Some Build-in lib in Python

heapq

(Still don’t get the main point of this module and heap)

This module provides an implementation of the heap queue algorithm, also known as the priority queue algorithm.

What is heap

• Heaps are binary trees for which every parent node has a value less than or equal to any of its children.
• Heaps are arrays for which a[k] <= a[2*k+1] and a[k] <= a[2*k+2] for all k, counting elements from 0.
• For the sake of comparison, non-existing elements are considered to be infinite.
• The interesting property of a heap is that its smallest element is always the root, heap[0].
• In a word, heaps are useful memory structures to know.

functions

heapq.nlargest(n, iterable, key=None)

Return a list with the n largest elements from the dataset defined by iterable.

json

json exposes an API familiar to users of the standard library marshal and pickle modules.

Functions

json.loads() and json.load()

conversion table:

json.loads(s, *)

Deserialize s (a str, bytes or bytearray instance containing a JSON document) to a Python object using this conversion table.

For example, If you have a JSON string, you can parse it by using the json.loads() method. it return a Python dictionary.

x = '{"name":"John", "age":30, "city":"New York"}'
dct = json.loads(x)

json.load(fp, *)

Deserialize fp (a .read()-supporting text file or binary file containing a JSON document) to a Python object using this conversion table.

json.dumps(obj, *)

Serialize obj to a JSON formatted str using this conversion table.

json.dump(obj, fp, *)

Serialize obj as a JSON formatted stream to fp (a .write()-supporting file-like object) using this conversion table.

Classes

You can create subclass of these defined classes:

class json.JSONDecoder

Simple JSON decoder.

method: decode(s)

Return the Python representation of s (a str instance containing a JSON document).

class json.JSONEncoder

Extensible JSON encoder for Python data structures.

method: default(o)

Implement this method in a subclass such that it returns a serializable object for o, or calls the base implementation (to raise a TypeError).

encode(o)

Return a JSON string representation of a Python data structure, o.

iterencode(o)

Encode the given object, o, and yield each string representation as available.

io module

• The io module provides Python’s main facilities for dealing with various types of I/O.
• There are three main types of I/O: text I/O, binary I/O and raw I/O.
• A concrete object belonging to any of these categories is called a file object. Other common terms are stream and file-like object.

Text I/O

Text I/O expects and produces str objects. The easiest way to create a text stream is with open(): f = open("myfile.txt", "r", encoding="utf-8")

In-memory text streams are also available as StringIO objects: f = io.StringIO("some initial text data")

Binary I/O

Binary I/O (also called buffered I/O) expects bytes-like objects and produces bytes objects.

The easiest way to create a binary stream is with open() with ‘b’ in the mode string: f = open("myfile.jpg", "rb")

In-memory binary streams are also available as BytesIO objects: f = io.BytesIO(b"some initial binary data: \x00\x01")