1. Yaml file introduction

Yaml is a special language for writing configuration files.

1. Yaml file rules
  • Case sensitive;
  • Use indentation to indicate hierarchy;
  • useThe blank space keyThe indentation, andThe Tab keyThe indentation
  • The number of indent Spaces is not fixed, only elements of the same level need to be aligned to the left;
  • Strings in the file do not need to be marked with quotation marks. However, if the string contains special characters, it must be marked with quotation marks.
  • The comment is identified with #
2. Yaml file data structure
  • Object: A collection of key-value pairs (” mapping or dictionary “for short). Key-value pairs are represented by colons (:), separated by Spaces
  • Array: An array of ordered values (” sequence or list “for short) preceded by a hyphen (-), separated by a space
  • Scalars: Single, non-separable values (strings, bool, integer, floating point, time, date, null, etc.) None can be represented by ~ with null

Read yamL configuration files in Python

1. Prerequisites

To read yaml files in Python, you need to install Pyyaml and import yaml modules:

  • To use YAMl, install pyyaml (pip3 install pyyaml);
  • The imported module is YAMl (import yaml)
2. Read yamL file data

Python reads file data in open mode and converts the data into a list or dictionary using the load function.

import yaml
import os

def get_yaml_data(yaml_file) :
    Open the YAML file
    print("*** Get yamL file data ***")
    file = open(yaml_file, 'r', encoding="utf-8")
    file_data = file.read()
    file.close()
    
    print(file_data)
    print("Type:".type(file_data))

    # Convert strings to dictionaries or lists
    print("*** Convert YAML data to dictionaries or lists ***")
    data = yaml.load(file_data)
    print(data)
    print("Type:".type(data))
    return data
current_path = os.path.abspath(".")
yaml_path = os.path.join(current_path, "config.yaml")
get_yaml_data(yaml_path)

Usr: my PSW: 123455 Type: 
      
        *** Convert YAMl data to dictionaries or lists *** {'usr': 'my', 'PSW ': 123455}
      
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3. The yamL file contains key-value pairs

(1) Contents in yamL file are key-value pairs:

# YAMl key-value pair: dictionary in Python
usr: my
psw: 123455
s: " abc\n"
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Python retrieves data from yaml files:

{'usr': 'my'.'psw': 123455, 's': ' abc\n'}
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(2) YamL file contains contents of “key-value pair ‘nested” key-value pair

# yamL key-value pair nesting: dictionary nesting in Python
usr1:
  name: a
  psw: 123
usr2:
  name: b
  psw: 456
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Python retrieves data from yaml files:

{'usr1': {'name': 'a'.'psw': 123}.'usr2': {'name': 'b'.'psw': 456}}
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(3) “array” nested in “key-value pair” in YAML file

# nested arrays in yamL key-value pairs
usr3:
  - a
  - b
  - c
usr4:
  - b
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Python retrieves data from yaml files:

{'usr3': ['a'.'b'.'c'].'usr4': ['b']}
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4. Yaml file data is an array

(1) YamL file contains an array

# yaml array
- a
- b
- 5
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Python retrieves data from yaml files:

['a', 'b', 5]
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(2) “key-value pairs” nested in yamL file “Array”

# yaml"Array"The nested"Key value pair"
- usr1: aaa
- psw1: 111
  usr2: bbb
  psw2: 222
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Python retrieves data from yaml files:

[{'usr1': 'aaa'}, {'psw1': 111, 'usr2': 'bbb'.'psw2': 222}]
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5. Basic data types in YAML files:
# scalar s_val: name's_val': 'name'}
spec_s_val: "name\n"# special string: {'spec_s_val': 'name\n'
num_val: 31.14# number: {'num_val': 31.14}
bol_val: true# Boolean: {'bol_val': True}
nul_val: null           # nullValue: {'nul_val': None}
nul_val1: ~             # nullValue: {'nul_val1': None}
time_val: 2018- 03- 01t11:33:22.55- 06:00# time value: {'time_val': datetime.datetime(2018.3.1.17.33.22.550000)}
date_val: 2019- 01- 10# date value: {'date_val': datetime.date(2019.1.10)}
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6. Reference in the YAML file

Yaml file contents

animal3: &animal3 fish
test: *animal3
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Data read by Python

{'animal3': 'fish'.'test': 'fish'}
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Read multiple YAML documents in Python

1. Multiple documents in a YAML file are segmented using a — partition method

For example, data in yamL files

Segment multiple documents in a YAML file
---
animal1: dog
age: 2
---
animal2: cat
age: 3
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2. The Python script reads multiple document methods in a YAML file

Python retrieves yamL data using the load_all function to parse the entire document and read the data from the object

When a YAML file contains multiple documents, fetch the data from the documents separately
def get_yaml_load_all(yaml_file) :
    Open the YAML file
    file = open(yaml_file, 'r', encoding="utf-8")
    file_data = file.read()
    file.close()
    all_data = yaml.load_all(file_data)
    for data in all_data:
        print(data)
current_path = os.path.abspath(".")
yaml_path = os.path.join(current_path, "config.yaml")
get_yaml_load_all(yaml_path)
"" "results {' animal1 ':' dog ', 'age, 2} {' animal2' : 'the cat', 'age: 3} "" "
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Python objects generate YAML documents

1. Directly import yamL documents generated by YAML

The yaml.dump() method does not convert list or dictionary data to yamL standard mode, but only generates the data into a YAML document

# Generate Python objects into YAML documents
import yaml
def generate_yaml_doc(yaml_file) :
    py_object = {'school': 'zhang'.'students': ['a'.'b']}
    file = open(yaml_file, 'w', encoding='utf-8')
    yaml.dump(py_object, file)
    file.close()
current_path = os.path.abspath(".")
yaml_path = os.path.join(current_path, "generate.yaml")
generate_yaml_doc(yaml_path)
Results School: Zhang Students: [A, B] ""
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2. Use the YAML method in ruamel module to generate standard YAML documents

(1) Use yamL prerequisites in ruamel module

  • Yaml: ruamel.yaml (pip3 install ruamel.yaml);
  • Import module: from ruamel import yaml

(2) The RUamel module generates yamL documents

def generate_yaml_doc_ruamel(yaml_file) :
    from ruamel import yaml
    py_object = {'school': 'zhang'.'students': ['a'.'b']}
    file = open(yaml_file, 'w', encoding='utf-8')
    yaml.dump(py_object, file, Dumper=yaml.RoundTripDumper)
    file.close()
current_path = os.path.abspath(".")
yaml_path = os.path.join(current_path, "generate.yaml")
generate_yaml_doc_ruamel(yaml_path)
""" Results School: Zhang Students: a-B ""
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(3) Ruamel module reads yamL document

# read yaml file from ruamel import yaml
def get_yaml_data_ruamel(yaml_file) :
    from ruamel import yaml
    file = open(yaml_file, 'r', encoding='utf-8')
    data = yaml.load(file.read(), Loader=yaml.Loader)
    file.close()
    print(data)
current_path = os.path.abspath(".")
yaml_path = os.path.join(current_path, "dict_config.yaml")
get_yaml_data_ruamel(yaml_path)
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