Boto3 Aws Api - Listing Available Instance Types
Solution 1:
There's now boto3.client('ec2').describe_instance_types()
and corresponding aws-cli command aws ec2 describe-instance-types
:
'''EC2 describe_instance_types usage example'''import boto3
defec2_instance_types(region_name):
'''Yield all available EC2 instance types in region <region_name>'''
ec2 = boto3.client('ec2', region_name=region_name)
describe_args = {}
whileTrue:
describe_result = ec2.describe_instance_types(**describe_args)
yieldfrom [i['InstanceType'] for i in describe_result['InstanceTypes']]
if'NextToken'notin describe_result:
break
describe_args['NextToken'] = describe_result['NextToken']
for ec2_type in ec2_instance_types('us-east-1'):
print(ec2_type)
Expect about 3s of running time.
Solution 2:
The EC2 API does not provide a way to get a list of all EC2 instance types. I wish it did. Some people have cobbled together their own lists of valid types by scraping sites like this but for now that is the only way.
Solution 3:
This information can be retrieved in the JSON provided by the recently-announced AWS Price List API. As a simple example using the Python requests
module:
#!/usr/bin/env python# List EC2 Instance Types# see: https://aws.amazon.com/blogs/aws/new-aws-price-list-api/import requests
offers = requests.get(
'https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/index.json'
)
ec2_offer_path = offers.json()['offers']['AmazonEC2']['currentVersionUrl']
ec2offer = requests.get(
'https://pricing.us-east-1.amazonaws.com%s' % ec2_offer_path
).json()
uniq = set()
for sku, data in ec2offer['products'].items():
if data['productFamily'] != 'Compute Instance':
# skip anything that's not an EC2 Instancecontinue
uniq.add(data['attributes']['instanceType'])
for itype insorted(uniq):
print(itype)
Note that this might take a while... as of today, the current EC2 Offers JSON file ( https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonEC2/current/index.json ) is 173MB, so it takes a while both to retrieve and to parse. The current result is 99 distinct instance types.
Solution 4:
Try this
'''
Created on Mar 22, 2017
@author: ijessop
'''import boto3
import urllib2
from bs4 import BeautifulSoup as soup
classEnumEc2():
def__init__(self, region):
self.client = boto3.client(
'ec2',
aws_access_key_id = 'YOUR_KEY' ,
aws_secret_access_key='YOUR_SECRET',
region_name = region
)
self.instance_types = None
self.instance_table_headers = None
self.max_col_width = {}
defgetInstanceTypes(self):
mp = soup(urllib2.urlopen('https://aws.amazon.com/ec2/instance-types').read(),'html.parser')
imx = mp.find(id="instance-type-matrix")
trs = imx.parent.parent.parent.next_sibling.next_sibling.find_all('tr')
rt = []
first_row = Truefor trow in trs:
td_strs = []
for td in trow.find_all("td"):
td_nested = []
for s in td.strings:
s.strip()
td_nested.append(s)
td_all = " ".join(td_nested).strip()
td_strs.append(td_all)
if first_row isTrue:
header_row = td_strs
for head in header_row:
self.max_col_width.update({head:(len(head) + 2)})
first_row = Falseelse:
dr = dict(zip(header_row,td_strs))
for k,v in dr.items():
cw = len(v)
if k in self.max_col_width.keys():
if cw >= self.max_col_width.get(k):
self.max_col_width.update({k:(cw +2)})
else:
self.max_col_width.update({k:cw})
rt.append(dr)
self.instance_table_headers = header_row
self.instance_types = rt
if __name__ == '__main__':
myen = EnumEc2('us-west-2')
myen.getInstanceTypes()
heads_I_want_to_see = ['Instance Type', u'vCPU', u'Memory (GiB)', u'Storage (GB)','Physical Processor', u'Clock Speed (GHz)']
out_str ="|"for h in heads_I_want_to_see:
out_str = "%s%s|" % (out_str,h.ljust(myen.max_col_width.get(h)))
print"%s" % "-" * len(out_str)
print"%s" % out_str
print"%s" % "-" * len(out_str)
for i in myen.instance_types:
out_str ="|"for k in myen.instance_table_headers: # to preserve the table column orderif k in heads_I_want_to_see:
out_str = "%s%s|" % (out_str, i.get(k).ljust(myen.max_col_width.get(k)))
print"%s" % out_str
print"%s" % "-" * len(out_str)
Solution 5:
I need it too, however, there are no suitable codes for this purpose. I modify one by myself. Enjoy! May someone need it also.
Following code is modified from libcloud/contrib/scrape-ec2-prices.py And this program will generate a dict about available instance types
#!/usr/bin/env pythonimport os
import re
import json
import time
from collections import defaultdict, OrderedDict
import requests
import demjson
LINUX_PRICING_URLS = [
# Deprecated instances (JSON format)'https://aws.amazon.com/ec2/pricing/json/linux-od.json',
# Previous generation instances (JavaScript file)'https://a0.awsstatic.com/pricing/1/ec2/previous-generation/linux-od.min.js',
# New generation instances (JavaScript file)'https://a0.awsstatic.com/pricing/1/ec2/linux-od.min.js'
]
EC2_REGIONS = [
'us-east-1',
'us-east-2',
'us-west-1',
'us-west-2',
'us-gov-west-1',
'eu-west-1',
'eu-west-2',
'eu-central-1',
'ca-central-1',
'ap-southeast-1',
'ap-southeast-2',
'ap-northeast-1',
'ap-northeast-2',
'ap-south-1',
'sa-east-1',
'cn-north-1',
]
INSTANCE_SIZES = [
'micro',
'small',
'medium',
'large',
'xlarge',
'x-large',
'extra-large'
]
RE_NUMERIC_OTHER = re.compile(r'(?:([0-9]+)|([-A-Z_a-z]+)|([^-0-9A-Z_a-z]+))')
PRICING_FILE_PATH = './price.json'
PRICING_FILE_PATH = os.path.abspath(PRICING_FILE_PATH)
defscrape_ec2_pricing():
result = {}
result['regions'] = []
result['prices'] = defaultdict(OrderedDict)
result['models'] = defaultdict(OrderedDict)
for url in LINUX_PRICING_URLS:
response = requests.get(url)
if re.match('.*?\.json$', url):
data = response.json()
elif re.match('.*?\.js$', url):
data = response.content
match = re.match('^.*callback\((.*?)\);?$', data,
re.MULTILINE | re.DOTALL)
data = match.group(1)
# demjson supports non-strict mode and can parse unquoted objects
data = demjson.decode(data)
regions = data['config']['regions']
for region_data in regions:
region_name = region_data['region']
if region_name notin result['regions']:
result['regions'].append(region_name)
libcloud_region_name = region_name
instance_types = region_data['instanceTypes']
for instance_type in instance_types:
sizes = instance_type['sizes']
for size in sizes:
price = size['valueColumns'][0]['prices']['USD']
ifstr(price).lower() == 'n/a':
# Price not availablecontinueifnot result['models'][libcloud_region_name].has_key(size['size']):
result['models'][libcloud_region_name][size['size']] = {}
result['models'][libcloud_region_name][size['size']]['CPU'] = int(size['vCPU'])
if size['ECU'] == 'variable':
ecu = 0else:
ecu = float(size['ECU'])
result['models'][libcloud_region_name][size['size']]['ECU'] = ecu
result['models'][libcloud_region_name][size['size']]['memoryGiB'] = float(size['memoryGiB'])
result['models'][libcloud_region_name][size['size']]['storageGB'] = size['storageGB']
result['prices'][libcloud_region_name][size['size']] = float(price)
return result
defupdate_pricing_file(pricing_file_path, pricing_data):
## with open(pricing_file_path, 'r') as fp:# content = fp.read()
data = {'compute': {}} # json.loads(content)
data['updated'] = int(time.time())
data['compute'].update(pricing_data)
# Always sort the pricing info
data = sort_nested_dict(data)
content = json.dumps(data, indent=4)
lines = content.splitlines()
lines = [line.rstrip() for line in lines]
content = '\n'.join(lines)
withopen(pricing_file_path, 'w') as fp:
fp.write(content)
defsort_nested_dict(value):
"""
Recursively sort a nested dict.
"""
result = OrderedDict()
for key, value insorted(value.items(), key=sort_key_by_numeric_other):
ifisinstance(value, (dict, OrderedDict)):
result[key] = sort_nested_dict(value)
else:
result[key] = value
return result
defsort_key_by_numeric_other(key_value):
"""
Split key into numeric, alpha and other part and sort accordingly.
"""returntuple((
int(numeric) if numeric elseNone,
INSTANCE_SIZES.index(alpha) if alpha in INSTANCE_SIZES else alpha,
other
) for (numeric, alpha, other) in RE_NUMERIC_OTHER.findall(key_value[0]))
defmain():
print('Scraping EC2 pricing data')
pricing_data = scrape_ec2_pricing()
update_pricing_file(pricing_file_path=PRICING_FILE_PATH,
pricing_data=pricing_data)
print('Pricing data updated')
if __name__ == '__main__':
main()
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