def test_no_params():
with pytest.raises(ValueError):
awscosts.EC2("t2.micro")
with pytest.raises(ValueError):
awscosts.EC2("t2.micro", ms_per_req=200)
with pytest.raises(ValueError):
awscosts.EC2("t2.micro", MB_per_req=200)
def get_ec2_cost(df: pd.DataFrame, flavor, **kwargs):
""" Given a Dataframe with requests per time unit, calculates the EC2 costs
for each row.
Args:
df (pandas.Dataframe): Dataframe with requests for each time unit per
row.
flavor (str): A valid EC2 instance flavor name (e.g. 'm4.large').
**kwargs: Keyword arguments to the awscosts.EC2 object (see awscosts
package)
Returns:
The same DataFrame with two new columns:
'FLAVOR': Cost of this period (row) to process the given requests.
'FLAVOR_instances': Number of instances needed to process the
requests in that row. FLAVOR is the actual name of the flavor.
'FLAVOR_sum': Accumulative cost of this and the previous rows.
"""
myec2 = awscosts.EC2(instance_type=flavor, **kwargs)
df[flavor] = df.apply(lambda x: myec2.get_cost_and_num_instances(
3600, reqs=x['requests'])[0],
axis=1)
df[flavor + '_instances'] = df.apply(
lambda x: myec2.get_num_instances(reqs=x['requests'] / 3600), axis=1)
df[flavor + '_sum'] = df[flavor].cumsum()
df = df.round({flavor: 2, flavor + '_sum': 2})
return df
def generate_costs_in_month(requests_range,
flavors,
memory,
time,
throughput_ratio=1):
"""Generates EC2 and Lambda costs in a month by a list of requests per
second.
Args:
requests_range (:obj:`list` of :obj:`int`): list of reqs/s.
flavors (:obj:`list` of :obj:`str`): list of valid EC2 flavors.
memory
time (int): duration (in milliseconds) of the Lambda request.
throughput_ratio (int, optional): 1
Returns:
Cost dict:
- 'lambda':
- REQS/S_1: COST_IN_DOLLARS
- REQS/S_2: COST_IN_DOLLARS
...
- REQS/S_n: COST_IN_DOLLARS
- FLAVOR_1:
- REQS/S_1: COST_IN_DOLLARS
...
...
"""
cost = dict()
SECONDS_IN_A_MONTH = 3600 * 24 * 30
# generate costs for EC2 instances:
for flavor in flavors:
myec2 = awscosts.EC2(
flavor,
MB_per_req=memory,
ms_per_req=time,
throughput_ratio=throughput_ratio,
)
cost[flavor] = dict()
for reqs_per_second in requests_range:
cost[flavor][reqs_per_second] = \
myec2.get_cost_per_second(reqs_per_second) * SECONDS_IN_A_MONTH
# generate costs for Lambda:
mylambda = awscosts.Lambda(
MB_per_req=memory,
ms_per_req=time,
)
cost['lambda'] = dict()
for reqs_per_second in requests_range:
requests_per_month = reqs_per_second * SECONDS_IN_A_MONTH
cost['lambda'][reqs_per_second] = \
mylambda.get_cost(requests_per_month, reset_free_tier=True)
return cost
def test_scalability():
max_reqs = 200
t2micro = awscosts.EC2('t2.micro', max_reqs_per_second=max_reqs)
assert t2micro.get_num_instances(max_reqs + 1) == 2
def test_max_reqs():
t2micro = awscosts.EC2('t2.micro', ms_per_req=200, MB_per_req=1024)
assert t2micro.max_reqs_per_second == 5
def test_init_1():
t2micro = awscosts.EC2('t2.micro', max_reqs_per_second=200)
assert t2micro.max_reqs_per_second == 200