def process():
config = Config()
server = JIRA(server=config.url, basic_auth=(config.login, config.password))
tab = tt.Texttable()
tab.header(['name','devd','time','fin','closed','ratio','sko','',''])
members = json.loads(config.team_members())
for member in members:
user = server.search_users(member)[0]
user_stat = get_full_stat(server, user)
tab.add_row(user_stat.values())
print(tab.draw())
def main():
args = get_args()
cfg = Config()
keys = [
["vectorizer", "batch_size"],
["vectorizer", "samples"],
["vectorizer", "vector_size"],
["vectorizer", "epochs"],
]
cfg.setup(keys)
v = Vectorize(
indir=args.indir,
batch_size=cfg.batch_size,
n_samples=cfg.samples,
epochs=cfg.epochs,
vector_size=cfg.vector_size,
)
v.run()
def get_config():
cfg = Config()
keys = [
["seq2vec", "gpu"],
["seq2vec", "load"],
["seq2vec", "epochs"],
["seq2vec", "lr"],
["seq2vec", "weight_decay"],
["seq2vec", "hidden_size"],
["seq2vec", "n_layers"],
["seq2vec", "bidirectional"],
["seq2vec", "batch_size"],
["seq2vec", "max_seqlen"],
["seq2vec", "train_samples"],
["seq2vec", "model_dir"],
["seq2vec", "predict_intervals"],
["seq2vec", "predict_samples"],
["visdom", "server"],
["visdom", "port"],
]
cfg.setup(keys)
return cfg
def process_for_user(name='g.frolov'):
config = Config()
server = JIRA(server=config.url, basic_auth=(config.login, config.password))
tab = tt.Texttable()
tab.header(
['name', 'devd', 'time', 'fin', 'closed', 'ratio', 'sko', '', ''])
member = name
user = server.search_users(member)[0]
periods = 8
period_len_days = 30
for period in xrange(periods):
user_stat = get_full_stat(server, user, during=period_len_days, since_days_back = period * period_len_days)
tab.add_row(user_stat.values())
print(tab.draw())
from datetime import timedelta
from fastapi import APIRouter, HTTPException
from starlette import status
from project.config import Config
from project.dal.retailer import RetailerRepository
from project.dtos.auth import Token, AuthData
from project.logger import Logger
from project.services.auth.auth_service import AuthService
config = Config()
logger = Logger()
router = APIRouter()
retailer_repository = RetailerRepository(config, logger)
auth_service = AuthService(config, logger, retailer_repository)
@router.post("/auth/token/", response_model=Token)
def login_for_access_token(auth_data: AuthData) -> Token:
retailer = auth_service.authenticate_retailer(email=auth_data.email,
password=auth_data.password)
if not retailer:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Incorrect username or password",
headers={"WWW-Authenticate": "Bearer"},
)
def config(self) -> Config:
return Config()
def config(self):
return Config("tests/config/project.cfg", "tests/config/project.spc")
def _load_invalid():
cfg = Config("tests/config/invalid.cfg",
"tests/config/project.spc")
from project.config import Config
from project.functionality import Example
# Random function to demonstrate we can pass _anything_ to 'make_config' inside 'Config'.
def uppercase(words):
return words.upper()
# We create our custom configuration without saving it.
Config(arg="hello world", func=uppercase)
# We initialize our Example object without passing the 'Config' object to it.
example = Example()
print(example.arg)
# >>> "HELLO WORLD"
def config() -> Config:
return Config()
from logging.config import fileConfig
from sqlalchemy import engine_from_config
from sqlalchemy import pool
from alembic import context
from project.config import Config
# this is the Alembic Config object, which provides
# access to the values within the .ini file in use.
config = context.config
app_config = Config()
host = app_config.get_config("DB_HOST")
port = app_config.get_config("DB_PORT")
user = app_config.get_config("DB_USER")
password = app_config.get_config("DB_PASSWORD")
database = app_config.get_config("DB_DATABASE")
database_url = f"mysql+mysqldb://{user}:{password}@{host}:{port}/{database}"
config.set_main_option("sqlalchemy.url", database_url)
# Interpret the config file for Python logging.
# This line sets up loggers basically.
fileConfig(config.config_file_name)
# add your model's MetaData object here
# for 'autogenerate' support
# from myapp import mymodel
# target_metadata = mymodel.Base.metadata