Python read text file as binary trading
After a file object is closed, either by a with statement or by calling f. The rest of the examples in this section will assume that a file object called f has already been created. Otherwise, at most size bytes are read and returned. If the end of the file has been reached, f. This makes the return value unambiguous; if f. For reading lines from a file, you can loop over the file object.
This is memory efficient, fast, and leads to simple code:. If you want to read all the lines of a file in a list you can also use list f or f. Other types of objects need to be converted — either to a string in text mode or a bytes object in binary mode — before writing them:. In text files those opened without a b in the mode string , only seeks relative to the beginning of the file are allowed the exception being seeking to the very file end with seek 0, 2 and the only valid offset values are those returned from the f.
Any other offset value produces undefined behaviour. File objects have some additional methods, such as isatty and truncate which are less frequently used; consult the Library Reference for a complete guide to file objects.
Strings can easily be written to and read from a file. Numbers take a bit more effort, since the read method only returns strings, which will have to be passed to a function like int , which takes a string like '' and returns its numeric value When you want to save more complex data types like nested lists and dictionaries, parsing and serializing by hand becomes complicated.
Reconstructing the data from the string representation is called deserializing. Between serializing and deserializing, the string representing the object may have been stored in a file or data, or sent over a network connection to some distant machine. The JSON format is commonly used by modern applications to allow for data exchange.
Many programmers are already familiar with it, which makes it a good choice for interoperability. If you have an object x , you can view its JSON string representation with a simple line of code:. Another variant of the dumps function, called dump , simply serializes the object to a text file. So if f is a text file object opened for writing, we can do this:. To decode the object again, if f is a text file object which has been opened for reading:.
This simple serialization technique can handle lists and dictionaries, but serializing arbitrary class instances in JSON requires a bit of extra effort. The reference for the json module contains an explanation of this. Contrary to JSON , pickle is a protocol which allows the serialization of arbitrarily complex Python objects.
As such, it is specific to Python and cannot be used to communicate with applications written in other languages. It is also insecure by default: Note use of 'end' on previous line This is the first line of the file. Second line of the file. See also pickle - the pickle module Contrary to JSON , pickle is a protocol which allows the serialization of arbitrarily complex Python objects.
Table Of Contents 7. Input and Output 7. Fancier Output Formatting 7. Old string formatting 7. Reading and Writing Files 7. Methods of File Objects 7. Saving structured data with json Previous topic 6. Modules Next topic 8.
The Python Software Foundation is a non-profit corporation. This can work in many cases, especially those where the ASCII markers are embedded in genuinely arbitrary binary data. In particular, some APIs that accept both bytes and text may be very strict about the encoding of the bytes they accept for example, the urllib. This section explores a number of use cases that can arise when processing text. All files must be processed without triggering any exceptions, but some risk of data corruption is deemed acceptable e.
This is the closest equivalent Python 3 offers to the permissive Python 2 text handling model. All files must be processed without triggering any exceptions, but some Unicode related errors are acceptable in order to reduce the risk of data corruption e. This use case describes the default behaviour in Python 3.
This is becoming more and more common, especially with many text file formats beginning to standardise on UTF-8 as the preferred text encoding. Nick Coghlan's Python Notes latest. What changed in Python 3? Python 3 always stores text strings as sequences of Unicode code points. These are values in the range x10FFFF. To store text as binary data, you must specify an encoding for that text.
The process of converting from a sequence of bytes i. For historical reasons, the most widely used encoding is ascii , which can only handle Unicode code points in the range x7F i. ASCII is a 7-bit encoding.