def __init__(self, plover_engine: IPlover.Engine) -> None:
""" Main entry point for Spectra's Plover plugin. The Plover engine is our only argument.
Command-line arguments are not used (sys.argv belongs to Plover), and translations are not read from files.
We must create the main application object *and* start it before __init__ returns.
The extension is added as attribute 'plover' solely to make it visible to the debug tools. """
spectra = Spectra(parse_args=False)
spectra.translations_paths = ()
self._app = app = build_app(spectra)
self._ext = app.plover = PloverExtension(
EngineWrapper(plover_engine), stroke_limit=self.STROKE_LIMIT)
app.async_run(self._start)
app.start()
def main() -> int:
""" Analyze translations files and create an examples index from them. Time the execution. """
opts = SpectraOptions("Batch script for creating an examples index.")
opts.add(
"size", Fcls.SIZE_DEFAULT,
f"Relative size of generated index ({Fcls.SIZE_MINIMUM}-{Fcls.SIZE_MAXIMUM})."
)
opts.add(
"processes", 0,
"Number of processes used for parallel execution (0 = one per CPU core)."
)
spectra = Spectra(opts)
log = spectra.logger.log
log("Compiling examples index...")
start_time = time()
io = spectra.resource_io
analyzer = spectra.analyzer
files_in = spectra.translations_paths
file_out = spectra.index_path
translations = io.load_json_translations(*files_in)
pairs = Fcls(opts.size).filter(translations.items())
examples = analyzer.compile_index(pairs, process_count=opts.processes)
io.save_json_examples(file_out, examples)
total_time = time() - start_time
log(f"Index complete in {total_time:.1f} seconds.")
return 0
def main() -> int:
""" In standalone mode, we must create a QApplication and run a GUI event loop indefinitely. """
q_app = QApplication(sys.argv)
opts = SpectraOptions("Run Spectra as a standalone GUI application.")
spectra = Spectra(opts)
app = build_app(spectra)
app.start()
return q_app.exec_()
def main() -> int:
""" In standalone mode, we must create a QApplication and run a GUI event loop indefinitely. """
q_app = QApplication(sys.argv)
opts = SpectraOptions("Run Spectra as a standalone GUI application.")
spectra = Spectra(opts)
try:
app = build_app(spectra)
app.start()
except Exception as e:
sys.excepthook(type(e), e, e.__traceback__)
return q_app.exec_()
def main() -> int:
""" Run the application as a Discord bot. """
opts = SpectraOptions("Run Spectra as a Discord bot.")
opts.add("token", "", "Discord bot token (REQUIRED).")
opts.add("command", "spectra", "!command string for Discord users.")
spectra = Spectra(opts)
log = spectra.logger.log
log("Loading Discord bot...")
app = build_app(spectra)
if not opts.token:
log("No token given. Opening test console...")
return app.run_console()
bot = DiscordBot(opts.token, log)
bot.add_command(opts.command, app.query)
log("Discord bot started.")
return bot.run()
def main() -> int:
""" Build the server, start it, and poll for connections indefinitely. """
opts = SpectraOptions("Run Spectra as an HTTP web server.")
opts.add("http-addr", "", "IP address or hostname for server.")
opts.add("http-port", 80, "TCP port to listen for connections.")
opts.add("http-dir", HTTP_PUBLIC_DEFAULT, "Root directory for public HTTP file service.")
spectra = Spectra(opts)
log = spectra.logger.log
log("Loading HTTP server...")
app = build_app(spectra)
dispatcher = build_dispatcher(app, opts.http_dir, log)
server = ThreadedTCPServer(dispatcher)
log("Server started.")
try:
server.start(opts.http_addr, opts.http_port)
finally:
server.shutdown()
log("Server stopped.")
return 0
def main() -> int:
""" Run the application as a Discord bot. """
opts = SpectraOptions("Run Spectra as a Discord bot.")
opts.add("token", "", "Discord bot token (REQUIRED).")
opts.add("command", "spectra", "!command string for Discord users.")
opts.add("cache_id", "", "Optional channel ID for image cache.")
spectra = Spectra(opts)
log.setHandler(spectra.logger.log)
log.info("Loading Discord bot...")
app = build_app(spectra, 400, 300, max_chars=100)
token = opts.token.strip()
if not token:
log.info("No token given. Opening test console...")
return introspect(app)
http = HTTPClient(token)
bot = DiscordBot(app, http, opts.cache_id)
cmds = CommandDispatcher()
cmds.add_command(opts.command, bot)
client = Client(http, token)
client.add_event_handler(cmds)
client.add_event_handler(bot)
log.info("Discord bot started.")
client.start()
return 0
""" Main feature tests for the Spectra steno lexer.
Tests translation search, lexical analysis, and graphical rendering. """
import re
import pytest
from spectra_lexer import Spectra
from . import TEST_TRANSLATIONS
_spectra = Spectra()
SEARCH_ENGINE = _spectra.search_engine
ANALYZER = _spectra.analyzer
BOARD_ENGINE = _spectra.board_engine
GRAPH_ENGINE = _spectra.graph_engine
del _spectra
SEARCH_ENGINE.set_translations(TEST_TRANSLATIONS)
TEST_TRANSLATION_PAIRS = list(TEST_TRANSLATIONS.items())
@pytest.mark.parametrize("keys, letters", TEST_TRANSLATION_PAIRS)
def test_search(keys, letters) -> None:
""" Go through each loaded test translation and check all search methods. """
search = SEARCH_ENGINE.search
assert search(keys, count=2, mode_strokes=True) == {keys: (letters, )}
assert search(letters, count=2) == {letters: (keys, )}
assert keys in search(re.escape(keys),
count=2,
mode_strokes=True,
mode_regex=True)
def _spectra():
from spectra_lexer import Spectra
return Spectra()
def main() -> int:
""" Load basic resources and run an interactive read-eval-print loop in a new console. """
opts = SpectraOptions("Run Spectra from scratch in an interactive Python console.")
spectra = Spectra(opts)
spectra.logger.log("Loading console...")
return introspect(spectra, include_private=False)