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Python bindings for AutoMan Runtime. Software is current in development, and not properly tested.

Project description


Python bindings for AutoMan. See AutoMan. This package is currently in development.

System Requirements

To use this package you must be running Python 2.7.15 or 3.2+,Java 8, and Scala 2.11.7+. This package relies on ScalaPB and gRPC. If you use SBT to build this project, all Scala dependencies will be downloaded. To install gRPC for Python (needed for the Python client), follow these instructions.

How to Install

Use pip to install AutoManPy.

pip install automanpy

This software package is currently in development, and will be updated regularly for bug fixes, etc. If you want to upgrade, or force the installation of the latest version, use '--no-cache-dir' and '--upgrade'

pip install --no-cache-dir automanpy --upgrade

How to Build Source

The easiest way to build this project is by using SBT.To build the source automatically, you can run ./ located in the root directory. This relies on sbt being installed.
To build this project manually, from the /AutomanPy directory, run

sbt clean compile pack

SBT will also compile the necessary .proto into Scala classes automatically. To generate the the python files needed, grpcio-tools and googleapis-common-protos need to be installed. These python dependencies are automatically installed by pip if this package is installed from the provided tarball (). To install the necessary packages manually, run the following two commands:

pip install grpcio-tools
pip install googleapis-common-protos

To use gRPC generate the python files needed for interacting with the RPC service, from the /AutomanPy directory, run the following command:

python -m grpc_tools.protoc -I src/main/protobuf/ --python_out=src/main/automanpy/automanpy/core/grpc_gen_classes/ --grpc_python_out=src/main/automanpy/automanpy/core/grpc_gen_classes src/main/protobuf/core/grpc_gen_classes/automanlib_rpc.proto src/main/protobuf/core/grpc_gen_classes/automanlib_classes.proto src/main/protobuf/core/grpc_gen_classes/automanlib_wrappers.proto

Move the files compiled by sbt into the correct directory by copying them:

cp -r target/pack/ src/main/automanpy/automanpy/core/rpc/server/

Then change to the directory containing and run it from there:

cd src/main/automanpy/
python clean sdist

How to Use

To run tasks, first create an Automan object. The constructor for Automan objects requires an adapter, and take optional parameters for the RPC server address and port number (default is 'localhost' and 50051). The adapter we pass to the constructor is simply a dictionary with the following required fields:

  • access_id - the login id for the crowdsource backend
  • access_key - the login access key for the crowdsource backend
  • type - the type of crowdsource backend. currently only "mturk" is an accepted type
  • any optional arguments for the adapter (currently only "sandbox_mode" for MTurk adapter)

First, import the Automan and EstimateOutcome classes from automanpy.automan, then create an adapter

Python 2.7.15 |Anaconda, Inc.| (default, May  1 2018, 18:37:05) 
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from automanpy.automan import Automan, EstimateOutcome
>>> adapter = {
...     "access_id" : "access id here",
...     "access_key" : "access key here",
...     "sandbox_mode" : "true",
...     "type" : "MTurk"
... }

When an Automan object is being initialized, if the server_addr is 'localhost' it will start a local AutoMan RPC server as a new process, configured to listen on the provided port number. Future functionality will allow users to connect to remote RPC servers. We can now use the Automan object to submit tasks to the crowdsource back-end. Currently, only the estimate function of Automan is available. See example code for usage.

>>> a = Automan(adapter, server_addr='localhost',port=50051)
python client is starting server...
Server Started on port 50051 ...
>>> photo_url = ""
>>> estim = a.estimate(text = "How many cars are in this parking lot?",budget = 6.00, title = "Car Counting",image_url = photo_url)

Each type of task has fields that are required. All tasks require text (a text description of the task), and budget (desired upper limit of cost of task). We specify the tasks we would like AutoMan to carry out, and either when the question has timed out and budget is exceeded (resulting in a low confidence or overbudget outcome respectively) or the desired confidence level has been met.

The outcome can be either:

  • Confident estimate
  • Low Confidence estimate
  • Overbudget

If the task went overbudget, the need and have fields of the returned EstimateOutcome are initialized, otherwise high, low, est, cost, and conf are initialized. AutomanPy uses gRPC's implementation of Futures. To ensure the future is resolved before values are accessed, only try to access respective values within code blocks that ensure those values are set. See methods isConfident(), isLowConfidence(), and isOverBudget() below. To see more example code, and an example for posting multiple tasks, see AutomanPy/examples

To simply print the result of the task, use printOutcome().

>>> estim.printOutcome()
Outcome: Low Confidence Estimate
Estimate low: 62.000000 high:62.000000 est:62.000000

Example Code

See example usage for submitting single and multiple estimate tasks in examples/


See the API under examples/

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