九铁

一个 Python 包构建，用作 VEKN官方卡片文本 和锦标赛获胜套牌档案 (TWDA)的接口。

它还包含不断增长的卡片规则列表，这要归功于我们贡献者的辛勤工作。

部分材料是 Paradox Interactive AB 的版权和商标，经许可使用。版权所有。欲了解更多信息，请访问white-wolf.com。

后代项目

KRCG 库已在多个offfpsring项目中使用：

• krcg-cli是库上一个方便的命令行界面

• krcg-static 用于为 Web 开发人员生成易于使用的静态文件。可在static.krcg.org在线获取

• krcg-api 是一个免费的 RESTful Web API，用于充分利用 Web 项目库。可在v2.api.krcg.org在线获取

• krcg-bot是一个友好的 Discord 机器人，免费提供官方卡片文本和规则。它是免费的。

安装

需要Python 3。

使用 pip 安装krcg工具：

pip install krcg

使用图书馆

KRCG 是一个用于 VTES 的 Python 库。该代码有很好的文档记录，可以使用 Python 的内置help函数进行探索。

以下是一些快速入门示例来展示如何使用该库：

VTES

krcg.vtes.VTES是卡片库。它需要使用VTES.load() 方法加载。请注意，这会从 KRCG 静态服务器加载数据，该服务器已经以 JSON 格式免费提供，任何想要使用它的人都可以使用。

或者，VTES.load_from_vekn()如果您想直接从官方的VEKN CSV 文件加载，您可以使用，尽管这会慢一些。这实际上是 [krcg-static] 生成用于标准加载的静态 JSON 文件的方式。

然后，您可以使用 VTES 来访问卡片、填写卡片名称或进行搜索。

>>> from krcg.vtes import VTES
>>> VTES.load()
>>> VTES["Alastor"].to_json()
{
  'id': 100038,
  'name': 'Alastor'
  '_name': 'Alastor',
  'url': 'https://static.krcg.org/card/alastor.jpg',
  'types': ['Political Action'],
  'card_text': (
    'Requires a justicar or Inner Circle member.\n'
    'Choose a ready Camarilla vampire. If this referendum is successful, '
    'search your library for an equipment card and place this card and the equipment '
    'on the chosen vampire. Pay half the cost (round down) of the equipment. '
    'This vampire may enter combat with any vampire controlled by another Methuselah '
    'as a +1 stealth Ⓓ action. This vampire cannot commit diablerie. '
    'A vampire may have only one Alastor.'),
  'artists': ['Monte Moore'],
  'sets': {
    'Gehenna': [{'release_date': '2004-05-17', 'rarity': 'Rare'}],
    'Kindred Most Wanted': [{'release_date': '2005-02-21', 'precon': 'Alastors', 'copies': 1}],
    'Keepers of Tradition': [{'release_date': '2008-11-19', 'rarity': 'Rare'}]},
 'rulings': {
   'text': [
     'If the given weapon costs blood, the target Alastor pays the cost. [LSJ 20040518]',
      'Requirements do not apply. [ANK 20200901]'
    ],
    'links': {
      '[LSJ 20040518]': 'https://groups.google.com/d/msg/rec.games.trading-cards.jyhad/4emymfUPwAM/B2SCC7L6kuMJ',
      '[ANK 20200901]': 'http://www.vekn.net/forum/rules-questions/78830-alastor-and-ankara-citadel#100653'
    }
  }
}
>>> VTES.complete("pentex")
['Pentex™ Loves You!',
 'Pentex™ Subversion',
 'Enzo Giovanni, Pentex Board of Directors',
 'Enzo Giovanni, Pentex Board of Directors (ADV)',
 'Harold Zettler, Pentex Director']
 >>> VTES.search(type=["political action"], sect=["anarch"], artist=["Drew Tucker"])
{<#100790 Free States Rant>}
>>> VTES.search(precon=["Fifth Edition: Nosferatu"])
{<#201534 Aunt Linda>,
 <#201536 Baixinho>,
 <#201537 Belinde>,
 <#100301 Carrion Crows>,
 <#100308 Cats' Guidance>,
 <#102213 Creeping Sabotage>,
 <#100515 Deep Song>,
 <#100698 Fame>,
 <#100863 Guard Dogs>,
 <#100866 Guardian Angel>,
 <#100897 Haven Uncovered>,
 <#201549 Horace Radcliffe>,
 <#100959 Immortal Grapple>,
 <#100995 Instinctive Reaction>,
 <#201553 Larissa Moreira>,
 <#201555 Lenny Burkhead>,
 <#101125 Lost in Crowds>,
 <#101254 Murder of Crows>,
 <#101321 On the Qui Vive>,
 <#101483 Preternatural Strength>,
 <#102214 Protected District>,
 <#101550 Raven Spy>,
 <#101564 Rebel>,
 <#102215 Roundhouse>,
 <#201568 Ryan>,
 <#101808 Slum Hunting Ground>,
 <#101811 Smiling Jack, The Anarch>,
 <#101945 Taste of Vitae>,
 <#201545 The Dowager>,
 <#101070 The Labyrinth>,
 <#102216 The Warrens>,
 <#102065 Underbridge Stray>,
 <#102113 Vessel>,
 <#102149 Warsaw Station>,
 <#201573 Wauneka>}
 >>> VTES.search(set=["Sword of Caine"], rarity=["Rare"])
{<#100167 Black Hand Emissary>,
 <#100314 Census Taker>,
 <#100360 Cloak of Blood>,
 <#100589 Drink the Blood of Ahriman>,
 <#100590 Drop Point Network>,
 <#100655 Epiphany>,
 <#100757 Follow the Blood>,
 <#100787 Framing an Ancient Grudge>,
 <#100865 Guarded Rubrics>,
 <#101024 Joseph Pander>,
 <#101111 Liquefy the Mortal Coil>,
 <#101161 Mantle of the Bestial Majesty>,
 <#101446 Praetorian Backer>,
 <#101489 Prison of the Mind>,
 <#101658 Ruins of Ceoris>,
 <#101724 Seraph's Second>,
 <#102057 The Uncoiling>,
 <#102022 Tribunal Judgment>,
 <#102027 Trophy: Chosen>,
 <#102158 Watchtower: The Wolves Feed>}

TWDA、分析仪和甲板

krcg.twda.TWDA是 TWDA 的接口。VTES它需要以与实例相同的方式加载，使用TWDA.load()方法。那个时候，使用 TWDA.load_from_vekn()相反的速度要慢得多。

加载后，它可用于浏览其中的牌组。

>>> from krcg.twda import TWDA
>>> TWDA.load()
>>> TWDA["2019ecday2pf"]
<Deck #2019ecday2pf: Finnish Politics>
>>> print(TWDA["2019ecday2pf"].to_txt())
EC 2019 - Day 2
Paris, France
August 18th 2019
3R+F
50 players
Otso Saariluoma

-- 2gw8.5 + 1.5vp in the final

Deck Name: Finnish Politics

Crypt (12 cards, min=4, max=38, avg=5.75)
-----------------------------------------
4x Anarch Convert     1 -none-                     Caitiff:ANY
3x Nana Buruku        8 ANI POT PRE                Guruhi:4
2x Nangila Were       9 ANI POT PRE obf ser        Guruhi:4
1x Enkidu, The Noah  11 ANI CEL OBF POT PRO for    Gangrel antitribu:4
1x Black Annis        9 OBF POT ani pro            Nosferatu antitribu:4
1x Andre LeRoux       3 aus                        Toreador:5

Library (65 cards)
Master (26; 6 trifle)
4x Anarch Revolt
1x Archon Investigation
6x Ashur Tablets
1x Dreams of the Sphinx
1x Fame
1x Giant's Blood
1x Information Highway
1x Mbare Market, Harare
2x Pentex(TM) Subversion
1x Powerbase: Luanda
1x Powerbase: Montreal
5x Villein
1x Wider View

Action (5)
3x Deep Song
1x Entrancement
1x Well-Marked

Retainer (1)
1x Mr. Winthrop

Reaction (6)
1x Cats' Guidance
1x Delaying Tactics
2x On the Qui Vive
2x Sense the Savage Way

Combat (26)
1x Canine Horde
5x Carrion Crows
1x Glancing Blow
5x Immortal Grapple
1x Mighty Grapple
1x Slam
1x Stunt Cycle
4x Taste of Vitae
2x Thrown Sewer Lid
4x Torn Signpost
1x Undead Strength

Event (1)
1x Dragonbound

>>> from datetime import date
>>> len([d for d in TWDA.values() if date(2019, 1, 1) < d.date < date(2020, 1, 1) and d.players_count >= 25])
27

krcg.analyzer可以提供关于一组牌组的一些统计数据：

>>> from krcg.analyzer import Analyzer
>>> # You can analyze the whole TWDA, or a fragment of it, or any collection of decks
>>> A = Analyzer([d for d in TWDA.values() if date(2019, 1, 1) < d.date < date(2020, 1, 1)])
>>> # A blank refresh will provide basic statistics
>>> A.refresh()
>>> A.played.most_common(5)
[(<#100588 Dreams of the Sphinx>, 101),
 (<#101384 Pentex™ Subversion>, 96),
 (<#101321 On the Qui Vive>, 86),
 (<#102121 Villein>, 83),
 (<#100824 Giant's Blood>, 74)]
>>> A.average[VTES["Villein"]]
4.409638554216869
>>> A.variance[VTES["Villein"]]
3.6876179416461032
>>> # Refreshing with a list of cards will compute cards affinity using similar decks
>>> # similarity=1 tells the engine to select decks that contains all provided cards
>>> A.refresh(VTES["Aid from Bats"], similarity=1)
>>> # now the candidates method can be used
>>> A.candidates(VTES["Aid from Bats"])[:5]
[(<#100515 Deep Song>, 1.0000000000000002),
 (<#100301 Carrion Crows>, 1.0000000000000002),
 (<#101945 Taste of Vitae>, 0.7777777777777779),
 (<#200185 Beetleman>, 0.6666666666666667),
 (<#100698 Fame>, 0.6666666666666667)]

该krcg.seating模块提供了计算最佳座位的功能：

>>> from krcg import seating
>>> # permutations gives you the list of players for each round
>>> seating.permutations(12, 3)
[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
 [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
 [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]]
>>> # things get funny when you have 6, 7 or 11 players: you need more rounds
>>> # but not all players play every round
>>> seating.permutations(7, 3)
[[4, 5, 6, 7],
 [1, 2, 3, 7],
 [3, 4, 5, 6],
 [1, 2, 6, 7],
 [1, 2, 3, 4, 5]]
>>> # you can use the Round class to get tables from the permutations
>>> [seating.Round(p) for p in seating.permutations(14, 3)]
[[[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14]],
 [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14]],
 [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14]]]
>>> # and the optimise function to search for an optimal seating
>>> result, score = seating.optimise(seating.permutations(12, 3), iterations=50000)
>>> result
[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]],
 [[2, 9, 6, 10], [12, 8, 1, 5], [3, 7, 4, 11]],
 [[11, 5, 10, 1], [6, 4, 12, 7], [8, 3, 9, 2]]]
>>> # score.rules gives a score over the nine official rules for optimal seating
>>> score.rules
[0, 0, 0.0, 9, 0, 0, 0, 1.118033988749895, 2]
>>> # you can inspect violations individualy
>>> # for example rule #4 (players are opponents twice) has 9 violations, to see them:
>>> score.R4
[[1, 5], [2, 3], [2, 9], [3, 4], [4, 7], [5, 8], [6, 7], [9, 10], [10, 11]]
>>> # for more details about the Score structure, check the docstring
>>> help(seating.Score)

最后，krcg.deck.Deck该类可用于解析和操作任何套牌。

>>> from krcg.deck import Deck
>>> with open("First_Blood_Nosferatu.txt") as f:
>>>     deck = Deck.from_txt(f)
>>> deck.crypt
[(<#200549 Gustaphe Brunnelle>, 2),
 (<#200571 Harold Tanner>, 2),
 (<#200696 Jeremy "Wix" Wyzchovsky>, 2),
 (<#201116 Petra>, 2),
 (<#200185 Beetleman>, 2),
 (<#200190 Benjamin Rose>, 2)]
>>> deck.library
[(<#100698 Fame>, 2),
 (<#100070 Animalism>, 2),
 (<#101015 J. S. Simmons, Esq.>, 1),
 (<#101070 The Labyrinth>, 1),
 (<#101073 Laptop Computer>, 2),
 (<#101125 Lost in Crowds>, 6),
 (<#100093 Army of Rats>, 2),
 (<#101550 Raven Spy>, 4),
 (<#101808 Slum Hunting Ground>, 1),
 (<#100199 Blood Doll>, 6),
 (<#100029 Aid from Bats>, 12),
 (<#100308 Cats' Guidance>, 4),
 (<#100362 Cloak the Gathering>, 6),
 (<#100390 Computer Hacking>, 4)]
>>> # fetch a deck from Amaranth UID
>>> deck = Deck.from_amaranth("4d3aa426-70da-44b7-8cb7-92377a1a0dbd")
>>> deck.name
'First Blood: Tremere'
>>> deck.crypt
[(<Card #201020 Muhsin Samir>, 2),
 (<Card #201213 Rutor>, 2),
 (<Card #201388 Troius>, 2),
 (<Card #201501 Zane>, 2),
 (<Card #200025 Aidan Lyle>, 2),
 (<Card #200280 Claus Wegener>, 2)]
>>> print(deck.to_txt("lackey"))
1	Academic Hunting Ground
1	Arcane Library
4	Blood Doll
1	Chantry
2	Vast Wealth
12	Govern the Unaligned
1	Thadius Zho
4	.44 Magnum
1	Ivory Bow
2	Sport Bike
1	Charnas the Imp
6	Bonding
4	Enhanced Senses
5	Forced Awakening
5	On the Qui Vive
4	Precognition
4	Spirit's Touch
8	Telepathic Misdirection
8	Apportation
10	Theft of Vitae
2	Walk of Flame
Crypt:
2	Muhsin Samir
2	Rutor
2	Troius
2	Zane
2	Aidan Lyle
2	Claus Wegener

贡献

随意提交拉取请求，只要通过测试，它们就会被合并。如果您想要实现某个功能，请不要犹豫提交问题或对其进行投票。

设计注意事项

该软件包在设计上不使用数据库。TWDA、搜索引擎和卡片字典保存在内存中以获得更好的性能。整个库会产生 128MB 到 256MB 之间的内存占用。

该软件包使用外部数据源作为卡片列表，因此在发布新集合或更改官方 VEKN CSV 文件时无需更新它：它可以在新数据集可用时立即使用它们。

贡献规则（非开发者）

请不要犹豫，贡献裁决：欢迎所有帮助。

使用您认为应该添加的裁决打开问题，提供指向其中一位规则主管的在线帖子的链接：

• 从 2016-12-04 起，Vincent Ripoll (ANK)
• 从 2011-07-06 起，Pascal Bertrand (PIB)
• 从 1998-06-22 起，L. Scott Johnson (LSJ)
• 从 1994-12-15 起，Thomas R Wylie (TOM)

贡献规则（开发者）

随意直接作为拉取请求贡献裁决，非常感谢。

将裁决链接添加到 rules-links.yaml中，将裁决本身添加到 cards-rules.yaml或 general-rules.yaml 中，具体取决于具体情况。

格式大多是不言自明的：

• 卡片以 ID 和名称的格式引用ID|Name。

• 规则文本中的卡名应该在括号之间，例如。{.44 Magnum}

• 中的个别裁决cards-rulings.yaml必须在文本末尾的括号之间提供一个或多个对裁决链接的引用，例如[LSJ 20100101]

在这样做时，请遵循以下准则：

• 保持 YAML 文件干净并按字母顺序排序（您可以使用 YAML 格式化程序）

• 使裁决尽可能简洁

• 在裁决前加上学科级别和/或裁决适用的类型（如果有），例如。[PRO] [COMBAT]如果该裁决仅适用于在上级 Protean 的战斗中打出的牌，则带有前缀。

• 使规则措辞适应它适用的卡片（即使用男性/女性形式）

• 您可以使用pytest命令运行测试以检查一切是否正常