cortado-core/setup.py at main · GroveGuard/cortado-core · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
from setuptools import setup

setup(
    name="cortado_core",
    version="1.3.27",
    author="Daniel Schuster",
    author_email="daniel.schuster@fit.fraunhofer.de",
    # package_dir={"": "cortado-core"},
    # packages=find_packages(where="cortado_core"),
    packages=[
        "cortado_core",
        "cortado_core.utils",
        "cortado_core.models",
        "cortado_core.freezing",
        "cortado_core.process_tree_utils",
        "cortado_core.performance",
        "cortado_core.variant_query_language",
        "cortado_core.variant_query_language.grammars",
        "cortado_core.alignments",
        "cortado_core.clustering",
        "cortado_core.alignments.infix_alignments",
        "cortado_core.alignments.infix_alignments.variants",
        "cortado_core.alignments.prefix_alignments",
        "cortado_core.alignments.prefix_alignments.variants",
        "cortado_core.alignments.suffix_alignments",
        "cortado_core.subprocess_discovery",
        "cortado_core.subprocess_discovery.subtree_mining",
        "cortado_core.subprocess_discovery.concurrency_trees",
        "cortado_core.subprocess_discovery.subtree_mining.right_most_path_extension",
        "cortado_core.subprocess_discovery.subtree_mining.metrics",
        "cortado_core.subprocess_discovery.subtree_mining.blanket_mining",
        "cortado_core.subprocess_discovery.subtree_mining.maximal_connected_components",
        "cortado_core.alignments.suffix_alignments",
        "cortado_core.eventually_follows_pattern_mining",
        "cortado_core.eventually_follows_pattern_mining.util",
        "cortado_core.eventually_follows_pattern_mining.occurrence_store",
        "cortado_core.eventually_follows_pattern_mining.frequency_counting",
        "cortado_core.eventually_follows_pattern_mining.candidate_enumeration",
        "cortado_core.eventually_follows_pattern_mining.candidate_enumeration.pruning_strategy",
        "cortado_core.eventually_follows_pattern_mining.blanket_mining",
        "cortado_core.eventually_follows_pattern_mining.blanket_mining.blanket_checks",
        "cortado_core.eventually_follows_pattern_mining.local_process_models",
        "cortado_core.eventually_follows_pattern_mining.local_process_models.clustering",
        "cortado_core.eventually_follows_pattern_mining.local_process_models.discovery",
        "cortado_core.eventually_follows_pattern_mining.local_process_models.similarity",
        "cortado_core.sequentializer",
        "cortado_core.variant_pattern_replications",
    ],
    install_requires=[
        "matplotlib>=3.8.0",
        "cycler",
        "antlr4-python3-runtime==4.7.2",
        "networkx>=3.2",
        "pm4py==2.4.1",
        "ortools",
        "tqdm>=4.66.0",
        "scikit-learn>=1.3.1",
        "zss==1.2.0",
        "numpy>=1.21.2,<2.0.0",
    ],
    python_requires=">=3.10",
)