81 lines
2.3 KiB
Python
81 lines
2.3 KiB
Python
# -*- mode: python ; coding: utf-8 -*-
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import os
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import dataui
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import confluent_kafka
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from PyInstaller.utils.hooks import collect_dynamic_libs, collect_submodules
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# ---- 定位 confluent_kafka.libs ----
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kafka_libs_dir = os.path.join(
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os.path.dirname(confluent_kafka.__file__),
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'..',
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'confluent_kafka.libs'
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)
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kafka_libs_dir = os.path.normpath(kafka_libs_dir)
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if not os.path.exists(kafka_libs_dir):
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alt_dir = os.path.join(
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os.path.dirname(os.path.dirname(confluent_kafka.__file__)),
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'confluent_kafka.libs'
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)
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if os.path.exists(alt_dir):
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kafka_libs_dir = alt_dir
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print(f"[SPEC] Kafka libs dir: {kafka_libs_dir}, exists: {os.path.exists(kafka_libs_dir)}")
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# ---- 收集 numpy/pandas 动态库（若使用） ----
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numpy_binaries = collect_dynamic_libs('numpy') if False else [] # 如果使用，改为 True
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pandas_binaries = collect_dynamic_libs('pandas') if False else []
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# 我们也可以直接通过 datas 包含它们的 .libs 目录（但更推荐用 collect_dynamic_libs）
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# 这里我们先用 collect_dynamic_libs 并合并到 binaries
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all_binaries = numpy_binaries + pandas_binaries # 加入 kafka 吗？不，我们用 datas
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duipath = os.path.dirname(dataui.__file__)
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block_cipher = None
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a = Analysis(
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['../src/kgadget.py'],
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pathex=['../src'],
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binaries=all_binaries, # 包含 numpy/pandas 的 .so
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datas=[
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(f'{duipath}/tmpl/bricks/*.*', 'dataui/tmpl/bricks'),
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(kafka_libs_dir, 'confluent_kafka.libs'), # 复制整个 kafka 目录
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],
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hiddenimports=[
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'sqlite3',
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'aiopg',
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'aiomysql',
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'confluent_kafka.admin',
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],
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hookspath=[],
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hooksconfig={},
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runtime_hooks=[],
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excludes=[],
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win_no_prefer_redirects=False,
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win_private_assemblies=False,
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cipher=block_cipher,
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noarchive=False
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)
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pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)
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exe = EXE(
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pyz,
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a.scripts,
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a.binaries,
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a.zipfiles,
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a.datas,
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[],
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name='kgadget',
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debug=False,
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bootloader_ignore_signals=False,
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strip=False,
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upx=False, # 务必关闭 UPX
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upx_exclude=[],
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runtime_tmpdir=None,
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console=True,
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disable_windowed_traceback=False,
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target_arch=None,
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codesign_identity=None,
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entitlements_file=None,
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onefile=False # 显式指定 onefile=False
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) |