Metadata-Version: 2.1
Name: krcg
Version: 2.13
Summary: "CLI, web API and Discord bot for VTES cards and TWDA.",
Home-page: http://github.com/lionel-panhaleux/krcg
Author: lionelpx
Author-email: lionel.panhaleux@gmail.com
License: "MIT"
Description: # KRCG
        
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        A Python package build to serve as an interface for
        the VEKN [official card texts](http://www.vekn.net/card-lists)
        and the [Tournament Winning Deck Archive (TWDA)](http://www.vekn.fr/decks/twd.htm).
        
        It also contains an ever-growing list of cards rulings, that is kept up to date
        thanks to the hard work of our contributors.
        
        Portions of the materials are the copyrights and trademarks of Paradox Interactive AB,
        and are used with permission. All rights reserved.
        For more information please visit [white-wolf.com](http://www.white-wolf.com).
        
        ![Dark Pack](https://raw.githubusercontent.com/lionel-panhaleux/krcg/master/dark-pack.png)
        
        ## Offspring projects
        
        The KRCG library has been used in multiple _offpsring_ projects:
        
        -   [krcg-cli](https://github.com/lionel-panhaleux/krcg-cli) is a convenient
            Command Line Interface over the library
        
        -   [krcg-static](https://github.com/lionel-panhaleux/krcg-static)
            is used to generate easy-to-use static files for web developers.
            It is available online at [static.krcg.org](https://static.krcg.org)
        
        -   [krcg-api](https://github.com/lionel-panhaleux/krcg-api)
            is a free RESTful web API exposing to get the most out of the library for web project.
            It is available online at [v2.api.krcg.org](https://v2.api.krcg.org)
        
        -   [krcg-bot](https://github.com/lionel-panhaleux/krcg-bot) is a friendly Discord bot
            that provides official card text and rulings for free.
            It is [available for free](https://discordapp.com/oauth2/authorize?client_id=703921850270613505&scope=bot).
        
        ## Installation
        
        [Python 3](https://www.python.org/downloads/) is required.
        
        Use pip to install the `krcg` tool:
        
        ```bash
        pip install krcg
        ```
        
        ## Using the library
        
        KRCG is a Python library for VTES.
        The code is well-documented and can be explored using Python's built-in `help` function.
        
        Here are a few quickstart examples to showcase how the library can be used:
        
        ### VTES
        
        `krcg.vtes.VTES` is the cards library. It needs to be loaded using the `VTES.load()`
        method. Note that this loads the data from the
        [KRCG static](https://static.krcg.org) server, where it's already available
        in JSON format for free, for anyone who would want to play with it.
        
        Alternatively, you can use `VTES.load_from_vekn()` if you want to load directly
        from the official [VEKN CSV files](https://www.vekn.net/card-lists),
        although that's a bit slower. That's actually the way [krcg-static] does it to generate
        the static JSON files used for the standard load.
        
        Then you can play around with VTES to access cards, complete card names or search.
        
        ```python
        >>> 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, Analyzer and Deck
        
        `krcg.twda.TWDA` is the interface to the TWDA. It needs to be loaded in the same way
        as the `VTES` instance, using the `TWDA.load()` method. That time, using
        `TWDA.load_from_vekn()` instead is considerably slower.
        
        Once loaded, it can be used to browse the decks in it.
        
        ```python
        >>> 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
        ```
        
        The `krcg.analyzer` can provide some statistics over a collection of decks:
        
        ```python
        >>> 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)]
        ```
        
        The `krcg.seating` module provides functions to compute optimal seatings:
        
        ```python
        >>> 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)
        ```
        
        And finally, the `krcg.deck.Deck` class can be useful to parse and manipulate any deck.
        
        ```python
        >>> 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
        ```
        
        ## Contribute
        
        Feel free to submit pull requests, they will be merged as long as they pass the tests.
        Do not hestitate to submit issues or vote on them if you want a feature implemented.
        
        ### Design considerations
        
        The package uses no database by design.
        The TWDA, search engine and cards dict are kept in memory for better performances.
        The whole library generates a memory footprint between 128MB and 256MB.
        
        The package uses external data sources for card list, so that it needs not be updated
        when new sets are released or official VEKN CSV files are changed: it can use
        new data sets as soon as they're available.
        
        ### Contribute Rulings (non-developers)
        
        Please do not hestitate to contribute rulings: all help is welcome.
        
        Open an [issue](https://github.com/lionel-panhaleux/krcg/issues)
        with a ruling you think should be added,
        provide a link to an online post by one of the rules directors:
        
        -   From 2016-12-04 onward, [Vincent Ripoll (ANK)](http://www.vekn.net/forum/news-and-announcements/75402-new-inner-circle-vekn-board-of-directors#79470)
        -   From 2011-07-06 onward, [Pascal Bertrand (PIB)](https://groups.google.com/d/msg/rec.games.trading-cards.jyhad/VzRGZO_Iuto/BjJGRVvJ5Z8J)
        -   From 1998-06-22 onward, [L. Scott Johnson (LSJ)](https://groups.google.com/d/msg/rec.games.trading-cards.jyhad/RIX1tLgOFjg/xKikfSarfd8J)
        -   From 1994-12-15 onward, [Thomas R Wylie (TOM)](https://groups.google.com/d/msg/rec.games.trading-cards.jyhad/Dm_gIP3YvUs/qTyKyq2NWv4J)
        
        ### Contribute Rulings (developers)
        
        Feel free to contribute rulings as Pull Requests directly, this is very appreciated.
        
        Add the ruling link to
        [rulings-links.yaml](https://github.com/lionel-panhaleux/krcg/blob/master/rulings/rulings-links.yaml),
        and the ruling itself to
        [cards-rulings.yaml](https://github.com/lionel-panhaleux/krcg/blob/master/rulings/cards-rulings.yaml) or
        [general-rulings.yaml](https://github.com/lionel-panhaleux/krcg/blob/master/rulings/general-rulings.yaml)
        depending on the case.
        
        The format is mostly self-explanatory:
        
        -   Cards are reference by ID and name in the format `ID|Name`.
        
        -   Card names inside rulings text should be between bracers, eg. `{.44 Magnum}`
        
        -   Individual rulings in `cards-rulings.yaml` must provide one or more references
            to ruling links at the end of the text, between brackets, eg `[LSJ 20100101]`
        
        In doing so, please follow the following guidelines:
        
        -   Keep the YAML files clean and alphabetically sorted (you can use a YAML formatter)
        
        -   Make the rulings as concise as possible
        
        -   Prefix the ruling with the discipline level and/or type the ruling applies to (if any),
            eg. prefix with `[PRO] [COMBAT]` if the ruling applies only to the card played in combat at superior Protean.
        
        -   Adapt the ruling wording to the cards it applies to (ie. use masculine/feminin forms)
        
        -   You can run the tests with the `pytest` command to check everything is OK
        
Keywords: vampire vtes vekn wod ccg twd
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Games/Entertainment
Description-Content-Type: text/markdown
Provides-Extra: dev
