I am new to Cloud foundry. Here is the use case which I want to achieve,
I want to write a python script, which will invoke the api end point, go to the corresponding org/space and then issue a cf push command.
I was able to login and get the metadata of the orgs using below script:
import os
from cloudfoundry_client.client import CloudFoundryClient
target_endpoint = 'https://run.api.pivotal.io'
proxy = dict(http=os.environ.get('HTTP_PROXY', ''), https=os.environ.get('HTTPS_PROXY', ''))
client = CloudFoundryClient(target_endpoint, proxy=proxy, skip_verification=True)
client.init_with_user_credentials('abcd#mail.com', 'password')
for organization in client.organizations:
print organization['metadata']['guid']
Please sugggest, also if there are any links do share.
Assuming you are using this library? https://github.com/cloudfoundry-community/cf-python-client, if not please clarify as your question leaves ambiguity.
The docs state that each entity manager exposes a generic _create method, and the App Entity manager does not look to expose a specific push method. You may be able to use the generic _create and pass a dict defining the application.
But I would suggest looking at the CF-CLI or Java Client which are both maintained by cloud foundry community, and much more well documented.
Related
I need to get the events for the current day from a personal Outlook calendar. I have found next to no feasible resources online besides maybe Microsoft's tutorial (https://learn.microsoft.com/en-us/graph/tutorials/python), but I do not want to build a Django app. Can anyone provide some other resources?
also: I have seen a lot of ppl calling APIs by using a GET <url> command. I cannot for the life of me understand how or where you can use this? Am I missing something crucial when it comes to using APIs?
First you should know that if you wanna call ms graph api, you need to get the access token first and add it to the request header like screenshot below. What I showed in the screenshot is create calendar events but they're similar. Therefore, you can't avoid to generate the token.
Then there're 2 ways lie in front of you, if you are composing a web app, then you can follow this section to find a suitable sample for you, and if you are composing a daemon application, that means you need to use clientcredentialflow here and you may refer to this section.
Anyway, whatever you use SDK or sending http request to call the api, you all need to choose a suitable flow to obtain access token.
For this purpose without using Microsoft Graph API via request in python, there is a PyPI package named O365.
By the following procedure you can easily read a Microsoft calendar:
install the package: pip install O365
register an application in the Microsoft Azure console and keep the application (client) id as well as client secret — this article can help you up.
check the signInAudience, it should be AzureADandPersonalMicrosoftAccount not PersonalMicrosoftAccount within Microsft Azure Manifest, otherwise, you can edit that.
next you should set delegated permission to what scopes you want, in your case it's Calendars.Read. Here's a snapshot of my configuration in Azure:
Now it's time to dive into the code:
from O365 import Account
CLIENT_ID = "xxx"
CLIENT_SECRET = "xxx"
credentials = (CLIENT_ID, CLIENT_SECRET)
scopes = ['Calendars.Read']
account = Account(credentials)
if not account.is_authenticated:
account.authenticate(scopes=scopes)
print('Authenticated!')
schedule = account.schedule()
calendar = schedule.get_default_calendar()
events = calendar.get_events(include_recurring=False)
for event in events:
print(event)
I am developing an application in python where i need to consume the current values of a metric for some pods(eg. cpu, memory). I can get this info through an API (/apis/metrics.k8s.io/v1beta1/pods) but i try to use the kubernetes client so as to access these metrics within my python app.
I see that the V2beta2PodsMetricStatus Model includes the information i need but i can not find the API endpoint i should use so as to reach this model.
Any help or alternative option would be very helpful since i am really stacked with this issue several days.
Thank you very much for you time.
I finally get the metrics by executing directly the relevant kubectl command. I do not like the solution but it works. Hope to be able to use the kubernetes-client instead at the near future.
import subprocess
p = subprocess.getoutput('kubectl get --raw /apis/metrics.k8s.io/v1beta1/namespaces/default/pods')
ret_metrics = json.loads(p)
items = ret_metrics['items']
for item in items:
print(item['metadata']['name'])
You could use the call_api method of api_client as below to call an API which is not part of core kubernetes API.
ret_metrics = api_client.call_api('/apis/metrics.k8s.io/v1beta1/pods', 'GET', auth_settings = ['BearerToken'], response_type='json', _preload_content=False)
response = ret_metrics[0].data.decode('utf-8')
There is an open issue to support it via V2beta2PodsMetricStatus model
I have code below that was given to me to list Google Cloud Service Accounts for a specific Project.
import os
from googleapiclient import discovery
from gcp import get_key
"""gets all Service Accounts from the Service Account page"""
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = get_key()
service = discovery.build('iam', 'v1')
project_id = 'projects/<google cloud project>'
request = service.projects().serviceAccounts().list(name=project_id)
response = request.execute()
accounts = response['accounts']
for account in accounts:
print(account['email'])
This code works perfectly and prints the accounts as I need them. What I'm trying to figure out is:
Where can I go to see how to construct code like this? I found a site that has references to the Python API Client, but I can't seem to figure out how to make the code above from it. I can see the Method to list the Service Accounts, but it's still not giving me enough information.
Is there somewhere else I should be going to educate myself. Any information you have is appreciated so I don't pull out the rest of my hair.
Thanks, Eric
Let me share with you this documentation page, where there is a detailed explanation on how to build a script such as the one you shared, and what does each line of code mean. It is extracted from the documentation of ML Engine, not IAM, but it is using the same Python Google API Client Libary, so just ignore the references to ML and the rest will be useful for you.
In any case, here it is a commented version of your code, so that you understand it better:
# Imports for the Client API Libraries and the key management
import os
from googleapiclient import discovery
from gcp import get_key
# Look for an environment variable containing the credentials for Google Cloud Platform
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = get_key()
# Build a Python representation of the REST API
service = discovery.build('iam', 'v1')
# Define the Project ID of your project
project_id = 'projects/<google cloud project>'
"""Until this point, the code is general to any API
From this point on, it is specific to the IAM API"""
# Create the request using the appropriate 'serviceAccounts' API
# You can substitute serviceAccounts by any other available API
request = service.projects().serviceAccounts().list(name=project_id)
# Execute the request that was built in the previous step
response = request.execute()
# Process the data from the response obtained with the request execution
accounts = response['accounts']
for account in accounts:
print(account['email'])
Once you understand the first part of the code, the last lines are specific to the API you are using, which in this case is the Google IAM API. In this link, you can find detailed information on the methods available and what they do.
Then, you can follow the Python API Client Library documentation that you shared in order to see how to call the methods. For instance, in the code you shared, the method used depends on service, which is the Python representation of the API, and then goes down the tree of methods in the last link as in projects(), then serviceAccounts() and finally the specificlist() method, which ends up in request = service.projects().serviceAccounts().list(name=project_id).
Finally, just in case you are interested in the other available APIs, please refer to this page for more information.
I hope the comments I made on your code were of help, and that the documentation shared makes it easier for you to understand how a code like that one could be scripted.
You can use ipython having googleapiclient installed - with something like:
sudo pip install --upgrade google-api-python-client
You can go to interactive python console and do:
from googleapiclient import discovery
dir(discovery)
help(discovery)
dir - gives all entries that object has - so:
a = ''
dir(a)
Will tell what you can do with string object. Doing help(a) will give help for string object. You can do dipper:
dir(discovery)
# and then for instance
help(discovery.re)
You can call your script in steps, and see what is result print it, do some research, having something - do %history to printout your session, and have solution that can be triggered as a script.
I'm trying to figure out how to authenticate and create an entry on quickbooks online through Python. Currently, when I try to click auth link in their API Explorer, I get 404 page.
What I'm trying to do is creating invoice through Python. However, it seems like their documentation is not complete. I contacted their support, and I haven't heard from them yet.
The python-quickbooks library is probably the correct choice now, as it is a "complete rework of quickbooks-python". It has pretty comprehensive instructions on getting and using the auth keys, though I wouldn't call it "simple", since the process is by definition somewhat complex. The instructions are "for Django", but the Django-specific code simply gets parameters out of a URL string.
We're using it to great effect, because the syntax is as easy as:
auth_client = AuthClient(
client_id = CLIENT_ID # from QB website
,client_secret = CLIENT_SECRET # from QB website
,environment = 'sandbox' # or 'production'
,redirect_uri = REDIRECT_URI
)
client = QuickBooks(
auth_client = auth_client
,refresh_token = REFRESH_TOKEN
,company_id = COMPANY_ID
)
account = Account.get(qbid, qb=client) # qbid can be retrieved from the AccountList
return account.CurrentBalance
This library will get the job done https://github.com/HaPsantran/quickbooks-python
It works in JSON so you would construct the Invoice based off of docs at https://developer.intuit.com/docs/0025_quickbooksapi/0050_data_services/030_entity_services_reference/invoice using the JSON examples.
The library doesn't support sandbox mode** so if you are going to use the development consumer key and secret than you would change this code.
base_url_v3 = "https://quickbooks.api.intuit.com/v3"
to
base_url_v3 = "https://sandbox-quickbooks.api.intuit.com/v3"
while in that mode.
** Sandbox mode only applies currently to U.S. QBO
Having written a lot of the module #Minimul mentions — with a very helpful start by simonv3, who figured out how to get it working first and then I just built on it — I am fairly confident that this will not support the oauth workflow of getting the request token, prompting the user to authenticate out of band, and then getting and storing the access token. It presumes you already have an access token.
Simon (or another Python developer) may be able to comment on how he gets the access token with Python, and if so, it'd be great if he (or they) could add it to the module for all to enjoy.
I had this same problem. I just figured it out and posed the step-by-step process here:
python with Quickbooks Online API v3
Hope this helps.
I looked at the existing python clients for quickbooks and found them to be either outdated or not having all the features. So i created a new python client for quickbooks which can be found at https://pypi.python.org/pypi/quickbooks-py
I am new to Flask.
I have a public api, call it api.example.com.
#app.route('/api')
def api():
name = request.args.get('name')
...
return jsonify({'address':'100 Main'})
I am building an app on top of my public api (call it www.coolapp.com), so in another app I have:
#app.route('/make_request')
def index():
params = {'name':'Fred'}
r = requests.get('http://api.example.com', params=params)
return render_template('really_cool.jinja2',address=r.text)
Both api.example.com and www.coolapp.com are hosted on the same server. It seems inefficient the way I have it (hitting the http server when I could access the api directly). Is there a more efficient way for coolapp to access the api and still be able to pass in the params that api needs?
Ultimately, with an API powered system, it's best to hit the API because:
It's user testing the API (even though you're the user, it's what others still access);
You can then scale easily - put a pool of API boxes behind a load balancer if you get big.
However, if you're developing on the same box you could make a virtual server that listens on localhost on a random port (1982) and then forwards all traffic to your api code.
To make this easier I'd abstract the API_URL into a setting in your settings.py (or whatever you are loading in to Flask) and use:
r = requests.get(app.config['API_URL'], params=params)
This will allow you to make a single change if you find using this localhost method isn't for you or you have to move off one box.
Edit
Looking at your comments you are hoping to hit the Python function directly. I don't recommend doing this (for the reasons above - using the API itself is better). I can also see an issue if you did want to do this.
First of all we have to make sure the api package is in your PYTHONPATH. Easy to do, especially if you're using virtualenvs.
We from api import views and replace our code to have r = views.api() so that it calls our api() function.
Our api() function will fail for a couple of reasons:
It uses the flask.request to extract the GET arg 'name'. Because we haven't made a request with the flask WSGI we will not have a request to use.
Even if we did manage to pass the request from the front end through to the API the second problem we have is using the jsonify({'address':'100 Main'}). This returns a Response object with an application type set for JSON (not just the JSON itself).
You would have to completely rewrite your function to take into account the Response object and handle it correctly. A real pain if you do decide to go back to an API system again...
Depending on how you structure your code, your database access, and your functions, you can simply turn the other app into package, import the relevant modules and call the functions directly.
You can find more information on modules and packages here.
Please note that, as Ewan mentioned, there's some advantages to using the API. I would advise you to use requests until you actually need faster requests (this is probably premature optimization).
Another idea that might be worth considering, depending on your particular code, is creating a library that is used by both applications.