elena-roff

import hashlib

def get_obj_key(obj: Type) -> str:
    """ Creates and returns a unique object id."""
    obj_key = '+'.join(
        [
          obj.attr1, str(obj.num_attr1), obj.attr2, ...
        ])
    return hashlib.md5(obj_key.encode('utf8')).hexdigest()

elena-roff

def api_get_data() -> List[Mapping]:
    """ Gets data from the API. """
    url = "{}/v1/booking".format(os.environ['CT_BOOKING_API_URI'])

    params: Dict = {
        ...
        'limit': 1000,
        'offset': 0,
        }

elena-roff

import requests
from custom_module import api_get_data

uri = 'http://<.....>'


def fail(*args, **kwargs):
    raise requests.exceptions.RequestException()

elena-roff

.PHONY:	test lint

lint:
	TEST=1 pylint <folder> --rcfile=pylint.cfg
	flake8

test:
	coverage run --rcfile=setup.cfg --source=<folder> -m pytest --ignore=<folder to ignore>
	coverage report --rcfile=setup.cfg

elena-roff

[flake8]
max-line-length = 100

[coverage:run]
branch=True
source=<folder to run coverage on>
omit=
    */<folder to omit>/*

[coverage:report]

elena-roff

[MASTER]

# run on all available cores
jobs=0

# Specify a configuration file.
#rcfile=

# Python code to execute, usually for sys.path manipulation such as
# pygtk.require().

elena-roff

from pymongo import MongoClient

def get_db():
    # For local use
    from pymongo import MongoClient
    # if your db is run locally
    client = MongoClient(host='localhost', port=27017)
    print(client.list_database_names())
    return client.warehouse

elena-roff

(pd.pivot_table(
  direct_roundtrip_flights.query('departure_and_destination in @most_common_dep_dest_pairs'),
  index=['departure_and_destination', 'type_of_flight', 'departure_time_interval', 'departure_day_of_week'],
  values='booking_id',
  aggfunc={'booking_id': np.count_nonzero})
  .rename(columns={'booking_id': 'n'})
  .sort_values('n', ascending=False)
  )

elena-roff

label_size = 30
plt.rcParams['xtick.labelsize'] = label_size
plt.figure(figsize=(100, 250))


# put on one date plain
df['departure_time_utc'] = df['departure_time_utc'].apply(lambda dt: dt.replace(year=2018, month=11, day=20))

# group by category
grouped = df.groupby('departure_and_destination')

elena-roff

import os
import unittest
import shutil

from setuptools import setup
from setuptools import Command
from <module> import __version__

try:
    import coverage