Neptune
neptune is a global object that you can use to start new tracked runs or re-connect to already existing ones. It also provides some convenience functionalities like obtaining the last created run.
Starts a new tracked run, and append it to the top of the Runs table view. All parameters are optional, hence minimal invocation: run = neptune.create_experiment().
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Run object that is used to manage the tracked run and log metadata to it.
import neptune.new as neptune# minimal invokerun = neptune.init()# create a tracked run with a namerun = neptune.init(name='first-pytorch-ever')# create a tracked run with a name and a description, and no sources files uploadedrun = neptune.init(name='neural-net-mnist',description='neural net trained on MNIST',source_files=[])# Send all py files in cwd (excluding hidden files with names beginning with a dot)run = neptune.init(upload_source_files='*.py')# Send all py files from all subdirectories (excluding hidden files with names beginning with a dot)# Supported on Python 3.5 and later.run = neptune.init(upload_source_files='**/*.py')# Send all files and directories in cwd (excluding hidden files with names beginning with a dot)run = neptune.init(upload_source_files='*')# Send all files and directories in cwd including hidden filesrun = neptune.init(upload_source_files=['*', '.*'])# Send files with names being a single character followed by '.py' extension.run = neptune.init(upload_source_files='?.py')# larger examplerun = neptune.init(name='first-pytorch-ever',description='write longer description here',tags=['list-of', 'tags', 'goes-here', 'as-list-of-strings'],upload_source_files=['training_with_pytorch.py', 'net.py'])
Returns last created Run object.
Run object last created by neptune global object.
import neptune.new as neptune# Crate a new tracked runneptune.init(name='A new approach', upload_source_files='**/*.py')# Oops! We didn't capture the reference to the Run object# Not a problem! We've got you covered.run = neptune.get_last_run()
Get a project with given name.
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Project object that can be used to interact with the project as a whole like fetching data from Runs table.
import neptune.new as neptune# Fetch project 'jack/sandbox'project = neptune.get_project(name='jack/sandbox')# Fetch all Runs metadata as Pandas DataFrameruns_table_df = project.fetch_runs_table().to_pandas()
Anonymous user API token. See ANONYMOUS_API_TOKEN.
Anonymous user API token. You can use this value as an api_token during .init() call both as a method parameter or by setting it as an environment variable.
