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mtg_python_deckbuilder/code/deck_builder/builder_utils.py

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"""Utility helper functions for deck builder.
This module houses pure/stateless helper logic that was previously embedded
inside the large builder.py module. Extracting them here keeps the DeckBuilder
class leaner and makes the logic easier to test independently.
Only import lightweight standard library modules here to avoid import cycles.
"""
from __future__ import annotations
from typing import Dict, Iterable
import re
import ast
import random as _rand
from . import builder_constants as bc
import math
COLOR_LETTERS = ['W', 'U', 'B', 'R', 'G']
def parse_theme_tags(val) -> list[str]:
"""Robustly parse a themeTags cell that may be a list, nested list, or string-repr.
Handles formats like:
['Tag1', 'Tag2']
"['Tag1', 'Tag2']"
Tag1, Tag2
Returns list of stripped string tags (may be empty)."""
if isinstance(val, list):
flat: list[str] = []
for v in val:
if isinstance(v, list):
flat.extend(str(x) for x in v)
else:
flat.append(str(v))
return [s.strip() for s in flat if s and str(s).strip()]
if isinstance(val, str):
s = val.strip()
# Try literal list first
try:
parsed = ast.literal_eval(s)
if isinstance(parsed, list):
return [str(x).strip() for x in parsed if str(x).strip()]
except Exception:
pass
# Fallback comma split
if s.startswith('[') and s.endswith(']'):
s = s[1:-1]
parts = [p.strip().strip("'\"") for p in s.split(',')]
out: list[str] = []
for p in parts:
if not p:
continue
clean = re.sub(r"^[\[\s']+|[\]\s']+$", '', p)
if clean:
out.append(clean)
return out
return []
def normalize_theme_list(raw) -> list[str]:
"""Parse then lowercase + strip each tag."""
tags = parse_theme_tags(raw)
return [t.lower().strip() for t in tags if t and t.strip()]
def compute_color_source_matrix(card_library: Dict[str, dict], full_df) -> Dict[str, Dict[str, int]]:
"""Build a matrix mapping card name -> {color: 0/1} indicating if that card
can (reliably) produce each color of mana on the battlefield.
Notes:
- Includes lands and non-lands (artifacts/creatures/enchantments/planeswalkers) that produce mana.
- Excludes instants/sorceries (rituals) by design; this is a "source" count, not ramp burst.
- Any-color effects set W/U/B/R/G (not C). Colorless '{C}' is tracked separately.
- For lands, we also infer from basic land types in the type line. For non-lands, we rely on text.
- Fallback name mapping applies only to exact basic lands (incl. Snow-Covered) and Wastes.
Parameters
----------
card_library : Dict[str, dict]
Current deck card entries (expects 'Card Type' and 'Count').
full_df : pandas.DataFrame | None
Full card dataset used for type/text lookups. May be None/empty.
"""
matrix: Dict[str, Dict[str, int]] = {}
lookup = {}
if full_df is not None and not getattr(full_df, 'empty', True) and 'name' in full_df.columns:
for _, r in full_df.iterrows(): # type: ignore[attr-defined]
nm = str(r.get('name', ''))
if nm and nm not in lookup:
lookup[nm] = r
for name, entry in card_library.items():
row = lookup.get(name, {})
entry_type = str(entry.get('Card Type') or entry.get('Type') or '').lower()
tline_full = str(row.get('type', row.get('type_line', '')) or '').lower()
# Land or permanent that could produce mana via text
is_land = ('land' in entry_type) or ('land' in tline_full)
text_field = str(row.get('text', row.get('oracleText', '')) or '').lower()
# Skip obvious non-permanents (rituals etc.)
if (not is_land) and ('instant' in entry_type or 'sorcery' in entry_type or 'instant' in tline_full or 'sorcery' in tline_full):
continue
# Keep only candidates that are lands OR whose text indicates mana production
produces_from_text = False
tf = text_field
if tf:
# Common patterns: "Add {G}", "Add {C}{C}", "Add one mana of any color/colour"
produces_from_text = (
('add one mana of any color' in tf) or
('add one mana of any colour' in tf) or
('add ' in tf and ('{w}' in tf or '{u}' in tf or '{b}' in tf or '{r}' in tf or '{g}' in tf or '{c}' in tf))
)
if not (is_land or produces_from_text):
continue
# Combine entry type and snapshot type line for robust parsing
tline = (entry_type + ' ' + tline_full).strip()
colors = {c: 0 for c in (COLOR_LETTERS + ['C'])}
# Land type-based inference
if is_land:
if 'plains' in tline:
colors['W'] = 1
if 'island' in tline:
colors['U'] = 1
if 'swamp' in tline:
colors['B'] = 1
if 'mountain' in tline:
colors['R'] = 1
if 'forest' in tline:
colors['G'] = 1
# Text-based inference for both lands and non-lands
if (
'add one mana of any color' in tf or
'add one mana of any colour' in tf or
('add' in tf and ('mana of any color' in tf or 'mana of any one color' in tf or 'any color of mana' in tf))
):
for k in COLOR_LETTERS:
colors[k] = 1
# Explicit colored/colorless symbols in add context
if 'add' in tf:
if '{w}' in tf:
colors['W'] = 1
if '{u}' in tf:
colors['U'] = 1
if '{b}' in tf:
colors['B'] = 1
if '{r}' in tf:
colors['R'] = 1
if '{g}' in tf:
colors['G'] = 1
if '{c}' in tf or 'colorless' in tf:
colors['C'] = 1
# Fallback: infer only for exact basic land names (incl. Snow-Covered) and Wastes
if not any(colors.values()) and is_land:
nm = str(name)
base = nm
if nm.startswith('Snow-Covered '):
base = nm[len('Snow-Covered '):]
mapping = {
'Plains': 'W',
'Island': 'U',
'Swamp': 'B',
'Mountain': 'R',
'Forest': 'G',
'Wastes': 'C',
}
col = mapping.get(base)
if col:
colors[col] = 1
# Only include cards that produced at least one color
if any(colors.values()):
matrix[name] = colors
return matrix
def compute_spell_pip_weights(card_library: Dict[str, dict], color_identity: Iterable[str]) -> Dict[str, float]:
"""Compute relative colored mana pip weights from non-land spells.
Hybrid symbols are split evenly among their component colors. If no colored
pips are found we fall back to an even distribution across the commander's
color identity (or 0s if identity empty).
"""
pip_counts = {c: 0 for c in COLOR_LETTERS}
total_colored = 0.0
for entry in card_library.values():
ctype = str(entry.get('Card Type', ''))
if 'land' in ctype.lower():
continue
mana_cost = entry.get('Mana Cost') or entry.get('mana_cost') or ''
if not isinstance(mana_cost, str):
continue
for match in re.findall(r'\{([^}]+)\}', mana_cost):
sym = match.upper()
if len(sym) == 1 and sym in pip_counts:
pip_counts[sym] += 1
total_colored += 1
else:
if '/' in sym:
parts = [p for p in sym.split('/') if p in pip_counts]
if parts:
weight_each = 1 / len(parts)
for p in parts:
pip_counts[p] += weight_each
total_colored += weight_each
if total_colored <= 0:
colors = [c for c in color_identity if c in pip_counts]
if not colors:
return {c: 0.0 for c in pip_counts}
share = 1 / len(colors)
return {c: (share if c in colors else 0.0) for c in pip_counts}
return {c: (pip_counts[c] / total_colored) for c in pip_counts}
__all__ = [
'compute_color_source_matrix',
'compute_spell_pip_weights',
'parse_theme_tags',
'normalize_theme_list',
'detect_viable_multi_copy_archetypes',
'prefer_owned_first',
'compute_adjusted_target',
'normalize_tag_cell',
'sort_by_priority',
'COLOR_LETTERS',
'tapped_land_penalty',
'replacement_land_score',
'build_tag_driven_suggestions',
'select_color_balance_removal',
'color_balance_addition_candidates',
'basic_land_names',
'count_basic_lands',
'choose_basic_to_trim',
'enforce_land_cap',
'is_color_fixing_land',
'weighted_sample_without_replacement',
'count_existing_fetches',
'select_top_land_candidates',
]
def compute_adjusted_target(category_label: str,
original_cfg: int,
existing: int,
output_func,
plural_word: str | None = None,
bonus_max_pct: float = 0.2,
rng=None) -> tuple[int, int]:
"""Compute how many additional cards of a category to add applying a random bonus.
Returns (to_add, bonus). to_add may be 0 if target already satisfied and bonus doesn't push above existing.
Parameters
----------
category_label : str
Human-readable label (e.g. 'Ramp', 'Removal').
original_cfg : int
Configured target count.
existing : int
How many already present.
output_func : callable
Function for emitting messages (e.g. print or logger).
plural_word : str | None
Phrase used in messages for plural additions. If None derives from label (lower + ' spells').
bonus_max_pct : float
Upper bound for random bonus percent (default 0.2 => up to +20%).
rng : object | None
Optional random-like object with uniform().
"""
if original_cfg <= 0:
return 0, 0
plural_word = plural_word or f"{category_label.lower()} spells"
# Random bonus between 0 and bonus_max_pct inclusive
roll = (rng.uniform(0.0, bonus_max_pct) if rng else _rand.uniform(0.0, bonus_max_pct))
bonus = math.ceil(original_cfg * roll) if original_cfg > 0 else 0
if existing >= original_cfg:
to_add = original_cfg + bonus - existing
if to_add <= 0:
output_func(f"{category_label} target met ({existing}/{original_cfg}). Random bonus {bonus} -> no additional {plural_word} needed.")
return 0, bonus
output_func(f"{category_label} target met ({existing}/{original_cfg}). Adding random bonus {bonus}; scheduling {to_add} extra {plural_word}.")
return to_add, bonus
remaining_need = original_cfg - existing
to_add = remaining_need + bonus
output_func(f"Existing {category_label.lower()} {existing}/{original_cfg}. Remaining need {remaining_need}. Random bonus {bonus}. Adding {to_add} {plural_word}.")
return to_add, bonus
def tapped_land_penalty(tline: str, text_field: str) -> tuple[int, int]:
"""Classify a land for tapped optimization.
Returns (tapped_flag, penalty). tapped_flag is 1 if the land counts toward
the tapped threshold. Penalty is higher for worse (slower) lands. Non-tapped
lands return (0, 0).
"""
tline_l = tline.lower()
text_l = text_field.lower()
if 'land' not in tline_l:
return 0, 0
always_tapped = 'enters the battlefield tapped' in text_l
shock_like = 'you may pay 2 life' in text_l # shocks can be untapped
conditional = any(kw in text_l for kw in ['unless you control', 'if you control', 'as long as you control']) or shock_like
tapped_flag = 0
if always_tapped and not shock_like:
tapped_flag = 1
elif conditional:
tapped_flag = 1
if not tapped_flag:
return 0, 0
tri_types = sum(1 for b in bc.BASIC_LAND_TYPE_KEYWORDS if b in tline_l) >= 3
any_color = any(p in text_l for p in bc.ANY_COLOR_MANA_PHRASES)
cycling = 'cycling' in text_l
life_gain = 'gain' in text_l and 'life' in text_l and 'you gain' in text_l
produces_basic_colors = any(sym in text_l for sym in bc.COLORED_MANA_SYMBOLS)
penalty = 8 if always_tapped and not conditional else 6
if tri_types:
penalty -= 3
if any_color:
penalty -= 3
if cycling:
penalty -= 2
if conditional:
penalty -= 2
if not produces_basic_colors and not any_color:
penalty += 1
if life_gain:
penalty += 1
return tapped_flag, penalty
def replacement_land_score(name: str, tline: str, text_field: str) -> int:
"""Heuristic scoring of candidate replacement lands (higher is better)."""
tline_l = tline.lower()
text_l = text_field.lower()
score = 0
lname = name.lower()
# Prioritize shocks explicitly
if any(kw in lname for kw in ['blood crypt', 'steam vents', 'watery grave', 'breeding pool', 'godless shrine', 'hallowed fountain', 'overgrown tomb', 'stomping ground', 'temple garden', 'sacred foundry']):
score += 20
if 'you may pay 2 life' in text_l:
score += 15
if any(p in text_l for p in bc.ANY_COLOR_MANA_PHRASES):
score += 10
types_present = [b for b in bc.BASIC_LAND_TYPE_KEYWORDS if b in tline_l]
score += len(types_present) * 3
if 'unless you control' in text_l:
score += 2
if 'cycling' in text_l:
score += 1
return score
def is_color_fixing_land(tline: str, text_lower: str) -> bool:
"""Heuristic to detect if a land significantly fixes colors.
Criteria:
- Two or more basic land types
- Produces any color (explicit text)
- Text shows two or more distinct colored mana symbols
"""
basic_count = sum(1 for bk in bc.BASIC_LAND_TYPE_KEYWORDS if bk in tline.lower())
if basic_count >= 2:
return True
if any(p in text_lower for p in bc.ANY_COLOR_MANA_PHRASES):
return True
distinct = {cw for cw in bc.COLORED_MANA_SYMBOLS if cw in text_lower}
return len(distinct) >= 2
# ---------------------------------------------------------------------------
# Weighted sampling & fetch helpers
# ---------------------------------------------------------------------------
def weighted_sample_without_replacement(pool: list[tuple[str, int | float]], k: int, rng=None) -> list[str]:
"""Sample up to k unique names from (name, weight) pool without replacement.
If total weight becomes 0, stops early. Stable for small pools used here.
"""
if k <= 0 or not pool:
return []
# _rand imported at module level
local_rng = rng if rng is not None else _rand
working = pool.copy()
chosen: list[str] = []
while working and len(chosen) < k:
total_w = sum(max(0, float(w)) for _, w in working)
if total_w <= 0:
break
r = local_rng.random() * total_w
acc = 0.0
pick_idx = 0
for idx, (nm, w) in enumerate(working):
acc += max(0, float(w))
if r <= acc:
pick_idx = idx
break
nm, _w = working.pop(pick_idx)
chosen.append(nm)
return chosen
# -----------------------------
# Land Debug Export Helper
# -----------------------------
def export_current_land_pool(builder, label: str) -> None:
"""Write a CSV snapshot of current land candidates (full dataframe filtered to lands).
Outputs to logs/debug/land_step_{label}_test.csv. Guarded so it only runs if the combined
dataframe exists. Designed for diagnosing filtering shrinkage between land steps.
"""
try: # pragma: no cover - diagnostics
df = getattr(builder, '_combined_cards_df', None)
if df is None or getattr(df, 'empty', True):
return
col = 'type' if 'type' in df.columns else ('type_line' if 'type_line' in df.columns else None)
if not col:
return
land_df = df[df[col].fillna('').str.contains('Land', case=False, na=False)].copy()
if land_df.empty:
return
import os
os.makedirs(os.path.join('logs','debug'), exist_ok=True)
export_cols = [c for c in ['name','type','type_line','manaValue','edhrecRank','colorIdentity','manaCost','themeTags','oracleText'] if c in land_df.columns]
path = os.path.join('logs','debug', f'land_step_{label}_test.csv')
try:
if export_cols:
land_df[export_cols].to_csv(path, index=False, encoding='utf-8')
else:
land_df.to_csv(path, index=False, encoding='utf-8')
except Exception:
land_df.to_csv(path, index=False)
try:
builder.output_func(f"[DEBUG] Wrote land_step_{label}_test.csv ({len(land_df)} rows)")
except Exception:
pass
except Exception:
pass
def count_existing_fetches(card_library: dict) -> int:
bc = __import__('deck_builder.builder_constants', fromlist=['FETCH_LAND_MAX_CAP'])
total = 0
generic = getattr(bc, 'GENERIC_FETCH_LANDS', [])
for n in generic:
if n in card_library:
total += card_library[n].get('Count', 1)
for seq in getattr(bc, 'COLOR_TO_FETCH_LANDS', {}).values():
for n in seq:
if n in card_library:
total += card_library[n].get('Count', 1)
return total
def select_top_land_candidates(df, already: set[str], basics: set[str], top_n: int) -> list[tuple[int,str,str,str]]:
"""Return list of (edh_rank, name, type_line, text_lower) for top_n remaining lands.
Falls back to large rank number if edhrecRank missing/unparseable.
"""
out: list[tuple[int,str,str,str]] = []
if df is None or getattr(df, 'empty', True):
return out
for _, row in df.iterrows(): # type: ignore[attr-defined]
try:
name = str(row.get('name',''))
if not name or name in already or name in basics:
continue
tline = str(row.get('type', row.get('type_line','')))
if 'land' not in tline.lower():
continue
edh = row.get('edhrecRank') if 'edhrecRank' in df.columns else None
try:
edh_val = int(edh) if edh not in (None,'','nan') else 999999
except Exception:
edh_val = 999999
text_lower = str(row.get('text', row.get('oracleText',''))).lower()
out.append((edh_val, name, tline, text_lower))
except Exception:
continue
out.sort(key=lambda x: x[0])
return out[:top_n]
# ---------------------------------------------------------------------------
# Misc land filtering helpers (mono-color exclusions & tribal weighting)
# ---------------------------------------------------------------------------
def is_mono_color(builder) -> bool:
try:
ci = getattr(builder, 'color_identity', []) or []
return len([c for c in ci if c in ('W','U','B','R','G')]) == 1
except Exception:
return False
def has_kindred_theme(builder) -> bool:
try:
tags = [t.lower() for t in (getattr(builder, 'selected_tags', []) or [])]
return any(('kindred' in t or 'tribal' in t) for t in tags)
except Exception:
return False
def is_kindred_land(name: str) -> bool:
"""Return True if the land is considered kindred-oriented (unified constant)."""
from . import builder_constants as bc # local import to avoid cycles
kindred = set(getattr(bc, 'KINDRED_LAND_NAMES', [])) or {d['name'] for d in getattr(bc, 'KINDRED_STAPLE_LANDS', [])}
return name in kindred
def misc_land_excluded_in_mono(builder, name: str) -> bool:
"""Return True if a land should be excluded in mono-color decks per constant list.
Exclusion rules:
- Only applies if deck is mono-color.
- Never exclude items in MONO_COLOR_MISC_LAND_KEEP_ALWAYS.
- Never exclude tribal/kindred lands (they may be down-weighted separately if no theme).
- Always exclude The World Tree if not 5-color identity.
"""
from . import builder_constants as bc
try:
ci = getattr(builder, 'color_identity', []) or []
# World Tree legality check (needs all five colors in identity)
if name == 'The World Tree' and set(ci) != {'W','U','B','R','G'}:
return True
if not is_mono_color(builder):
return False
if name in getattr(bc, 'MONO_COLOR_MISC_LAND_KEEP_ALWAYS', []):
return False
if is_kindred_land(name):
return False
if name in getattr(bc, 'MONO_COLOR_MISC_LAND_EXCLUDE', []):
return True
except Exception:
return False
return False
def adjust_misc_land_weight(builder, name: str, base_weight: int | float) -> int | float:
"""Adjust weight for tribal lands when no tribal theme present.
If land is tribal and no kindred theme, weight is reduced (min 1) by factor.
"""
if is_kindred_land(name) and not has_kindred_theme(builder):
try:
# Ensure we don't drop below 1 (else risk exclusion by sampling step)
return max(1, int(base_weight * 0.5))
except Exception:
return base_weight
return base_weight
# ---------------------------------------------------------------------------
# Generic DataFrame helpers (tag normalization & sorting)
# ---------------------------------------------------------------------------
def normalize_tag_cell(cell):
"""Normalize a themeTags-like cell into a lowercase list of tags.
Accepts list, nested list, or string forms. Mirrors logic previously in multiple
methods inside builder.py.
"""
if isinstance(cell, list):
out: list[str] = []
for v in cell:
if isinstance(v, list):
out.extend(str(x).strip().lower() for x in v if str(x).strip())
else:
vs = str(v).strip().lower()
if vs:
out.append(vs)
return out
if isinstance(cell, str):
raw = cell.lower()
for ch in '[]"':
raw = raw.replace(ch, ' ')
parts = [p.strip().strip("'\"") for p in raw.replace(';', ',').split(',') if p.strip()]
return [p for p in parts if p]
return []
def sort_by_priority(df, columns: list[str]):
"""Sort DataFrame by listed columns ascending if present; ignores missing.
Returns new DataFrame (does not mutate original)."""
present = [c for c in columns if c in df.columns]
if not present:
return df
return df.sort_values(by=present, ascending=[True]*len(present), na_position='last')
def _normalize_tags_list(tags: list[str]) -> list[str]:
out: list[str] = []
seen = set()
for t in tags or []:
tt = str(t).strip().lower()
if tt and tt not in seen:
out.append(tt)
seen.add(tt)
return out
def _color_subset_ok(required: list[str], commander_ci: list[str]) -> bool:
if not required:
return True
ci = {c.upper() for c in commander_ci}
need = {c.upper() for c in required}
return need.issubset(ci)
def detect_viable_multi_copy_archetypes(builder) -> list[dict]:
"""Return ranked viable multi-copy archetypes for the given builder.
Output items: { id, name, printed_cap, type_hint, score, reasons }
Never raises; returns [] on missing data.
"""
try:
from . import builder_constants as bc
except Exception:
return []
# Commander color identity and tags
try:
ci = list(getattr(builder, 'color_identity', []) or [])
except Exception:
ci = []
# Gather tags from selected + commander summary
tags: list[str] = []
try:
tags.extend([t for t in getattr(builder, 'selected_tags', []) or []])
except Exception:
pass
try:
cmd = getattr(builder, 'commander_dict', {}) or {}
themes = cmd.get('Themes', [])
if isinstance(themes, list):
tags.extend(themes)
except Exception:
pass
tags_norm = _normalize_tags_list(tags)
out: list[dict] = []
# Exclusivity prep: if multiple in same group qualify, we still compute score, suppression happens in consumer or by taking top one.
for aid, meta in getattr(bc, 'MULTI_COPY_ARCHETYPES', {}).items():
try:
# Color gate
if not _color_subset_ok(meta.get('color_identity', []), ci):
continue
# Tag triggers
trig = meta.get('triggers', {}) or {}
any_tags = _normalize_tags_list(trig.get('tags_any', []) or [])
all_tags = _normalize_tags_list(trig.get('tags_all', []) or [])
score = 0
reasons: list[str] = []
# +2 for color match baseline
if meta.get('color_identity'):
score += 2
reasons.append('color identity fits')
# +1 per matched any tag (cap small to avoid dwarfing)
matches_any = [t for t in any_tags if t in tags_norm]
if matches_any:
bump = min(3, len(matches_any))
score += bump
reasons.append('tags: ' + ', '.join(matches_any[:3]))
# +1 if all required tags matched
if all_tags and all(t in tags_norm for t in all_tags):
score += 1
reasons.append('all required tags present')
if score <= 0:
continue
out.append({
'id': aid,
'name': meta.get('name', aid),
'printed_cap': meta.get('printed_cap'),
'type_hint': meta.get('type_hint', 'noncreature'),
'exclusive_group': meta.get('exclusive_group'),
'default_count': meta.get('default_count', 25),
'rec_window': meta.get('rec_window', (20,30)),
'thrumming_stone_synergy': bool(meta.get('thrumming_stone_synergy', True)),
'score': score,
'reasons': reasons,
})
except Exception:
continue
# Suppress lower-scored siblings within the same exclusive group, keep the highest per group
grouped: dict[str, list[dict]] = {}
rest: list[dict] = []
for item in out:
grp = item.get('exclusive_group')
if grp:
grouped.setdefault(grp, []).append(item)
else:
rest.append(item)
kept: list[dict] = rest[:]
for grp, items in grouped.items():
items.sort(key=lambda d: d.get('score', 0), reverse=True)
kept.append(items[0])
kept.sort(key=lambda d: d.get('score', 0), reverse=True)
return kept
def prefer_owned_first(df, owned_names_lower: set[str], name_col: str = 'name'):
"""Stable-reorder DataFrame to put owned names first while preserving prior sort.
- Adds a temporary column to flag ownership, sorts by it desc with mergesort, then drops it.
- If the name column is missing or owned_names_lower empty, returns df unchanged.
"""
try:
if df is None or getattr(df, 'empty', True):
return df
if not owned_names_lower:
return df
if name_col not in df.columns:
return df
tmp_col = '_ownedPref'
# Avoid clobbering if already present
while tmp_col in df.columns:
tmp_col = tmp_col + '_x'
ser = df[name_col].astype(str).str.lower().isin(owned_names_lower).astype(int)
df = df.assign(**{tmp_col: ser})
df = df.sort_values(by=[tmp_col], ascending=[False], kind='mergesort')
df = df.drop(columns=[tmp_col])
return df
except Exception:
return df
# ---------------------------------------------------------------------------
# Tag-driven land suggestion helpers
# ---------------------------------------------------------------------------
def build_tag_driven_suggestions(builder) -> list[dict]: # type: ignore[override]
"""Return a list of suggestion dicts based on selected commander tags.
Each dict fields:
name, reason, condition (callable taking builder), flex (bool), defer_if_full (bool)
"""
tags_lower = [t.lower() for t in getattr(builder, 'selected_tags', [])]
existing = set(builder.card_library.keys())
suggestions: list[dict] = []
def cond_always(_):
return True
def cond_artifact_threshold(b):
art_count = sum(1 for v in b.card_library.values() if 'artifact' in str(v.get('Card Type', '')).lower())
return art_count >= 10
mapping = [
(['+1/+1 counters', 'counters matter'], 'Gavony Township', cond_always, '+1/+1 Counters support', True),
(['token', 'tokens', 'wide'], 'Castle Ardenvale', cond_always, 'Token strategy support', True),
(['graveyard', 'recursion', 'reanimator'], 'Boseiju, Who Endures', cond_always, 'Graveyard interaction / utility', False),
(['graveyard', 'recursion', 'reanimator'], 'Takenuma, Abandoned Mire', cond_always, 'Recursion utility', True),
(['artifact'], "Inventors' Fair", cond_artifact_threshold, 'Artifact payoff (conditional)', True),
]
for tag_keys, land_name, condition, reason, flex in mapping:
if any(k in tl for k in tag_keys for tl in tags_lower):
if land_name not in existing:
suggestions.append({
'name': land_name,
'reason': reason,
'condition': condition,
'flex': flex,
'defer_if_full': True
})
# Landfall fetch cap soft bump (side-effect set on builder)
if any('landfall' in tl for tl in tags_lower) and not hasattr(builder, '_landfall_fetch_bump_applied'):
setattr(builder, '_landfall_fetch_bump_applied', True)
builder.dynamic_fetch_cap = getattr(__import__('deck_builder.builder_constants', fromlist=['FETCH_LAND_MAX_CAP']), 'FETCH_LAND_MAX_CAP', 7) + 1 # safe fallback
return suggestions
# ---------------------------------------------------------------------------
# Color balance swap helpers
# ---------------------------------------------------------------------------
def select_color_balance_removal(builder, deficit_colors: set[str], overages: dict[str, float]) -> str | None:
"""Select a land to remove when performing color balance swaps.
Preference order:
1. Flex lands not producing any deficit colors
2. Basic land of the most overrepresented color
3. Mono-color non-flex land not producing deficit colors
"""
matrix_current = builder._compute_color_source_matrix()
land_names = set(matrix_current.keys()) # ensure we only ever remove lands
# Flex lands first
for name, entry in builder.card_library.items():
if name not in land_names:
continue
if entry.get('Role') == 'flex':
colors = matrix_current.get(name, {})
if not any(colors.get(c, 0) for c in deficit_colors):
return name
# Basic of most overrepresented color
if overages:
color_remove = max(overages.items(), key=lambda x: x[1])[0]
basic_map = {'W': 'Plains', 'U': 'Island', 'B': 'Swamp', 'R': 'Mountain', 'G': 'Forest'}
candidate = basic_map.get(color_remove)
if candidate and candidate in builder.card_library and candidate in land_names:
return candidate
# Mono-color non-flex lands
for name, entry in builder.card_library.items():
if name not in land_names:
continue
if entry.get('Role') == 'flex':
continue
colors = matrix_current.get(name, {})
color_count = sum(1 for v in colors.values() if v)
if color_count <= 1 and not any(colors.get(c, 0) for c in deficit_colors):
return name
return None
def color_balance_addition_candidates(builder, target_color: str, combined_df) -> list[str]:
"""Rank potential addition lands for a target color (best first)."""
if combined_df is None or getattr(combined_df, 'empty', True):
return []
existing = set(builder.card_library.keys())
out: list[tuple[str, int]] = []
for _, row in combined_df.iterrows(): # type: ignore[attr-defined]
name = str(row.get('name', ''))
if not name or name in existing or any(name == o[0] for o in out):
continue
tline = str(row.get('type', row.get('type_line', ''))).lower()
if 'land' not in tline:
continue
text_field = str(row.get('text', row.get('oracleText', ''))).lower()
produces = False
if target_color == 'W' and ('plains' in tline or '{w}' in text_field):
produces = True
if target_color == 'U' and ('island' in tline or '{u}' in text_field):
produces = True
if target_color == 'B' and ('swamp' in tline or '{b}' in text_field):
produces = True
if target_color == 'R' and ('mountain' in tline or '{r}' in text_field):
produces = True
if target_color == 'G' and ('forest' in tline or '{g}' in text_field):
produces = True
if not produces:
continue
any_color = 'add one mana of any color' in text_field
basic_types = sum(1 for b in bc.BASIC_LAND_TYPE_KEYWORDS if b in tline)
score = 0
if any_color:
score += 30
score += basic_types * 10
if 'enters the battlefield tapped' in text_field and 'you may pay 2 life' not in text_field:
score -= 5
out.append((name, score))
out.sort(key=lambda x: x[1], reverse=True)
return [n for n, _ in out]
# ---------------------------------------------------------------------------
# Basic land / land cap helpers
# ---------------------------------------------------------------------------
def basic_land_names() -> set[str]:
names = set(getattr(__import__('deck_builder.builder_constants', fromlist=['BASIC_LANDS']), 'BASIC_LANDS', []))
names.update(getattr(__import__('deck_builder.builder_constants', fromlist=['SNOW_BASIC_LAND_MAPPING']), 'SNOW_BASIC_LAND_MAPPING', {}).values())
names.add('Wastes')
return names
def count_basic_lands(card_library: dict) -> int:
basics = basic_land_names()
total = 0
for name, entry in card_library.items():
if name in basics:
total += entry.get('Count', 1)
return total
def choose_basic_to_trim(card_library: dict) -> str | None:
basics = basic_land_names()
candidates: list[tuple[int, str]] = []
for name, entry in card_library.items():
if name in basics:
cnt = entry.get('Count', 1)
if cnt > 0:
candidates.append((cnt, name))
if not candidates:
return None
candidates.sort(reverse=True)
return candidates[0][1]
def enforce_land_cap(builder, step_label: str = ""):
if not hasattr(builder, 'ideal_counts') or not getattr(builder, 'ideal_counts'):
return
bc = __import__('deck_builder.builder_constants', fromlist=['DEFAULT_LAND_COUNT'])
land_target = builder.ideal_counts.get('lands', getattr(bc, 'DEFAULT_LAND_COUNT', 35))
min_basic = builder.ideal_counts.get('basic_lands', getattr(bc, 'DEFAULT_BASIC_LAND_COUNT', 20))
# math not needed; using ceil via BASIC_FLOOR_FACTOR logic only
floor_basics = math.ceil(bc.BASIC_FLOOR_FACTOR * min_basic)
current_land = builder._current_land_count()
if current_land <= land_target:
return
builder.output_func(f"\nLand Cap Enforcement after {step_label}: Over target ({current_land}/{land_target}). Trimming basics...")
removed = 0
while current_land > land_target:
basic_total = count_basic_lands(builder.card_library)
if basic_total <= floor_basics:
builder.output_func(f"Stopped trimming: basic lands at floor {basic_total} (floor {floor_basics}). Still {current_land}/{land_target}.")
break
target_basic = choose_basic_to_trim(builder.card_library)
if not target_basic or not builder._decrement_card(target_basic):
builder.output_func("No basic lands available to trim further.")
break
removed += 1
current_land = builder._current_land_count()
if removed:
builder.output_func(f"Trimmed {removed} basic land(s). New land count: {current_land}/{land_target}. Basic total now {count_basic_lands(builder.card_library)} (floor {floor_basics}).")
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