Merge pull request #9 from MaxTretikov/master

Fix all pylint errors and add pylint to CI pipeline

.github/workflows/test.yml

@@ -27,4 +27,7 @@ jobs:
           pip install .[dev]
       - name: Run unit tests
         run: |
-          pytest -v tests/unit
+          pytest -v tests/unit
+      - name: Lint for errors
+        run: |
+          pylint comfy

.pylintrc

@@ -0,0 +1,880 @@
+[MAIN]
+
+# Analyse import fallback blocks. This can be used to support both Python 2 and
+# 3 compatible code, which means that the block might have code that exists
+# only in one or another interpreter, leading to false positives when analysed.
+analyse-fallback-blocks=no
+
+# Clear in-memory caches upon conclusion of linting. Useful if running pylint
+# in a server-like mode.
+clear-cache-post-run=no
+
+# Load and enable all available extensions. Use --list-extensions to see a list
+# all available extensions.
+#enable-all-extensions=
+
+# In error mode, messages with a category besides ERROR or FATAL are
+# suppressed, and no reports are done by default. Error mode is compatible with
+# disabling specific errors.
+#errors-only=
+
+# Always return a 0 (non-error) status code, even if lint errors are found.
+# This is primarily useful in continuous integration scripts.
+#exit-zero=
+
+# A comma-separated list of package or module names from where C extensions may
+# be loaded. Extensions are loading into the active Python interpreter and may
+# run arbitrary code.
+extension-pkg-allow-list=
+
+# A comma-separated list of package or module names from where C extensions may
+# be loaded. Extensions are loading into the active Python interpreter and may
+# run arbitrary code. (This is an alternative name to extension-pkg-allow-list
+# for backward compatibility.)
+extension-pkg-whitelist=
+
+# Return non-zero exit code if any of these messages/categories are detected,
+# even if score is above --fail-under value. Syntax same as enable. Messages
+# specified are enabled, while categories only check already-enabled messages.
+fail-on=
+
+# Specify a score threshold under which the program will exit with error.
+fail-under=10
+
+# Interpret the stdin as a python script, whose filename needs to be passed as
+# the module_or_package argument.
+#from-stdin=
+
+# Files or directories to be skipped. They should be base names, not paths.
+ignore=CVS
+
+# Add files or directories matching the regular expressions patterns to the
+# ignore-list. The regex matches against paths and can be in Posix or Windows
+# format. Because '\\' represents the directory delimiter on Windows systems,
+# it can't be used as an escape character.
+ignore-paths=
+
+# Files or directories matching the regular expression patterns are skipped.
+# The regex matches against base names, not paths. The default value ignores
+# Emacs file locks
+ignore-patterns=^\.#
+
+# List of module names for which member attributes should not be checked and
+# will not be imported (useful for modules/projects where namespaces are
+# manipulated during runtime and thus existing member attributes cannot be
+# deduced by static analysis). It supports qualified module names, as well as
+# Unix pattern matching.
+ignored-modules=
+
+# Python code to execute, usually for sys.path manipulation such as
+# pygtk.require().
+#init-hook=
+
+# Use multiple processes to speed up Pylint. Specifying 0 will auto-detect the
+# number of processors available to use, and will cap the count on Windows to
+# avoid hangs.
+jobs=1
+
+# Control the amount of potential inferred values when inferring a single
+# object. This can help the performance when dealing with large functions or
+# complex, nested conditions.
+limit-inference-results=100
+
+# List of plugins (as comma separated values of python module names) to load,
+# usually to register additional checkers.
+load-plugins=
+
+# Pickle collected data for later comparisons.
+persistent=yes
+
+# Resolve imports to .pyi stubs if available. May reduce no-member messages and
+# increase not-an-iterable messages.
+prefer-stubs=no
+
+# Minimum Python version to use for version dependent checks. Will default to
+# the version used to run pylint.
+py-version=3.12
+
+# Discover python modules and packages in the file system subtree.
+recursive=no
+
+# Add paths to the list of the source roots. Supports globbing patterns. The
+# source root is an absolute path or a path relative to the current working
+# directory used to determine a package namespace for modules located under the
+# source root.
+source-roots=
+
+# When enabled, pylint would attempt to guess common misconfiguration and emit
+# user-friendly hints instead of false-positive error messages.
+suggestion-mode=yes
+
+# Allow loading of arbitrary C extensions. Extensions are imported into the
+# active Python interpreter and may run arbitrary code.
+unsafe-load-any-extension=no
+
+# In verbose mode, extra non-checker-related info will be displayed.
+#verbose=
+
+
+[BASIC]
+
+# Naming style matching correct argument names.
+argument-naming-style=snake_case
+
+# Regular expression matching correct argument names. Overrides argument-
+# naming-style. If left empty, argument names will be checked with the set
+# naming style.
+#argument-rgx=
+
+# Naming style matching correct attribute names.
+attr-naming-style=snake_case
+
+# Regular expression matching correct attribute names. Overrides attr-naming-
+# style. If left empty, attribute names will be checked with the set naming
+# style.
+#attr-rgx=
+
+# Bad variable names which should always be refused, separated by a comma.
+bad-names=foo,
+          bar,
+          baz,
+          toto,
+          tutu,
+          tata
+
+# Bad variable names regexes, separated by a comma. If names match any regex,
+# they will always be refused
+bad-names-rgxs=
+
+# Naming style matching correct class attribute names.
+class-attribute-naming-style=any
+
+# Regular expression matching correct class attribute names. Overrides class-
+# attribute-naming-style. If left empty, class attribute names will be checked
+# with the set naming style.
+#class-attribute-rgx=
+
+# Naming style matching correct class constant names.
+class-const-naming-style=UPPER_CASE
+
+# Regular expression matching correct class constant names. Overrides class-
+# const-naming-style. If left empty, class constant names will be checked with
+# the set naming style.
+#class-const-rgx=
+
+# Naming style matching correct class names.
+class-naming-style=PascalCase
+
+# Regular expression matching correct class names. Overrides class-naming-
+# style. If left empty, class names will be checked with the set naming style.
+#class-rgx=
+
+# Naming style matching correct constant names.
+const-naming-style=UPPER_CASE
+
+# Regular expression matching correct constant names. Overrides const-naming-
+# style. If left empty, constant names will be checked with the set naming
+# style.
+#const-rgx=
+
+# Minimum line length for functions/classes that require docstrings, shorter
+# ones are exempt.
+docstring-min-length=-1
+
+# Naming style matching correct function names.
+function-naming-style=snake_case
+
+# Regular expression matching correct function names. Overrides function-
+# naming-style. If left empty, function names will be checked with the set
+# naming style.
+#function-rgx=
+
+# Good variable names which should always be accepted, separated by a comma.
+good-names=i,
+           j,
+           k,
+           ex,
+           Run,
+           _
+
+# Good variable names regexes, separated by a comma. If names match any regex,
+# they will always be accepted
+good-names-rgxs=
+
+# Include a hint for the correct naming format with invalid-name.
+include-naming-hint=no
+
+# Naming style matching correct inline iteration names.
+inlinevar-naming-style=any
+
+# Regular expression matching correct inline iteration names. Overrides
+# inlinevar-naming-style. If left empty, inline iteration names will be checked
+# with the set naming style.
+#inlinevar-rgx=
+
+# Naming style matching correct method names.
+method-naming-style=snake_case
+
+# Regular expression matching correct method names. Overrides method-naming-
+# style. If left empty, method names will be checked with the set naming style.
+#method-rgx=
+
+# Naming style matching correct module names.
+module-naming-style=snake_case
+
+# Regular expression matching correct module names. Overrides module-naming-
+# style. If left empty, module names will be checked with the set naming style.
+#module-rgx=
+
+# Colon-delimited sets of names that determine each other's naming style when
+# the name regexes allow several styles.
+name-group=
+
+# Regular expression which should only match function or class names that do
+# not require a docstring.
+no-docstring-rgx=^_
+
+# List of decorators that produce properties, such as abc.abstractproperty. Add
+# to this list to register other decorators that produce valid properties.
+# These decorators are taken in consideration only for invalid-name.
+property-classes=abc.abstractproperty
+
+# Regular expression matching correct type alias names. If left empty, type
+# alias names will be checked with the set naming style.
+#typealias-rgx=
+
+# Regular expression matching correct type variable names. If left empty, type
+# variable names will be checked with the set naming style.
+#typevar-rgx=
+
+# Naming style matching correct variable names.
+variable-naming-style=snake_case
+
+# Regular expression matching correct variable names. Overrides variable-
+# naming-style. If left empty, variable names will be checked with the set
+# naming style.
+#variable-rgx=
+
+
+[CLASSES]
+
+# Warn about protected attribute access inside special methods
+check-protected-access-in-special-methods=no
+
+# List of method names used to declare (i.e. assign) instance attributes.
+defining-attr-methods=__init__,
+                      __new__,
+                      setUp,
+                      asyncSetUp,
+                      __post_init__
+
+# List of member names, which should be excluded from the protected access
+# warning.
+exclude-protected=_asdict,_fields,_replace,_source,_make,os._exit
+
+# List of valid names for the first argument in a class method.
+valid-classmethod-first-arg=cls
+
+# List of valid names for the first argument in a metaclass class method.
+valid-metaclass-classmethod-first-arg=mcs
+
+
+[DESIGN]
+
+# List of regular expressions of class ancestor names to ignore when counting
+# public methods (see R0903)
+exclude-too-few-public-methods=
+
+# List of qualified class names to ignore when counting class parents (see
+# R0901)
+ignored-parents=
+
+# Maximum number of arguments for function / method.
+max-args=5
+
+# Maximum number of attributes for a class (see R0902).
+max-attributes=7
+
+# Maximum number of boolean expressions in an if statement (see R0916).
+max-bool-expr=5
+
+# Maximum number of branch for function / method body.
+max-branches=12
+
+# Maximum number of locals for function / method body.
+max-locals=15
+
+# Maximum number of parents for a class (see R0901).
+max-parents=7
+
+# Maximum number of public methods for a class (see R0904).
+max-public-methods=20
+
+# Maximum number of return / yield for function / method body.
+max-returns=6
+
+# Maximum number of statements in function / method body.
+max-statements=50
+
+# Minimum number of public methods for a class (see R0903).
+min-public-methods=2
+
+
+[EXCEPTIONS]
+
+# Exceptions that will emit a warning when caught.
+overgeneral-exceptions=builtins.BaseException,builtins.Exception
+
+
+[FORMAT]
+
+# Expected format of line ending, e.g. empty (any line ending), LF or CRLF.
+expected-line-ending-format=
+
+# Regexp for a line that is allowed to be longer than the limit.
+ignore-long-lines=^\s*(# )?<?https?://\S+>?$
+
+# Number of spaces of indent required inside a hanging or continued line.
+indent-after-paren=4
+
+# String used as indentation unit. This is usually "    " (4 spaces) or "\t" (1
+# tab).
+indent-string='    '
+
+# Maximum number of characters on a single line.
+max-line-length=100
+
+# Maximum number of lines in a module.
+max-module-lines=1000
+
+# Allow the body of a class to be on the same line as the declaration if body
+# contains single statement.
+single-line-class-stmt=no
+
+# Allow the body of an if to be on the same line as the test if there is no
+# else.
+single-line-if-stmt=no
+
+
+[IMPORTS]
+
+# List of modules that can be imported at any level, not just the top level
+# one.
+allow-any-import-level=
+
+# Allow explicit reexports by alias from a package __init__.
+allow-reexport-from-package=no
+
+# Allow wildcard imports from modules that define __all__.
+allow-wildcard-with-all=no
+
+# Deprecated modules which should not be used, separated by a comma.
+deprecated-modules=
+
+# Output a graph (.gv or any supported image format) of external dependencies
+# to the given file (report RP0402 must not be disabled).
+ext-import-graph=
+
+# Output a graph (.gv or any supported image format) of all (i.e. internal and
+# external) dependencies to the given file (report RP0402 must not be
+# disabled).
+import-graph=
+
+# Output a graph (.gv or any supported image format) of internal dependencies
+# to the given file (report RP0402 must not be disabled).
+int-import-graph=
+
+# Force import order to recognize a module as part of the standard
+# compatibility libraries.
+known-standard-library=
+
+# Force import order to recognize a module as part of a third party library.
+known-third-party=enchant
+
+# Couples of modules and preferred modules, separated by a comma.
+preferred-modules=
+
+
+[LOGGING]
+
+# The type of string formatting that logging methods do. `old` means using %
+# formatting, `new` is for `{}` formatting.
+logging-format-style=old
+
+# Logging modules to check that the string format arguments are in logging
+# function parameter format.
+logging-modules=logging
+
+
+[MESSAGES CONTROL]
+
+# Only show warnings with the listed confidence levels. Leave empty to show
+# all. Valid levels: HIGH, CONTROL_FLOW, INFERENCE, INFERENCE_FAILURE,
+# UNDEFINED.
+confidence=HIGH,
+           CONTROL_FLOW,
+           INFERENCE,
+           INFERENCE_FAILURE,
+           UNDEFINED
+
+# Disable the message, report, category or checker with the given id(s). You
+# can either give multiple identifiers separated by comma (,) or put this
+# option multiple times (only on the command line, not in the configuration
+# file where it should appear only once). You can also use "--disable=all" to
+# disable everything first and then re-enable specific checks. For example, if
+# you want to run only the similarities checker, you can use "--disable=all
+# --enable=similarities". If you want to run only the classes checker, but have
+# no Warning level messages displayed, use "--disable=all --enable=classes
+# --disable=W".
+disable=raw-checker-failed,
+        bad-inline-option,
+        locally-disabled,
+        file-ignored,
+        suppressed-message,
+        useless-suppression,
+        deprecated-pragma,
+        use-symbolic-message-instead,
+        use-implicit-booleaness-not-comparison-to-string,
+        use-implicit-booleaness-not-comparison-to-zero,
+        useless-option-value,
+        no-classmethod-decorator,
+        no-staticmethod-decorator,
+        useless-object-inheritance,
+        property-with-parameters,
+        cyclic-import,
+        consider-using-from-import,
+        consider-merging-isinstance,
+        too-many-nested-blocks,
+        simplifiable-if-statement,
+        redefined-argument-from-local,
+        no-else-return,
+        consider-using-ternary,
+        trailing-comma-tuple,
+        stop-iteration-return,
+        simplify-boolean-expression,
+        inconsistent-return-statements,
+        useless-return,
+        consider-swap-variables,
+        consider-using-join,
+        consider-using-in,
+        consider-using-get,
+        chained-comparison,
+        consider-using-dict-comprehension,
+        consider-using-set-comprehension,
+        simplifiable-if-expression,
+        no-else-raise,
+        unnecessary-comprehension,
+        consider-using-sys-exit,
+        no-else-break,
+        no-else-continue,
+        super-with-arguments,
+        simplifiable-condition,
+        condition-evals-to-constant,
+        consider-using-generator,
+        use-a-generator,
+        consider-using-min-builtin,
+        consider-using-max-builtin,
+        consider-using-with,
+        unnecessary-dict-index-lookup,
+        use-list-literal,
+        use-dict-literal,
+        unnecessary-list-index-lookup,
+        use-yield-from,
+        duplicate-code,
+        too-many-ancestors,
+        too-many-instance-attributes,
+        too-few-public-methods,
+        too-many-public-methods,
+        too-many-return-statements,
+        too-many-branches,
+        too-many-arguments,
+        too-many-locals,
+        too-many-statements,
+        too-many-boolean-expressions,
+        too-many-positional,
+        literal-comparison,
+        comparison-with-itself,
+        comparison-of-constants,
+        wrong-spelling-in-comment,
+        wrong-spelling-in-docstring,
+        invalid-characters-in-docstring,
+        unnecessary-dunder-call,
+        bad-file-encoding,
+        bad-classmethod-argument,
+        bad-mcs-method-argument,
+        bad-mcs-classmethod-argument,
+        single-string-used-for-slots,
+        unnecessary-lambda-assignment,
+        unnecessary-direct-lambda-call,
+        non-ascii-name,
+        non-ascii-module-import,
+        line-too-long,
+        too-many-lines,
+        trailing-whitespace,
+        missing-final-newline,
+        trailing-newlines,
+        multiple-statements,
+        superfluous-parens,
+        mixed-line-endings,
+        unexpected-line-ending-format,
+        multiple-imports,
+        wrong-import-order,
+        ungrouped-imports,
+        wrong-import-position,
+        useless-import-alias,
+        import-outside-toplevel,
+        unnecessary-negation,
+        consider-using-enumerate,
+        consider-iterating-dictionary,
+        consider-using-dict-items,
+        use-maxsplit-arg,
+        use-sequence-for-iteration,
+        consider-using-f-string,
+        use-implicit-booleaness-not-len,
+        use-implicit-booleaness-not-comparison,
+        invalid-name,
+        disallowed-name,
+        typevar-name-incorrect-variance,
+        typevar-double-variance,
+        typevar-name-mismatch,
+        empty-docstring,
+        missing-module-docstring,
+        missing-class-docstring,
+        missing-function-docstring,
+        singleton-comparison,
+        unidiomatic-typecheck,
+        unknown-option-value,
+        logging-not-lazy,
+        logging-format-interpolation,
+        logging-fstring-interpolation,
+        fixme,
+        keyword-arg-before-vararg,
+        arguments-out-of-order,
+        non-str-assignment-to-dunder-name,
+        isinstance-second-argument-not-valid-type,
+        kwarg-superseded-by-positional-arg,
+        modified-iterating-list,
+        attribute-defined-outside-init,
+        bad-staticmethod-argument,
+        protected-access,
+        implicit-flag-alias,
+        arguments-differ,
+        signature-differs,
+        abstract-method,
+        super-init-not-called,
+        non-parent-init-called,
+        invalid-overridden-method,
+        arguments-renamed,
+        unused-private-member,
+        overridden-final-method,
+        subclassed-final-class,
+        redefined-slots-in-subclass,
+        super-without-brackets,
+        useless-parent-delegation,
+        global-variable-undefined,
+        global-variable-not-assigned,
+        global-statement,
+        global-at-module-level,
+        unused-import,
+        unused-variable,
+        unused-argument,
+        unused-wildcard-import,
+        redefined-outer-name,
+        redefined-builtin,
+        undefined-loop-variable,
+        unbalanced-tuple-unpacking,
+        cell-var-from-loop,
+        possibly-unused-variable,
+        self-cls-assignment,
+        unbalanced-dict-unpacking,
+        using-f-string-in-unsupported-version,
+        using-final-decorator-in-unsupported-version,
+        unnecessary-ellipsis,
+        non-ascii-file-name,
+        unnecessary-semicolon,
+        bad-indentation,
+        wildcard-import,
+        reimported,
+        import-self,
+        preferred-module,
+        misplaced-future,
+        shadowed-import,
+        deprecated-module,
+        missing-timeout,
+        useless-with-lock,
+        bare-except,
+        duplicate-except,
+        try-except-raise,
+        raise-missing-from,
+        binary-op-exception,
+        raising-format-tuple,
+        wrong-exception-operation,
+        broad-exception-caught,
+        broad-exception-raised,
+        bad-open-mode,
+        boolean-datetime,
+        redundant-unittest-assert,
+        bad-thread-instantiation,
+        shallow-copy-environ,
+        invalid-envvar-default,
+        subprocess-popen-preexec-fn,
+        subprocess-run-check,
+        unspecified-encoding,
+        forgotten-debug-statement,
+        method-cache-max-size-none,
+        deprecated-method,
+        deprecated-argument,
+        deprecated-class,
+        deprecated-decorator,
+        deprecated-attribute,
+        bad-format-string-key,
+        unused-format-string-key,
+        bad-format-string,
+        missing-format-argument-key,
+        unused-format-string-argument,
+        format-combined-specification,
+        missing-format-attribute,
+        invalid-format-index,
+        duplicate-string-formatting-argument,
+        f-string-without-interpolation,
+        format-string-without-interpolation,
+        anomalous-backslash-in-string,
+        anomalous-unicode-escape-in-string,
+        implicit-str-concat,
+        inconsistent-quotes,
+        redundant-u-string-prefix,
+        useless-else-on-loop,
+        unreachable,
+        dangerous-default-value,
+        pointless-statement,
+        pointless-string-statement,
+        expression-not-assigned,
+        unnecessary-lambda,
+        duplicate-key,
+        exec-used,
+        eval-used,
+        confusing-with-statement,
+        using-constant-test,
+        missing-parentheses-for-call-in-test,
+        self-assigning-variable,
+        redeclared-assigned-name,
+        assert-on-string-literal,
+        duplicate-value,
+        named-expr-without-context,
+        pointless-exception-statement,
+        return-in-finally,
+        lost-exception,
+        assert-on-tuple,
+        unnecessary-pass,
+        comparison-with-callable,
+        nan-comparison,
+        contextmanager-generator-missing-cleanup,
+        nested-min-max,
+        bad-chained-comparison,
+        not-callable
+
+# Enable the message, report, category or checker with the given id(s). You can
+# either give multiple identifier separated by comma (,) or put this option
+# multiple time (only on the command line, not in the configuration file where
+# it should appear only once). See also the "--disable" option for examples.
+enable=
+
+
+[METHOD_ARGS]
+
+# List of qualified names (i.e., library.method) which require a timeout
+# parameter e.g. 'requests.api.get,requests.api.post'
+timeout-methods=requests.api.delete,requests.api.get,requests.api.head,requests.api.options,requests.api.patch,requests.api.post,requests.api.put,requests.api.request
+
+
+[MISCELLANEOUS]
+
+# List of note tags to take in consideration, separated by a comma.
+notes=FIXME,
+      XXX,
+      TODO
+
+# Regular expression of note tags to take in consideration.
+notes-rgx=
+
+
+[REFACTORING]
+
+# Maximum number of nested blocks for function / method body
+max-nested-blocks=5
+
+# Complete name of functions that never returns. When checking for
+# inconsistent-return-statements if a never returning function is called then
+# it will be considered as an explicit return statement and no message will be
+# printed.
+never-returning-functions=sys.exit,argparse.parse_error
+
+# Let 'consider-using-join' be raised when the separator to join on would be
+# non-empty (resulting in expected fixes of the type: ``"- " + " -
+# ".join(items)``)
+suggest-join-with-non-empty-separator=yes
+
+
+[REPORTS]
+
+# Python expression which should return a score less than or equal to 10. You
+# have access to the variables 'fatal', 'error', 'warning', 'refactor',
+# 'convention', and 'info' which contain the number of messages in each
+# category, as well as 'statement' which is the total number of statements
+# analyzed. This score is used by the global evaluation report (RP0004).
+evaluation=max(0, 0 if fatal else 10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10))
+
+# Template used to display messages. This is a python new-style format string
+# used to format the message information. See doc for all details.
+msg-template=
+
+# Set the output format. Available formats are: text, parseable, colorized,
+# json2 (improved json format), json (old json format) and msvs (visual
+# studio). You can also give a reporter class, e.g.
+# mypackage.mymodule.MyReporterClass.
+#output-format=
+
+# Tells whether to display a full report or only the messages.
+reports=no
+
+# Activate the evaluation score.
+score=yes
+
+
+[SIMILARITIES]
+
+# Comments are removed from the similarity computation
+ignore-comments=yes
+
+# Docstrings are removed from the similarity computation
+ignore-docstrings=yes
+
+# Imports are removed from the similarity computation
+ignore-imports=yes
+
+# Signatures are removed from the similarity computation
+ignore-signatures=yes
+
+# Minimum lines number of a similarity.
+min-similarity-lines=4
+
+
+[SPELLING]
+
+# Limits count of emitted suggestions for spelling mistakes.
+max-spelling-suggestions=4
+
+# Spelling dictionary name. No available dictionaries : You need to install
+# both the python package and the system dependency for enchant to work.
+spelling-dict=
+
+# List of comma separated words that should be considered directives if they
+# appear at the beginning of a comment and should not be checked.
+spelling-ignore-comment-directives=fmt: on,fmt: off,noqa:,noqa,nosec,isort:skip,mypy:
+
+# List of comma separated words that should not be checked.
+spelling-ignore-words=
+
+# A path to a file that contains the private dictionary; one word per line.
+spelling-private-dict-file=
+
+# Tells whether to store unknown words to the private dictionary (see the
+# --spelling-private-dict-file option) instead of raising a message.
+spelling-store-unknown-words=no
+
+
+[STRING]
+
+# This flag controls whether inconsistent-quotes generates a warning when the
+# character used as a quote delimiter is used inconsistently within a module.
+check-quote-consistency=no
+
+# This flag controls whether the implicit-str-concat should generate a warning
+# on implicit string concatenation in sequences defined over several lines.
+check-str-concat-over-line-jumps=no
+
+
+[TYPECHECK]
+
+# List of decorators that produce context managers, such as
+# contextlib.contextmanager. Add to this list to register other decorators that
+# produce valid context managers.
+contextmanager-decorators=contextlib.contextmanager
+
+# List of members which are set dynamically and missed by pylint inference
+# system, and so shouldn't trigger E1101 when accessed. Python regular
+# expressions are accepted.
+generated-members=
+
+# Tells whether to warn about missing members when the owner of the attribute
+# is inferred to be None.
+ignore-none=yes
+
+# This flag controls whether pylint should warn about no-member and similar
+# checks whenever an opaque object is returned when inferring. The inference
+# can return multiple potential results while evaluating a Python object, but
+# some branches might not be evaluated, which results in partial inference. In
+# that case, it might be useful to still emit no-member and other checks for
+# the rest of the inferred objects.
+ignore-on-opaque-inference=yes
+
+# List of symbolic message names to ignore for Mixin members.
+ignored-checks-for-mixins=no-member,
+                          not-async-context-manager,
+                          not-context-manager,
+                          attribute-defined-outside-init
+
+# List of class names for which member attributes should not be checked (useful
+# for classes with dynamically set attributes). This supports the use of
+# qualified names.
+ignored-classes=optparse.Values,thread._local,_thread._local,argparse.Namespace
+
+# Show a hint with possible names when a member name was not found. The aspect
+# of finding the hint is based on edit distance.
+missing-member-hint=yes
+
+# The minimum edit distance a name should have in order to be considered a
+# similar match for a missing member name.
+missing-member-hint-distance=1
+
+# The total number of similar names that should be taken in consideration when
+# showing a hint for a missing member.
+missing-member-max-choices=1
+
+# Regex pattern to define which classes are considered mixins.
+mixin-class-rgx=.*[Mm]ixin
+
+# List of decorators that change the signature of a decorated function.
+signature-mutators=
+
+
+[VARIABLES]
+
+# List of additional names supposed to be defined in builtins. Remember that
+# you should avoid defining new builtins when possible.
+additional-builtins=
+
+# Tells whether unused global variables should be treated as a violation.
+allow-global-unused-variables=yes
+
+# List of names allowed to shadow builtins
+allowed-redefined-builtins=
+
+# List of strings which can identify a callback function by name. A callback
+# name must start or end with one of those strings.
+callbacks=cb_,
+          _cb
+
+# A regular expression matching the name of dummy variables (i.e. expected to
+# not be used).
+dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_
+
+# Argument names that match this expression will be ignored.
+ignored-argument-names=_.*|^ignored_|^unused_
+
+# Tells whether we should check for unused import in __init__ files.
+init-import=no
+
+# List of qualified module names which can have objects that can redefine
+# builtins.
+redefining-builtins-modules=six.moves,past.builtins,future.builtins,builtins,io

comfy/analytics/analytics.py

@@ -6,7 +6,8 @@ from typing import Optional
 
 from .multi_event_tracker import MultiEventTracker
 from .plausible import PlausibleTracker
-from ..api.components.schema.prompt import Prompt
+from ..api.components.schema.prompt import Prompt, PromptDict
+from ..api.schemas.validation import immutabledict
 
 _event_tracker: MultiEventTracker
 
@@ -44,7 +45,7 @@ def initialize_event_tracking(loop: Optional[asyncio.AbstractEventLoop] = None):
     prompt_queue_put = PromptQueue.put
 
     def prompt_queue_put_tracked(self: PromptQueue, item: QueueItem):
-        prompt = Prompt.validate(item.prompt)
+        prompt: PromptDict = immutabledict(Prompt.validate(item.prompt))
 
         samplers = [v for _, v in prompt.items() if
                     "positive" in v.inputs and "negative" in v.inputs]

comfy/api/paths/view/get/parameters/parameter_1/schema.py

@@ -13,19 +13,22 @@ from comfy.api.shared_imports.schema_imports import *  # pyright: ignore [report
 
 
 class SchemaEnums:
-
+    @classmethod
-    @schemas.classproperty
+    def output(cls) -> typing.Literal["output"]:
-    def OUTPUT(cls) -> typing.Literal["output"]:
         return Schema.validate("output")
 
-    @schemas.classproperty
+    @classmethod
-    def INPUT(cls) -> typing.Literal["input"]:
+    def input(cls) -> typing.Literal["input"]:
         return Schema.validate("input")
 
-    @schemas.classproperty
+    @classmethod
-    def TEMP(cls) -> typing.Literal["temp"]:
+    def temp(cls) -> typing.Literal["temp"]:
         return Schema.validate("temp")
 
+    OUTPUT = property(output)
+    INPUT = property(input)
+    TEMP = property(temp)
+
 
 @dataclasses.dataclass(frozen=True)
 class Schema(

comfy/api/paths/view/get/query_parameters.py

@@ -15,32 +15,19 @@ AdditionalProperties: typing_extensions.TypeAlias = schemas.NotAnyTypeSchema
 from comfy.api.paths.view.get.parameters.parameter_0 import schema
 from comfy.api.paths.view.get.parameters.parameter_1 import schema as schema_3
 from comfy.api.paths.view.get.parameters.parameter_2 import schema as schema_2
-Properties = typing.TypedDict(
+
-    'Properties',
+
-    {
+class Properties(typing.TypedDict):
-        "filename": typing.Type[schema.Schema],
+    filename: typing.Type[schema.Schema]
-        "subfolder": typing.Type[schema_2.Schema],
+    subfolder: typing.Type[schema_2.Schema]
-        "type": typing.Type[schema_3.Schema],
+    type: typing.Type[schema_3.Schema]
-    }
+
-)
+class QueryParametersRequiredDictInput(typing.TypedDict):
-QueryParametersRequiredDictInput = typing.TypedDict(
+    filename: str
-    'QueryParametersRequiredDictInput',
+
-    {
+class QueryParametersOptionalDictInput(typing.TypedDict, total=False):
-        "filename": str,
+    subfolder: str
-    }
+    type: typing.Literal["output", "input", "temp"]
-)
-QueryParametersOptionalDictInput = typing.TypedDict(
-    'QueryParametersOptionalDictInput',
-    {
-        "subfolder": str,
-        "type": typing.Literal[
-            "output",
-            "input",
-            "temp"
-        ],
-    },
-    total=False
-)
 
 
 class QueryParametersDict(schemas.immutabledict[str, schemas.OUTPUT_BASE_TYPES]):

comfy/api/schemas/__init__.py

@@ -14,7 +14,6 @@ import typing_extensions
 from .schema import (
     get_class,
     none_type_,
-    classproperty,
     Bool,
     FileIO,
     Schema,
@@ -104,7 +103,6 @@ def raise_if_key_known(
 __all__ = [
     'get_class',
     'none_type_',
-    'classproperty',
     'Bool',
     'FileIO',
     'Schema',

comfy/api/schemas/schema.py

@@ -96,17 +96,6 @@ class FileIO(io.FileIO):
         pass
 
 
-class classproperty(typing.Generic[W]):
-    def __init__(self, method: typing.Callable[..., W]):
-        self.__method = method
-        functools.update_wrapper(self, method) # type: ignore
-
-    def __get__(self, obj, cls=None) -> W:
-        if cls is None:
-            cls = type(obj)
-        return self.__method(cls)
-
-
 class Bool:
     _instances: typing.Dict[typing.Tuple[type, bool], Bool] = {}
     """
@@ -139,13 +128,16 @@ class Bool:
             return f'<Bool: True>'
         return f'<Bool: False>'
 
-    @classproperty
+    @classmethod
-    def TRUE(cls):
+    def true(cls):
         return cls(True) # type: ignore
 
-    @classproperty
+    @classmethod
-    def FALSE(cls):
+    def false(cls):
         return cls(False) # type: ignore
+    
+    TRUE = property(true)
+    FALSE = property(false)
 
     @functools.lru_cache()
     def __bool__(self) -> bool:
@@ -403,11 +395,11 @@ class Schema(typing.Generic[T, U], validation.SchemaValidator, metaclass=Singlet
             return used_arg
         output_cls = type_to_output_cls[arg_type]
         if arg_type is tuple:
-            inst = super(output_cls, output_cls).__new__(output_cls, used_arg) # type: ignore
+            inst = tuple.__new__(output_cls, used_arg) # type: ignore
             inst = typing.cast(U, inst)
             return inst
         assert issubclass(output_cls, validation.immutabledict)
-        inst = super(output_cls, output_cls).__new__(output_cls, used_arg) # type: ignore
+        inst = validation.immutabledict.__new__(output_cls, used_arg) # type: ignore
         inst = typing.cast(T, inst)
         return inst
 

comfy/client/aio_client.py

@@ -11,6 +11,7 @@ from aiohttp import WSMessage, ClientResponse
 from typing_extensions import Dict
 
 from .client_types import V1QueuePromptResponse
+from ..api.schemas import immutabledict
 from ..api.components.schema.prompt import PromptDict
 from ..api.api_client import JSONEncoder
 from ..api.components.schema.prompt_request import PromptRequest
@@ -106,7 +107,9 @@ class AsyncRemoteComfyClient:
                         break
             async with session.get(urljoin(self.server_address, "/history")) as response:
                 if response.status == 200:
-                    history_json = GetHistoryDict.validate(await response.json())
+                    history_json = immutabledict(GetHistoryDict.validate(await response.json()))
+                else:
+                    raise RuntimeError("Couldn't get history")
 
             # images have filename, subfolder, type keys
             # todo: use the OpenAPI spec for this when I get around to updating it

comfy/cmd/latent_preview.py

@@ -25,7 +25,7 @@ def preview_to_image(latent_image):
 
 class LatentPreviewer:
     def decode_latent_to_preview(self, x0):
-        pass
+        raise NotImplementedError
 
     def decode_latent_to_preview_image(self, preview_format, x0):
         preview_image = self.decode_latent_to_preview(x0)

comfy/cmd/main.py

@@ -134,7 +134,7 @@ async def main():
     if args.windows_standalone_build:
         folder_paths.create_directories()
         try:
-            import new_updater
+            from . import new_updater
             new_updater.update_windows_updater()
         except:
             pass
@@ -161,7 +161,7 @@ async def main():
         await q.init()
     else:
         distributed = False
-        from execution import PromptQueue
+        from .execution import PromptQueue
         q = PromptQueue(server)
     server.prompt_queue = q
 

comfy/cmd/main_pre.py

@@ -37,7 +37,7 @@ from ..cli_args import args
 
 if args.cuda_device is not None:
     os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
-    logging.info("Set cuda device to:", args.cuda_device)
+    logging.info("Set cuda device to: {}".format(args.cuda_device))
 
 if args.deterministic:
     if 'CUBLAS_WORKSPACE_CONFIG' not in os.environ:

comfy/cmd/server.py

@@ -22,7 +22,7 @@ import aiohttp
 from PIL import Image
 from PIL.PngImagePlugin import PngInfo
 from aiohttp import web
-from can_ada import URL, parse as urlparse
+from can_ada import URL, parse as urlparse  # pylint: disable=no-name-in-module
 from typing_extensions import NamedTuple
 
 from .. import interruption
@@ -382,7 +382,7 @@ class PromptServer(ExecutorToClientProgress):
             return web.json_response(dt["__metadata__"])
 
         @routes.get("/system_stats")
-        async def get_queue(request):
+        async def get_system_stats(request):
             device = model_management.get_torch_device()
             device_name = model_management.get_torch_device_name(device)
             vram_total, torch_vram_total = model_management.get_total_memory(device, torch_total_too=True)
@@ -458,7 +458,7 @@ class PromptServer(ExecutorToClientProgress):
             return web.json_response(self.prompt_queue.get_history(max_items=max_items))
 
         @routes.get("/history/{prompt_id}")
-        async def get_history(request):
+        async def get_history_prompt(request):
             prompt_id = request.match_info.get("prompt_id", None)
             return web.json_response(self.prompt_queue.get_history(prompt_id=prompt_id))
 
@@ -555,7 +555,7 @@ class PromptServer(ExecutorToClientProgress):
             return web.Response(status=200)
 
         @routes.post("/api/v1/prompts")
-        async def post_prompt(request: web.Request) -> web.Response | web.FileResponse:
+        async def post_api_prompt(request: web.Request) -> web.Response | web.FileResponse:
             # check if the queue is too long
             accept = request.headers.get("accept", "application/json")
             content_type = request.headers.get("content-type", "application/json")
@@ -685,7 +685,7 @@ class PromptServer(ExecutorToClientProgress):
                 return web.Response(status=204)
 
         @routes.get("/api/v1/prompts")
-        async def get_prompt(_: web.Request) -> web.Response:
+        async def get_api_prompt(_: web.Request) -> web.Response:
             history = self.prompt_queue.get_history()
             history_items = list(history.values())
             if len(history_items) == 0:

comfy/diffusers_load.py

@@ -26,6 +26,7 @@ def load_diffusers(model_path, output_vae=True, output_clip=True, embedding_dire
     if text_encoder2_path is not None:
         text_encoder_paths.append(text_encoder2_path)
 
+    unet = None
     if unet_path is not None:
         unet = sd.load_unet(unet_path)
 

comfy/extra_samplers/uni_pc.py

@@ -357,6 +357,7 @@ class UniPC:
         predict_x0=True,
         thresholding=False,
         max_val=1.,
+        dynamic_thresholding_ratio=0.995,
         variant='bh1',
     ):
         """Construct a UniPC. 
@@ -369,6 +370,7 @@ class UniPC:
         self.predict_x0 = predict_x0
         self.thresholding = thresholding
         self.max_val = max_val
+        self.dynamic_thresholding_ratio = dynamic_thresholding_ratio
 
     def dynamic_thresholding_fn(self, x0, t=None):
         """
@@ -377,7 +379,7 @@ class UniPC:
         dims = x0.dim()
         p = self.dynamic_thresholding_ratio
         s = torch.quantile(torch.abs(x0).reshape((x0.shape[0], -1)), p, dim=1)
-        s = expand_dims(torch.maximum(s, self.thresholding_max_val * torch.ones_like(s).to(s.device)), dims)
+        s = expand_dims(torch.maximum(s, self.max_val * torch.ones_like(s).to(s.device)), dims)
         x0 = torch.clamp(x0, -s, s) / s
         return x0
 
@@ -634,16 +636,18 @@ class UniPC:
 
         # now predictor
         use_predictor = len(D1s) > 0 and x_t is None
+        
         if len(D1s) > 0:
             D1s = torch.stack(D1s, dim=1) # (B, K)
-            if x_t is None:
-                # for order 2, we use a simplified version
-                if order == 2:
-                    rhos_p = torch.tensor([0.5], device=b.device)
-                else:
-                    rhos_p = torch.linalg.solve(R[:-1, :-1], b[:-1])
         else:
             D1s = None
+        
+        if use_predictor:
+            # for order 2, we use a simplified version
+            if order == 2:
+                rhos_p = torch.tensor([0.5], device=b.device)
+            else:
+                rhos_p = torch.linalg.solve(R[:-1, :-1], b[:-1])
 
         if use_corrector:
             # print('using corrector')

comfy/images.py

@@ -1,5 +1,6 @@
 import os.path
 from contextlib import contextmanager
+from typing import Iterator
 
 import cv2
 from PIL import Image
@@ -8,11 +9,11 @@ from . import node_helpers
 
 
 def _open_exr(exr_path) -> Image.Image:
-    return Image.fromarray(cv2.imread(exr_path, cv2.IMREAD_COLOR))
+    return Image.fromarray(cv2.imread(exr_path, cv2.IMREAD_COLOR)) # pylint: disable=no-member
 
 
 @contextmanager
-def open_image(file_path: str) -> Image.Image:
+def open_image(file_path: str) -> Iterator[Image.Image]:
     _, ext = os.path.splitext(file_path)
     if ext == ".exr":
         yield _open_exr(file_path)

comfy/k_diffusion/sampling.py

@@ -612,7 +612,6 @@ def sample_dpmpp_2m_sde(model, x, sigmas, extra_args=None, callback=None, disabl
 
     old_denoised = None
     h_last = None
-    h = None
 
     for i in trange(len(sigmas) - 1, disable=disable):
         denoised = model(x, sigmas[i] * s_in, **extra_args)
@@ -621,6 +620,7 @@ def sample_dpmpp_2m_sde(model, x, sigmas, extra_args=None, callback=None, disabl
         if sigmas[i + 1] == 0:
             # Denoising step
             x = denoised
+            h = None
         else:
             # DPM-Solver++(2M) SDE
             t, s = -sigmas[i].log(), -sigmas[i + 1].log()
@@ -640,7 +640,7 @@ def sample_dpmpp_2m_sde(model, x, sigmas, extra_args=None, callback=None, disabl
                 x = x + noise_sampler(sigmas[i], sigmas[i + 1]) * sigmas[i + 1] * (-2 * eta_h).expm1().neg().sqrt() * s_noise
 
         old_denoised = denoised
-        h_last = h
+        h_last = h if h is not None else h_last
     return x
 
 @torch.no_grad()

comfy/language/chat_templates.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import logging
-from importlib.abc import Traversable
+from importlib.abc import Traversable  # pylint: disable=no-name-in-module
 from importlib.resources import files
 from pathlib import Path
 

comfy/ldm/cascade/stage_a.py

@@ -78,15 +78,18 @@ class VectorQuantize(nn.Module):
         return ((x + epsilon) / (n + x.size(0) * epsilon) * n)
 
     def _updateEMA(self, z_e_x, indices):
-        mask = nn.functional.one_hot(indices, self.ema_element_count.size(0)).float()
+        if self.ema_loss:
-        elem_count = mask.sum(dim=0)
+            mask = nn.functional.one_hot(indices, self.ema_element_count.size(0)).float()
-        weight_sum = torch.mm(mask.t(), z_e_x)
+            elem_count = mask.sum(dim=0)
+            weight_sum = torch.mm(mask.t(), z_e_x)
 
-        self.ema_element_count = (self.ema_decay * self.ema_element_count) + ((1-self.ema_decay) * elem_count)
+            self.register_buffer('ema_element_count', self._laplace_smoothing(
-        self.ema_element_count = self._laplace_smoothing(self.ema_element_count, 1e-5)
+                (self.ema_decay * self.ema_element_count) + ((1-self.ema_decay) * elem_count), 
-        self.ema_weight_sum = (self.ema_decay * self.ema_weight_sum) + ((1-self.ema_decay) * weight_sum)
+                1e-5)
+            )
+            self.register_buffer('ema_weight_sum', (self.ema_decay * self.ema_weight_sum) + ((1-self.ema_decay) * weight_sum))
 
-        self.codebook.weight.data = self.ema_weight_sum / self.ema_element_count.unsqueeze(-1)
+            self.codebook.weight.data = self.ema_weight_sum / self.ema_element_count.unsqueeze(-1)
 
     def idx2vq(self, idx, dim=-1):
         q_idx = self.codebook(idx)

comfy/ldm/models/autoencoder.py

@@ -1,4 +1,5 @@
 import torch
+import math
 from contextlib import contextmanager
 from typing import Any, Dict, List, Optional, Tuple, Union
 import logging as logpy
@@ -113,7 +114,7 @@ class AutoencodingEngine(AbstractAutoencoder):
 
         self.encoder: torch.nn.Module = instantiate_from_config(encoder_config)
         self.decoder: torch.nn.Module = instantiate_from_config(decoder_config)
-        self.regularization: AbstractRegularizer = instantiate_from_config(
+        self.regularization: DiagonalGaussianRegularizer = instantiate_from_config(
             regularizer_config
         )
 
@@ -169,10 +170,6 @@ class AutoencodingEngineLegacy(AutoencodingEngine):
         self.post_quant_conv = ops.disable_weight_init.Conv2d(embed_dim, ddconfig["z_channels"], 1)
         self.embed_dim = embed_dim
 
-    def get_autoencoder_params(self) -> list:
-        params = super().get_autoencoder_params()
-        return params
-
     def encode(
         self, x: torch.Tensor, return_reg_log: bool = False
     ) -> Union[torch.Tensor, Tuple[torch.Tensor, dict]]:

comfy/ldm/modules/attention.py

@@ -11,8 +11,8 @@ from .sub_quadratic_attention import efficient_dot_product_attention
 from ... import model_management
 
 if model_management.xformers_enabled():
-    import xformers
+    import xformers  # pylint: disable=import-error
-    import xformers.ops
+    import xformers.ops # pylint: disable=import-error
 
 from ...cli_args import args
 from ... import ops
@@ -303,12 +303,10 @@ def attention_split(q, k, v, heads, mask=None, attn_precision=None):
     return r1
 
 BROKEN_XFORMERS = False
-try:
+if model_management.xformers_enabled():
     x_vers = xformers.__version__
     # XFormers bug confirmed on all versions from 0.0.21 to 0.0.26 (q with bs bigger than 65535 gives CUDA error)
     BROKEN_XFORMERS = x_vers.startswith("0.0.2") and not x_vers.startswith("0.0.20")
-except:
-    pass
 
 def attention_xformers(q, k, v, heads, mask=None, attn_precision=None):
     b, _, dim_head = q.shape

comfy/ldm/modules/diffusionmodules/mmdit.py

@@ -1,5 +1,6 @@
 import logging
 import math
+from functools import partial
 from typing import Dict, Optional
 
 import numpy as np
@@ -836,9 +837,9 @@ class MMDiT(nn.Module):
 
         self.final_layer = FinalLayer(self.hidden_size, patch_size, self.out_channels, dtype=dtype, device=device, operations=operations)
 
+        self.compile_core = compile_core
         if compile_core:
-            assert False
+            self.forward_core_with_concat_compiled = torch.compile(self.forward_core_with_concat)
-            self.forward_core_with_concat = torch.compile(self.forward_core_with_concat)
 
     def cropped_pos_embed(self, hw, device=None):
         p = self.x_embedder.patch_size[0]
@@ -894,6 +895,8 @@ class MMDiT(nn.Module):
         c_mod: torch.Tensor,
         context: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
+        if self.compile_core:
+            return self.forward_core_with_concat_compiled(x, c_mod, context)
         if self.register_length > 0:
             context = torch.cat(
                 (

comfy/ldm/modules/diffusionmodules/model.py

@@ -11,8 +11,8 @@ from .... import ops
 ops = ops.disable_weight_init
 
 if model_management.xformers_enabled_vae():
-    import xformers
+    import xformers  # pylint: disable=import-error
-    import xformers.ops
+    import xformers.ops # pylint: disable=import-error
 
 def get_timestep_embedding(timesteps, embedding_dim):
     """
@@ -216,10 +216,10 @@ def xformers_attention(q, k, v):
         (q, k, v),
     )
 
-    try:
+    if model_management.xformers_enabled_vae():
         out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None)
         out = out.transpose(1, 2).reshape(B, C, H, W)
-    except NotImplementedError as e:
+    else:
         out = slice_attention(q.view(B, -1, C), k.view(B, -1, C).transpose(1, 2), v.view(B, -1, C).transpose(1, 2)).reshape(B, C, H, W)
     return out
 

comfy/ldm/modules/ema.py

@@ -23,14 +23,13 @@ class LitEma(nn.Module):
         self.collected_params = []
 
     def reset_num_updates(self):
-        del self.num_updates
         self.register_buffer('num_updates', torch.tensor(0, dtype=torch.int))
 
     def forward(self, model):
         decay = self.decay
 
         if self.num_updates >= 0:
-            self.num_updates += 1
+            self.register_buffer('num_updates', torch.tensor(1 + self.num_updates, dtype=torch.int))
             decay = min(self.decay, (1 + self.num_updates) / (10 + self.num_updates))
 
         one_minus_decay = 1.0 - decay

comfy/lora.py

@@ -30,8 +30,9 @@ def load_lora(lora, to_load):
         regular_lora = "{}.lora_up.weight".format(x)
         diffusers_lora = "{}_lora.up.weight".format(x)
         transformers_lora = "{}.lora_linear_layer.up.weight".format(x)
-        A_name = None
+        A_name = B_name = None
 
+        mid_name = None
         if regular_lora in lora.keys():
             A_name = regular_lora
             B_name = "{}.lora_down.weight".format(x)
@@ -39,11 +40,9 @@ def load_lora(lora, to_load):
         elif diffusers_lora in lora.keys():
             A_name = diffusers_lora
             B_name = "{}_lora.down.weight".format(x)
-            mid_name = None
         elif transformers_lora in lora.keys():
             A_name = transformers_lora
             B_name ="{}.lora_linear_layer.down.weight".format(x)
-            mid_name = None
 
         if A_name is not None:
             mid = None

comfy/model_base.py

@@ -26,6 +26,7 @@ from .model_sampling import EPS, V_PREDICTION, EDM, ModelSamplingDiscrete, Model
 
 
 def model_sampling(model_config, model_type):
+    c = EPS
     s = ModelSamplingDiscrete
 
     if model_type == ModelType.EPS:
@@ -35,15 +36,15 @@ def model_sampling(model_config, model_type):
     elif model_type == ModelType.V_PREDICTION_EDM:
         c = V_PREDICTION
         s = ModelSamplingContinuousEDM
-    elif model_type == ModelType.FLOW:
-        c = CONST
-        s = ModelSamplingDiscreteFlow
     elif model_type == ModelType.STABLE_CASCADE:
         c = EPS
         s = StableCascadeSampling
     elif model_type == ModelType.EDM:
         c = EDM
         s = ModelSamplingContinuousEDM
+    elif model_type == ModelType.FLOW:
+        c = CONST
+        s = ModelSamplingDiscreteFlow
 
     class ModelSampling(s, c):
         pass
@@ -110,7 +111,7 @@ class BaseModel(torch.nn.Module):
         return self.adm_channels > 0
 
     def encode_adm(self, **kwargs):
-        return None
+        raise NotImplementedError
 
     def extra_conds(self, **kwargs):
         out = {}
@@ -153,6 +154,7 @@ class BaseModel(torch.nn.Module):
                         cond_concat.append(self.blank_inpaint_image_like(noise))
             data = torch.cat(cond_concat, dim=1)
             out['c_concat'] = conds.CONDNoiseShape(data)
+
         adm = self.encode_adm(**kwargs)
         if adm is not None:
             out['y'] = conds.CONDRegular(adm)
@@ -475,7 +477,10 @@ class SD_X4Upscaler(BaseModel):
         out['y'] = conds.CONDRegular(noise_level)
         return out
 
-class IP2P:
+class IP2P(BaseModel):
+    def process_ip2p_image_in(self, image):
+        raise NotImplementedError
+
     def extra_conds(self, **kwargs):
         out = {}
 

comfy/model_management.py

@@ -47,11 +47,10 @@ if args.deterministic:
     logging.info("Using deterministic algorithms for pytorch")
     torch.use_deterministic_algorithms(True, warn_only=True)
 
-directml_enabled = False
+directml_device = None
 if args.directml is not None:
-    import torch_directml
+    import torch_directml # pylint: disable=import-error
 
-    directml_enabled = True
     device_index = args.directml
     if device_index < 0:
         directml_device = torch_directml.device()
@@ -62,7 +61,7 @@ if args.directml is not None:
     lowvram_available = False  # TODO: need to find a way to get free memory in directml before this can be enabled by default.
 
 try:
-    import intel_extension_for_pytorch as ipex
+    import intel_extension_for_pytorch as ipex # pylint: disable=import-error
 
     if torch.xpu.is_available():
         xpu_available = True
@@ -90,10 +89,9 @@ def is_intel_xpu():
 
 
 def get_torch_device():
-    global directml_enabled
+    global directml_device
     global cpu_state
-    if directml_enabled:
+    if directml_device:
-        global directml_device
         return directml_device
     if cpu_state == CPUState.MPS:
         return torch.device("mps")
@@ -111,7 +109,7 @@ def get_torch_device():
 
 
 def get_total_memory(dev=None, torch_total_too=False):
-    global directml_enabled
+    global directml_device
     if dev is None:
         dev = get_torch_device()
 
@@ -119,14 +117,12 @@ def get_total_memory(dev=None, torch_total_too=False):
         mem_total = psutil.virtual_memory().total
         mem_total_torch = mem_total
     else:
-        if directml_enabled:
+        if directml_device:
             mem_total = 1024 * 1024 * 1024  # TODO
             mem_total_torch = mem_total
         elif is_intel_xpu():
-            stats = torch.xpu.memory_stats(dev)
-            mem_reserved = stats['reserved_bytes.all.current']
-            mem_total_torch = mem_reserved
             mem_total = torch.xpu.get_device_properties(dev).total_memory
+            mem_total_torch = mem_total
         else:
             stats = torch.cuda.memory_stats(dev)
             mem_reserved = stats['reserved_bytes.all.current']
@@ -162,8 +158,8 @@ if args.disable_xformers:
     XFORMERS_IS_AVAILABLE = False
 else:
     try:
-        import xformers
+        import xformers # pylint: disable=import-error
-        import xformers.ops
+        import xformers.ops # pylint: disable=import-error
 
         XFORMERS_IS_AVAILABLE = True
         try:
@@ -710,7 +706,7 @@ def supports_cast(device, dtype): #TODO
         return True
     if is_device_mps(device):
         return False
-    if directml_enabled: #TODO: test this
+    if directml_device: #TODO: test this
         return False
     if dtype == torch.bfloat16:
         return True
@@ -725,7 +721,7 @@ def device_supports_non_blocking(device):
         return False  # pytorch bug? mps doesn't support non blocking
     if args.deterministic: #TODO: figure out why deterministic breaks non blocking from gpu to cpu (previews)
         return False
-    if directml_enabled:
+    if directml_device:
         return False
     return True
 
@@ -762,13 +758,13 @@ def cast_to_device(tensor, device, dtype, copy=False):
 
 
 def xformers_enabled():
-    global directml_enabled
+    global directml_device
     global cpu_state
     if cpu_state != CPUState.GPU:
         return False
     if is_intel_xpu():
         return False
-    if directml_enabled:
+    if directml_device:
         return False
     return XFORMERS_IS_AVAILABLE
 
@@ -809,7 +805,7 @@ def force_upcast_attention_dtype():
         return None
 
 def get_free_memory(dev=None, torch_free_too=False):
-    global directml_enabled
+    global directml_device
     if dev is None:
         dev = get_torch_device()
 
@@ -817,16 +813,12 @@ def get_free_memory(dev=None, torch_free_too=False):
         mem_free_total = psutil.virtual_memory().available
         mem_free_torch = mem_free_total
     else:
-        if directml_enabled:
+        if directml_device:
             mem_free_total = 1024 * 1024 * 1024  # TODO
             mem_free_torch = mem_free_total
         elif is_intel_xpu():
-            stats = torch.xpu.memory_stats(dev)
+            mem_free_total = torch.xpu.get_device_properties(dev).total_memory
-            mem_active = stats['active_bytes.all.current']
+            mem_free_torch = mem_free_total
-            mem_reserved = stats['reserved_bytes.all.current']
-            mem_free_torch = mem_reserved - mem_active
-            mem_free_xpu = torch.xpu.get_device_properties(dev).total_memory - mem_reserved
-            mem_free_total = mem_free_xpu + mem_free_torch
         else:
             stats = torch.cuda.memory_stats(dev)
             mem_active = stats['active_bytes.all.current']
@@ -871,7 +863,7 @@ def is_device_cuda(device):
 
 
 def should_use_fp16(device=None, model_params=0, prioritize_performance=True, manual_cast=False):
-    global directml_enabled
+    global directml_device
 
     if device is not None:
         if is_device_cpu(device):
@@ -887,7 +879,7 @@ def should_use_fp16(device=None, model_params=0, prioritize_performance=True, ma
     if FORCE_FP32:
         return False
 
-    if directml_enabled:
+    if directml_device:
         return False
 
     if mps_mode():
@@ -950,7 +942,7 @@ def should_use_bf16(device=None, model_params=0, prioritize_performance=True, ma
     if FORCE_FP32:
         return False
 
-    if directml_enabled:
+    if directml_device:
         return False
 
     if cpu_mode() or mps_mode():

comfy/model_patcher.py

@@ -360,11 +360,13 @@ class ModelPatcher(ModelManageable):
             if isinstance(v, list):
                 v = (self.calculate_weight(v[1:], v[0].clone(), key),)
 
-            if len(v) == 1:
+            patch_type = "diff"
-                patch_type = "diff"
+            if len(v) == 2:
-            elif len(v) == 2:
                 patch_type = v[0]
                 v = v[1]
+            elif len(v) != 1:
+                logging.warning("patch {} not recognized: {}".format(key, v))
+                continue
 
             if patch_type == "diff":
                 w1 = v[0]

comfy/model_sampling.py

@@ -3,6 +3,8 @@ from .ldm.modules.diffusionmodules.util import make_beta_schedule
 import math
 
 class EPS:
+    sigma_data: float
+
     def calculate_input(self, sigma, noise):
         sigma = sigma.view(sigma.shape[:1] + (1,) * (noise.ndim - 1))
         return noise / (sigma ** 2 + self.sigma_data ** 2) ** 0.5

comfy/nodes/base_nodes.py

@@ -854,6 +854,8 @@ class DualCLIPLoader:
             clip_type = sd.CLIPType.STABLE_DIFFUSION
         elif type == "sd3":
             clip_type = sd.CLIPType.SD3
+        else:
+            raise ValueError(f"Unknown clip type argument passed: {type} for model {clip_name1} and {clip_name2}")
 
         clip = sd.load_clip(ckpt_paths=[clip_path1, clip_path2], embedding_directory=folder_paths.get_folder_paths("embeddings"), clip_type=clip_type)
         return (clip,)

comfy/open_exr.py

@@ -36,6 +36,8 @@ from torch import Tensor
 from .component_model.images_types import RgbMaskTuple
 
 
+read_exr = lambda fp: cv.imread(fp, cv.IMREAD_UNCHANGED).astype(np.float32) # pylint: disable=no-member
+
 def mut_srgb_to_linear(np_array) -> None:
     less = np_array <= 0.0404482362771082
     np_array[less] = np_array[less] / 12.92
@@ -49,7 +51,7 @@ def mut_linear_to_srgb(np_array) -> None:
 
 
 def load_exr(file_path: str, srgb: bool) -> RgbMaskTuple:
-    image = cv.imread(file_path, cv.IMREAD_UNCHANGED).astype(np.float32)
+    image = read_exr(file_path)
     rgb = np.flip(image[:, :, :3], 2).copy()
     if srgb:
         mut_linear_to_srgb(rgb)
@@ -64,7 +66,7 @@ def load_exr(file_path: str, srgb: bool) -> RgbMaskTuple:
 
 
 def load_exr_latent(file_path: str) -> Tuple[Tensor]:
-    image = cv.imread(file_path, cv.IMREAD_UNCHANGED).astype(np.float32)
+    image = read_exr(file_path)
     image = image[:, :, np.array([2, 1, 0, 3])]
     image = torch.unsqueeze(torch.from_numpy(image), 0)
     image = torch.movedim(image, -1, 1)
@@ -83,4 +85,4 @@ def save_exr(images: Tensor, filepaths_batched: Sequence[str], colorspace="linea
         bgr[:, :, :, 3] = np.clip(1 - linear[:, :, :, 3], 0, 1)  # invert alpha
 
     for i in range(len(linear.shape[0])):
-        cv.imwrite(filepaths_batched[i], bgr[i])
+        cv.imwrite(filepaths_batched[i], bgr[i]) # pylint: disable=no-member

comfy/samplers.py

@@ -701,6 +701,8 @@ def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model
 
 
 def calculate_sigmas(model_sampling, scheduler_name, steps):
+    sigmas = None
+    
     if scheduler_name == "karras":
         sigmas = k_diffusion_sampling.get_sigmas_karras(n=steps, sigma_min=float(model_sampling.sigma_min), sigma_max=float(model_sampling.sigma_max))
     elif scheduler_name == "exponential":
@@ -713,8 +715,10 @@ def calculate_sigmas(model_sampling, scheduler_name, steps):
         sigmas = ddim_scheduler(model_sampling, steps)
     elif scheduler_name == "sgm_uniform":
         sigmas = normal_scheduler(model_sampling, steps, sgm=True)
-    else:
+    
+    if sigmas is None:
         logging.error("error invalid scheduler {}".format(scheduler_name))
+
     return sigmas
 
 def sampler_object(name):

comfy/sd1_clip.py

@@ -28,46 +28,7 @@ def gen_empty_tokens(special_tokens, length):
     output += [pad_token] * (length - len(output))
     return output
 
-
+class SDClipModel(torch.nn.Module):
-class ClipTokenWeightEncoder:
-    def encode_token_weights(self, token_weight_pairs):
-        to_encode = list()
-        max_token_len = 0
-        has_weights = False
-        for x in token_weight_pairs:
-            tokens = list(map(lambda a: a[0], x))
-            max_token_len = max(len(tokens), max_token_len)
-            has_weights = has_weights or not all(map(lambda a: a[1] == 1.0, x))
-            to_encode.append(tokens)
-
-        sections = len(to_encode)
-        if has_weights or sections == 0:
-            to_encode.append(gen_empty_tokens(self.special_tokens, max_token_len))
-
-        out, pooled = self.encode(to_encode)
-        if pooled is not None:
-            first_pooled = pooled[0:1].to(model_management.intermediate_device())
-        else:
-            first_pooled = pooled
-
-        output = []
-        for k in range(0, sections):
-            z = out[k:k + 1]
-            if has_weights:
-                z_empty = out[-1]
-                for i in range(len(z)):
-                    for j in range(len(z[i])):
-                        weight = token_weight_pairs[k][j][1]
-                        if weight != 1.0:
-                            z[i][j] = (z[i][j] - z_empty[j]) * weight + z_empty[j]
-            output.append(z)
-
-        if (len(output) == 0):
-            return out[-1:].to(model_management.intermediate_device()), first_pooled
-        return torch.cat(output, dim=-2).to(model_management.intermediate_device()), first_pooled
-
-
-class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder):
     """Uses the CLIP transformer encoder for text (from huggingface)"""
     LAYERS = [
         "last",
@@ -171,7 +132,7 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder):
         backup_embeds = self.transformer.get_input_embeddings()
         device = backup_embeds.weight.device
         tokens = self.set_up_textual_embeddings(tokens, backup_embeds)
-        tokens = torch.LongTensor(tokens).to(device)
+        tokens = torch.tensor(tokens, dtype=torch.long).to(device)
 
         attention_mask = None
         if self.enable_attention_masks:
@@ -206,6 +167,42 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder):
     def encode(self, tokens):
         return self(tokens)
 
+    def encode_token_weights(self, token_weight_pairs):
+        to_encode = list()
+        max_token_len = 0
+        has_weights = False
+        for x in token_weight_pairs:
+            tokens = list(map(lambda a: a[0], x))
+            max_token_len = max(len(tokens), max_token_len)
+            has_weights = has_weights or not all(map(lambda a: a[1] == 1.0, x))
+            to_encode.append(tokens)
+
+        sections = len(to_encode)
+        if has_weights or sections == 0:
+            to_encode.append(gen_empty_tokens(self.special_tokens, max_token_len))
+
+        out, pooled = self.encode(to_encode)
+        if pooled is not None:
+            first_pooled = pooled[0:1].to(model_management.intermediate_device())
+        else:
+            first_pooled = pooled
+
+        output = []
+        for k in range(0, sections):
+            z = out[k:k + 1]
+            if has_weights:
+                z_empty = out[-1]
+                for i in range(len(z)):
+                    for j in range(len(z[i])):
+                        weight = token_weight_pairs[k][j][1]
+                        if weight != 1.0:
+                            z[i][j] = (z[i][j] - z_empty[j]) * weight + z_empty[j]
+            output.append(z)
+
+        if (len(output) == 0):
+            return out[-1:].to(model_management.intermediate_device()), first_pooled
+        return torch.cat(output, dim=-2).to(model_management.intermediate_device()), first_pooled
+
     def load_sd(self, sd):
         return self.transformer.load_state_dict(sd, strict=False)
 

comfy/vendor/appdirs.py

@@ -19,11 +19,6 @@ __version_info__ = tuple(int(segment) for segment in __version__.split("."))
 import sys
 import os
 
-PY3 = sys.version_info[0] == 3
-
-if PY3:
-    unicode = str
-
 if sys.platform.startswith('java'):
     import platform
     os_name = platform.java_ver()[3][0]
@@ -464,10 +459,7 @@ def _get_win_folder_from_registry(csidl_name):
     registry for this guarantees us the correct answer for all CSIDL_*
     names.
     """
-    if PY3:
+    import winreg  # pylint: disable=import-error
-        import winreg as _winreg
-    else:
-        import _winreg
 
     shell_folder_name = {
         "CSIDL_APPDATA": "AppData",
@@ -475,11 +467,11 @@ def _get_win_folder_from_registry(csidl_name):
         "CSIDL_LOCAL_APPDATA": "Local AppData",
     }[csidl_name]
 
-    key = _winreg.OpenKey(
+    key = winreg.OpenKey(
-        _winreg.HKEY_CURRENT_USER,
+        winreg.HKEY_CURRENT_USER,
         r"Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders"
     )
-    dir, type = _winreg.QueryValueEx(key, shell_folder_name)
+    dir, type = winreg.QueryValueEx(key, shell_folder_name)
     return dir
 
 
@@ -509,32 +501,6 @@ def _get_win_folder_with_ctypes(csidl_name):
 
     return buf.value
 
-def _get_win_folder_with_jna(csidl_name):
-    import array
-    from com.sun import jna
-    from com.sun.jna.platform import win32
-
-    buf_size = win32.WinDef.MAX_PATH * 2
-    buf = array.zeros('c', buf_size)
-    shell = win32.Shell32.INSTANCE
-    shell.SHGetFolderPath(None, getattr(win32.ShlObj, csidl_name), None, win32.ShlObj.SHGFP_TYPE_CURRENT, buf)
-    dir = jna.Native.toString(buf.tostring()).rstrip("\0")
-
-    # Downgrade to short path name if have highbit chars. See
-    # <http://bugs.activestate.com/show_bug.cgi?id=85099>.
-    has_high_char = False
-    for c in dir:
-        if ord(c) > 255:
-            has_high_char = True
-            break
-    if has_high_char:
-        buf = array.zeros('c', buf_size)
-        kernel = win32.Kernel32.INSTANCE
-        if kernel.GetShortPathName(dir, buf, buf_size):
-            dir = jna.Native.toString(buf.tostring()).rstrip("\0")
-
-    return dir
-
 def _get_win_folder_from_environ(csidl_name):
     env_var_name = {
         "CSIDL_APPDATA": "APPDATA",
@@ -547,23 +513,12 @@ def _get_win_folder_from_environ(csidl_name):
 if system == "win32":
     try:
         from ctypes import windll
+        _get_win_folder = _get_win_folder_with_ctypes
     except ImportError:
         try:
-            import com.sun.jna
+            _get_win_folder = _get_win_folder_from_registry
         except ImportError:
-            try:
+            _get_win_folder = _get_win_folder_from_environ
-                if PY3:
-                    import winreg as _winreg
-                else:
-                    import _winreg
-            except ImportError:
-                _get_win_folder = _get_win_folder_from_environ
-            else:
-                _get_win_folder = _get_win_folder_from_registry
-        else:
-            _get_win_folder = _get_win_folder_with_jna
-    else:
-        _get_win_folder = _get_win_folder_with_ctypes
 
 
 #---- self test code

requirements-dev.txt

@@ -6,4 +6,5 @@ testcontainers
 testcontainers-rabbitmq
 mypy>=1.6.0
 freezegun
-coverage
+coverage
+pylint