Python version restriction (#22)

* version bump

* clean up

* python version support 3.2+

.gitignore

@@ -5,3 +5,5 @@
 redisai.egg-info
 .idea
 .mypy_cache/
+build/
+dist/

README.md

@@ -27,18 +27,6 @@ $ pip install ml2rt
 
 [RedisAI example repo](https://github.com/RedisAI/redisai-examples) shows few examples made using redisai-py under `python_client` section. Checkout [ml2rt](https://github.com/hhsecond/ml2rt) for convenient functions those might help in converting models (sparkml, sklearn, xgboost to ONNX), serializing models to disk, loading it back to redisai-py etc.
 
-For a quick walk through, checkout this example
-
-```python
-
-
-print(client.tensorget('mul'))
-
-# Try with a script
-script = ml2rt.load_script('test/testdata/script.txt')
-client.scriptset('ket', Device.cpu, script)
-client.scriptrun('ket', 'bar', input=['a', 'b'], output='c')
-```
 
 ## Documentation
 APIs available in redisai-py

redisai/client.py

@@ -1,5 +1,5 @@
 from redis import StrictRedis
-from typing import Union, Any, AnyStr, ByteString, Collection, Type
+from typing import Union, Any, AnyStr, ByteString, Sequence, Type
 
 try:
     import numpy as np
@@ -32,8 +32,8 @@ def modelset(self,
                  backend: Backend,
                  device: Device,
                  data: ByteString,
-                 inputs: Union[AnyStr, Collection[AnyStr], None] = None,
-                 outputs: Union[AnyStr, Collection[AnyStr], None] = None
+                 inputs: Union[AnyStr, Sequence[AnyStr], None] = None,
+                 outputs: Union[AnyStr, Sequence[AnyStr], None] = None
                  ) -> AnyStr:
         args = ['AI.MODELSET', name, backend.value, device.value]
         if backend == Backend.tf:
@@ -58,8 +58,8 @@ def modeldel(self, name: AnyStr) -> AnyStr:
 
     def modelrun(self,
                  name: AnyStr,
-                 inputs: Union[AnyStr, Collection[AnyStr]],
-                 outputs: Union[AnyStr, Collection[AnyStr]]
+                 inputs: Union[AnyStr, Sequence[AnyStr]],
+                 outputs: Union[AnyStr, Sequence[AnyStr]]
                  ) -> AnyStr:
         args = ['AI.MODELRUN', name]
         args += ['INPUTS'] + str_or_strsequence(inputs)
@@ -69,7 +69,7 @@ def modelrun(self,
     def tensorset(self,
                   key: AnyStr,
                   tensor: Union[Tensor, np.ndarray, list, tuple],
-                  shape: Union[Collection[int], None] = None,
+                  shape: Union[Sequence[int], None] = None,
                   dtype: Union[DType, None] = None) -> Any:
         """
         Set the values of the tensor on the server using the provided Tensor object
@@ -140,8 +140,8 @@ def scriptdel(self, name):
     def scriptrun(self,
                   name: AnyStr,
                   function: AnyStr,
-                  inputs: Union[AnyStr, Collection[AnyStr]],
-                  outputs: Union[AnyStr, Collection[AnyStr]]
+                  inputs: Union[AnyStr, Sequence[AnyStr]],
+                  outputs: Union[AnyStr, Sequence[AnyStr]]
                   ) -> AnyStr:
         args = ['AI.SCRIPTRUN', name, function, 'INPUTS']
         args += str_or_strsequence(inputs)

redisai/tensor.py

@@ -1,4 +1,4 @@
-from typing import Union, ByteString, Collection
+from typing import Union, ByteString, Sequence
 import warnings
 from .utils import convert_to_num
 from .constants import DType
@@ -13,7 +13,7 @@ class Tensor(object):
 
     def __init__(self,
                  dtype: DType,
-                 shape: Collection[int],
+                 shape: Sequence[int],
                  value):
         warnings.warn("Tensor APIs are depricated and "
                       "will be removed from the future release.", UserWarning)
@@ -44,7 +44,7 @@ def __repr__(self):
             id=id(self))
 
     @classmethod
-    def from_resp(cls, dtype: DType, shape: Collection[int], value) -> 'Tensor':
+    def from_resp(cls, dtype: DType, shape: Sequence[int], value) -> 'Tensor':
         convert_to_num(dtype, value)
         return cls(dtype, shape, value)
 
@@ -64,7 +64,7 @@ class BlobTensor(Tensor):
 
     def __init__(self,
                  dtype: DType,
-                 shape: Collection[int],
+                 shape: Sequence[int],
                  *blobs: Union['BlobTensor', ByteString]
                  ):
         """

redisai/version.py

@@ -2,4 +2,4 @@
 # 1) we don't load dependencies by storing it in __init__.py
 # 2) we can import it in setup.py for the same reason
 # 3) we can import it into your module module
-__version__ = '0.4.0'
+__version__ = '0.4.1'

setup.py

@@ -2,7 +2,11 @@
 #!/usr/bin/env python
 from setuptools import setup, find_packages
 
-exec(open('redisai/version.py', encoding='utf-8').read())
+try:
+    exec(open('redisai/version.py', encoding='utf-8').read())
+except TypeError:
+    exec(open('redisai/version.py').read())
+
 with open('README.md') as f:
     long_description = f.read()
 
@@ -18,6 +22,7 @@
     author_email='oss@redislabs.com',
     packages=find_packages(),
     install_requires=['redis', 'hiredis', 'rmtest'],
+    python_requires='>=3.2',
     classifiers=[
         'Development Status :: 4 - Beta',
         'Intended Audience :: Developers',