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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 ...
The 95 isprint codes 32 to 126 are known as the ASCII printable characters. Some older and today uncommon formats include BOO, BTOA , and USR encoding. Most of these encodings generate text containing only a subset of all ASCII printable characters: for example, the base64 encoding generates text that only contains upper case and lower case ...
<length character> is a character indicating the number of data bytes which have been encoded on that line. This is an ASCII character determined by adding 32 to the actual byte count, with the sole exception of a grave accent "`" (ASCII code 96) signifying zero bytes. All data lines, except the last (if the data length was not divisible by 45 ...
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 ...
The representation has a limited precision. For example, only 15 decimal digits can be represented with a 64-bit real. If a very small floating-point number is added to a large one, the result is just the large one. The small number was too small to even show up in 15 or 16 digits of resolution, and the computer effectively discards it.
Base36 is a binary-to-text encoding scheme that represents binary data in an ASCII string format by translating it into a radix-36 representation.The choice of 36 is convenient in that the digits can be represented using the Arabic numerals 0–9 and the Latin letters A–Z [1] (the ISO basic Latin alphabet).
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Conversely, precision can be lost when converting representations from integer to floating-point, since a floating-point type may be unable to exactly represent all possible values of some integer type. For example, float might be an IEEE 754 single precision type, which cannot represent the integer 16777217 exactly, while a 32-bit integer type ...