Merge pull request #1 from DoubleML/m-prepare-publication

prepare upload of working paper to arXiv and serverless application to the AWS Serverless Application Repository

Author: MalteKurz

.github/workflows/pytest.yml

@@ -35,4 +35,4 @@ jobs:
         pip install .
     - name: Test with pytest
       run: |
-        pytest -m ci
+        pytest

README.md

@@ -43,7 +43,7 @@ The corresponding serverless application consists of the following components:
 
 There are two options for deployment:
 
-1. A version of DoubleML-Serverless is available in the AWS Serverless Application Repository. It can be deployed by clicking on the `Deploy` button.
+1. A version of DoubleML-Serverless is available in the AWS Serverless Application Repository: [https://serverlessrepo.aws.amazon.com/applications/eu-central-1/839779594349/doubleml-serverless](https://serverlessrepo.aws.amazon.com/applications/eu-central-1/839779594349/doubleml-serverless). It can be deployed by clicking on the `Deploy` button.
 
 2. The second option for deployment is based on AWS Serverless Application Model (AWS SAM).
 

aws_lambda_app/lambda_layers/requirements.txt

@@ -1,3 +1,3 @@
 numpy
 pandas
-sklearn
+scikit-learn==0.23.2

aws_lambda_app/template.yaml

@@ -1,23 +1,6 @@
 AWSTemplateFormatVersion: '2010-09-09'
 Transform: AWS::Serverless-2016-10-31
-Description: SAM Template for doubleml-serverless
-
-Metadata:
-  AWS::ServerlessRepo::Application:
-    Name: doubleml-serverless
-    Description: Distributed Double Machine Learning with a Serverless Architecture
-    Author: Malte S. Kurz
-    SpdxLicenseId: MIT
-    LicenseUrl: ../LICENSE
-    ReadmeUrl: ../README.md
-    Labels: ['machine-learning', 'python', 'ml', 'scikit-learn']
-    HomePageUrl: https://github.com/DoubleML/doubleml-serverless
-    SemanticVersion: 0.0.1
-    SourceCodeUrl: https://github.com/DoubleML/doubleml-serverless
-
-Globals:
-  Function:
-    Timeout: 180
+Description: Distributed Double Machine Learning with a Serverless Architecture
 
 Parameters:
   CreateS3BucketForDataTransfer:

doubleml_serverless/tests/__init__.py

@@ -10,8 +10,8 @@
 
 import doubleml as dml
 import doubleml_serverless as dml_lambda
-from helper_local_lambda_calls import DoubleMLIIVMServerlessLocal
 
+from doubleml_serverless.tests.helper_local_lambda_calls import DoubleMLIIVMServerlessLocal
 from doubleml_serverless.tests.helper_general import get_n_datasets
 
 # number of datasets per dgp

doubleml_serverless/tests/test_iivm.py

@@ -10,8 +10,8 @@
 
 import doubleml as dml
 import doubleml_serverless as dml_lambda
-from helper_local_lambda_calls import DoubleMLIRMServerlessLocal
 
+from doubleml_serverless.tests.helper_local_lambda_calls import DoubleMLIRMServerlessLocal
 from doubleml_serverless.tests.helper_general import get_n_datasets
 
 # number of datasets per dgp

doubleml_serverless/tests/test_irm.py

@@ -9,8 +9,8 @@
 
 import doubleml as dml
 import doubleml_serverless as dml_lambda
-from helper_local_lambda_calls import DoubleMLPLIVServerlessLocal
 
+from doubleml_serverless.tests.helper_local_lambda_calls import DoubleMLPLIVServerlessLocal
 from doubleml_serverless.tests.helper_general import get_n_datasets
 
 # number of datasets per dgp

doubleml_serverless/tests/test_pliv.py

@@ -9,8 +9,8 @@
 
 import doubleml as dml
 import doubleml_serverless as dml_lambda
-from helper_local_lambda_calls import DoubleMLPLRServerlessLocal
 
+from doubleml_serverless.tests.helper_local_lambda_calls import DoubleMLPLRServerlessLocal
 from doubleml_serverless.tests.helper_general import get_n_datasets
 
 # number of datasets per dgp

doubleml_serverless/tests/test_plr.py

@@ -1,9 +1,9 @@
-DoubleML
+DoubleML>=0.1.2
 joblib
 numpy
 pandas
 scipy
 sklearn
 statsmodels
-boto3==1.14.44
 aiobotocore==1.1.2
+boto3==1.14.44