def _process_recognition(self, node, extras):
has_parameters = node.words()[1] != "no-param"
type = node.words()[1 if has_parameters else 2]
string = "def "
name = None
if type == "constructor":
name = "__init__"
elif "text" in extras:
name = formatter.format_snake_case(extras["text"])
if name is not None:
string += name
parameters_start = "("
if type in ("method", "constructor"):
parameters_start += "self, " if has_parameters else "self"
string += parameters_start + ")"
text(string).execute()
if has_parameters:
global_state.add_nesting_level(1)
if name is None:
name_offset = len(parameters_start)
if not has_parameters:
name_offset += 1
global_state.add_nesting_level(name_offset)
def _process_recognition(self, node, extras):
integer = extras["m"]
number = str(integer)
if "n" in extras:
floating_point = extras["n"]
number += "." + str(floating_point)
text(number).execute()
def _process_recognition(self, node, extras):
has_arguments = node.words()[1] != "empty"
string = formatter.format_text(extras["text"],
formatter.FormatType.pascalCase)
string += "()"
text(string).execute()
if has_arguments:
global_state.add_nesting_level(1)
def _process_recognition(self, node, extras):
has_parameters = node.words()[0] != "no-param"
string = "lambda"
if not has_parameters:
string += ":"
else:
string += " :"
text(string).execute()
if has_parameters:
global_state.add_nesting_level(1)
def _change_visibility(prefix):
mouse("left/3").execute()
key("s-f6/20").execute()
name = get_selected_text()
if name.startswith("__"):
name = name[2:]
elif name.startswith("_"):
name = name[1:]
name = prefix + name
text(name).execute()
key("enter/3").execute()
def _process_recognition(self, node, extras):
is_constructor = "text" not in extras
name = "__init__" if is_constructor else formatter.format_text(
extras["text"], formatter.FormatType.snakeCase)
has_arguments = node.words()[1] != "empty"
has_period = node.words()[len(node.words()) - 1] == "on"
string = "." if has_period else ""
string += name
string += "()"
text(string).execute()
if has_arguments:
global_state.add_nesting_level(1)
def _process_recognition(self, node, extras):
is_child = node.words()[1] == "child"
string = "class "
if "text" in extras:
string += formatter.format_text(extras["text"],
formatter.FormatType.pascalCase)
if is_child:
string += "()"
text(string).execute()
if is_child:
global_state.add_nesting_level(1)
if "text" not in extras:
global_state.add_nesting_level(1)
class PluralRule(MappingRule):
mapping = {"plural": text("s")}
def __init__(self, exported):
MappingRule.__init__(self,
name=get_unique_rule_name(),
exported=exported)
def _process_recognition(self, node, extras):
type = node.words()[1]
string = ""
if "text" in extras:
if type == "variable":
name = formatter.format_snake_case(extras["text"])
else:
name = formatter.format_text(extras["text"], [
formatter.FormatType.snakeCase,
formatter.FormatType.upperCase
])
string = name
string += " = "
text(string).execute()
if "text" not in extras:
global_state.add_nesting_level(3)
def list_comprehension():
text("[ for in ]").execute()
global_state.add_nesting_level(1)
global_state.add_nesting_level(4)
global_state.add_nesting_level(5)
def ternary():
text(" if else ").execute()
global_state.add_nesting_level(6)
global_state.add_nesting_level(4)
def format_variable(text, prefix="", suffix=""):
name = formatter.format_text(text, formatter.FormatType.snakeCase)
_text(prefix + name + suffix).execute()
def class_name(text):
name = formatter.format_text(text, formatter.FormatType.pascalCase)
_text(name).execute()
rules = MappingRule(
mapping={
# Commands and keywords:
"and":
text(" and "),
"as":
text("as "),
"assign":
text(" = "),
"assert":
text("assert "),
"break":
text("break"),
"comment":
text("# "),
"class":
text("class "),
"continue":
text("continue"),
"del":
def _process_recognition(self, node, extras):
symbol = extras["symbol"]
text(symbol).execute()
def _process_recognition(self, node, extras):
text(node).execute()
def _process_recognition(self, node, extras):
letter = extras["letter"][1]
text(letter).execute()
def _process_recognition(self, node, extras):
text(reduce(lambda x, y: x + y, extras["symbols"])).execute()
