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update README notes on 0.12 blob support
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README.md

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@@ -44,7 +44,7 @@ dj.config["enable_python_native_blobs"] = True
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You can safely enable this setting if both of the following are true:
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* All blobs in your current DataJoint databases contain only numerical arrays.
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* You do not need to share blob data between Python and Matlab
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* You do not need to share blob data between Python and MATLAB.
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Otherwise, read the following explanation.
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@@ -54,7 +54,7 @@ and lists of strings.
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Prior to DataJoint v0.12, certain python native datatypes such as
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dictionaries were 'squashed' into numpy structured arrays when saved into
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blob attributes. This facilitated easier data sharing between Matlab
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blob attributes. This facilitated easier data sharing between MATLAB
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and Python for certain record types. However, this created a discrepancy
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between insert and fetch datatypes which could cause problems in other
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portions of users pipelines.
@@ -71,14 +71,14 @@ Furthermore, DataJoint for MATLAB does not yet support unpacking native Python d
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With `dj.config["enable_python_native_blobs"]` set to `False` (default),
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any attempt to insert any datatype other than a numpy array will result in an exception.
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This is meant to get users to read this message in order to allow proper testing
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and migration of pre-0.12 pipelines to 0.11 in a safe manner.
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and migration of pre-0.12 pipelines to 0.12 in a safe manner.
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The exact process to update a specific pipeline will vary depending on
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the situation, but generally the following strategies may apply:
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* Altering code to directly store numpy structured arrays or plain
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multidimensional arrays. This strategy is likely best one for those
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tables requiring compatibility with Matlab.
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tables requiring compatibility with MATLAB.
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* Adjust code to deal with both structured array and native fetched data
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for those tables that are populated with `dict`s in blobs in pre-0.12 version.
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In this case, insert logic is not adjusted, but downstream consumers

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