[python-package] fix some warnings from mypy

python-package/lightgbm/dask.py

@@ -9,7 +9,7 @@
 import socket
 from collections import defaultdict
 from copy import deepcopy
-from typing import Any, Callable, Dict, Iterable, List, Optional, Type, Union
+from typing import Any, Callable, Dict, Iterable, List, Optional, Type, Union, Set
 from urllib.parse import urlparse
 
 import numpy as np
@@ -77,7 +77,6 @@ def _find_open_port(worker_ip: str, local_listen_port: int, ports_to_skip: Itera
         A free port on the machine referenced by ``worker_ip``.
     """
     max_tries = 1000
-    out_port = None
     found_port = False
     for i in range(max_tries):
         out_port = local_listen_port + i
@@ -117,7 +116,7 @@ def _find_ports_for_workers(client: Client, worker_addresses: Iterable[str], loc
     result : Dict[str, int]
         Dictionary where keys are worker addresses and values are an open port for LightGBM to use.
     """
-    lightgbm_ports = set()
+    lightgbm_ports: Set[int] = set()
     worker_ip_to_port = {}
     for worker_address in worker_addresses:
         port = client.submit(
@@ -306,11 +305,11 @@ def _train(
     wait(parts)
 
     for part in parts:
-        if part.status == 'error':
+        if part.status == 'error':  # type: ignore
             return part  # trigger error locally
 
     # Find locations of all parts and map them to particular Dask workers
-    key_to_part_dict = {part.key: part for part in parts}
+    key_to_part_dict = {part.key: part for part in parts}  # type: ignore
     who_has = client.who_has(parts)
     worker_map = defaultdict(list)
     for key, workers in who_has.items():

python-package/lightgbm/sklearn.py

@@ -824,8 +824,8 @@ def fit(self, X, y,
         return self
 
     _base_doc = LGBMModel.fit.__doc__
-    _base_doc = (_base_doc[:_base_doc.find('group :')]
-                 + _base_doc[_base_doc.find('eval_set :'):])
+    _base_doc = (_base_doc[:_base_doc.find('group :')]  # type: ignore
+                 + _base_doc[_base_doc.find('eval_set :'):])  # type: ignore
     _base_doc = (_base_doc[:_base_doc.find('eval_class_weight :')]
                  + _base_doc[_base_doc.find('eval_init_score :'):])
     fit.__doc__ = (_base_doc[:_base_doc.find('eval_group :')]
@@ -897,8 +897,8 @@ def fit(self, X, y,
         return self
 
     _base_doc = LGBMModel.fit.__doc__
-    _base_doc = (_base_doc[:_base_doc.find('group :')]
-                 + _base_doc[_base_doc.find('eval_set :'):])
+    _base_doc = (_base_doc[:_base_doc.find('group :')]  # type: ignore
+                 + _base_doc[_base_doc.find('eval_set :'):])  # type: ignore
     fit.__doc__ = (_base_doc[:_base_doc.find('eval_group :')]
                    + _base_doc[_base_doc.find('eval_metric :'):])
 
@@ -989,8 +989,8 @@ def fit(self, X, y,
         return self
 
     _base_doc = LGBMModel.fit.__doc__
-    fit.__doc__ = (_base_doc[:_base_doc.find('eval_class_weight :')]
-                   + _base_doc[_base_doc.find('eval_init_score :'):])
+    fit.__doc__ = (_base_doc[:_base_doc.find('eval_class_weight :')]  # type: ignore
+                   + _base_doc[_base_doc.find('eval_init_score :'):])  # type: ignore
     _base_doc = fit.__doc__
     _before_early_stop, _early_stop, _after_early_stop = _base_doc.partition('early_stopping_rounds :')
     fit.__doc__ = (_before_early_stop

python-package/setup.py

@@ -322,7 +322,7 @@ def run(self):
     if os.path.isfile(os.path.join(CURRENT_DIR, os.path.pardir, 'VERSION.txt')):
         copy_file(os.path.join(CURRENT_DIR, os.path.pardir, 'VERSION.txt'),
                   os.path.join(CURRENT_DIR, 'lightgbm', 'VERSION.txt'),
-                  verbose=0)
+                  verbose=0)  # type:ignore
     version = open(os.path.join(CURRENT_DIR, 'lightgbm', 'VERSION.txt'), encoding='utf-8').read().strip()
     readme = open(os.path.join(CURRENT_DIR, 'README.rst'), encoding='utf-8').read()