def setup_network_configurations(data):
print()
proceed = YesNo(prompt=_("Do you want to adjust network configurations? "
"(connection timeout) "),
default="n",
prompt_prefix="[yN] ").launch()
if not proceed:
return
print_wrapped(_(
"For meanings and significances of the following values, please "
"consult the module documentations."
))
print()
print("https://etm.1a23.studio/")
print()
if YesNo(prompt=_("Do you want to change timeout settings? "),
prompt_prefix="[yN] ", default="n").launch():
if data.data.get('request_kwargs') is None:
data.data['request_kwargs'] = {}
data.data['request_kwargs']['read_timeout'] = \
Numbers(prompt=_("read_timeout (in seconds): ")).launch()
data.data['request_kwargs']['connect_timeout'] = \
Numbers(prompt=_("connect_timeout (in seconds): ")).launch()
def AddAdvice():
clear()
Add = SlidePrompt([
Input("Marca del teléfono: ",
default="",
word_color=colors.foreground["yellow"]),
Bullet("Sistema operativo:",
choices=["Android", "IOS"],
margin=2,
background_on_switch=colors.background["white"],
word_on_switch=colors.foreground["black"]),
Numbers("RAM: ", word_color=colors.foreground["yellow"], type=int),
Input("CPU: ", default="", word_color=colors.foreground["yellow"]),
Numbers("Números de ventas en el año: ",
word_color=colors.foreground["yellow"],
type=int)
])
actualDevice = Add.launch()
deviceDic = {
'brand': actualDevice[0][1],
'os': actualDevice[1][1],
'ram': actualDevice[2][1],
'cpu': actualDevice[3][1],
'sales': actualDevice[4][1]
}
devices.append(deviceDic)
def setup_experimental_flags(data):
print_wrapped(
_("EWS does not require any configuration, you only need to scan "
"a QR code when you start up EH Forwarder Bot. It’s as simple as "
"that.\n"
"\n"
"We has provided some experimental features that you can use. "
"They are not required to be enabled for EWS to work. If you do not "
"want to enable these feature, just press ENTER, and you are good to go."
))
widget = YesNo(prompt=_("Do you want to config experimental features? "),
prompt_prefix="[yN] ")
if not widget.launch(default="n"):
return
for key, value in flags_settings.items():
default, cat, params, desc = value
if data.data['flags'].get(key) is not None:
default = data.data['flags'].get(key)
print()
print(key)
print_wrapped(desc)
if cat == 'bool':
prompt_prefix = '[Yn] ' if default else '[yN] '
ans = YesNo(prompt=f"{key}? ",
prompt_prefix=prompt_prefix) \
.launch(default='y' if default else 'n')
data.data['flags'][key] = ans
elif cat == 'int':
ans = Numbers(prompt=f"{key} [{default}]? ") \
.launch(default=default)
data.data['flags'][key] = ans
elif cat == 'choices':
ans = Bullet(prompt=f"{key}?", choices=params) \
.launch(default=default)
data.data['flags'][key] = ans
elif cat == 'multiple':
ans = Check(prompt=f"{key}?",
choices=params).launch(default=default)
data.data['flags'][key] = ans
elif cat == 'str':
ans = input(f"{key} [{default}]: ")
data.data['flags'][key] = ans or default
else:
print(_("Skipped."))
print(_("Saving configurations..."), end="", flush=True)
data.save()
print(_("OK"))
def setup_experimental_flags(data):
print()
print_wrapped(
_("EFMS has also provided some experimental features that you can use. "
"They are not required to be enabled for EFMS to work."))
widget = YesNo(prompt=_("Do you want to config experimental features? "),
prompt_prefix="[yN] ",
default="n")
if not widget.launch():
return
for key, value in flags_settings.items():
default, cat, params, desc = value
if data.data['flags'].get(key) is not None:
default = data.data['flags'].get(key)
if cat == 'bool':
prompt_prefix = '[Yn] ' if default else '[yN] '
print()
print(key)
print_wrapped(desc)
ans = YesNo(prompt=f"{key}? ",
prompt_prefix=prompt_prefix,
default='y' if default else 'n') \
.launch()
data.data['flags'][key] = ans
elif cat == 'int':
print()
print(key)
print_wrapped(desc)
ans = Numbers(prompt=f"{key} [{default}]? ", type=int) \
.launch(default=default)
data.data['flags'][key] = ans
elif cat == 'choices':
print()
print(key)
print_wrapped(desc)
ans = Bullet(prompt=f"{key}?", choices=params) \
.launch(default=default)
data.data['flags'][key] = ans
print(_("Saving configurations..."), end="", flush=True)
data.save()
print(_("OK"))
def setup_experimental_flags(data):
print()
widget = YesNo(prompt=_("Do you want to config experimental features? "),
prompt_prefix="[yN] ", default="n")
if not widget.launch():
return
for key, value in flags_settings.items():
default, cat, params, desc = value
if data.data['flags'].get(key) is not None:
default = data.data['flags'].get(key)
if cat == 'bool':
prompt_prefix = '[Yn] ' if default else '[yN] '
print()
print(key)
print_wrapped(desc)
ans = YesNo(prompt=f"{key}? ",
default='y' if default else 'n',
prompt_prefix=prompt_prefix) \
.launch()
data.data['flags'][key] = ans
elif cat == 'int':
print()
print(key)
print_wrapped(desc)
ans = Numbers(prompt=f"{key} [{default}]? ", type=int) \
.launch(default=default)
data.data['flags'][key] = ans
elif cat == 'choices':
try:
assert isinstance(params, list)
default = params.index(default)
except ValueError:
default = 0
print()
print(key)
print_wrapped(desc)
ans = Bullet(prompt=f"{key}?", choices=params) \
.launch(default=default)
data.data['flags'][key] = ans
def setup_network_configurations(data):
print()
proceed = YesNo(prompt=_("Do you want to adjust network configurations? "
"(connection timeout and proxy) "),
prompt_prefix="[yN] ").launch(default='n')
if not proceed:
return
print_wrapped(
_("For meanings and significances of the following values, please "
"consult the module documentations."))
print()
print("https://github.com/blueset/efb-telegram-master/")
print()
if YesNo(prompt=_("Do you want to change timeout settings? "),
prompt_prefix="[yN] ").launch(default='n'):
if data.data.get('request_kwargs') is None:
data.data['request_kwargs'] = {}
data.data['request_kwargs']['read_timeout'] = \
Numbers(prompt=_("read_timeout (in seconds): ")).launch()
data.data['request_kwargs']['connect_timeout'] = \
Numbers(prompt=_("connect_timeout (in seconds): ")).launch()
if YesNo(prompt=_("Do you want to run ETM behind a proxy? "),
prompt_prefix="[yN] ").launch(default='n'):
if data.data.get('request_kwargs') is None:
data.data['request_kwargs'] = {}
proxy_type = Bullet(prompt=_("Select proxy type"),
choices=['http', 'socks5']).launch()
host = input(_("Proxy host (domain/IP): "))
port = input(_("Proxy port: "))
username = None
password = None
if YesNo(prompt=_("Does it require authentication?"),
prompt_prefix="[yN] ").launch(default='n'):
username = input(_("Username: "******"Password: "******"http://{host}:{port}/"
if username is not None and password is not None:
data.data['request_kwargs']['username'] = username
data.data['request_kwargs']['password'] = password
elif proxy_type == 'socks5':
try:
import socks
except ModuleNotFoundError as e:
print_wrapped(
_("You have not installed required extra package "
"to use SOCKS5 proxy, please install with the "
"following command:"))
print()
print("pip install python-telegram-bot[socks]")
print()
raise e
data.data['request_kwargs'][
'proxy_url'] = f"socks5://{host}:{port}"
if username is not None and password is not None:
data.data['request_kwargs']['urllib3_proxy_kwargs'] = {
"username": username,
"password": password
}
from bullet import SlidePrompt, Bullet, Numbers
DISTRIBUTIONS = [
'Uniform',
'Normal',
]
cli = SlidePrompt(
[
Bullet(prompt="Choose the distribution(Y)", choices=DISTRIBUTIONS),
Numbers(prompt="Distribution mean(μ) / Starting point(a): ", type=float),
Numbers(prompt="Distribution standard deviation(σ) / End point(b): ", type=float),
Numbers(prompt="Delivery time(l): ", type=float),
Numbers(prompt="Fixed cost of the order(A): ", type=float),
Numbers(prompt="Unitary item cost(c): ", type=float),
Numbers(prompt="Storage cost per item per timestep(h): ", type=float),
Numbers(prompt="Out of stock cost per item(p'): ", type=float),
Numbers(prompt="Stopping rate of change(ε): ", type=float),
]
)
def get_args_from_cli(cli_obj):
args = cli_obj.launch()
return dict(
distribution=args[0][1],
mean=args[1][1],
std_deviation=args[2][1],
delivery_time=args[3][1],
from bullet import colors
cli = SlidePrompt(
[
YesNo("Are you a student? ",
word_color = colors.foreground["yellow"]),
YesNo("Are you a good student? ",
default = 'y',
word_color = colors.foreground["yellow"]),
Input("Who are you? ",
default = "Batman",
word_color = colors.foreground["yellow"]),
Input("Really? ",
word_color = colors.foreground["yellow"]),
Numbers("How old are you? ",
word_color = colors.foreground["yellow"],
type = int),
Bullet("What is your favorite programming language? ",
choices = ["C++", "Python", "Javascript", "Not here!"],
bullet = " >",
margin = 2,
bullet_color = colors.bright(colors.foreground["cyan"]),
background_color = colors.background["black"],
background_on_switch = colors.background["black"],
word_color = colors.foreground["white"],
word_on_switch = colors.foreground["white"]
),
Check("What food do you like? ",
choices = ["🍣 Sushi",
"🍜 Ramen",
"🌭 Hotdogs",
# for every line, take the points and store them
nodelist = []
for i in range(start_index, dimension + start_index - 1):
x, y = lines[i].strip().split()[1:]
nodelist.append([float(x), float(y)])
# calculate the euclidean distances between every point.
# this creates a matrix of distances between every pair
# of points. now we are ready to calculate the optimal path.
dists = euclidean_distances(nodelist)
print()
print("> Starting execution for file: {}".format(name))
print("> Matrix dimensions: {}\n".format(dists.shape))
cli_n = Numbers(prompt="> Select number of iterations: ")
iterations = cli_n.launch()
print()
print(
"> Calculating solution. \nProblems over 500 cities can take several minutes...\n"
)
start_time = time.time()
solution = solve_float_matrix(dists, runs=iterations)
end_time = time.time() - start_time
solution_pairs = sliding_window_view(solution, 2)
total_length = np.sum([dists[pair[0], pair[1]] for pair in solution_pairs])
training_dir, _, base_pipeline_config_path = load_model_paths(
model2resume, model2download, alt_model_name)
checkpoints = [
ckpt.replace('.meta', '') for ckpt in listdir(training_dir)
if '.meta' in ckpt
]
ckpt_prefix = Bullet(prompt="Choose checkpoint to resume from:",
choices=['[ last checkpoint ]'] + checkpoints,
**ocean_style_dolphin).launch()
# the function pipeline.set_training_config below figures this out on its own.
ckpt_prefix = None if ckpt_prefix == '[ last checkpoint ]' else ckpt_prefix
num_steps = Numbers(prompt="\nPick a number of training epochs: ",
type=int,
indent=alignment['indent']).launch()
num_eval_steps = Numbers(prompt="\nEnter max number of evaluations: ",
type=int,
indent=alignment['indent']).launch()
batch_size = Numbers(prompt="\nEnter desired batch size: ",
type=int,
indent=alignment['indent']).launch()
training_config_file_path = join(training_dir, 'training.config')
print('\n⇒ writing training config to {}'.format(training_config_file_path))
# defaults :: current input dataset converted to tfrecords
test_record_fname = './input/tf_records/test.record'
from bullet import Bullet, Prompt, Check, Input, YesNo, Numbers
from bullet import styles
from bullet import colors
cli = Prompt(
[
YesNo("Are you a student? "),
Input("Who are you? "),
Numbers("How old are you? "),
Bullet("What is your favorite programming language? ",
choices = ["C++", "Python", "Javascript", "Not here!"]),
],
spacing = 1,
separator = "-",
separator_color = colors.foreground["cyan"]
)
result = cli.launch()
cli.summarize()
from bullet import Numbers
prompt = Numbers("How old are you? ", type=int)
prompt.launch()