Merge pull request #5 from RasaHQ/scoped-imports

scoped imports

rasa/__main__.py

@@ -3,18 +3,17 @@
 import argparse
 import logging
 
-import rasa_core.utils
-
-from rasa.cli import scaffold, run, train, configure, interactive, shell, test, \
-    show, data
-from rasa.utils import print_versions
+from rasa import version
+from rasa.cli import (scaffold, run, train, configure, interactive, shell, test,
+                      show, data)
+from rasa_core.cli.arguments import add_logging_option_arguments
+from rasa_core.utils import configure_colored_logging
 
 logger = logging.getLogger(__name__)
 
 
 def create_argument_parser():
     """Parse all the command line arguments for the training script."""
-
     parser = argparse.ArgumentParser(
         prog="rasa",
         description='Rasa command line interface. Rasa allows you to build '
@@ -26,7 +25,7 @@ def create_argument_parser():
                         help="Print installed Rasa version.")
 
     parent_parser = argparse.ArgumentParser(add_help=False)
-    rasa_core.utils.add_logging_option_arguments(parent_parser)
+    add_logging_option_arguments(parent_parser)
     parent_parsers = [parent_parser]
 
     subparsers = parser.add_subparsers(help='Rasa commands')
@@ -44,16 +43,20 @@ def create_argument_parser():
     return parser
 
 
+def print_version():
+    print("Rasa", version.__version__)
+
+
 def main():
     # Running as standalone python application
     arg_parser = create_argument_parser()
     cmdline_arguments = arg_parser.parse_args()
 
     if hasattr(cmdline_arguments, "func"):
-        rasa_core.utils.configure_colored_logging(cmdline_arguments.loglevel)
+        configure_colored_logging(cmdline_arguments.loglevel)
         cmdline_arguments.func(cmdline_arguments)
     elif cmdline_arguments.version:
-        print_versions()
+        print_version()
     else:
         # user has not provided a subcommand, let's print the help
         logger.error("No command specified.")

rasa/cli/__init__.py

@@ -1,2 +1,2 @@
 import rasa.cli.run
-import rasa.cli.train
+import rasa.cli.train

rasa/cli/configure.py

@@ -1,8 +1,6 @@
 import os
 
 import questionary
-import rasa_core.utils
-from rasa_core.utils import print_error, print_success
 
 
 def add_subparser(subparsers):
@@ -17,6 +15,9 @@ def add_subparser(subparsers):
 
 
 def configure_channel(channel):
+    from rasa_core.utils import print_error, print_success
+    import rasa_core.utils
+
     credentials_file = questionary.text(
         "Please enter a path where to store the credentials file",
         default="credentials.yml").ask()

rasa/cli/data.py

@@ -1,7 +1,6 @@
-from rasa_nlu import convert
-
-
 def add_subparser(subparsers, parents):
+    from rasa_nlu import convert
+
     data_parser = subparsers.add_parser(
         "data",
         conflict_handler="resolve",
@@ -13,7 +12,7 @@ def add_subparser(subparsers, parents):
         "convert", help="Convert Rasa data between different formats.")
 
     convert_subparsers = convert_parser.add_subparsers()
-    convert_nlu_parser=convert_subparsers.add_parser(
+    convert_nlu_parser = convert_subparsers.add_parser(
         "nlu", help="Convert NLU training data between markdown and json.")
 
     convert.add_arguments(convert_parser)

rasa/cli/interactive.py

@@ -1,11 +1,8 @@
-import os
 import shutil
 
 import rasa.cli as cli
 from rasa.model import unpack_model
 
-from rasa_core.train import do_interactive_learning
-
 
 def add_subparser(subparsers, parents):
     interactive_parser = subparsers.add_parser(
@@ -32,7 +29,9 @@ def _add_interactive_arguments(parser):
 
 
 def interactive(args):
-    args.finetune = False # Don't support finetuning
+    from rasa_core.train import do_interactive_learning
+
+    args.finetune = False  # Don't support finetuning
 
     zipped_model = cli.train.train(args)
     model_path, core_path, nlu_path = unpack_model(zipped_model,

rasa/cli/run.py

@@ -2,17 +2,9 @@
 import logging
 import os
 import shutil
-import tempfile
-
-from rasa_core.broker import PikaProducer
-from rasa_core.interpreter import RasaNLUInterpreter
-import rasa_core.run
-from rasa_core.tracker_store import TrackerStore
-from rasa_core.utils import AvailableEndpoints
-import rasa_nlu.server
 
 from rasa.cli.default_arguments import add_model_param
-from rasa.model import get_latest_model, get_model, DEFAULT_MODELS_PATH
+from rasa.model import DEFAULT_MODELS_PATH, get_latest_model, get_model
 
 logger = logging.getLogger(__name__)
 
@@ -46,7 +38,6 @@ def add_subparser(subparsers, parents):
         help="Run a trained NLU model"
     )
 
-    rasa_nlu.server.add_run_arguments(nlu_subparser)
     _add_nlu_arguments(nlu_subparser)
     nlu_subparser.set_defaults(func=run_nlu)
 
@@ -62,7 +53,9 @@ def add_subparser(subparsers, parents):
 
 
 def add_run_arguments(parser):
-    rasa_core.run.add_run_options(parser)
+    from rasa_core.cli.run import add_run_arguments
+
+    add_run_arguments(parser)
     add_model_param(parser)
 
     parser.add_argument(
@@ -72,6 +65,9 @@ def add_run_arguments(parser):
 
 
 def _add_nlu_arguments(parser):
+    from rasa_nlu.cli.server import add_server_arguments
+
+    add_server_arguments(parser)
     parser.add_argument('--path',
                         default=DEFAULT_MODELS_PATH,
                         help="working directory of the server. Models are"
@@ -82,6 +78,9 @@ def _add_nlu_arguments(parser):
 
 
 def run_nlu(args):
+    import rasa_nlu.server
+    import tempfile
+
     model = get_latest_model(args.model)
     working_directory = tempfile.mkdtemp()
     model_path = model.unpack_model(model, working_directory)
@@ -97,6 +96,12 @@ def run_sdk(args):
 
 
 def run(args):
+    from rasa_core.broker import PikaProducer
+    from rasa_core.interpreter import RasaNLUInterpreter
+    import rasa_core.run
+    from rasa_core.tracker_store import TrackerStore
+    from rasa_core.utils import AvailableEndpoints
+
     model_paths = get_model(args.model, subdirectories=True)
 
     if model_paths is None:

rasa/cli/scaffold.py

@@ -1,11 +1,7 @@
 import os
-from distutils.dir_util import copy_tree
 
 import questionary
 from rasa.cli import train
-from rasa_core.utils import print_success
-from rasa_core import constants
-
 from rasa.cli.shell import shell
 from rasa.cli.train import create_default_output_path
 
@@ -24,6 +20,8 @@ def scaffold_path():
 
 
 def print_train_or_instructions(args, path):
+    from rasa_core.utils import print_success
+
     print_success("Your bot initial_project is ready to go!")
     should_train = questionary.confirm("Do you want me to train an initial "
                                        "model for the bot?").ask()
@@ -44,6 +42,8 @@ def print_train_or_instructions(args, path):
 
 
 def print_run_or_instructions(args, path):
+    from rasa_core import constants
+
     should_run = questionary.confirm("Do you want me to run the trained model "
                                      "in the command line?").ask()
 
@@ -63,6 +63,8 @@ def print_run_or_instructions(args, path):
 
 
 def init_project(args, path):
+    from distutils.dir_util import copy_tree
+
     copy_tree(scaffold_path(), path)
 
     print("Created project directory at '{}'.".format(os.path.abspath(path)))

rasa/cli/show.py

@@ -1,10 +1,9 @@
 import argparse
 import os
 
-import rasa_core.visualize as visualize
-
-from rasa.cli.default_arguments import add_domain_param, add_stories_param, \
-    add_config_param
+from rasa.cli.default_arguments import (
+    add_config_param, add_domain_param,
+    add_stories_param)
 from rasa.model import DEFAULTS_NLU_DATA_PATH
 
 
@@ -30,12 +29,16 @@ def add_subparser(subparsers, parents):
 
 
 def add_core_visualization_params(parser):
-    visualize.add_visualization_arguments(parser)
+    from rasa_core.cli.visualization import add_visualization_arguments
+
+    add_visualization_arguments(parser)
     add_domain_param(parser)
     add_stories_param(parser)
 
 
 def show(args):
+    import rasa_core.visualize as visualize
+
     args.config = [args.config]
     args.url = None
 

rasa/cli/test.py

@@ -1,17 +1,9 @@
 import argparse
 import logging
 import os
-import tempfile
-
-import rasa_core.evaluate
-import rasa_nlu
-from rasa_core.utils import AvailableEndpoints
-from rasa_nlu import utils as nlu_utils
-from rasa_core.interpreter import NaturalLanguageInterpreter
-from rasa_core.agent import Agent
 
 from rasa.cli.default_arguments import add_model_param, add_stories_param
-from rasa.model import get_model, get_latest_model, DEFAULT_MODELS_PATH
+from rasa.model import DEFAULT_MODELS_PATH, get_latest_model, get_model
 
 logger = logging.getLogger(__name__)
 
@@ -54,8 +46,9 @@ def add_subparser(subparsers, parents):
 
 
 def _add_core_arguments(parser):
-    rasa_core.evaluate.add_args_to_parser(parser)
+    from rasa_core.cli.evaluation import add_evaluation_arguments
 
+    add_evaluation_arguments(parser)
     add_model_param(parser, "Core")
     add_stories_param(parser, "test")
 
@@ -117,6 +110,12 @@ def _add_nlu_subparser_arguments(parser):
 
 
 def test_core(args, model_path=None):
+    import rasa_core.evaluate
+    from rasa_nlu import utils as nlu_utils
+    from rasa_core.utils import AvailableEndpoints
+    from rasa_core.interpreter import NaturalLanguageInterpreter
+    from rasa_core.agent import Agent
+
     logging.basicConfig(level=args.loglevel)
     _endpoints = AvailableEndpoints.read_endpoints(
         args.endpoints)
@@ -159,6 +158,8 @@ def test_core(args, model_path=None):
 
 
 def test_nlu(args, model_path=None):
+    import rasa_nlu
+
     model_path = model_path or args.model
     if model_path:
         unpacked_model = get_model(args.model)