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julia smartreceive table defaults to a dataframe

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narawat
2026-03-10 12:06:31 +07:00
parent 99f1b2e720
commit 8f50039a68
2 changed files with 11 additions and 8 deletions
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2
Project.toml
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@@ -1,6 +1,6 @@
name = "NATSBridge" name = "NATSBridge"
uuid = "f2724d33-f338-4a57-b9f8-1be882570d10" uuid = "f2724d33-f338-4a57-b9f8-1be882570d10"
version = "0.5.3" version = "0.5.4"
authors = ["narawat <narawat@gmail.com>"] authors = ["narawat <narawat@gmail.com>"]
[deps] [deps]

17
src/NATSBridge.jl
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@@ -931,8 +931,8 @@ It handles "text" (string), "dictionary" (JSON deserialization), "arrowtable" (A
2. Converts bytes to appropriate Julia data type based on format 2. Converts bytes to appropriate Julia data type based on format
3. For text: converts bytes to string 3. For text: converts bytes to string
4. For dictionary: converts bytes to JSON string then parses to Julia object 4. For dictionary: converts bytes to JSON string then parses to Julia object
5. For arrowtable: reads Arrow IPC format and returns Arrow.Table 5. For arrowtable: reads Arrow IPC format and returns a DataFrame
6. For jsontable: converts bytes to JSON string then parses to Vector{Dict} 6. For jsontable: converts bytes to JSON string then parses to Vector{Dict} and return a DataFrame
7. For image/audio/video/binary: returns bytes directly 7. For image/audio/video/binary: returns bytes directly
# Arguments: # Arguments:
@@ -958,11 +958,11 @@ json_data = _deserialize_data(json_bytes, "dictionary", "correlation123")
# Arrow IPC data (arrowtable) # Arrow IPC data (arrowtable)
arrow_bytes = Vector{UInt8}([1, 2, 3]) # Arrow IPC bytes arrow_bytes = Vector{UInt8}([1, 2, 3]) # Arrow IPC bytes
arrow_table = _deserialize_data(arrow_bytes, "arrowtable", "correlation123") df = _deserialize_data(arrow_bytes, "arrowtable", "correlation123")
# JSON table data (jsontable) # JSON table data (jsontable)
json_table_bytes = UInt8[91, 123, 34, 105, 100, 34, 58, 49, 44, 34, 110, 97, 109, 101, 34, 58, 34, 65, 108, 105, 99, 101, 34, 125] # [{"id":1,"name":"Alice"}] json_table_bytes = UInt8[91, 123, 34, 105, 100, 34, 58, 49, 44, 34, 110, 97, 109, 101, 34, 58, 34, 65, 108, 105, 99, 101, 34, 125] # [{"id":1,"name":"Alice"}]
json_table = _deserialize_data(json_table_bytes, "jsontable", "correlation123") df = _deserialize_data(json_table_bytes, "jsontable", "correlation123")
``` ```
""" """
function _deserialize_data( function _deserialize_data(
@@ -977,11 +977,14 @@ function _deserialize_data(
return JSON.parse(json_str) # Parse JSON string to JSON object return JSON.parse(json_str) # Parse JSON string to JSON object
elseif payload_type == "arrowtable" # Arrow table data - deserialize Arrow IPC stream elseif payload_type == "arrowtable" # Arrow table data - deserialize Arrow IPC stream
io = IOBuffer(data) # Create buffer from bytes io = IOBuffer(data) # Create buffer from bytes
table = Arrow.Table(io) # Read Arrow IPC format from buffer arrowtable = Arrow.Table(io) # Read Arrow IPC format from buffer
return table # Return Arrow.Table df = DataFrame(arrowtable)
return df
elseif payload_type == "jsontable" # JSON table data - deserialize JSON elseif payload_type == "jsontable" # JSON table data - deserialize JSON
json_str = String(data) # Convert bytes to string json_str = String(data) # Convert bytes to string
return JSON.parse(json_str) # Parse JSON string to Vector{Dict} jsontable = JSON.parse(json_str) # Parse JSON string to jsontable i.e. Vector{Dict}
df = DataFrame(jsontable)
return df
elseif payload_type == "image" # Image data - return binary elseif payload_type == "image" # Image data - return binary
return data # Return bytes directly return data # Return bytes directly
elseif payload_type == "audio" # Audio data - return binary elseif payload_type == "audio" # Audio data - return binary