"MicroPython官方文档1.17：Python标准库和微型库概览"

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MicroPython官方文档1.17是由Damien P. George、Paul Sokolovsky和其他贡献者共同编写的。该文档包括了MicroPython的核心库和标准库，以及一些用于处理特定硬件的微型库。MicroPython是一种精简的Python编程语言实现，专门针对微控制器和嵌入式系统。该文档主要介绍了MicroPython的标准库和选定的微型库的详细内容。其中包括了array、binascii、builtins等库的具体用法和功能描述。MicroPython库设计精巧、紧凑，非常适合在资源受限的嵌入式系统上运行。整个文档涵盖了MicroPython标准库和微型库的方方面面，无论是初学者还是有经验的开发人员都能在其中找到所需的信息。 MicroPython的标准库包含了一系列Python语言的核心功能和常用模块。它们被设计成尽可能接近Python的标准库，以便让开发者能够轻松地将现有的Python代码移植到MicroPython中。此外，MicroPython还提供了一些专门针对嵌入式系统优化的微型库。这些微型库主要用于处理特定硬件的输入输出、通信、传感器和其他外围设备的功能。通过MicroPython的官方文档1.17，用户可以详细了解到这些库的使用方法和功能特点。其中，array库提供了对数值数据进行管理和操作的功能。通过array库，用户可以创建和操作各种类型的数值数组，包括整数、浮点数等。这为嵌入式系统的数字信号处理和数据存储提供了便利。另外，binascii库则提供了二进制和ASCII之间的转换功能。在嵌入式系统中，经常需要对二进制数据和ASCII字符串进行相互转换，binascii库提供了方便的工具来满足这些需求。此外，builtins库收录了Python语言的内建函数和异常处理，为MicroPython提供了更完善的语言支持。总的来说，MicroPython的官方文档1.17内容丰富、覆盖面广，为开发者提供了一个全面了解MicroPython库的重要参考。不仅详细介绍了MicroPython的标准库和微型库的使用方法和功能特点，还提供了丰富的示例代码和应用案例，使开发者可以更快、更全面地掌握MicroPython编程的技巧和方法。通过阅读该文档，开发者可以更好地利用MicroPython的丰富功能，开发出更加稳定、高效的嵌入式系统应用。Micropython的官方文档1.17是MicroPython用户学习和开发的必备之物。

MicroPython Documentation, Release 1.17

Functions

cmath.

cos

(

)

Return the cosine of z.

cmath.exp(z)

Return the exponential of z.

cmath.log(z)

Return the natural logarithm of z. The branch cut is along the negative real axis.

cmath.log10(z)

Return the base-10 logarithm of z. The branch cut is along the negative real axis.

cmath.phase(z)

Returns the phase of the number z, in the range (-pi, +pi].

cmath.polar(z)

Returns, as a tuple, the polar form of z.

cmath.rect(r, phi)

Returns the complex number with modulus r and phase phi.

cmath.sin(z)

Return the sine of z.

cmath.sqrt(z)

Return the square-root of z.

Constants

cmath.e

base of the natural logarithm

cmath.pi

the ratio of a circles circumference to its diameter

1.1.5 collections – collection and container types

This module implements a subset of the corresponding CPython module, as described below. For more information,

refer to the original CPython documentation: collections.

This module implements advanced collection and container types to hold/accumulate various objects.

Classes

collections.deque(iterable, maxlen[, ﬂags ])

Deques (double-ended queues) are a list-like container that support O(1) appends and pops from either side of

the deque. New deques are created using the following arguments:

• iterable must be the empty tuple, and the new deque is created empty.

• maxlen must be speciﬁed and the deque will be bounded to this maximum length. Once the deque is full,

any new items added will discard items from the opposite end.

• The optional ﬂags can be 1 to check for overﬂow when adding items.

As well as supporting

bool

and

len

, deque objects have the following methods:

6 Chapter 1. MicroPython libr aries

MicroPython Documentation, Release 1.17

OOM, a collection will be triggered each time after amount bytes have been allocated (in total, since the previous

time such an amount of bytes have been allocated). amount is usually speciﬁed as less than the full heap size,

with the intention to trigger a collection earlier than when the heap becomes exhausted, and in the hope that an

early collection will prevent excessive memory fragmentation. This is a heuristic measure, the eﬀect of which

will vary from application to application, as well as the optimal value of the amount parameter.

Calling the function without argument will return the current value of the threshold. A value of -1 means a

disabled allocation threshold.

Diﬀerence to CPython

This function is a MicroPython extension. CPython has a similar function - set_threshold(), but due to

diﬀerent GC implementations, its signature and semantics are diﬀerent.

1.1.8 hashlib – hashing algorithms

This module implements a subset of the corresponding CPython module, as described below. For more information,

refer to the original CPython documentation: hashlib.

This module implements binar y data hashing algorithms. The exact inventory of available algorithms depends on a

board. Among the algorithms which may be implemented:

• SHA256 - The current generation, modern hashing algorithm (of SHA2 series). It is suitable for

cryptographically-secure purposes. Included in the MicroPython core and any board is recommended to pro-

vide this, unless it has particular code size constraints.

• SHA1 - A previous generation algorithm. Not recommended for new usages, but SHA1 is a part of number of

Internet standards and existing applications, so boards targeting network connectivity and interoperability will

try to provide this.

• MD5 - A legacy algorithm, not considered cryptographically secure. Only selected boards, targeting interoper-

ability with legacy applications, will oﬀer this.

Constructors

class hashlib.sha256([data ])

Create an SHA256 hasher object and optionally feed data into it.

class hashlib.sha1([data ])

Create an SHA1 hasher object and optionally feed data into it.

class hashlib.md5([data ])

Create an MD5 hasher object and optionally feed data into it.

Methods

hash.update(data)

Feed more binary data into hash.

hash.digest()

Return hash for all data passed through hash, as a bytes object. After this method is called, more data cannot be

fed into the hash any longer.

hash.hexdigest()

This method is NOT implemented. Use binascii.hexlify(hash.digest()) to achieve a similar eﬀect.

1.1. Python standard libraries and micro-libraries 9

MicroPython Documentation, Release 1.17

1.1.9 heapq – heap queue algorithm

This module implements a subset of the corresponding CPython module, as described below. For more information,

refer to the original CPython documentation: heapq.

This module implements the min heap queue algorithm .

A heap queue is essentially a list that has its elements stored in such a way that the ﬁrst item of the list is always the

smallest.

Functions

heapq.heappush(heap, item)

Push the item onto the heap.

heapq.heappop(heap)

Pop the ﬁrst item from the heap, and return it. Raise IndexError if heap is empty.

The returned item will be the smallest item in the heap.

heapq.heapify(x)

Convert the list x into a heap. This is an in-place operation.

1.1.10 io – input/output streams

This module implements a subset of the corresponding CPython module, as described below. For more information,

refer to the original CPython documentation: io.

This module contains additional types of

stream

(ﬁle-like) objects and helper functions.

Conceptual hierarchy

Diﬀerence to CPython

Conceptual hierarchy of stream base classes is simpliﬁed in MicroPython, as described in this section.

(Abstract) base stream classes, which serve as a foundation for behaviour of all the concrete classes, adhere to few

dichotomies (pair-wise classiﬁcations) in CPython. In MicroPython, they are somewhat simpliﬁed and made implicit

to achieve higher eﬃciencies and save resources.

An important dichotomy in CPython is unbuﬀered vs buﬀered streams. In MicroPython, all streams are currently

unbuﬀered. This is because all modern OSes, and even many RTOSes and ﬁlesystem drivers already perform buﬀering

on their side. Adding another layer of buﬀering is counter- productive (an issue known as buﬀerbloat) and takes precious

memory. Note that there still cases where buﬀering may be useful, so we may introduce optional buﬀering support at

a later time.

But in CPython, another important dichotomy is tied with buﬀeredness - its whether a stream may incur short read/writes

or not. A short read is when a user asks e.g. 10 bytes from a stream, but gets less, similarly for writes. In CPython,

unbuﬀered streams are automatically short operation susceptible, while buﬀered are guarantee against them. The no

short read/writes is an important trait, as it allows to develop more concise and eﬃcient programs - something which

is highly desirable for MicroPython. So, while MicroPython doesnt support buﬀered streams, it still provides for no-

short-operations streams. Whether there will be short operations or not depends on each particular class needs, but

developers are strongly advised to favour no-short-operations behaviour for the reasons stated above. For example,

10 Chapter 1. MicroPython libr aries

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