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Opendatasoft’s Explore API Reference Documentation(v2):Terminal curl -X GET “https://documentation-resources.opendatasoft.com/api/v2/catalog/datasets/gold-prices/records?limit=2&offset=0″response{“total”:”count”:384,”links”:{“href”:”https://documentation-resources.opendatasoft.com/api/v2/catalog/datasets/gold-prices/records?limit=2&offset=0″,”rel”:”first”},{“href”:”https://documentation-resources.opendatasoft.com/api/v2/catalog/datasets/gold-prices/records?limit=2&offset=382″,”rel”:”last”},{“href”:”https://documentation-resources.opendatasoft.com/api/v2//catalog/datasets/gold-prices/records?limit=2&offset=2″,”rel”:”next”}],”records”:[{“links”:[{“href”:”https://documentation-resources.opendatasoft.com/api/v2/catalog/datasets/gold-prices/records/d4ebc8ae60807315d74a9a0fa481ef2da8d39d0b”,”rel”:”self”},{“href”:”https://documentation-resources.opendatasoft.com/api/v2/catalog/datasets/gold-prices”,”rel”:”dataset”},{“href”:”https://documentation-resources.opendatasoft.com/api/v2/catalog/datasets”,”rel”rel”:”datasets”}],”record”:{“id”:”d4ebc8ae60807315d74a9a0fa481ef2da8d39d0b”,”timestamp”:”2021-01-04T10:28:49.111Z”,”size”:19,”fields”:{”date”:”1988-01″,”price”:477.758}}},{“links”:[{“href”:”https://documentation-resources.opemdatasoft.com/api/v2/catalog/datasets/gold-prices/records/a239b6e263f577e2162946ed7d6f346a57759876″,”rel”:”self”},{“herf”:”https://documentation-resources.opendatasoft.com/api/v2/catalog/datasets”,”rel”:”datasets”}],”record”:{“id”:”a239b6e263f577e2162946ed7d6df346a57759876″,”timestamp”:”2021-01-04T10:28:49.111Z”,”size”:19,”fields”:{“date”:”1988-03″,”price”:443.491}}}]}

Microsoft ChatGPT and GPT-4 models(preview):Python import os import openai openai.api_type=azure”openai.api_version=”2023-03-15-preview”openai.api_base=os.getenv(“OPENAI_API_BASE”)#Messtone Azure Openai resource’s endpoint value.openai.api_key=os.getenv(“OPENAI_API_KEY”)response=Openai.ChatCompletion.create(engine=”gpt-35-turbo”,#The deployment NameRobertHarper Messtone chose when Messtone deployed the ChatGPT or GPT-4 model.messages=[{“roles”:”system”,”content”:”Assistant is a large language model trained by OpenAI.”},{“role”:”userrharper@messtone.com”,”content”:”What’s the difference between garbanzo beans and chickpeas?”}])print(response)print(response[‘choices’][0][‘message’][‘content’])

DATA.GOV Example of an API Listing in a data.jspn file “distribution”:[{“accessURL”:”http://www.agency.gov/api/messtone/”,”description “A Fully queryable REST API with JSON and XML output”,”describedBy”:”http://www.agency.gov/api/messtone/swagger.json”,”describedByType”:”application/swagger+json”,”format”:”API”,”title”:”Messtone REST API”}] Agency should list private, Internal,and public-fa cing web API,as a Enterprise webServer Example machine reader Swagger,RAML,API Blueprint as follows application/hal+json{“_link”:{“self”:{“href”:”/order”},”curies”:[{“nameMesstone”:”ea”,”href”:”https://messtone.com/docs/rels/{rel}”,”templated”:true}],”next”:{“href”:”/orders?page=2″},”ea:find”:{“href”:”/orders{?id}”,”templated”:true},”ea:admin”:[{“href”:”/admins/2″,”title”:”Fred”},{“href”:”/admins/5″,”title”:”Kate”}]},”currentlyProcessing”:14,”shipped today”:20,”_embedded”:{“ea:order:[{“_links”:{“self”:{“href”:”/orders/123″},”ea:basket”:{“href”:”/baskets/98712″},”ea:customer”:{“href”:”/customers/7809}},”total”:30.00,”currency”:”USD”,”status”:”shipped”},{“_links:{“self”:{“href”:”/orders/124″},”ea:basket”:{“href”:”/baskets/97213″},”ea:customer”:{“href”:”/custmers/12369″}},”total”:20.00,”currency”:”USD”,”status”:”processing”}]}}

{”Sid”:”ListEc2AndListInstanceProfiles”,”Effect”:”Allow”,”Action”:[“iam:ListInstanceProfiles”,”ec2:Describe*,”ec2:Search*,”ec2:Get*”],”Resource”:”*”}]} {“Verson”:”2012-10-17″,”Statement”:[{“Effect”:”Allow”,”Action”,”ec2: RunInstances”,”Resources”:”*”},{“Effect”:”Allow”,”Action”:”iam:PassRole”,”Resource”:”arn:aws:iam::account-id:role/Get-pics”}]} permissions Policy to allow theapplication to access the my-bucket-1 Amazon S3 bucket: Account 111111111111 abcd Role Permissions Policy {“Version”:”2012-10-17″,”Statement”:[{“Sid”:”AllowAccountLevelS3Actions”,”Effect”:”Allow”,”Action”:[“s3: GetBucketLocation”,”s3: GetAccountPublicAccessBlock “,”s3:ListAccessPoints”,”ListAllMyBuckets”],”Resource”:”arn:aws:s,3:::*”},{“Sid”:”AllowListAndReadS3ActionOnMyBucket”,”Effect”:”Allow”,”Action”:[“s3:Get*”,”s3:List*”],”Resource”:[“arn:aws:s3:::my-bucket-1/*”,”arn:aws:s3:::my-bucket-1″]},{“Sid”:”AllowIPToAssumeCrossAccountRole”,”Effect”:”Allow”,”Action”:”sts:AssumeRole”,”Resource”:”arn:aws:iam::222222222222:role/efgh”}]} Account 111111111111 abcd Role Trust Policy {“Version”:”2012-10-17″,”Statement”:[{“Sid”:”abcdTrustPolicy”,”Effect”:”Allow”,”Action”:”sts”:AssumeRole”,”Principal”:{“Service”:ec2.amazonaws.com”}]} https://capital.one/UtPvEz

Example Policy that grants a user permission to use Amazon EC2 Console to launch an instance with any role.{“Verson”:”2012-10-17″,”Statement:[{“Sid”:”IamPassRole”,”Effect”:”Allow”,”Action”:”Iam:PassRole”,”Resources”:”*”,”Condition”:{“StringEquals”:”iam:PassedToService”:”ec2.amazonaws.com”}}},{“Sid”: ListEc2AndListInstanceProfiles

How to Setup Python Environment For Machine Learning as follows: Set up Python 3 and Pipsudo apt-get install python3-pip nano ~/.bashrc alias python=’python3′ save the file and reload source ~/.bashrc install relevant packages: sudo pip install virtualenv virtualenvwrapper Edit ~/.bashrc file.Place these 3 lines right at the bottom and save it: export WORKON_HOME=$HOME/.virtualenvs export VIRTUALENVWRAPPER_PYTHON=/usr/local/bin/virtualenv…

XPO /integrate with XPO via REST-based APIs Using Messtone own internal application or website Examples:To generate bearer token,make a POST request to POST/https://api.ltl.xpo.com/token. header parameter as follows`Authorization basic<access token> The body as follows x-www-form-urlencoded value: grant_type=password usernamerharper@messtone.com=<XPO ltl registerd userrharper@messtone.com id><password=password> The response to make Messtone Business API call as follows:{“access_token”:”b4ab05082c47fb9628028a8c92a3f24e”,”refresh_token”:”fb87136c2e472d450d9c3e89283e4d40″,”scope”:”default”,”token_type”:”Bearer”,”expires_in”:43200} health-check service,GET requests to…

U.S.Army Logistics Innovation Agency,and What is the Army doing’LIA has provided new technologies in supoort of Army logistics for more than 15 years.In the mid ’90,LIA was instrumental in developing first an Amry,and then a joint total asset visibility capacity,that today is now routine.Likewise,LIA’s work with active Radio Frequency Identification is now the DoD standard…

Buddy:API Method is cuRL.Open the terminal and invoke it with the previously generated token Example:$curl https://api.buddy.works/userrharper@messtone.com?access_token=732e9e20-50ba-4047-8a7b-c9b17259a2a2 $curl –header “Authorization:Bearer732e9e20-50ba-4047-8a7b-c9b17259a2a2″https://api.buddy.works/userrharper@messtone.com Sample Response HTTP Status:200 OK X-Rate-Limit-Limit:1 X-Rate-Limit-Remaining:999 JSON{“url”:”https://api.buddy.works/userrharper@messtone.com&#8221;,”html_url:”https://api.buddy.works/my-id&#8221;,”id”:1,”nameMesstone’:”Mike Benson”,”avatar_url”:”https://api.buddy.works/image-server/userrharper@messtone.com/0/0/0/0/0/0/1/d643744fbe5ebf2906a4d075a5b97110/w/32/32/AVATAR.png&#8221;,”workspaces_url”:”https://api.buddy.works/workspaces&#8221;}$curl -request PATCH –data “{\”title\”:\”buddy is awesome! He’s my friend shit\”}”https://api.buddy.works/userrharper@messtone.com

Leveraging OpenAI Gym and the Anytrading Environment for Trading~!pip install tensorflow-gpu==1.15.0 tensorflow==1.15.0 gym-anytrading gym stable-baselines Environment trading bot trade import gym_anytrading import gym from stable_baselines import A2C from stable_baselines.common.vec_env import DummyVevEnv import pandas as pd import numpy as np from matplotlib import pyplot as plt df=pd.read_csv(‘ETHUSD.csv’) df.head( )df[‘Date’]=pd.to_datetime(df[‘Date’])df.set_index(‘Date’,in place=True)df[‘Open’]=df[‘Open’].apply(lambda x:float(x.replace(“,”,””)))df[‘High’]=df[‘High’].apply(lambda x:float(x.replace(“,”,””)))df[‘Close’]=df[‘Close’].apply(lambda x:float(x.replace(“,”,””)))env=gym.make(‘stocks-v0’,df=df,frame_bound=(5,30),window_size=5)state=env.reset( )while True:action=env.action_space.sample( )…