def q(self,
questions: Union[List[dict], dict],
clear: bool = False,
save_prompt: bool = True):
"""Ask questions and handle interruptions.
Args:
questions: Single dictionary or a list with question dictionaries
clear: Set to True to clear screen before questioning.
save_prompt: Set to False to disable asking about saving progress if the user interrupts.
Returns:
Dictionary with answers
"""
if clear:
clear_screen()
if isinstance(questions, dict):
questions = [questions]
# Wrap and indent question
max_width = min(console.size[0], 80)
tw1 = textwrap.TextWrapper(width=max_width,
break_long_words=False,
subsequent_indent=" ")
tw2 = textwrap.TextWrapper(width=max_width,
break_long_words=False,
initial_indent=" ",
subsequent_indent=" ")
for q in questions:
q["message"] = "\n".join(
tw1.fill(line) if i == 0 else tw2.fill(line)
for i, line in enumerate(q["message"].splitlines()))
answer = prompt(questions, style=style)
# Handle interruptions
if not answer:
if save_prompt:
if prompt([{
"type":
"confirm",
"name":
"answer",
"message":
"Do you want to save your progress so far to be able to resume the wizard later?"
}],
style=style).get("answer"):
self.save_config()
sys.exit()
return answer
def get_login_info(self) -> Optional[Tuple[str, str]]:
'''Returns the (email, password) pair for login'''
args = get_args()
if args.login:
return args.login
# end if
if args.suppress:
return None
# end if
answer = prompt([
{
'type': 'confirm',
'name': 'login',
'message': 'Do you want to log in?',
'default': False
},
])
if answer['login']:
answer = prompt([
{
'type':
'input',
'name':
'email',
'message':
'User/Email:',
'validate':
lambda a: True if a else 'User/Email should be not be empty'
},
{
'type':
'password',
'name':
'password',
'message':
'Password:'******'validate':
lambda a: True if a else 'Password should be not be empty'
},
])
return answer['email'], answer['password']
# end if
return None
def server_configuration_questionaire(dirs, instance_name):
"""Questionary to generate a config file for the node instance."""
config = q.prompt([
{
"type": "text",
"name": "description",
"message": "Enter a human-readable description:"
},
{
"type": "text",
"name": "ip",
"message": "ip:",
"default": "0.0.0.0"
},
{
"type": "text",
"name": "port",
"message": "Enter port to which the server listens:",
"default": "5000"
},
{
"type": "text",
"name": "api_path",
"message": "Path of the api:",
"default": "/api"
},
{
"type": "text",
"name": "uri",
"message": "Database URI:",
"default": "sqlite:///default.sqlite"
},
{
"type": "select",
"name": "allow_drop_all",
"message": "Allowed to drop all tables: ",
"choices": ["True", "False"]
}
])
res = q.select("Which level of logging would you like?",
choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL", "NOTSET"]
).ask()
constant_jwt_secret = q.confirm("Do you want a constant JWT secret?").ask()
if constant_jwt_secret:
config["jwt_secret_key"] = str(uuid.uuid1())
config["logging"] = {
"level": res,
"file": f"{instance_name}.log",
"use_console": True,
"backup_count":5,
"max_size": 1024,
"format": "%(asctime)s - %(name)-14s - %(levelname)-8s - %(message)s",
"datefmt": "%Y-%m-%d %H:%M:%S"
}
return config
def ask_dictstyle(**kwargs):
questions = [
{
"type": "confirm",
"name": "conditional_step",
"message": "Would you like the next question?",
"default": True,
},
{
"type": "text",
"name": "next_question",
"message": "Name this library?",
# Validate if the first question was answered with yes or no
"when": lambda x: x["conditional_step"],
# Only accept questionary as answer
"validate": lambda val: val == "questionary",
},
{
"type": "select",
"name": "second_question",
"message": "Select item",
"choices": ["item1", "item2",
Separator(), "other"],
},
{
"type": "text",
# intentionally overwrites result from previous question
"name": "second_question",
"message": "Insert free text",
"when": lambda x: x["second_question"] == "other",
},
]
return prompt(questions)
def user_selects(message: str,
choices: list,
selection_type="list",
sort_choices=True) -> Union[str, list]:
"""Prompts the user to select a choice(s) given a message
Args:
message (str): the message to give to the user before they choose
choices (list): a list of the options to provide
selection_type (str, optional): Defaults to "list". Should be "list"
or "checkbox" for radio-button-style or checkbox-style selections
sort_choices (bool, optional): Defaults to True. Whether to
alphabetically sort the choices in the list provided to the user
Returns:
str or list: the str for the choice selected if "list" is the
selection_type
the list of the choices selected if "checkbox" is the
selection_type
"""
question = [
{
"type": selection_type,
"name": 'value',
"message": message,
"choices": sorted(choices) if sort_choices else choices
},
]
answer = prompt(question)
return answer['value']
def user_input(message: str, default="", validator=None) -> str:
"""Prompts the user for input
Args:
message (str): the message to give to the user before they provide
input
default (str, optional): Defaults to "". The default input response
validator (Validator, optional): Defaults to None. A PyInquirer
validator used to validate input before proceeding
Returns:
str: the user's response
"""
if validator is not None:
question = [
{
"type": "input",
"name": 'value',
"message": message,
"default": default,
"validate": validator,
},
]
else:
question = [
{
"type": "input",
"name": 'value',
"message": message,
"default": default
},
]
answer = prompt(question)
return answer["value"]
def q0() -> BaseTask:
'''
This question is used to select the task you wish to alter with pdpp.
'''
tasks = get_riggable_tasks()
click_clear()
choice_list = []
for task in tasks:
choice_list.append(Choice(
title=task.target_dir,
value=task,
))
questions_0 = [{
'type': 'list',
'name': 'target_dir',
'message': 'Select the task you would like to rig:',
'choices': choice_list
}]
return prompt(questions_0, style=custom_style_fancy)['target_dir']
def get_answers(self) -> AnyByStrDict:
"""Obtain answers for all questions.
It produces a TUI for querying the user if `ask_user` is true. Otherwise,
it gets answers from other sources.
"""
previous_answers = self.get_best_answers()
if self.ask_user:
# HACK https://github.com/tmbo/questionary/pull/79
# TODO Remove type: ignore comments when fixed
self.answers_user = prompt(
(question.get_questionary_structure()
for question in self.questions), # type: ignore
answers=previous_answers, # type: ignore
)
# HACK https://github.com/tmbo/questionary/issues/74
if not self.answers_user and self.questions:
raise KeyboardInterrupt
else:
# Avoid prompting to not requiring a TTy when --force
for question in self.questions:
new_answer = question.get_default()
previous_answer = previous_answers.get(question.var_name)
if new_answer != previous_answer:
self.answers_user[question.var_name] = new_answer
return self.answers_user
def q_extant() -> StandardTask:
'''
This question is used to select the directory you wish to automate.
'''
task_dirs = [d.target_dir for d in get_pdpp_tasks()]
click_clear()
dir_list = [
d.name for d in os.scandir() if d.name not in task_dirs and d.is_dir()
]
choice_list = []
print(task_dirs)
print(dir_list)
for _dir in dir_list:
choice_list.append(Choice(
title=_dir,
value=_dir,
))
questions_0 = [{
'type': 'list',
'name': 'target_dir',
'message': 'Select the directory you would like to automate:',
'choices': choice_list
}]
dirname = prompt(questions_0, style=custom_style_fancy)['target_dir']
return StandardTask(target_dir=dirname)
def get_kpi(preloaded_matrix, preloaded_KPIs):
"""Prompts for user selection on KPIs to print.
Invokes benchmarking.get_selected_metrics() to calculate KPIs.
Lastly, display menu to user after calculation.
Args:
preloaded_matrix (obj): Matrix used for calculating KPIs
preloaded_KPIs (obj): Metrics used for calculating KPIs
"""
benchmarking_kpi_choice = prompt(menu_options.benchmarking_kpi, style=blue)
sid = benchmarking_kpi_choice['sid']
percentile = benchmarking_kpi_choice['percentile']
kpi_selected = benchmarking_kpi_choice['kpi_selected']
# Display metrics for user selection
benchmarking.get_selected_metrics(kpi_selected, sid, percentile,
preloaded_matrix, preloaded_KPIs)
# Display menu
while True:
choice_after = questionary.select(
"---Run Benchmarking---",
choices=[
'Run benchmarking for another SID', 'Go back to main menu',
'Exit'
],
style=blue).ask()
if choice_after == 'Run benchmarking for another SID':
get_kpi(preloaded_matrix, preloaded_KPIs)
elif choice_after == 'Go back to main menu':
load_main_menu()
elif choice_after == 'Exit':
sys.exit()
def export_menu():
"""
Second level menu with the purpose to catch all functionality related to exporting the data to a target.
"""
export_menu_answers = questionary.prompt(export_menu_questions)
choice_export_menu = export_menu_answers.get("export_menu_target")
choice_pretty_print_sort = export_menu_answers.get("export_menu_prettyprint_1")
choice_pretty_print_indent = export_menu_answers.get("export_menu_prettyprint_2")
if not choice_pretty_print_indent:
choice_pretty_print_indent = None
else:
choice_pretty_print_indent = int(choice_pretty_print_indent)
if choice_export_menu == "String":
print(os_signatures.exportsignatures(ExportTypes.STRING, sort_keys=choice_pretty_print_sort,
indent=choice_pretty_print_indent))
elif choice_export_menu == "File":
input_export_menu_2 = export_menu_questions2.ask()
if input_export_menu_2 == "":
print("Target path for the file was not entered correctly. Returning to main menu.")
return
os_signatures.exportsignatures(ExportTypes.FILE, input_export_menu_2, choice_pretty_print_sort,
choice_pretty_print_indent)
elif choice_export_menu == "Go back":
return
else:
print("Unknown option selected. Returning to the main menu.")
return
def display_open_folder(folder_path: str):
args = get_args()
if args.suppress:
return
answer = prompt([
{
'type': 'confirm',
'name': 'exit',
'message': 'Open the output folder?',
'default': True,
},
])
if not answer['exit']:
return
if Icons.isWindows:
import subprocess
subprocess.Popen('explorer /select,"' + folder_path + '"')
else:
import pathlib
import webbrowser
url = pathlib.Path(folder_path).as_uri()
webbrowser.open_new(url)
def ask_dictstyle(**kwargs):
questions = [{
"type":
"checkbox",
"qmark":
"😃",
"message":
"Select toppings",
"name":
"toppings",
"choices": [
{
"name": "foo",
"checked": True
},
Separator(),
{
"name": "bar",
"disabled": "nope"
},
"bazz",
Separator("--END--"),
],
}]
return prompt(questions, style=custom_style_dope, **kwargs)
def _ask_for_credentials():
""" Prompt for key id and secret keys.
Returns:
str, str: Kei ID, Secret Key
"""
credentials = questionary.prompt([{
"type":
"text",
"name":
"key_id",
"message":
"Key:",
"qmark":
">",
"validate":
lambda value: bool(re.fullmatch(KEY_ID, value)) or "Invalid Key"
}, {
"type":
"password",
"name":
"secret_key",
"message":
"Secret:",
"qmark":
">",
"validate":
lambda value: bool(re.fullmatch(SECRET_KEY, value)) or
"Invalid Secret",
}])
if not credentials:
return
return list(credentials.values())
def get_output_path(self):
'''Returns a valid output path where the files are stored'''
args = get_args()
output_path = args.output_path
if args.suppress:
if not output_path:
output_path = self.app.output_path
# end if
if not output_path:
output_path = os.path.join('Lightnovels', 'Unknown Novel')
# end if
# end if
if not output_path:
answer = prompt([
{
'type': 'input',
'name': 'output',
'message': 'Enter output directory:',
'default': os.path.abspath(self.app.output_path),
},
])
output_path = answer['output']
# end if
output_path = os.path.abspath(output_path)
if os.path.exists(output_path):
if self.force_replace_old():
shutil.rmtree(output_path, ignore_errors=True)
# end if
# end if
os.makedirs(output_path, exist_ok=True)
return output_path
def get_output_formats(self):
'''Returns a dictionary of output formats.'''
args = get_args()
formats = args.output_formats
if not (formats or args.suppress):
answer = prompt([
{
'type':
'checkbox',
'name':
'formats',
'message':
'Which output formats to create?',
'choices': [{
'name': x,
'checked': x in ['epub', 'json']
} for x in available_formats],
},
])
formats = answer['formats']
# end if
if not formats or len(formats) == 0:
formats = ['epub'] # default to epub if none selected
# end if
return {x: (x in formats) for x in available_formats}
def get_novel_url(self):
'''Returns a novel page url or a query'''
args = get_args()
if args.query and len(args.query) > 1:
return args.query
# end if
url = args.novel_page
if url:
if re.match(r'^https?://.+\..+$', url):
return url
else:
raise LNException('Invalid URL of novel page')
# end if
# end if
try:
if args.suppress:
raise LNException()
# end if
answer = prompt([
{
'type': 'input',
'name': 'novel',
'message': 'Enter novel page url or query novel:',
'validate': lambda a: True
if a else 'Input should not be empty',
},
])
return answer['novel'].strip()
except Exception:
raise LNException('Novel page url or query was not given')
def get_crawlers_to_search(self) -> List[str]:
'''Returns user choice to search the choosen sites for a novel'''
links = self.app.crawler_links
if not links:
return []
# end if
args = get_args()
if args.suppress or 'sources' not in args:
return links
# end if
if args.sources:
links = [l for l in links if re.search(args.sources, l)]
# end if
if args.suppress or len(links) <= 1:
return links
# end if
answer = prompt([{
'type':
'checkbox',
'name':
'sites',
'message':
'Where to search?',
'choices': [{
'name': x,
'checked': True
} for x in sorted(links)],
}])
selected = answer['sites']
return selected if len(selected) > 0 else links
def force_replace_old(self):
args = get_args()
if args.force:
return True
elif args.ignore:
return False
# end if
if args.suppress:
return False
# end if
# answer = prompt([
# {
# 'type': 'confirm',
# 'name': 'force',
# 'message': 'Detected existing folder. Replace it?',
# 'default': False,
# },
# ])
# return answer['force']
answer = prompt([
{
'type': 'list',
'name': 'replace',
'message': 'What to do with existing folder?',
'choices': [
'Remove old folder and start fresh',
'Download remaining chapters only',
],
},
])
return answer['replace'].startswith('Remove')
def main_menu(self):
questions = [{
'type': 'list',
'name': 'questions',
'message': 'What do you want to do?',
'choices': ['Encrypt', 'Open config', 'Quit'],
'filter': lambda val: val.lower(),
}]
answer = prompt(questions, style=custom_style_fancy)
while answer['questions'] != 'quit':
if answer['questions'] == 'encrypt':
self.encrypt()
elif answer['questions'] == 'open config':
self.configure_public_key()
answer = prompt(questions, style=custom_style_fancy)
print('Bye Bye...')
def get_base_version() -> str:
"""
Show runtime options to the user.
Returns:
base_version (str): selected base version
"""
with loading_indicator("Loading base version list..."):
versions = get_supported_base_versions()
version_choices = [{
"value": base_version["version"],
"name": base_version["label"]
} for base_version in versions]
questions = [
{
"type": "list",
"name": "base_version",
"message": "Please select the bot runtime version:",
"choices": version_choices,
},
]
answers = prompt(questions)
base_version = answers["base_version"]
return base_version
def first_question_batch():
# ask for age and education
# RETURNS: DICT
questions = [{
'type':
'select',
'name':
'age',
'message':
'\nWhat is Your age?\n',
'choices': [
Separator(), '0 - 12', '12 - 18', '18 - 25', '25 - 45', '45+',
Separator()
]
}, {
'type':
'select',
'name':
'education',
'message':
'\nWhat is Your education level?\n',
'choices':
[Separator(), 'primary', 'high school', 'university',
Separator()]
}]
return prompt(questions)
def ask_dictstyle(**kwargs):
questions = [{
"type": "password",
"message": "Enter your git password",
"name": "password"
}]
return prompt(questions, style=custom_style_dope, **kwargs)
def interactive_kwargs_instanciation(self) -> Config:
"""
Instanciate dictionary of 'kwargs' arguments from an interactive prompt
:return: the 'kwargs' dictionary
"""
questions = [
x.get_pyinquirer_question() for x in self.get_hyperparameters()
]
conditions = self.get_conditions()
# applying conditions if any
for condition in conditions:
child = condition.get_child()
parent = condition.get_parent()
condition_type = condition.get_type()
values = condition.get_values()
question = List([x for x in questions if x.get('name') == child])\
.head_option()\
.get_or_else(None)
if question is not None and condition_type == 'IN':
question['name'] = parent
# Need to keep the double lambda because of python scope and closure stuff pb
question['when'] = (lambda parent_key, values_value: lambda x:
x.get(parent_key) in values_value)(parent,
values)
# Put the question with a 'when' value at the end
questions = sorted(questions,
key=lambda q: str(q.get('when') is not None))
# In case of time series forecast, add horizon and discount
if self.category == AlgorithmConfigurationCategory.TIME_SERIES_FORECAST:
questions.append({
'type': 'input',
'name': 'forecasting_horizon_steps',
'message': f'forecasting_horizon_steps must be at least 1',
'default': str(1),
'validate': IntegerValidator,
'filter': int
})
questions.append({
'type': 'input',
'name': 'forecasting_discount',
'message':
f'forecasting_discount must be between 0.0 (excluded) and 1.1 (included)',
'default': str(1.0),
'validate': FloatValidator,
'filter': float
})
# Prompting for answers
answers = questionary.prompt(questions)
config = self.instance_config()
for k, v in answers.items():
config.add_kwargs(k, v)
return config
def resume_session():
args = get_args()
output_path = args.resume or C.DEFAULT_OUTPUT_PATH
resumable_meta_data = []
for meta_file in Path(output_path).glob('**/' + C.META_FILE_NAME):
with open(meta_file, 'r', encoding="utf-8") as file:
data = json.load(file)
if 'session' in data and not data['session']['completed']:
resumable_meta_data.append(data)
# end if
# end with
# end for
metadata = None
if len(resumable_meta_data) == 1:
metadata = resumable_meta_data[0]
elif len(resumable_meta_data) > 1:
answer = prompt([{
'type':
'list',
'name':
'resume',
'message':
'Which one do you want to resume?',
'choices':
display.format_resume_choices(resumable_meta_data),
}])
index = int(answer['resume'].split('.')[0])
metadata = resumable_meta_data[index - 1]
# end if
if not metadata:
print('No unfinished download to resume\n')
display.app_complete()
return
# end if
app = load_session_from_metadata(metadata)
assert isinstance(app.crawler, Crawler)
print('Resuming', app.crawler.novel_title)
print('Output path:', app.output_path)
app.initialize()
app.crawler.initialize()
if app.can_do('login') and app.login_data:
logger.debug('Login with %s', app.login_data)
app.crawler.login(*list(app.login_data))
# end if
app.start_download()
app.bind_books()
app.compress_books()
app.destroy()
display.app_complete()
display_open_folder(app.output_path)
def ask_dictstyle(**kwargs):
questions = [{
'type': 'text',
'name': 'phone',
'message': "What's your phone number",
'validate': PhoneNumberValidator
}]
return prompt(questions, style=custom_style_dope, **kwargs)
def get_bot_uuid() -> str:
"""
Show bot options to the user, returns the selected bot ID.
Returns:
bot_uuid (str): ID of the selected bot.
"""
NEXT_PAGE = "__NEXT_PAGE__"
PREV_PAGE = "__PREV_PAGE__"
NONE = "__NONE__"
META_RESPONSES = [NEXT_PAGE, PREV_PAGE, NONE]
bot_uuid = NONE
page = 0
while bot_uuid in META_RESPONSES:
if bot_uuid == NEXT_PAGE:
page += 1
if bot_uuid == PREV_PAGE:
page -= 1
with loading_indicator("Loading bot list..."):
bots = get_bots(page)
bot_choices = list(map(get_bot_choice, bots.content))
page_count = math.ceil(bots.totalElements / bots.size)
if page < page_count - 1:
bot_choices.append({"name": "> Next page...", "value": NEXT_PAGE})
if page > 0:
bot_choices.append({
"name": "> Previous page...",
"value": PREV_PAGE
})
questions = [
{
"type":
"list",
"name":
"bot_id",
"message":
"Please select the bot you would like to implement:",
"choices": [
Choice(title=bot["name"], value=bot["value"]) if
(bot["value"] == NEXT_PAGE
or bot["value"] == PREV_PAGE) else Choice(
title=str(bot["name"] + " (" + bot["value"] + ")"),
value=bot["value"],
) for bot in bot_choices
],
},
]
answers = prompt(questions)
bot_uuid = answers["bot_id"]
return bot_uuid
def ask_dictstyle(**kwargs):
questions = [{
"type": "text",
"name": "phone",
"message": "What's your phone number",
"validate": PhoneNumberValidator,
}]
return prompt(questions, style=custom_style_dope, **kwargs)
def calculate_matrix(extracted_data):
"""Calculates matrix based on user input weights and extracted data.
Invokes benchmarking_calc.create_similarity_score_matrix() to create similarity matrix.
Invokes benchmarking_calc.create_customer_KPI_database() to create KPI database.
Lastly, display menu to user after calculation.
Args:
extracted_data (pandas df obj): Pandas dataframe containing data extracted from 71lbs database
"""
# Get user input for metric weights
metric_weights = {
'weight_vs': 1 / 6,
'weight_vpz': 1 / 6,
'weight_vpm': 1 / 6,
'weight_ws': 1 / 6,
'weight_wpz': 1 / 6,
'weight_wpm': 1 / 6
}
EVEN = questionary.confirm(
"Create a new similarity matrix with even metric weights?").ask()
if not EVEN:
print(
"\nPlease enter weight for each metric. Please make sure that sum of all 6 weights is approximately = 1"
)
metric_weights = prompt(menu_options.benchmarking_metric_weights,
style=blue)
metric_weights_sum = sum(metric_weights.values())
print("\nRecalibrating weights...")
for weight in metric_weights:
metric_weights[
weight] = metric_weights[weight] / metric_weights_sum
print("\nWeights:", metric_weights, "\n")
print("\nCreating similarity score matrix...")
model_id = utilities.get_timestamp()
benchmarking_calc.create_similarity_score_matrix(
extract_data=extracted_data,
input_weights=metric_weights,
model_id=model_id)
benchmarking_calc.create_customer_KPI_database(arg_df=extracted_data,
model_id=model_id)
while True:
choice_after = questionary.select(
"---Calculate similarity matrix---",
choices=[
'Calculate another similarity matrix', 'Go back to main menu',
'Exit'
],
style=blue).ask()
if choice_after == 'Calculate another similarity matrix':
calculate_matrix(extracted_data)
elif choice_after == 'Go back to main menu':
load_main_menu()
elif choice_after == 'Exit':
sys.exit()
def ask_dictstyle(**kwargs):
questions = [
{
'type': 'password',
'message': 'Enter your git password',
'name': 'password'
}
]
return prompt(questions, style=custom_style_dope, **kwargs)