-t] [--version] target_ip

Perform a network port scan of a host IP address

positional arguments:
  target_ip          Target IP address (xxx.xxx.xxx.xxx)

optional arguments:
  -h, --help         show this help message and exit
  -s , --startport   Port number to start scanning (default: 1)
  -e , --endport     End port number of scan range (default: 1024, max: 65535)
  -t , --threads     number of scan threads to run (default: 32, max: 1024)
  --version          prints version informationbasic IP scanwill scan an IP address from ports 1-1024 using 32 threadsskanr 10.37.129.9

skanr v 0.0.1
Scanning IP: 10.37.129.9 ports: 1 - 1024 threads: 32
-=================================================================-
port 21 :open
port 23 :open
port 22 :open
port 53 :open
port 80 :open
port 110 :open
port 111 :open
port 139 :open
port 143 :open
port 445 :open
port 901 :openscan port range on targetTo scan a port range on the target machine use-sand-eto specify the start and end portsif no start ot end prot is given then defaults applyskanr 10.37.129.9 -s 20 -e 100

skanr v 0.0.1
Scanning IP: 10.37.129.9 ports: 20 - 100 threads: 32
-=================================================================-
port 21 :open
port 22 :open
port 23 :open
port 53 :open
port 80 :openspecifing threadsTo speed up the port scanning the number of threads can be passed using the-targument up to a max of 1024 threads, to prevent starting unwanted threads, the number of threads started will never be greater than the number of ports to be scanned.skanr 10.37.129.9 -e 65535 -t 1024

skanr v 0.0.1
Scanning IP: 10.37.129.9 ports: 1 - 65535 threads: 1024
-=================================================================-
port 21 :open
port 22 :open
port 23 :open
port 53 :open
port 80 :open
port 110 :open
port 111 :open
port 139 :open
port 143 :open
port 445 :open
port 901 :open
port 2049 :open
port 6665 :open
port 6666 :open
port 6669 :open
port 6667 :open
port 6668 :open
port 8787 :open
port 37159 :open
port 44180 :open
port 50166 :open
Package: skanym
Skanym CoreThis repository contains The core fonctionalities to create, edit and export 3D animations using the skeletal animation principle.Wikis(Motion Machine)[Link to the wiki]
(Skanym)[Link to the wiki]Historical contextThe skeletal-animation package was originally developed as part of a bachelor thesis in 2021-2022 (linkto the original repository [access required]). It was then maintained/extended for future use (linkto the latest version [access required]).
This repository contains a fork of the core modules of the skeletal-animation package. The goal is to improve upon those modules
to better fit the requirements for the Motion Machine project.
Package: skanym-gui
Skanym GUIThis repository contains a basic GUI program made for the GeeXLab engine (LINK).
The program uses the Skanym librairy (LINK) to load and play skeletal animations.This is only an optional extension for Skanym and does not accomplish anything on its own.It allows basic control of the animation playback.
It is compatible with FBX and GLB file formats, as well as .pkl files created by the Skanym librairy.