我也需要它，但是，没有合适的代码用于此目的。我自己修改一个。享受！可能有人也需要它。
以下代码修改自 libcloud/contrib/scrape-ec2-prices.py
这个程序将生成一个关于可用实例类型的字典
#!/usr/bin/env python
import 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)
def scrape_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 not in 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']
if str(price).lower() == 'n/a':
# Price not available
continue
if not 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 = 0
else:
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
def update_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)
with open(pricing_file_path, 'w') as fp:
fp.write(content)
def sort_nested_dict(value):
"""
Recursively sort a nested dict.
"""
result = OrderedDict()
for key, value in sorted(value.items(), key=sort_key_by_numeric_other):
if isinstance(value, (dict, OrderedDict)):
result[key] = sort_nested_dict(value)
else:
result[key] = value
return result
def sort_key_by_numeric_other(key_value):
"""
Split key into numeric, alpha and other part and sort accordingly.
"""
return tuple((
int(numeric) if numeric else None,
INSTANCE_SIZES.index(alpha) if alpha in INSTANCE_SIZES else alpha,
other
) for (numeric, alpha, other) in RE_NUMERIC_OTHER.findall(key_value[0]))
def main():
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()