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import json
import os
from datetime import date, timedelta
def list_files(startpath):
for root, dirs, files in os.walk(startpath):
level = root.replace(startpath, "").count(os.sep)
indent = " " * 4 * (level)
print("{}{}/".format(indent, os.path.basename(root)))
subindent = " " * 4 * (level + 1)
for f in files:
print("{}{}".format(subindent, f))
def load_configs(configs_file_path):
"""Load a configuration file containing keys and secrets and return them as a dictionary.
Args:
config_file_path (str): The path to the configuration file to load.
Returns:
dict: A dictionary containing the keys and secrets loaded from
"""
with open(configs_file_path) as f:
configs = json.load(f)
return configs
def wilson_score_interval(obs, conf_level=0.95):
import math
from scipy import stats
"""
Calculates the Wilson score interval for a given list of observations.
Args:
obs (list): A list of observations (0s and 1s).
conf_level (float): The desired confidence level (default: 0.95).
Returns:
tuple: A tuple with the lower and upper bounds of the confidence interval.
"""
n = len(obs)
if n == 0:
return None
z = stats.norm.ppf(1 - (1 - conf_level) / 2)
phat = sum(obs) / n
term = z * math.sqrt(phat * (1 - phat) / n + z * z / (4 * n * n))
lower_bound = (phat + z * z / (2 * n) - term) / (1 + z * z / n)
upper_bound = (phat + z * z / (2 * n) + term) / (1 + z * z / n)
return round(lower_bound, 2), round(upper_bound, 2)
def get_yesterday_date():
today = date.today()
yesterday = today - timedelta(days=1)
return yesterday
def load_data_from_file(filename):
"""
Loads data from a file in JSON format if the file exists.
Args:
filename (str): The name of the file to load.
Returns:
The loaded data, or None if the file doesn't exist.
"""
if os.path.isfile(filename):
with open(filename, "r") as f:
data = json.load(f)
return data
else:
return None
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