Skylab Studio Python Client
SkylabTech Studio Python client.
Requirements
Installation
$ pip install skylab_studio
Example usage
# CREATE PROFILE
payload = {
"name": "profile name",
}
api.create_profile(payload=payload)
# CREATE JOB
payload={
"name": "job name",
"profile_id": profile_id
}
job = api.create_job(payload)
# UPLOAD JOB PHOTO(S)
filePath = "/path/to/photo"
api.upload_job_photo(filePath, job.id)
# QUEUE JOB
payload = { "callback_url" = "YOUR_CALLBACK_ENDPOINT" }
api.queue_job(job.id, payload)
# NOTE: Once the job is queued, it will get processed then complete
# We will send a response to the specified callback_url with the output photo download urls
Usage
For all examples, assume:
import skylab_studio
api = skylab_studio.api(api_key='YOUR-API-KEY')
Error Handling
By default, the API calls return a response object no matter the type of response.
Endpoints
List all jobs
api.list_jobs()
Create job
payload = {
'profile_id': 1
}
api.create_job(payload=payload)
For all payload options, consult the API documentation.
Get job
api.get_job(job_id)
Update job
payload = {
'profile_id': 2
}
api.update_job(job_id, payload=payload)
For all payload options, consult the API documentation.
Queue job
payload = {
"callback_url": "desired_callback_url"
}
api.queue_job(job_id, payload)
Delete job
api.delete_job(job_id)
Cancel job
api.cancel_job(job_id)
Jobs in front
Use after queueing job to check number of jobs ahead of yours
api.fetch_jobs_in_front(job_id)
List all profiles
api.list_profiles()
Create profile
payload = {
'name': 'My profile'
}
api.create_profile(payload=payload)
For all payload options, consult the API documentation.
Get profile
api.get_profile(profile_id)
Update profile
payload = {
'name': 'My profile'
}
api.update_profile(profile_id, payload=payload)
For all payload options, consult the API documentation.
List all photos
api.list_photos()
Get photo
api.get_photo(photo_id)
Upload job photo
This function handles validating a photo, creating a photo object and uploading it to your job/profile's s3 bucket. If the bucket upload process fails, it retries 3 times and if failures persist, the photo object is deleted.
api.upload_job_photo(photo_path, job_id)
Upload profile photo
This function handles validating a background photo for a profile. Note: enable_extract and replace_background (profile attributes) MUST be true in order to create background photos. Follows the same upload process as upload_job_photo.
api.upload_profile_photo(photo_path, profile_id)
Returns: { photo: { photo_object }, upload_response: bucket_upload_response_status }
If upload fails, the photo object is deleted for you. If upload succeeds and you later decide you no longer want to include that image, use delete_photo to remove it.
Delete photo
This will remove the photo from the job/profile's bucket. Useful for when you've accidentally uploaded an image that you'd like removed.
api.delete_photo(photo_id)
Validate hmac headers
Applicable if you utilize the job callback url. Use to validate the job payload integrity.
-
secret_key (string): Obtain from Skylab
-
job_json (string): Stringified json object obtained from callback PATCH request
-
request_timestamp (string): Obtained from callback PATCH request header 'X-Skylab-Timestamp'
-
signature (string): Signature generated by Skylab to compare. Obtained from callback PATCH request header 'X-Skylab-Signature'
Returns True or False based on whether or not the signatures match.
api.validate_hmac_headers(secret_key, job_json, request_timestamp, signature)
Expected Responses
Success
>>> response.status_code
200
>>> response.json().get('success')
True
>>> response.json().get('status')
u'OK'
>>> response.json().get('profile_id')
u'numeric-profile-id'
Error
- Malformed request
>>> response.status_code
422
- Bad API key
>>> response.status_code
403
Troubleshooting
General Troubleshooting
- Enable debug mode
- Make sure you're using the latest Python client
- Capture the response data and check your logs — often this will have the exact error
Enable Debug Mode
Debug mode prints out the underlying request information as well as the data
payload that gets sent to Studio. You will most likely find this information
in your logs. To enable it, simply put debug=True
as a parameter when instantiating
the API object. Use the debug mode to compare the data payload getting
sent to Studio' API docs.
import skylab_studio
api = skylab_studio.api(api_key='YOUR-API-KEY', debug=True)
Response Ranges
Studio' API typically sends responses back in these ranges:
- 2xx – Successful Request
- 4xx – Failed Request (Client error)
- 5xx – Failed Request (Server error)
If you're receiving an error in the 400 response range follow these steps:
- Double check the data and ID's getting passed to Studio
- Ensure your API key is correct
- Log and check the body of the response
Distribution
To package:
python -m build
python -m twine upload dist/*