简体   繁体   English

boto3 aws api - 列出可用的实例类型

[英]boto3 aws api - Listing available instance types

Instance types: (t2.micro, t2.small, c4.large...) those listed here: http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-types.html实例类型:(t2.micro、t2.small、c4.large...)此处列出的那些: http ://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-types.html

I want to access a list of these through boto3.我想通过 boto3 访问这些列表。 something like:就像是:

conn.get_all_instance_types()

or even甚至

conn.describe_instance_types()['InstanceTypes'][0]['Name']

which everything seems to look like in this weird api.在这个奇怪的 api 中,一切看起来都像。

I've looked through the docs for client and ServiceResource, but i can't find anything that seems to come close.我已经浏览了客户端和 ServiceResource 的文档,但我找不到任何似乎接近的内容。 I haven't even found a hacky solution that lists something else that happen to represent all the instance types.我什至还没有找到一个 hacky 解决方案,它列出了恰好代表所有实例类型的其他东西。

Anyone with more experience of boto3?有人对boto3有更多经验吗?

There's now boto3.client('ec2').describe_instance_types() and corresponding aws-cli command aws ec2 describe-instance-types :现在有boto3.client('ec2').describe_instance_types()和相应的 aws-cli 命令aws ec2 describe-instance-types

'''EC2 describe_instance_types usage example'''

import boto3

def ec2_instance_types(region_name):
    '''Yield all available EC2 instance types in region <region_name>'''
    ec2 = boto3.client('ec2', region_name=region_name)
    describe_args = {}
    while True:
        describe_result = ec2.describe_instance_types(**describe_args)
        yield from [i['InstanceType'] for i in describe_result['InstanceTypes']]
        if 'NextToken' not in 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.预计大约 3 秒的运行时间。

The EC2 API does not provide a way to get a list of all EC2 instance types. EC2 API 不提供获取所有 EC2 实例类型列表的方法。 I wish it did.我希望它做到了。 Some people have cobbled together their own lists of valid types by scraping sites like this but for now that is the only way.有些人通过刮样的网站拼凑自己的有效类型列表连接起来这个,但现在这是唯一的办法。

This information can be retrieved in the JSON provided by the recently-announced AWS Price List API .可以在最近发布的AWS Price List API提供的 JSON 中检索此信息。 As a simple example using the Python requests module:作为使用 Python requests模块的简单示例:

#!/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 Instance
        continue
    uniq.add(data['attributes']['instanceType'])
for itype in sorted(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.请注意,这可能需要一段时间......截至今天,当前的 EC2 Offers JSON 文件 ( https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonEC2/current/index以.json )是173MB,所以需要一段时间都以检索和分析。 The current result is 99 distinct instance types.当前结果是 99 个不同的实例类型。

Try this尝试这个

'''
Created on Mar 22, 2017

@author: ijessop
'''

import boto3
import urllib2
from bs4 import BeautifulSoup as soup

class EnumEc2():

    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 = {}


    def getInstanceTypes(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 = True
        for 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 is True:
                header_row = td_strs
                for head in header_row:
                    self.max_col_width.update({head:(len(head) + 2)})
                first_row = False

            else:
                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 order
            if 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)

I need it too, however, there are no suitable codes for this purpose.我也需要它,但是,没有适合此目的的代码。 I modify one by myself.我自己修改了一个。 Enjoy!享受! May someone need it also.可能有人也需要它。

Following code is modified from libcloud/contrib/scrape-ec2-prices.py And this program will generate a dict about available instance types以下代码是从 libcloud/contrib/scrape-ec2-prices.py 修改而来的,这个程序会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()

声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM