2020-05-22 第十三章 支持向量机模型(python)

Posted 2023-04-20

参考技术A SVM 是 Support Vector Machine 的简称，它的中文名为支持向量机，属于一种有监督的机器学习算法，可用于离散因变量的分类和连续因变量的预测。通常情况下，该算法相对于其他单一的分类算法（如 Logistic 回归、决策树、朴素贝叶斯、 KNN 等）会有更好的预测准确率，主要是因为它可以将低维线性不可分的空间转换为高维的线性可分空间。

“分割带”代表了模型划分样本点的能力或可信度，“分割带”越宽，说明模型能够将样本点划分得越清晰，进而保证模型泛化能力越强，分类的可信度越高；反之，“分割带”越窄，说明模型的准确率越容易受到异常点的影响，进而理解为模型的预测能力越弱，分类的可信度越低。

线性可分的 所对应的函数间隔满足 的条件，故 就等于 。所以，可以将目标函数 等价为如下的表达式：

假设存在一个需要最小化的目标函数 ，并且该目标函数同时受到 的约束。如需得到最优化的解，则需要利用拉格朗日对偶性将原始的最优化问题转换为对偶问题，即：

分割面的求解

分割面的表达式

对于非线性SVM模型而言，需要经过两个步骤，一个是将原始空间中的样本点映射到高维的新空间中，另一个是在新空间中寻找一个用于识别各类别样本点线性“超平面”。
假设原始空间中的样本点为 ，将样本通过某种转换 映射到高维空间中，则非线性SVM模型的目标函数可以表示为：

其中，内积 可以利用核函数替换，即 。对于上式而言，同样需要计算最优的拉格朗日乘积 ，进而可以得到线性“超平面” 与 的值：

假设原始空间中的两个样本点为 ，在其扩展到高维空间后，它们的内积 如果等于样本点 在原始空间中某个函数的输出，那么该函数就称为核函数。
线性核函数的表达式为 ，故对应的分割“超平面”为：

多项式核函数的表达式为 ，故对应的分割“超平面”为：

高斯核函数的表达式为 ，故对应的分割“超平面”为：

Sigmoid 核函数的表达式为 ，故对应的分割“超平面”为：

在实际应用中， SVM 模型对核函数的选择是非常敏感的，所以需要通过先验的领域知识或者交叉验证的方法选出合理的核函数。大多数情况下，选择高斯核函数是一种相对偷懒而有效的方法，因为高斯核是一种指数函数，它的泰勒展开式可以是无穷维的，即相当于把原始样本点映射到高维空间中。

output_13_0.png

那些年被我坑过的Python——第十三章：一夫当关（设计堡垒机）

堡垒机架构 

堡垒机的主要作用权限控制和用户行为审计，堡垒机就像一个城堡的大门，城堡里的所有建筑就是你不同的业务系统 ， 每个想进入城堡的人都必须经过城堡大门并经过大门守卫的授权，每个进入城堡的人必须且只能严格按守卫的分配进入指定的建筑，且每个建筑物还有自己的权限访 问控制，不同级别的人可以到建筑物里不同楼层的访问级别也是不一样的。还有就是，每个进入城堡的人的所有行为和足迹都会被严格的监控和纪录下来，一旦发生 犯罪事件，城堡管理人员就可以通过这些监控纪录来追踪责任人。 

 堡垒要想成功完全记到他的作用，只靠堡垒机本身是不够的， 还需要一系列安全上对用户进行限制的配合，堡垒机部署上后，同时要确保你的网络达到以下条件：

• 所有人包括运维、开发等任何需要访问业务系统的人员，只能通过堡垒机访问业务系统
  • 回收所有对业务系统的访问权限，做到除了堡垒机管理人员，没有人知道业务系统任何机器的登录密码
  • 网络上限制所有人员只能通过堡垒机的跳转才能访问业务系统 
• 确保除了堡垒机管理员之外，所有其它人对堡垒机本身无任何操作权限，只有一个登录跳转功能
• 确保用户的操作纪录不能被用户自己以任何方式获取到并篡改　　

堡垒机表结构设计

对象分析：

需要堡垒机管理的对象包括：人员、人员组、系统账户+登录认证+账户权限（唯一通道）、主机、主机组、操作日志（命令、上传、下载）

PyYaml模块的使用

 1 import yaml
 2 
 3 try:
 4     from yaml import CLoader as Loader, CDumper as Dumper
 5 except ImportError:
 6     from yaml import Loader, Dumper
 7 
 8 
 9 def print_err(msg, quit=False):
10     output = "\\033[31;1mError: %s\\033[0m" % msg
11     if quit:
12         exit(output)
13     else:
14         print(output)
15 
16 
17 def yaml_parser(yml_filename):
18     ‘‘‘
19     load yaml file and return
20     :param yml_filename:
21     :return:
22     ‘‘‘
23     # yml_filename = "%s/%s.yml" % (settings.StateFileBaseDir,yml_filename)
24     try:
25         yaml_file = open(yml_filename, ‘r‘)
26         data = yaml.load(yaml_file)
27         return data
28     except Exception as e:
29         print_err(e)

PyYaml示例

http://pyyaml.org/wiki/PyYAMLDocumentation

YAML syntax

A good introduction to the YAML syntax is  Chapter 2 of the YAML specification.

You may also check  the YAML cookbook. Note that it is focused on a Ruby implementation and uses the old YAML 1.0 syntax.

Here we present most common YAML constructs together with the corresponding Python objects.

Documents

YAML stream is a collection of zero or more documents. An empty stream contains no documents. Documents are separated with ---. Documents may optionally end with .... A single document may or may not be marked with ---.

Example of an implicit document:

- Multimedia
- Internet
- Education

Example of an explicit document:

---
- Afterstep
- CTWM
- Oroborus
...

Example of several documents in the same stream:

---
- Ada
- APL
- ASP

- Assembly
- Awk
---
- Basic
---
- C
- C#    # Note that comments are denoted with ‘ #‘ (space then #).
- C++
- Cold Fusion

Block sequences

In the block context, sequence entries are denoted by - (dash then space):

# YAML
- The Dagger ‘Narthanc‘
- The Dagger ‘Nimthanc‘
- The Dagger ‘Dethanc‘

# Python
["The Dagger ‘Narthanc‘", "The Dagger ‘Nimthanc‘", "The Dagger ‘Dethanc‘"]

Block sequences can be nested:

# YAML
-
  - HTML
  - LaTeX
  - SGML
  - VRML
  - XML
  - YAML
-
  - BSD
  - GNU Hurd
  - Linux

# Python
[[‘HTML‘, ‘LaTeX‘, ‘SGML‘, ‘VRML‘, ‘XML‘, ‘YAML‘], [‘BSD‘, ‘GNU Hurd‘, ‘Linux‘]]

It‘s not necessary to start a nested sequence with a new line:

# YAML
- 1.1
- - 2.1
  - 2.2
- - - 3.1
    - 3.2
    - 3.3

# Python
[1.1, [2.1, 2.2], [[3.1, 3.2, 3.3]]]

A block sequence may be nested to a block mapping. Note that in this case it is not necessary to indent the sequence.

# YAML
left hand:
- Ring of Teleportation
- Ring of Speed

right hand:
- Ring of Resist Fire
- Ring of Resist Cold
- Ring of Resist Poison

# Python
{‘right hand‘: [‘Ring of Resist Fire‘, ‘Ring of Resist Cold‘, ‘Ring of Resist Poison‘],
‘left hand‘: [‘Ring of Teleportation‘, ‘Ring of Speed‘]}

Block mappings

In the block context, keys and values of mappings are separated by : (colon then space):

# YAML
base armor class: 0
base damage: [4,4]
plus to-hit: 12
plus to-dam: 16
plus to-ac: 0

# Python
{‘plus to-hit‘: 12, ‘base damage‘: [4, 4], ‘base armor class‘: 0, ‘plus to-ac‘: 0, ‘plus to-dam‘: 16}

Complex keys are denoted with ? (question mark then space):

# YAML
? !!python/tuple [0,0]
: The Hero
? !!python/tuple [0,1]
: Treasure
? !!python/tuple [1,0]
: Treasure
? !!python/tuple [1,1]
: The Dragon

# Python
{(0, 1): ‘Treasure‘, (1, 0): ‘Treasure‘, (0, 0): ‘The Hero‘, (1, 1): ‘The Dragon‘}

Block mapping can be nested:

# YAML
hero:
  hp: 34
  sp: 8
  level: 4
orc:
  hp: 12
  sp: 0
  level: 2

# Python
{‘hero‘: {‘hp‘: 34, ‘sp‘: 8, ‘level‘: 4}, ‘orc‘: {‘hp‘: 12, ‘sp‘: 0, ‘level‘: 2}}

A block mapping may be nested in a block sequence:

# YAML
- name: PyYAML
  status: 4
  license: MIT
  language: Python
- name: PySyck
  status: 5
  license: BSD
  language: Python

# Python
[{‘status‘: 4, ‘language‘: ‘Python‘, ‘name‘: ‘PyYAML‘, ‘license‘: ‘MIT‘},
{‘status‘: 5, ‘license‘: ‘BSD‘, ‘name‘: ‘PySyck‘, ‘language‘: ‘Python‘}]

Flow collections

The syntax of flow collections in YAML is very close to the syntax of list and dictionary constructors in Python:

# YAML
{ str: [15, 17], con: [16, 16], dex: [17, 18], wis: [16, 16], int: [10, 13], chr: [5, 8] }

# Python
{‘dex‘: [17, 18], ‘int‘: [10, 13], ‘chr‘: [5, 8], ‘wis‘: [16, 16], ‘str‘: [15, 17], ‘con‘: [16, 16]}

Scalars

There are 5 styles of scalars in YAML: plain, single-quoted, double-quoted, literal, and folded:

# YAML
plain: Scroll of Remove Curse
single-quoted: ‘EASY_KNOW‘
double-quoted: "?"
literal: |    # Borrowed from http://www.kersbergen.com/flump/religion.html
  by hjw              ___
     __              /.-.    /  )_____________\\\\  Y
   /_ /=== == === === =\\ _\\_
  ( /)=== == === === == Y      `-------------------(  o  )
                        \\___/
folded: >
  It removes all ordinary curses from all equipped items.
  Heavy or permanent curses are unaffected.

# Python
{‘plain‘: ‘Scroll of Remove Curse‘,
‘literal‘:
    ‘by hjw              ___\\n‘
    ‘   __              /.-.\\\\\\n‘
    ‘  /  )_____________\\\\\\\\  Y\\n‘
    ‘ /_ /=== == === === =\\\\ _\\\\_\\n‘
    ‘( /)=== == === === == Y   \\\\\\n‘
    ‘ `-------------------(  o  )\\n‘
    ‘                      \\\\___/\\n‘,
‘single-quoted‘: ‘EASY_KNOW‘,
‘double-quoted‘: ‘?‘,
‘folded‘: ‘It removes all ordinary curses from all equipped items. Heavy or permanent curses are unaffected.\\n‘}

Each style has its own quirks. A plain scalar does not use indicators to denote its start and end, therefore it‘s the most restricted style. Its natural applications are names of attributes and parameters.

Using single-quoted scalars, you may express any value that does not contain special characters. No escaping occurs for single quoted scalars except that a pair of adjacent quotes ‘‘ is replaced with a lone single quote ‘.

Double-quoted is the most powerful style and the only style that can express any scalar value. Double-quoted scalars allow escaping. Using escaping sequences \\x** and \\u****, you may express any ASCII or Unicode character.

There are two kind of block scalar styles: literal and folded. The literal style is the most suitable style for large block of text such as source code. The folded style is similar to the literal style, but two adjacent non-empty lines are joined to a single line separated by a space character.

Aliases

Note that PyYAML does not yet support recursive objects.

Using YAML you may represent objects of arbitrary graph-like structures. If you want to refer to the same object from different parts of a document, you need to use anchors and aliases.

Anchors are denoted by the & indicator while aliases are denoted by *. For instance, the document

left hand: &A
  name: The Bastard Sword of Eowyn
  weight: 30
right hand: *A

expresses the idea of a hero holding a heavy sword in both hands.

PyYAML now fully supports recursive objects. For instance, the document

&A [ *A ]

will produce a list object containing a reference to itself.

Tags

Tags are used to denote the type of a YAML node. Standard YAML tags are defined at  http://yaml.org/type/index.html.

Tags may be implicit:

boolean: true
integer: 3
float: 3.14

{‘boolean‘: True, ‘integer‘: 3, ‘float‘: 3.14}

or explicit:

boolean: !!bool "true"
integer: !!int "3"
float: !!float "3.14"

{‘boolean‘: True, ‘integer‘: 3, ‘float‘: 3.14}

Plain scalars without explicitly defined tags are subject to implicit tag resolution. The scalar value is checked against a set of regular expressions

and if one of them matches, the corresponding tag is assigned to the scalar. PyYAML allows an application to add custom implicit tag resolvers.

YAML tags and Python types

The following table describes how nodes with different tags are converted to Python objects.

YAML tag	Python type
Standard YAML tags
!!null	None
!!bool	bool
!!int	int or long (int in Python 3)
!!float	float
!!binary	str (bytes in Python 3)
!!timestamp	datetime.datetime
!!omap, !!pairs	list of pairs
!!set	set
!!str	str or unicode (str in Python 3)
!!seq	list
!!map	dict
Python-specific tags
!!python/none	None
!!python/bool	bool
!!python/bytes	(bytes in Python 3)
!!python/str	str (str in Python 3)
!!python/unicode	unicode (str in Python 3)
!!python/int	int
!!python/long	long (int in Python 3)
!!python/float	float
!!python/complex	complex
!!python/list	list
!!python/tuple	tuple
!!python/dict	dict
Complex Python tags
!!python/name:module.name	module.name
!!python/module:package.module	package.module
!!python/object:module.cls	module.cls instance
!!python/object/new:module.cls	module.cls instance
!!python/object/apply:module.f	value of f(...)

String conversion (Python 2 only)

There are four tags that are converted to str and unicode values: !!str, !!binary, !!python/str, and !!python/unicode.

!!str-tagged scalars are converted to str objects if its value is ASCII. Otherwise it is converted to unicode. !!binary-tagged scalars are converted to str objects with its value decoded using the base64 encoding. !!python/str scalars are converted to str objects encoded with utf-8 encoding. !!python/unicode scalars are converted to unicode objects.

Conversely, a str object is converted to

1. a !!str scalar if its value is ASCII.
2. a !!python/str scalar if its value is a correct utf-8 sequence.
3. a !!binary scalar otherwise.

A unicode object is converted to

1. a !!python/unicode scalar if its value is ASCII.
2. a !!str scalar otherwise.

String conversion (Python 3 only)

In Python 3, str objects are converted to !!str scalars and bytes objects to !!binary scalars. For compatibility reasons, tags !!python/str and !!python/unicode are still supported and converted to str objects.

Names and modules

In order to represent static Python objects like functions or classes, you need to use a complex !!python/name tag. For instance, the function yaml.dump can be represented as

!!python/name:yaml.dump

Similarly, modules are represented using the tag !python/module:

!!python/module:yaml

Objects

Any pickleable object can be serialized using the !!python/object tag:

!!python/object:module.Class { attribute: value, ... }

In order to support the pickle protocol, two additional forms of the !!python/object tag are provided:

!!python/object/new:module.Class
args: [argument, ...]
kwds: {key: value, ...}
state: ...
listitems: [item, ...]
dictitems: [key: value, ...]

!!python/object/apply:module.function
args: [argument, ...]
kwds: {key: value, ...}
state: ...
listitems: [item, ...]
dictitems: [key: value, ...]

If only the args field is non-empty, the above records can be shortened:

!!python/object/new:module.Class [argument, ...]

!!python/object/apply:module.function [argument, ...]

Reference

Warning: API stability is not guaranteed‘‘‘

The yaml package

scan(stream, Loader=Loader)

scan(stream) scans the given stream and produces a sequence of tokens.

parse(stream, Loader=Loader)

emit(events, stream=None, Dumper=Dumper,
    canonical=None,
    indent=None,
    width=None,
    allow_unicode=None,
    line_break=None)

parse(stream) parses the given stream and produces a sequence of parsing events.

emit(events, stream=None) serializes the given sequence of parsing events and writes them to the stream. if stream is None, it returns the produced stream.

compose(stream, Loader=Loader)
compose_all(stream, Loader=Loader)

serialize(node, stream=None, Dumper=Dumper,
    encoding=‘utf-8‘, # encoding=None (Python 3)
    explicit_start=None,
    explicit_end=None,
    version=None,
    tags=None,
    canonical=None,
    indent=None,
    width=None,
    allow_unicode=None,
    line_break=None)
serialize_all(nodes, stream=None, Dumper=Dumper, ...)

compose(stream) parses the given stream and returns the root of the representation graph for the first document in the stream. If there are no documents in the stream, it returns None.

compose_all(stream) parses the given stream and returns a sequence of representation graphs corresponding to the documents in the stream.

serialize(node, stream=None) serializes the given representation graph into the stream. If stream is None, it returns the produced stream.

serialize_all(node, stream=None) serializes the given sequence of representation graphs into the given stream. If stream is None, it returns the produced stream.

load(stream, Loader=Loader)
load_all(stream, Loader=Loader)

safe_load(stream)
safe_load_all(stream)

dump(data, stream=None, Dumper=Dumper,
    default_style=None,
    default_flow_style=None,
    encoding=‘utf-8‘, # encoding=None (Python 3)
    explicit_start=None,
    explicit_end=None,
    version=None,
    tags=None,
    canonical=None,
    indent=None,
    width=None,
    allow_unicode=None,
    line_break=None)
dump_all(data, stream=None, Dumper=Dumper, ...)

safe_dump(data, stream=None, ...)
safe_dump_all(data, stream=None, ...)

load(stream) parses the given stream and returns a Python object constructed from for the first document in the stream. If there are no documents in the stream, it returns None.

load_all(stream) parses the given stream and returns a sequence of Python objects corresponding to the documents in the stream.

safe_load(stream) parses the given stream and returns a Python object constructed from for the first document in the stream. If there are no documents in the stream, it returns None. safe_load recognizes only standard YAML tags and cannot construct an arbitrary Python object.

A python object can be marked as safe and thus be recognized by yaml.safe_load. To do this, derive it from yaml.YAMLObject (as explained in section Constructors, representers, resolvers) and explicitly set its class property yaml_loader to yaml.SafeLoader.

safe_load_all(stream) parses the given stream and returns a sequence of Python objects corresponding to the documents in the stream. safe_load_all recognizes only standard YAML tags and cannot construct an arbitrary Python object.

dump(data, stream=None) serializes the given Python object into the stream. If stream is None, it returns the produced stream.

dump_all(data, stream=None) serializes the given sequence of Python objects into the given stream. If stream is None, it returns the produced stream. Each object is represented as a YAML document.

safe_dump(data, stream=None) serializes the given Python object into the stream. If stream is None, it returns the produced stream. safe_dump produces only standard YAML tags and cannot represent an arbitrary Python object.

safe_dump_all(data, stream=None) serializes the given sequence of Python objects into the given stream. If stream is None, it returns the produced stream. Each object is represented as a YAML document. safe_dump_all produces only standard YAML tags and cannot represent an arbitrary Python object.

def constructor(loader, node):
    # ...
    return data

def multi_constructor(loader, tag_suffix, node):
    # ...
    return data

add_constructor(tag, constructor, Loader=Loader)
add_multi_constructor(tag_prefix, multi_constructor, Loader=Loader)

add_constructor(tag, constructor) specifies a constructor for the given tag. A constructor is a function that converts a node of a YAML representation graph to a native Python object. A constructor accepts an instance of Loader and a node and returns a Python object.

add_multi_constructor(tag_prefix, multi_constructor) specifies a multi_constructor for the given tag_prefix. A multi-constructor is a function that converts a node of a YAML representation graph to a native Python object. A multi-constructor accepts an instance of Loader, the suffix of the node tag, and a node and returns a Python object.

def representer(dumper, data):
    # ...
    return node

def multi_representer(dumper, data):
    # ...
    return node

add_representer(data_type, representer, Dumper=Dumper)
add_multi_representer(base_data_type, multi_representer, Dumper=Dumper)

add_representer(data_type, representer) specifies a representer for Python objects of the given data_type. A representer is a function that converts a native Python object to a node of a YAML representation graph. A representer accepts an instance of Dumper and an object and returns a node.

add_multi_representer(base_data_type, multi_representer) specifies a multi_representer for Python objects of the given base_data_type or any of its subclasses. A multi-representer is a function that converts a native Python object to a node of a YAML representation graph. A multi-representer accepts an instance of Dumper and an object and returns a node.

add_implicit_resolver(tag, regexp, first, Loader=Loader, Dumper=Dumper)
add_path_resolver(tag, path, kind, Loader=Loader, Dumper=Dumper)

add_implicit_resolver(tag, regexp, first) adds an implicit tag resolver for plain scalars. If the scalar value is matched the given regexp, it is assigned the tag. first is a list of possible initial characters or None.

add_path_resolver(tag, path, kind) adds a path-based implicit tag resolver. A path is a list of keys that form a path to a node in the representation graph. Paths elements can be string values, integers, or None. The kind of a node can be str, list, dict, or None.

Mark

Mark(name, index, line, column, buffer, pointer)

An instance of Mark points to a certain position in the input stream. name is the name of the stream, for instance it may be the filename if the input stream is a file. line and column is the line and column of the position (starting from 0). buffer, when it is not None, is a part of the input stream that contain the position and pointer refers to the position in the buffer.

YAMLError

YAMLError()

If the YAML parser encounters an error condition, it raises an exception which is an instance of YAMLError or of its subclass. An application may catch this exception and warn a user.

try:
    config = yaml.load(file(‘config.yaml‘, ‘r‘))
except yaml.YAMLError, exc:
    print "Error in configuration file:", exc

An exception produced by the YAML processor may point to the problematic position.

>>> try:
...     yaml.load("unbalanced blackets: ][")
... except yaml.YAMLError, exc:
...     if hasattr(exc, ‘problem_mark‘):
...         mark = exc.problem_mark
...         print "Error position: (%s:%s)" % (mark.line+1, mark.column+1)

Error position: (1:22)

Tokens

Tokens are produced by a YAML scanner. They are not really useful except for low-level YAML applications such as syntax highlighting.

The PyYAML scanner produces the following types of tokens:

StreamStartToken(encoding, start_mark, end_mark) # Start of the stream.
StreamEndToken(start_mark, end_mark) # End of the stream.
DirectiveToken(name, value, start_mark, end_mark) # YAML directive, either %YAML or %TAG.
DocumentStartToken(start_mark, end_mark) # ‘---‘.
DocumentEndToken(start_mark, end_mark) # ‘...‘.
BlockSequenceStartToken(start_mark, end_mark) # Start of a new block sequence.
BlockMappingStartToken(start_mark, end_mark) # Start of a new block mapping.
BlockEndToken(start_mark, end_mark) # End of a block collection.
FlowSequenceStartToken(start_mark, end_mark) # ‘[‘.
FlowMappingStartToken(start_mark, end_mark) # ‘{‘.
FlowSequenceEndToken(start_mark, end_mark) # ‘]‘.
FlowMappingEndToken(start_mark, end_mark) # ‘}‘.
KeyToken(start_mark, end_mark) # Either ‘?‘ or start of a simple key.
ValueToken(start_mark, end_mark) # ‘:‘.
BlockEntryToken(start_mark, end_mark) # ‘-‘.
FlowEntryToken(start_mark, end_mark) # ‘,‘.
AliasToken(value, start_mark, end_mark) # ‘*value‘.
AnchorToken(value, start_mark, end_mark) # ‘&value‘.
TagToken(value, start_mark, end_mark) # ‘!value‘.
ScalarToken(value, plain, style, start_mark, end_mark) # ‘value‘.

start_mark and end_mark denote the beginning and the end of a token.

Example:

>>> document = """
... ---
... block sequence:
... - BlockEntryToken
... block mapping:
...   ? KeyToken
...   : ValueToken
... flow sequence: [FlowEntryToken, FlowEntryToken]
... flow mapping: {KeyToken: ValueToken}
... anchors and tags:
... - &A !!int ‘5‘
... - *A
... ...
... """

>>> for token in yaml.scan(document):
...     print token

StreamStartToken(encoding=‘utf-8‘)

DocumentStartToken()

BlockMappingStartToken()

KeyToken()
ScalarToken(plain=True, style=None, value=u‘block sequence‘)

ValueToken()
BlockEntryToken()
ScalarToken(plain=True, style=None, value=u‘BlockEntryToken‘)

KeyToken()
ScalarToken(plain=True, style=None, value=u‘block mapping‘)

ValueToken()
BlockMappingStartToken()

KeyToken()
ScalarToken(plain=True, style=None, value=u‘KeyToken‘)
ValueToken()
ScalarToken(plain=True, style=None, value=u‘ValueToken‘)
BlockEndToken()

KeyToken()
ScalarToken(plain=True, style=None, value=u‘flow sequence‘)

ValueToken()
FlowSequenceStartToken()
ScalarToken(plain=True, style=None, value=u‘FlowEntryToken‘)
FlowEntryToken()
ScalarToken(plain=True, style=None, value=u‘FlowEntryToken‘)
FlowSequenceEndToken()

KeyToken()
ScalarToken(plain=True, style=None, value=u‘flow mapping‘)

ValueToken()
FlowMappingStartToken()
KeyToken()
ScalarToken(plain=True, style=None, value=u‘KeyToken‘)
ValueToken()
ScalarToken(plain=True, style=None, value=u‘ValueToken‘)
FlowMappingEndToken()

KeyToken()
ScalarToken(plain=True, style=None, value=u‘anchors and tags‘)

ValueToken()
BlockEntryToken()
AnchorToken(value=u‘A‘)
TagToken(value=(u‘!!‘, u‘int‘))
ScalarToken(plain=False, style="‘", value=u‘5‘)

BlockEntryToken()
AliasToken(value=u‘A‘)

BlockEndToken()

DocumentEndToken()

StreamEndToken()

Events

Events are used by the low-level Parser and Emitter interfaces, which are similar to the SAX API. While the Parser parses a YAML stream and produces a sequence of events, the Emitter accepts a sequence of events and emits a YAML stream.

The following events are defined:

StreamStartEvent(encoding, start_mark, end_mark)
StreamEndEvent(start_mark, end_mark)
DocumentStartEvent(explicit, version, tags, start_mark, end_mark)
DocumentEndEvent(start_mark, end_mark)
SequenceStartEvent(anchor, tag, implicit, flow_style, start_mark, end_mark)
SequenceEndEvent(start_mark, end_mark)
MappingStartEvent(anchor, tag, implicit, flow_style, start_mark, end_mark)
MappingEndEvent(start_mark, end_mark)
AliasEvent(anchor, start_mark, end_mark)
ScalarEvent(anchor, tag, implicit, value, style, start_mark, end_mark)

The flow_style flag indicates if a collection is block or flow. The possible values are None, True, False. The style flag of a scalar event indicates the style of the scalar. Possible values are None, ‘‘, ‘\\‘‘, ‘"‘, ‘|‘, ‘>‘. The implicit flag of a collection start event indicates if the tag may be omitted when the collection is emitted. The implicit flag of a scalar event is a pair of boolean values that indicate if the tag may be omitted when the scalar is emitted in a plain and non-plain style correspondingly.

Example:

>>> document = """
... scalar: &A !!int ‘5‘
... alias: *A
... sequence: [1, 2, 3]
... mapping: [1: one, 2: two, 3: three]
... """

>>> for event in yaml.parse(document):
...     print event

StreamStartEvent()

DocumentStartEvent()

MappingStartEvent(anchor=None, tag=None, implicit=True)

ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘scalar‘)
ScalarEvent(anchor=u‘A‘, tag=u‘tag:yaml.org,2002:int‘, implicit=(False, False), value=u‘5‘)

ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘alias‘)
AliasEvent(anchor=u‘A‘)

ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘sequence‘)
SequenceStartEvent(anchor=None, tag=None, implicit=True)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘1‘)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘2‘)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘3‘)
SequenceEndEvent()

ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘mapping‘)
MappingStartEvent(anchor=None, tag=None, implicit=True)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘1‘)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘one‘)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘2‘)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘two‘)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘3‘)
ScalarEvent(anchor=None, tag=None, implicit=(True, False), value=u‘three‘)
MappingEndEvent()

MappingEndEvent()

DocumentEndEvent()

StreamEndEvent()

>>> print yaml.emit([
...     yaml.StreamStartEvent(encoding=‘utf-8‘),
...     yaml.DocumentStartEvent(explicit=True),
...     yaml.MappingStartEvent(anchor=None, tag=u‘tag:yaml.org,2002:map‘, implicit=True, flow_style=False),
...     yaml.ScalarEvent(anchor=None, tag=u‘tag:yaml.org,2002:str‘, implicit=(True, True), value=u‘agile languages‘),
...     yaml.SequenceStartEvent(anchor=None, tag=u‘tag:yaml.org,2002:seq‘, implicit=True, flow_style=True),
...     yaml.ScalarEvent(anchor=None, tag=u‘tag:yaml.org,2002:str‘, implicit=(True, True), value=u‘Python‘),
...     yaml.ScalarEvent(anchor=None, tag=u‘tag:yaml.org,2002:str‘, implicit=(True, True), value=u‘Perl‘),
...     yaml.ScalarEvent(anchor=None, tag=u‘tag:yaml.org,2002:str‘, implicit=(True, True), value=u‘Ruby‘),
...     yaml.SequenceEndEvent(),
...     yaml.MappingEndEvent(),
...     yaml.DocumentEndEvent(explicit=True),
...     yaml.StreamEndEvent(),
... ])

---
agile languages: [Python, Perl, Ruby]
...

Nodes

Nodes are entities in the YAML informational model. There are three kinds of nodes: scalar, sequence, and mapping. In PyYAML, nodes are produced by Composer and can be serialized to a YAML stream by Serializer.

ScalarNode(tag, value, style, start_mark, end_mark)
SequenceNode(tag, value, flow_style, start_mark, end_mark)
MappingNode(tag, value, flow_style, start_mark, end_mark)

The style and flow_style flags have the same meaning as for events. The value of a scalar node must be a unicode string. The value of a sequence node is a list of nodes. The value of a mapping node is a list of pairs consisting of key and value nodes.

Example:

>>> print yaml.compose("""
... kinds:
... - scalar
... - sequence
... - mapping
... """)

MappingNode(tag=u‘tag:yaml.org,2002:map‘, value=[
    (ScalarNode(tag=u‘tag:yaml.org,2002:str‘, value=u‘kinds‘), SequenceNode(tag=u‘tag:yaml.org,2002:seq‘, value=[
        ScalarNode(tag=u‘tag:yaml.org,2002:str‘, value=u‘scalar‘),
        ScalarNode(tag=u‘tag:yaml.org,2002:str‘, value=u‘sequence‘),
        ScalarNode(tag=u‘tag:yaml.org,2002:str‘, value=u‘mapping‘)]))])

>>> print yaml.serialize(yaml.SequenceNode(tag=u‘tag:yaml.org,2002:seq‘, value=[
...     yaml.ScalarNode(tag=u‘tag:yaml.org,2002:str‘, value=u‘scalar‘),
...     yaml.ScalarNode(tag=u‘tag:yaml.org,2002:str‘, value=u‘sequence‘),
...     yaml.ScalarNode(tag=u‘tag:yaml.org,2002:str‘, value=u‘mapping‘)]))

- scalar
- sequence
- mapping

Loader

Loader(stream)
SafeLoader(stream)
BaseLoader(stream)

# The following classes are available only if you build LibYAML bindings.
CLoader(stream)
CSafeLoader(stream)
CBaseLoader(stream)

Loader(stream) is the most common of the above classes and should be used in most cases. stream is an input YAML stream. It can be a string, a Unicode string, an open file, an open Unicode file.

Loader supports all predefined tags and may construct an arbitrary Python object. Therefore it is not safe to use Loader to load a document received from an untrusted source. By default, the functions scan, parse, compose, construct, and others use Loader.

SafeLoader(stream) supports only standard YAML tags and thus it does not construct class instances and probably safe to use with documents received from an untrusted source. The functions safe_load and safe_load_all use SafeLoader to parse a stream.

BaseLoader(stream) does not resolve or support any tags and construct only basic Python objects: lists, dictionaries and Unicode strings.

CLoader, CSafeLoader, CBaseLoader are versions of the above classes written in C using the LibYAML library.

Loader.check_token(*TokenClasses)
Loader.peek_token()
Loader.get_token()

Loader.check_token(*TokenClasses) returns True if the next token in the stream is an instance of one of the given TokenClasses. Otherwise it returns False.

Loader.peek_token() returns the next token in the stream, but does not remove it from the internal token queue. The function returns None at the end of the stream.

Loader.get_token() returns the next token in the stream and removes it from the internal token queue. The function returns None at the end of the stream.

Loader.check_event(*EventClasses)
Loader.peek_event()
Loader.get_event()

Loader.check_event(*EventClasses) returns True if the next event in the stream is an instance of one of the given EventClasses. Otherwise it returns False.

Loader.peek_event() returns the next event in the stream, but does not remove it from the internal event queue. The function returns None at the end of the stream.

Loader.get_event() returns the next event in the stream and removes it from the internal event queue. The function returns None at the end of the stream.

Loader.check_node()
Loader.get_node()

Loader.check_node() returns True is there are more documents available in the stream. Otherwise it returns False.

Loader.get_node() construct the representation graph of the next document in the stream and returns its root node.

Loader.check_data()
Loader.get_data()

Loader.add_constructor(tag, constructor) # Loader.add_constructor is a class method.
Loader.add_multi_constructor(tag_prefix, multi_constructor) # Loader.add_multi_constructor is a class method.

Loader.construct_scalar(node)
Loader.construct_sequence(node)
Loader.construct_mapping(node)

Loader.check_data() returns True is there are more documents available in the stream. Otherwise it returns False.

Loader.get_data() constructs and returns a Python object corresponding to the next document in the stream.

Loader.add_constructor(tag, constructor): see add_constructor.

Loader.add_multi_constructor(tag_prefix, multi_constructor): see add_multi_constructor.

Loader.construct_scalar(node) checks that the given node is a scalar and returns its value. This function is intended to be used in constructors.

Loader.construct_sequence(node) checks that the given node is a sequence and returns a list of Python objects corresponding to the node items. This function is intended to be used in constructors.

Loader.construct_mapping(node) checks that the given node is a mapping and returns a dictionary of Python objects corresponding to the node keys and values. This function is intended to be used in constructors.

Loader.add_implicit_resolver(tag, regexp, first) # Loader.add_implicit_resolver is a class method.
Loader.add_path_resolver(tag, path, kind) # Loader.add_path_resolver is a class method.

Loader.add_implicit_resolver(tag, regexp, first): see add_implicit_resolver.

Loader.add_path_resolver(tag, path, kind): see add_path_resolver.

Dumper

Dumper(stream,
    default_style=None,
    default_flow_style=None,
    canonical=None,
    indent=None,
    width=None,
    allow_unicode=None,
    line_break=None,
    encoding=None,
    explicit_start=None,
    explicit_end=None,
    version=None,
    tags=None)
SafeDumper(stream, ...)
BaseDumper(stream, ...)

# The following classes are available only if you build LibYAML bindings.
CDumper(stream, ...)
CSafeDumper(stream, ...)
CBaseDumper(stream, ...)

Dumper(stream) is the most common of the above classes and should be used in most cases. stream is an output YAML stream. It can be an open file or an open Unicode file.

Dumper supports all predefined tags and may represent an arbitrary Python object. Therefore it may produce a document that cannot be loaded by other YAML processors. By default, the functions emit, serialize, dump, and others use Dumper.

SafeDumper(stream) produces only standard YAML tags and thus cannot represent class instances and probably more compatible with other YAML processors. The functions safe_dump and safe_dump_all use SafeDumper to produce a YAML document.

BaseDumper(stream) does not support any tags and is useful only for subclassing.

CDumper, CSafeDumper, CBaseDumper are versions of the above classes written in C using the LibYAML library.

Dumper.emit(event)

Dumper.emit(event) serializes the given event and writes it to the output stream.

Dumper.open()
Dumper.serialize(node)
Dumper.close()

Dumper.open() emits StreamStartEvent.

Dumper.serialize(node) serializes the given representation graph into the output stream.

Dumper.close() emits StreamEndEvent.

Dumper.represent(data)

Dumper.add_representer(data_type, representer) # Dumper.add_representer is a class method.
Dumper.add_multi_representer(base_data_type, multi_representer) # Dumper.add_multi_representer is a class method.

Dumper.represent_scalar(tag, value, style=None)
Dumper.represent_sequence(tag, value, flow_style=None)
Dumper.represent_mapping(tag, value, flow_style=None)

Dumper.represent(data) serializes the given Python object to the output YAML stream.

Dumper.add_representer(data_type, representer): see add_representer.

Dumper.add_multi_representer(base_data_type, multi_representer): see add_multi_representer.

Dumper.represent_scalar(tag, value, style=None) returns a scalar node with the given tag, value, and style. This function is intended to be used in representers.

Dumper.represent_sequence(tag, sequence, flow_style=None) return a sequence node with the given tag and subnodes generated from the items of the given sequence.

Dumper.represent_mapping(tag, mapping, flow_style=None) return a mapping node with the given tag and subnodes generated from the keys and values of the given mapping.

Dumper.add_implicit_resolver(tag, regexp, first) # Dumper.add_implicit_resolver is a class method.
Dumper.add_path_resolver(tag, path, kind) # Dumper.add_path_resolver is a class method.

Dumper.add_implicit_resolver(tag, regexp, first): see add_implicit_resolver.

Dumper.add_path_resolver(tag, path, kind): see add_path_resolver.

YAMLObject

class MyYAMLObject(YAMLObject):
    yaml_loader = Loader
    yaml_dumper = Dumper

    yaml_tag = u‘...‘
    yaml_flow_style = ...

    @classmethod
    def from_yaml(cls, loader, node):
        # ...
        return data

    @classmethod
    def to_yaml(cls, dumper, data):
        # ...
        return node

Subclassing YAMLObject is an easy way to define tags, constructors, and representers for your classes. You only need to override the yaml_tag attribute. If you want to define your custom constructor and representer, redefine the from_yaml and to_yaml method correspondingly.

Deviations from the specification

need to update this section

• rules for tabs in YAML are confusing. We are close, but not there yet. Perhaps both the spec and the parser should be fixed. Anyway, the best rule for tabs in YAML is to not use them at all.
• Byte order mark. The initial BOM is stripped, but BOMs inside the stream are considered as parts of the content. It can be fixed, but it‘s not really important now.
• Empty plain scalars are not allowed if alias or tag is specified. This is done to prevent anomalities like [ !tag, value], which can be interpreted both as [ !<!tag,> value ] and [ !<!tag> "", "value" ]. The spec should be fixed.
• Indentation of flow collections. The spec requires them to be indented more than their block parent node. Unfortunately this rule renders many intuitively correct constructs invalid, for instance,

  block: {
  } # this is indentation violation according to the spec.
  

• ‘:‘ is not allowed for plain scalars in the flow mode. {1:2} is interpreted as { 1 : 2 }.

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