forked from log2timeline/dftimewolf
-
Notifications
You must be signed in to change notification settings - Fork 0
/
pytype.conf
77 lines (55 loc) · 2.21 KB
/
pytype.conf
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
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
# NOTE: All relative paths are relative to the location of this file.
[pytype]
# Space-separated list of files or directories to exclude.
#exclude =
# **/*_test.py
# **/test_*.py
# Space-separated list of files or directories to process.
inputs = dftimewolf tests
# Keep going past errors to analyze as many files as possible.
keep_going = True
# Run N jobs in parallel. When 'auto' is used, this will be equivalent to the
# number of CPUs on the host system.
jobs = auto
# All pytype output goes here.
output = .pytype
# Platform (e.g., "linux", "win32") that the target code runs on.
platform = linux
# Paths to source code directories, separated by ':'.
pythonpath =
.
# Python version (major.minor) of the target code.
python_version = 3.11
# Always use function return type annotations. This flag is temporary and will
# be removed once this behavior is enabled by default.
always_use_return_annotations = True
# Enable parameter count checks for overriding methods. This flag is temporary
# and will be removed once this behavior is enabled by default.
overriding_parameter_count_checks = True
# Enable return type checks for overriding methods. This flag is temporary and
# will be removed once this behavior is enabled by default.
overriding_return_type_checks = True
# Use the enum overlay for more precise enum checking. This flag is temporary
# and will be removed once this behavior is enabled by default.
use_enum_overlay = False
# Opt-in: Do not allow Any as a return type.
no_return_any = False
# Experimental: Support pyglib's @cached.property.
enable_cached_property = False
# Experimental: Infer precise return types even for invalid function calls.
precise_return = True
# Experimental: Solve unknown types to label with structural types.
protocols = False
# Experimental: Only load submodules that are explicitly imported.
strict_import = False
# Experimental: Enable exhaustive checking of function parameter types.
strict_parameter_checks = True
# Experimental: Emit errors for comparisons between incompatible primitive
# types.
strict_primitive_comparisons = False
# Comma or space separated list of error names to ignore.
disable =
pyi-error
import-error
# Don't report errors.
report_errors = True