Require python 3.7 (#378)

Summary:
Pull Request resolved: #378

This allows us to use
- postponed evaluations of annotations (PEP 563)
- dataclasses (PEP 557)

Reviewed By: ldworkin

Differential Revision: D20113101

fbshipit-source-id: 34e5ae22e9f590894a4c0ab200139380a297a248

Author: Balandat

.circleci/config.yml

@@ -94,9 +94,9 @@ commands:
 
 jobs:
 
-  lint_test_py36_pip:
+  lint_test_py38_pip:
     docker:
-      - image: circleci/python:3.6.9
+      - image: circleci/python:3.8.1
     steps:
       - checkout
       - pip_install:
@@ -124,7 +124,7 @@ jobs:
 
   auto_deploy_site:
     docker:
-      - image: circleci/python:3.6.9-node
+      - image: circleci/python:3.8.1-node
     steps:
       - checkout
       - pip_install:
@@ -150,7 +150,7 @@ workflows:
 
   lint_and_test:
     jobs:
-      - lint_test_py36_pip:
+      - lint_test_py38_pip:
           filters: *exclude_ghpages_fbconfig
       - lint_test_py37_conda:
           filters: *exclude_ghpages_fbconfig

.conda/meta.yaml

@@ -13,7 +13,7 @@ build:
 
 requirements:
   host:
-    - python>=3.6
+    - python>=3.7
   run:
     - pytorch>=1.4
     - gpytorch>=1.0.0

CONTRIBUTING.md

@@ -34,7 +34,7 @@ Travis will fail on your PR if it does not adhere to the black formatting style.
 
 #### Type Hints
 
-BoTorch is fully typed using python 3.6+
+BoTorch is fully typed using python 3.7+
 [type hints](https://www.python.org/dev/peps/pep-0484/).
 We expect any contributions to also use proper type annotations. While we
 currently do not enforce full consistency of these in our continuous integration

README.md

@@ -49,7 +49,7 @@ Optimization simply use Ax.
 ## Installation
 
 **Installation Requirements**
-- Python >= 3.6
+- Python >= 3.7
 - PyTorch >= 1.4
 - gpytorch >= 1.0
 - scipy

botorch/acquisition/acquisition.py

@@ -8,6 +8,8 @@
 Abstract base module for all botorch acquisition functions.
 """
 
+from __future__ import annotations
+
 import warnings
 from abc import ABC, abstractmethod
 from typing import Optional

botorch/acquisition/active_learning.py

@@ -21,6 +21,8 @@
     ArXiv 2017.
 """
 
+from __future__ import annotations
+
 from typing import Optional
 
 from botorch import settings

botorch/acquisition/analytic.py

@@ -9,6 +9,8 @@
 Monte-Carlo sampling.
 """
 
+from __future__ import annotations
+
 from abc import ABC
 from copy import deepcopy
 from typing import Dict, Optional, Tuple, Union

botorch/acquisition/cost_aware.py

@@ -9,6 +9,8 @@
 To be used in a context where there is an objective/cost tradeoff.
 """
 
+from __future__ import annotations
+
 import warnings
 from abc import ABC, abstractmethod
 from typing import Any, Callable, Optional

botorch/acquisition/fixed_feature.py

@@ -9,6 +9,8 @@
 This is useful e.g. for performing contextual optimization.
 """
 
+from __future__ import annotations
+
 from typing import List, Union
 
 import torch

botorch/acquisition/knowledge_gradient.py

@@ -24,6 +24,8 @@
     bayesian optimization. NIPS 2016.
 """
 
+from __future__ import annotations
+
 from copy import deepcopy
 from typing import Callable, Optional, Tuple, Union