Saravanan666/pypi-org huggingface dataset:
Package: wow.activityapi
ContentsChange history0.1 (09-13-10)0.2 (09-13-10)0.3 (09-13-10)0.4 (09-16-10)Detailed DocumentationIntroductionUsageContributorsDownloadChange historyChangelog0.1 (09-13-10)Initial release0.2 (09-13-10)Added doctest0.3 (09-13-10)More detailed doctest (also used as readme)0.4 (09-16-10)Fixed a typo in the doctestModified to fetch en_GB XML if Plone language is “en”, if “de” -> de_DE XML, for better i18nChanged get_activity(self, name, realm, zone, language) to get_activity(self, name, realm, zone, language, count) so you can
manipulate how many activities it returnsDetailed DocumentationIntroductionThe activity-API reads the character-activity-sheet from the Armory to get the five last actions of the character.UsageTo use the API, just do an import like this>>> from activity_api import ActivityMock Realmstatus.get_realm_statusReturns output similar to what we would get from the API,  so
that this test can be used while offline>>> from test_activity import mocked_get_activityMocking the functions>>> Activity.get_activity = mocked_get_activityFirst create an instance of the Activity object>>> activity = Activity()To get the recent activities, use get_activity(name, realm, zone, count)
count must be <your desired count of activities> + 1, if you want 5, count must be 6, etc.>>> activities = activity.get_activity("Kutschurft", "Azshara", "EU", 6)
>>> test_activities = [u'Earned the achievement [Neck-Deep in Vile (10 player)].',
...                    u'Has now completed [Victories over the Lich King (Icecrown 10 player)] 4 times.',
...                    u'Has now completed [Sindragosa kills (Heroic Icecrown 10 player)] 2 times.',
...                    u'Has now completed [Valithria Dreamwalker rescues (Heroic Icecrown 10 player)] 4 times.',
...                    u'Has now completed [Blood Queen Lanathel kills (Heroic Icecrown 10 player)] 6 times.']

>>> activities == test_activities
TrueContributorsMarc Goetz, AuthorDownload
Package: wow-addon-packager
wapA developer-friendly World of Warcraft addon packager.FeaturesBuildsRetail, Wrath, Classic addons (or all
three!)Publishesyour addons to CurseForgeGenerates valid TOC filesautomagicallyContinuously rebuildsyour addon during
developmentSets up new addon projects quickly, ready to go with onecommandConsolidates all configuration inone easy-to-edit fileSupports and is tested on Windows, macOS, and LinuxHas awesomedocumentationwap in 5 minutesThese instructions create and upload a working addon without editing a single line of code!Download and installPython 3.11.Installwap:pip install --upgrade --user wow-addon-packagerCreate a new a project:wap new-projectAnd then, answer the prompts. Don't worry too much about your answers -- you can always change
them later in your configuration file.Change to your new project's directory. For example, if you named itMyAddonin the last step,
you'd type:cd MyAddonBuild your addon package and link it to your local World of Warcraft installation:wap build --linkAt this point,you can play the game with your addon.Upload your addon to CurseForge with yourAPI tokenso that others can use it:wap publish --curseforge-token "<api-token>"Project InformationLicense: MITPyPI:https://pypi.org/project/wow-addon-packager/Source Code:https://github.com/t-mart/wapDocumentation:https://t-mart.github.io/wap/Supported Python Versions: 3.11 and laterBadge:Contribution Guide:https://t-mart.github.io/wap/contributing
Package: wow-ai-mms
wow_ai_mmsA simple Python package to easily useMeta's Massively Multilingual Speech (MMS) project.Thecurrent MMS codeis using subprocess to call another Python script, which is not very convenient to use, and might lead to severalissues.
This package is created to address those problems and to wrap up the project in an API to easily integrate it with other projects.InstallationQuickstartASRASR with AlignmentTTSLIDAPI referenceLicenseDisclaimer & CreditsInstallationYou will needffmpegfor audio processingInstallwow-ai-mmsfrom Pypipipinstallwow-ai-mmsor from sourcepipinstallgit+https://github.com/wow-ai-ml/wow-ai-mmsIf you want to use theAlignmentmodel:you will needperlto useuroman.
Check theperl websitefor installation instructions on different platforms.You will need a nightly version oftorchaudio:pipinstall-U--pretorchaudio--index-urlhttps://download.pytorch.org/whl/nightly/cu118You might needsoxas well.Fairseqhas not included theMMSproject yet in the released PYPI version, so until the next release, you will need to installfairseqfrom source:pipuninstallfairseq&&pipinstallgit+https://github.com/facebookresearch/fairseqQuickstart:warning: There is anissuewithfairseqwhen running the code in interactive environments like Jupyter notebooks.Please use normal Python filesor use the colab notebook provided above.ASRYou will need first to download the model weights, you can find and download all the supported models fromhere.fromwow_ai_mms.models.asrimportASRModelasr=ASRModel(model='/path/to/mms/model')files=['path/to/media_file_1','path/to/media_file_2']transcriptions=asr.transcribe(files,lang='eng',align=False)fori,transcriptioninenumerate(transcriptions):print(f">>> file{files[i]}")print(transcription)ASR with Alignmentfromwow_ai_mms.models.asrimportASRModelasr=ASRModel(model='/path/to/mms/model')files=['path/to/media_file_1','path/to/media_file_2']transcriptions=asr.transcribe(files,lang='eng',align=True)fori,transcriptioninenumerate(transcriptions):print(f">>> file{files[i]}")forsegmentintranscription:print(f"{segment['start_time']}->{segment['end_time']}:{segment['text']}")print("----")Alignment model onlyfromwow_ai_mms.models.alignmentimportAlignmentModelalign_model=AlignmentModel()transcriptions=align_model.align('path/to/wav_file.wav',transcript=["segment 1","segment 2"],lang='eng')fortranscriptionintranscriptions:forsegmentintranscription:print(f"{segment['start_time']}->{segment['end_time']}:{segment['text']}")TTSfromwow_ai_mms.models.ttsimportTTSModeltts=TTSModel('eng')res=tts.synthesize("This is a simple example")tts.save(res)LIDComing SoonAPI referenceYou can check theAPI reference documentationfor more details.LicenseSince the models arereleased under the CC-BY-NC 4.0 license.
This project is following the sameLicense.Disclaimer & CreditsThis project is not endorsed or certified by Meta AI and is just simplifying the use of the MMS project.All credit goes to the authors and to Meta for open sourcing the models.Please check their paperScaling Speech Technology to 1000+ languagesand theirblog post.
Package: wowair
InstallRun the following command to install wowair using pip$pipinstallwowairUsage:fromwowairimportWowAirQuery,Currencyfromdatetimeimporttimedelta,date# Fetch available citiescities=WowAirQuery.get_cities()forcinsorted(cities,key=lambdacity:cities[city]):printcities[c],c# Fetch tickets for the next week from Montreal to Dublinquery=WowAirQuery(origin='YUL',destination='DUB')forticketinquery.get_tickets():printticket# Fetch Available tickets from New York to Anywhere in the NEXT 30 DAYSdepart_date_from=date.today()depart_date_to=depart_date_from+timedelta(days=30)query=WowAirQuery(origin='EWR',depart_date=(depart_date_from,depart_date_to),currency=Currency.USD)forticketinquery.get_tickets():ifticket.status=='Available':printticket
Package: wow-ai-sam
Fine-tune Segment-Anything ModelThis library allows you to fine-tune the powerful Segment-Anything model from MetaAI for your custom COCO-format datasets. The library is built on top of Lightning AI's Fabric framework, providing an efficient and easy-to-use implementation for achieving state-of-the-art instance segmentation results.This repo is an experiment; A PoC to see if fine-tuning SAM using bounding boxes as prompts would increase the IoU or improve the quality of the masks in general. One can use a COCO format dataset to fine-tune SAM for a specific task where SAM does not perform well (e.g., segmenting text on documents) and then use that model with interactive prompts just like SAM.For generating bboxes from text and prompt them to SAM you may check:wow-ai-segment-anythingFeaturesSupports custom COCO-format datasetsBuilt on Lightning AI's Fabric frameworkEfficient fine-tuning of Segment-Anything model from MetaAIIncludes training and validation loopsResultsUsing bbox prompt, the table below shows the mask quality of the original and fine-tuned models.DatasetTypeMean IoUMean F1EpochCOCO2017Original SAM0.79780.8749COCO2017Fine-tuned0.80700.88162TrashCan 1.0Original SAM0.66430.7808TrashCan 1.0Fine-tuned0.78880.87385TrashCan 1.0Fine-tuned0.80000.879514WGISDOriginal SAM0.85360.9178WGISDFine-tuned0.87320.929819Comparison imagesTrashCan 1.0
GT | 6 Epochs Fine-tuned SAM | Original SAMInstallationgit clone https://github.com/wow-ai-ml/wow-ai-segment-anything
cd wow-ai-sam
pip install .Quick StartPrepare your custom COCO-format dataset. The dataset should include a JSON file with annotations and an images folder with corresponding images.Edit src/config.py with your dataset paths.Run src/train.py.NotesUses the original implementation of SAM.Loss calculated as stated on the paper (20 * focal loss + dice loss + mse loss).Only supports bounding box input prompts.ResourcesSegment AnythingLightning AILicenseThis project is licensed same as SAM model.
Package: wow.armoryapi
ContentsChange history0.5 (09-13-10)0.6 (09-13-10)0.7 (09-13-10)0.8 (09-16-10)Detailed DocumentationIntroductionUsageContributorsDownloadChange historyChangelog0.5 (09-13-10)Initial release0.6 (09-13-10)Added doctest0.7 (09-13-10)More detailed doctest (also used as readme)0.8 (09-16-10)Fixed a typo in the doctestModified to fetch en_GB XML if Plone language is “en”, if “de” -> de_DE XML, for better i18n
(getCharacter(self, raiderName, raiderServer, raiderZone) -> getCharacter(self, raiderName, raiderServer, raiderZone, language))Detailed DocumentationIntroductionThe armory-API is a modified version of the armorypy @http://code.google.com/p/armorypy/.The additional info you can get from it:Primary & secondary spec with name and icon (to build a icon link with wowhead or wow-europe)Major and minor glyphs for the active spec with name, type and effect2v2, 3v3 and 5v5 arenateams with name, rating and rankingSecondary professions (cooking, fishing etc.) with name and valuePrefix titles, such as Private, Twilight Vanquisher etc.UsageTo use the API, just do an import like this>>> from armory_api import ArmoryMock Armory.getCharacterReturns a dictionary similar to the dictionary we would get from the API,  so
that this test can be used while offline>>> from test_armory import mocked_getCharacterMocking the function>>> Armory.getCharacter = mocked_getCharacterFirst create an instance of the Armory object>>> armory = Armory()To get the character info, use getCharacter(name, realm, zone, language)
currently only “de” and “en” are supported>>> raider = armory.getCharacter("Kutschurft","Azshara","EU", "en")Now you can get the info with get(<key>)>>> name = raider.get("name")
>>> name == "Kutschurft"
True

>>> server = raider.get("server")
>>> server == "Azshara"
True

>>> zone = raider.get("zone")
>>> zone == "EU"
TrueContributorsMarc Goetz, AuthorDownload
Package: wowfile
WowFileA library to manipulate SparkMaker WOW filesWowViewerA graphical tool using WowFile to display and change parameter in SparkMaker WOW FilesInstallIf you are under windows and just want use the GUI tool, get it from one of the buildreleasesElse you can use pip to install the library and viewer:sudo pip install WowFileThis will add "wowviewer" in your path, and you can access theWowFileclass from python.
Package: wowlib
这是WOW部门用的Excel转换工具包，可支持将Excel数据转换成供C/C++,C#使用的二进制文件和  
字段结构描述文件，也支持转换成文本型的可供lua,JavaScript(TypeScript)使用的配置数据典型的Excel文件格式#索引国际字符串字符串浮点字节短整整数整数数组中文描述行(可选)##v>=1000v.find('铁')>=0len(v)>=7v!=0v>=100v<-30000 or v>30000字段检验行，支持VB和JS校验(可选)###CSCCCSCSCSCSS类型行:C-Client,S-Server(可选)IdNameStrPropFloatPropProp1Prop2Prop3IntArray字段名(必须)indexnstringstringfloatbyteshortintint[]字段类型(必须)1000低级铁剑Good Excel567.3100-32768-21474836481|2|31001中级铁剑n\0 error0.223255327672147483647-1|-2|-31002高级铁剑It's test0.0005250327662147483648|-1|0|1|1003超级铁剑"love" it?-2147483649100-32760-21474836480修改记录V1.6.0[2018.10.31]ts中字符串过长的处理V1.5.9[2018.10.30]小改动V1.5.8[2018.10.30]ts中map类型的字符串，去掉两边的引号，因为TSLint报错V1.5.7[2018.10.28]字符串中的\n会被转成\n的问题V1.5.6[2018.10.27]修改描述V1.5.5[2018.10.27]发现Python有BytesIO这种类似于MemoryStream之类的东西，果断把文件写操作修改了下V1.5.4[2018.10.26]修改生成的TypeScript脚本的格式，使表对象初始化滞后V1.5.3[2018.10.26]改动描述V1.5.2[2018.10.26]减少一些不必要的导出函数V1.5.1[2018.10.26]对容错做了增强，防止Excel文件不合法V1.5.0[2018.10.26]支持Excel转成lua数据格式改进了APIV1.4.0[2018.10.25]支持Excel转成用于C++读取的DBC文件和C/C++头文件格式V1.3.1[2018.10.25]支持Excel转成BCC文件，这种是C#读取的二进制文件V1.3.0[2018.10.24]支持Excel转换为C#结构，近期会实现转成C#能解析的二进制文件V1.2.0[2018.10.23]支持数据校验对byte,short等数据有内置的数据范围校验单元格数据访问方式为：单个数据为v，数组类数据访问方式为v[i]V1.1.4[2018.10.23]支持字符串中的反斜杠和双引号能够进行转义处理V1.1.3[2018.10.22]修改字符串的引号为双引号，保持与原来VBA转换的结果一致V1.1.2[2018.10.22]修正第一列是map类型时导致只有一行记录输出的错误V1.1.1[2018.10.21]支持_GT标记导出函数RealExcelToTargetV1.1.0[2018.10.21]修改README.md文件内容V1.0.1[2018.10.21]让类型行可选，即所有#开头的行都可以忽略V1.0.0[2018.10.20]支持将Excel文件转换成TypeScript格式的文件
Package: wow-ocr
WoW Screenshot OCRDeep learning OCR models to read text from WoW screenshots. Based on a detector that spots text frames, and a recognizer that reads text from detected frames.ChatCombat logNameplatesUI framesMapInstallationpip install wow-ocrUsageModels use pre trained weights, you don't have to train anything.Try it on Colabimport wow_ocr

# Init pipeline, detector and recognizer models with pre trained weights
pipeline = wow_ocr.pipeline.Pipeline()


# Screenshots example
images = [
    wow_ocr.tools.read(url)
    for url in [
        "https://image_url.com/1.jpg",
        "https://image_url.com/2.jpg",
    ]
]

# Results - Image to Text
prediction_groups = pipeline.recognize(images)
# # Each list of predictions in prediction_groups is a list of
# # (word, box) tuples.
Package: wowp
WOWP====[![Build Status](https://travis-ci.com/coobas/wowp.svg?branch=master)](https://travis-ci.com/coobas/wowp)**WOWP** (A **WO**rkflo**W** Framework in **P**ython) is a modern,light-weight framework for integrated simulations in science.Our goal--------Wowp enables flow based programming in Python via actors and workflows.We prefer having a clean, straightforward API for creating andconnecting actors and workflows. The target coding style should be assimple as``` {.sourceCode .python}# connect two actorsactor2.inports['x'] += actor1.outports['y']# get the workflowworkflow = actor2.get_workflow()# run the workflowworkflow(x=1)```Installation------------Using pip + latest development version:``` {.sourceCode .bash}pip install git+https://github.com/coobas/wowp.git```Using pypi (may be outdated)``` {.sourceCode .bash}pip install wowp# or pip install wowp[all] to include also optional dependencies.```### Dependencies-   decorator-   future-   networkx-   nose-   six-   clickVarious parallel schedulers require at least one of-   [ipyparallel](https://github.com/ipython/ipyparallel)-   [distributed](https://github.com/dask/distributed)-   [mpi4py](http://pythonhosted.org/mpi4py/)Documentation-------------See <http://pythonic.eu/wowp>*Copyright (c) 2015-2017 Jakub Urban, Jan Pipek under The MIT License(MIT)*
Package: wowpy
WowPyDescriptionThis is a python3 wrapper for wowza cloud api callsUsagepip install wowpy➜  python3
>>> from wowpy.livestreams import LiveStream
>>> LiveStream.get_live_stream('ytzbkw49')
Endpoint: https://api.cloud.wowza.com/api/v1.4/live_streams/ytzbkw49, Method: get, Data: {}, Description: not description
Endpoint https://api.cloud.wowza.com/api/v1.4/live_streams/ytzbkw49 succesfully reached
Package: wow.realmstatusapi
ContentsChange history0.1 (09-13-10)0.2 (09-13-10)0.3 (09-13-10)0.4 (09-16-10)Detailed DocumentationIntroductionUsageContributorsDownloadChange historyChangelog0.1 (09-13-10)Initial release0.2 (09-13-10)Added doctest0.3 (09-13-10)More detailed doctest (also used as readme)0.4 (09-16-10)Fixed a typo in the doctestChanged get_realm_status(self, name) and get_realm_type(self, name) to (self, * names)Detailed DocumentationIntroductionThe realmstatus-API reads the realmstatus-xml from wow-europe.com to get the status of a specified realm (“Realm Up/Realm Down”) and
the type of the realm (PvE,PvP etc.).UsageTo use the API, just do an import like this>>> from realmstatus_api import RealmstatusMock Realmstatus.get_realm_status and Realmstatus.get_realm_typeReturns output similar to what we would get from the API,  so
that this test can be used while offline>>> from test_realmstatus import mocked_get_realm_status, mocked_get_realm_typeMocking the functions>>> Realmstatus.get_realm_status = mocked_get_realm_status
>>> Realmstatus.get_realm_type = mocked_get_realm_typeFirst create an instance of the Realmstatus object>>> realmstatus = Realmstatus()To get the status of a realm, use get_realm_status(* names).
If you want, you can get the status of multiple realms (in a dictionary)>>> status = realmstatus.get_realm_status("Azshara")["Azshara"]
>>> status == "Realm Up"
TrueTo get the type of a realm, use get_realm_type(* names).
If you want, you can get the type of multiple realms (in a dictionary)>>> type = realmstatus.get_realm_type("Azshara")["Azshara"]
>>> type == "PvP"
TrueContributorsMarc Goetz, AuthorDownload
Package: wowspy
# Warships.pyA  Python3 World of Warships API wrapperInstallation instruction:``pip install wowspy``Please consult the official documentation [here](https://developers.wargaming.net/reference)Example usage:```pyfrom wowspy import Wowsdef example():api_key = 'YOUR_WOWS_API_KEY'my_api = Wows(api_key)# We will search for a player and then get its stats in this exampleplayer_name = 'PotatoSquad'# Api response from Wargaming# We only want one result, thus it's specified limitplayer_id_response = my_api.players(my_api.region.NA, player_name, fields='account_id', limit=1)# Get the player id from the api responseplayer_id = player_id_response['data'][0]['account_id']# Now we will use this id to search for the player's stats# We only want the pvp stats here, it's specified in fields paramplayer_stats_response = my_api.player_personal_data(my_api.region.NA, player_id, fields='statistics.pvp')print(player_stats_response)if __name__ == '__main__':example()```Example usage(with Aiohttp):```pyfrom asyncio import get_event_loopfrom aiohttp import ClientSessionfrom wowspy import WowsAsyncasync def example():api_key = 'YOUR_WOWS_API_KEY'session = ClientSession()my_api = WowsAsync(api_key, session)# We will search for a player and then get its stats in this exampleplayer_name = 'PotatoSquad'# Api response from Wargaming# We only want one result, thus it's specified limitplayer_id_response = await my_api.players(my_api.region.NA, player_name, fields='account_id', limit=1)# Get the player id from the api responseplayer_id = player_id_response['data'][0]['account_id']# Now we will use this id to search for the player's stats# We only want the pvp stats here, it's specified in fields paramplayer_stats_response = await my_api.player_personal_data(my_api.region.NA, player_id, fields='statistics.pvp')print(player_stats_response)if __name__ == '__main__':loop = get_event_loop()loop.run_until_complete(example())loop.close()```
Package: wows-shell
wows_shellC++ header only library for calculating shell performance in World of WarshipsExperimentally verified to be nearly identical to the World of Warships ballistics modelLegalAll copyrighted material provided by Wargaming.net are owned by Wargaming.net.All other material is available under the MIT License.Original Model Information & Source Code:Original Model:CodePost-Penetration FormulasRevised Model:CodeFeatures:Shell FlightComputes shell flight path.At Impact:Outputs:Angle of ImpactImpact VelocityRaw, Belt/Deck, Normalization Adjusted PenetrationShell flight time (Real / In-game)Ability to change trajectory computation methodForward Euler (default - also in-game method)Runge-Kutta 2 and 4Adams-Bashforth 5Lateral Angles:Computes lateral angles where penetration, AP fuzing, and ricochets occur while adjusting for impact angle and vertical armor inclination.Definition: Angles where that represent the horizontal angling of a ship:Bow-in: 90 degreesFull-broadside: 0 degreesOutputs:Maximum Lateral Angle for PenetrationMinimum Lateral Angle for FusingRicochet Lateral AnglesDispersionComputes dispersion approximations based on experimental data.Outputs:Dispersion Types:Horizontal DispersionVertical DispersionArea DispersionStatistical TypesMax DispersionStandard Deviation of Dispersion50% Error RadiusPost-Penetration:Shell detonation distance after penetration while adjusting for ship angling, and vertical armor inclinations.Ability to modify the way the calculations are doneEnable or Disable Normalization changing directionLinear estimation or full air drag modelingFitting:Capability to fit shells to real world data using gradient descent.Air Drag CoefficientKruppCompatibility:Requires C++17 supporting compilerSupports multithreading and vectorization for improved performanceExtensions:PythonRequires Pybind11Tested with Python 3.7.4 (Anaconda), 3.8.5Available from PyPIpip install wows-shellWebAssemblyRequires EmscriptenUsed inhttps://github.com/jcw780/wows_ballisticsFuture Goals:Wiki / TutorialExtend more features to Python and WebAssemblyWill continue to update the model when new information is acquired
Package: wowsunpack
WoWsUnpackBased onEdibleBug/WoWS-GameParams, this fork useswowsunpack.exeto extractGameParams.databefore unpacking toGameParams.json.wowsunpack.exeis provided byWARGAMING.NET.中文版本Optional featuresDecode game languagesUnpack game mapsUnpack game iconsPack game assetsSetupUse Python 3 andpython3 -m venv .envto create a virtual environmentInstall dependencies withpip install -r requirements.txtRunpython3 run.pyPaste the game path intogame.pathRunpython3 run.pyagain to unpackUse without PythonDownload the latest binaryDouble click onunpack.exePaste the game path intogame.pathDouble click onunpack.exeagain to unpackWindows may scanunpack.exeonly for the first time. The binary is built withpyinstaller.WoWsUnpackis not responsible for anything ifpyinstallerinjects any malicious code while generating the binary. Please use the binary at your own risk.Arguments--lang: Decode game languages--maps: Unpack game maps--icons: Unpack all game icons--assets: Pack game assets into foldersAny other arguments are not valid. The program will exit with error code 1. Call the program like./unpack.exe --langfrom the terminal. Double clicking will not pass in any arguments.BuildingRunbuild_exe.pyto build the binary, and it will be placed indist/ready to goRunpython3 -m buildto build the package, and it will also be placed indist/Install it locally withpip install wowsunpack --find-links=distPublishingCheck withtwine check dist/*Upload to TestPyPI before publishing ittwine upload -r testpypi dist/*Install withpip install wowsunpack -i https://testpypi.python.org/pypiPublish it withtwine upload dist/*World of Warships GameParams to JSONLegal Notice and LicenseI acknowledge and agree to the rights and Terms of Use (ToS) provided byWargaming.net (WG). Any users wishing to use the code or WoWSFT must also acknowledge and agree to the rights and ToS underlined by WG. I am not held responsible for any issues or problems that may occur related to using WoWSFT and/or provided codes.Any codes and materials created by me are underMIT License.InstructionUse Python 3.Legacy folder is outdated, do not use.Extract GameParams.data into same folder.OneFileToRuleThemAll.pyExtracts into a huge JSON file with everything included. This file is not intended for reading.OneFileToSplitThemAll.pySplits into many JSON files, with file name as key and value as content.Example folder/file structure__ root
  |__ sub
     |__ 0
        |__ Ability
        |  |__ PCY001_CrashCrew.json
        |  |__ ...
        |__ Achievement
        |  |__ PCH001_DoubleKill.json
        |  |__ ...
        |__ ...Original codes from XeNTax forum, modified a while ago due to incompatibility with data.GameParams2Jsonreferenced when refactoring code.