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A binary-to-text encoding is encoding of data in plain text.More precisely, it is an encoding of binary data in a sequence of printable characters.These encodings are necessary for transmission of data when the communication channel does not allow binary data (such as email or NNTP) or is not 8-bit clean.
Base64 is particularly prevalent on the World Wide Web [1] where one of its uses is the ability to embed image files or other binary assets inside textual assets such as HTML and CSS files. [2] Base64 is also widely used for sending e-mail attachments, because SMTP – in its original form – was designed to transport 7-bit ASCII characters ...
(via JSON APIs implemented with Smile backend, on Jackson, Python) — SOAP: W3C: XML: Yes W3C Recommendations: SOAP/1.1 SOAP/1.2: Partial (Efficient XML Interchange, Binary XML, Fast Infoset, MTOM, XSD base64 data) Yes Built-in id/ref, XPointer, XPath: WSDL, XML schema: DOM, SAX, XQuery, XPath — Structured Data eXchange Formats: Max ...
More common today is the Base64 format, which is based on the same concept of alphanumeric-only as opposed to ASCII 32–95. All three formats use 6 bits (64 different characters) to represent their input data. Base64 can also be generated by the uuencode program and is similar in format, except for the actual character translation:
Since Base64 encoded data is approximately 33% larger than original data, it is recommended to use Base64 data URIs only if the server supports HTTP compression or embedded files are smaller than 1KB. The data, separated from the preceding part by a comma (,). The data is a sequence of zero or more octets represented as characters. The comma is ...
MessagePack is more compact than JSON, but imposes limitations on array and integer sizes.On the other hand, it allows binary data and non-UTF-8 encoded strings. In JSON, map keys have to be strings, but in MessagePack there is no such limitation and any type can be a map key, including types like maps and arrays, and, like YAML, numbers.
Beautiful Soup is a Python package for parsing HTML and XML documents, including those with malformed markup. It creates a parse tree for documents that can be used to extract data from HTML, [ 3 ] which is useful for web scraping .
Requests is an HTTP client library for the Python programming language. [2] [3] Requests is one of the most downloaded Python libraries, [2] with over 300 million monthly downloads. [4] It maps the HTTP protocol onto Python's object-oriented semantics. Requests's design has inspired and been copied by HTTP client libraries for other programming ...