Fixes for numpy 2, and more

Fixed issues from running with numpy 2. Also cleaned up some linting issues.

python/pjrmi/__init__.py

@@ -1369,7 +1369,7 @@ def _send(self, msg_type, payload):
         internally.
         """
 
-        assert(payload is not None)
+        assert payload is not None
 
         # We can't currently send messages larger than 2GB in size. This will
         # require a number of changes on both sides, partly since Java arrays
@@ -1455,7 +1455,7 @@ def _recv(self):
             payload = b''
             while len(payload) < payload_size:
                 payload += self._transport.recv(payload_size - len(payload))
-            assert(len(payload) == payload_size)
+            assert len(payload) == payload_size
 
             # See if it happened to be a callback
             if request_id == self._CALLBACK_REQUEST_ID:
@@ -2533,7 +2533,7 @@ def _format_string(self, string):
         Format a string as [int32:size][bytes[]:string], to send down the wire
         """
 
-        if type(string) != bytes:
+        if type(string) is not bytes:
             string = string.encode('ascii')
         return self._format_int32(len(string)) + string
 
@@ -2625,10 +2625,9 @@ def _format_array(self, value, dtype):
         if len(arr) > self._MAX_JAVA_ARRAY_SIZE:
             raise TypeError('The given array is larger than Java can represent')
 
-        return bytes(numpy.array(strict_array(dtype.type, arr),
-                                 dtype=dtype,
-                                 copy=False,
-                                 order='C').data)
+        return bytes(numpy.asarray(strict_array(dtype.type, arr),
+                                   dtype=dtype,
+                                   order='C').data)
 
 
     def _format_method_as(self, value, klass):
@@ -2682,7 +2681,7 @@ def _format_as_lambda(self,
         # argument list, or none at all
         if not method._is_static:
             if (len(args) == len(method._argument_type_ids) + 1 and
-                type(args[0]) == method._klass):
+                type(args[0]) is method._klass):
                 this = args[0]
                 args = args[1:]
             else:
@@ -3078,17 +3077,17 @@ def _format_by_class(self, klass, value,
                                           for el in value))
 
                 elif isinstance(value, int):
-                    if numpy.can_cast(value, numpy.int8):
+                    if  -128 <= value < 128:
                         return (self._ARGUMENT_VALUE +
                                 self._format_int32(self._java_lang_Byte._type_id) +
                                 self._format_int8(strict_number(numpy.int8, value)))
 
-                    elif numpy.can_cast(value, numpy.int16):
+                    elif -16384 <= value < 16384:
                         return (self._ARGUMENT_VALUE +
                                 self._format_int32(self._java_lang_Short._type_id) +
                                 self._format_int16(strict_number(numpy.int16, value)))
 
-                    elif numpy.can_cast(value, numpy.int32):
+                    elif -2147483648 <= value < 2147483648:
                         return (self._ARGUMENT_VALUE +
                                 self._format_int32(self._java_lang_Integer._type_id) +
                                 self._format_int32(strict_number(numpy.int32, value)))
@@ -3254,7 +3253,7 @@ def _format_by_class(self, klass, value,
                 # If the user has given us a numpy type then we assume that they
                 # know what they are doing when it comes to types, and we
                 # disallow a lossy conversion.
-                if type(value) == numpy.float64:
+                if type(value) is numpy.float64:
                     raise ValueError("%s is not assignable to %s" %
                                      (type(value), klass._classname))
                 else:
@@ -3542,7 +3541,7 @@ def _format_by_class(self, klass, value,
                         self._format_int32(self._get_object_id(value)))
 
             elif (klass._type_id == self._com_deshaw_hypercube_Hypercube._type_id and
-                  type(value) == numpy.ndarray):
+                  type(value) is numpy.ndarray):
                 return (self._ARGUMENT_VALUE +
                         self._format_int32(klass._type_id) +
                         self._format_by_class(self._L_java_lang_long, value.shape) +