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Types 2 and 3 have a count field which encodes the length in bytes of the payload. Type 2 is an unstructured byte string. Type 3 is a UTF-8 text string. A short count of 31 indicates an indefinite-length string. This is followed by zero or more definite-length strings of the same type, terminated by a "break" marker byte.
JSON streaming comprises communications protocols to delimit JSON objects built upon lower-level stream-oriented protocols (such as TCP), that ensures individual JSON objects are recognized, when the server and clients use the same one (e.g. implicitly coded in). This is necessary as JSON is a non-concatenative protocol (the concatenation of ...
The most expansive form using tag pairs results in a much larger (in character count) representation than JSON, but if data is stored in attributes and 'short tag' form where the closing tag is replaced with />, the representation is often about the same size as JSON or just a little larger. However, an XML attribute can only have a single ...
The type and length are fixed in size (typically 1–4 bytes), and the value field is of variable size. These fields are used as follows: Type A binary code, often simply alphanumeric, which indicates the kind of field that this part of the message represents; Length The size of the value field (typically in bytes); Value
Content-Length: The length of the request body in octets (8-bit bytes). Content-Length: 348: Permanent RFC 9110: Content-MD5: A Base64-encoded binary MD5 sum of the content of the request body. Content-MD5: Q2hlY2sgSW50ZWdyaXR5IQ== Obsolete [15] RFC 1544, 1864, 4021: Content-Type: The Media type of the body of the request (used with POST and ...
doc2vec, generates distributed representations of variable-length pieces of texts, such as sentences, paragraphs, or entire documents. [ 14 ] [ 15 ] doc2vec has been implemented in the C , Python and Java / Scala tools (see below), with the Java and Python versions also supporting inference of document embeddings on new, unseen documents.
Run-length encoding (RLE) is a form of lossless data compression in which runs of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather than as the original run. As an imaginary example of the concept, when encoding an image built up from ...
As a collection algorithm, reference counting tracks, for each object, a count of the number of references to it held by other objects. If an object's reference count reaches zero, the object has become inaccessible, and can be destroyed. When an object is destroyed, any objects referenced by that object also have their reference counts decreased.