59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
"""
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Generate a JSON Ability Tree [atree_constants_idfied.json] with:
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- All references replaced by numerical IDs
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given a JSON Ability Tree with reference as string AND a JSON Ability Names to IDs.
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"""
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import json
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# Ability names to IDs data
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with open("atree_ids.json") as f:
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id_data = json.loads(f.read())
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# Ability tree data with reference as string
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with open("atree_constants.json") as f:
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atree_data = json.loads(f.read())
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for _class, info in atree_data.items():
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def translate(path, ref):
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ref_dict = info
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for x in path:
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ref_dict = ref_dict[x]
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ref_dict[ref] = id_data[_class][ref_dict[ref]]
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for abil in range(len(info)):
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info[abil]["id"] = id_data[_class][info[abil]["display_name"]]
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for ref in range(len(info[abil]["parents"])):
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translate([abil, "parents"], ref)
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for ref in range(len(info[abil]["dependencies"])):
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translate([abil, "dependencies"], ref)
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for ref in range(len(info[abil]["blockers"])):
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translate([abil, "blockers"], ref)
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if "base_abil" in info[abil]:
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base_abil_name = info[abil]["base_abil"]
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if base_abil_name in id_data[_class]:
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translate([abil], "base_abil")
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if "effects" not in info[abil]:
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print(info[abil])
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info[abil]["effects"] = []
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for effect in info[abil]["effects"]:
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if effect["type"] == "raw_stat":
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for bonus in effect["bonuses"]:
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if "abil" in bonus:
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bonus["abil"] = id_data[_class][bonus["abil"]]
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elif effect["type"] == "stat_scaling":
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if "inputs" in effect: # Might not exist for sliders
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for _input in effect["inputs"]:
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if "abil" in _input:
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_input["abil"] = id_data[_class][_input["abil"]]
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if "abil" in effect["output"]:
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effect["output"]["abil"] = id_data[_class][effect["output"]["abil"]]
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with open('atree_constants_idfied.json', 'w', encoding='utf-8') as abil_dest:
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json.dump(atree_data, abil_dest, ensure_ascii=False, indent=4)
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