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[#]: subject: (Use Python to parse configuration files)
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[#]: via: (https://opensource.com/article/21/6/parse-configuration-files-python)
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[#]: author: (Moshe Zadka https://opensource.com/users/moshez)
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[#]: collector: (lujun9972)
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[#]: translator: (zepoch)
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[#]: reviewer: ( )
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[#]: publisher: ( )
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[#]: url: ( )
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Use Python to parse configuration files
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======
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The first step is choosing a configuration format: INI, JSON, YAML, or
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TOML.
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![Python programming language logo with question marks][1]
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Sometimes, a program needs enough parameters that putting them all as command-line arguments or environment variables is not pleasant nor feasible. In those cases, you will want to use a configuration file.
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There are several popular formats for configuration files. Among them are the venerable (although occasionally under-defined) `INI` format, the popular but sometimes hard to write by hand `JSON` format, the extensive yet occasionally surprising in details `YAML` format, and the newest addition, `TOML`, which many people have not heard of yet.
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Your first task is to choose a format and then to document that choice. With this easy part out of the way, it is time to parse the configuration.
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It is sometimes a good idea to have a class that corresponds to the "abstract" data in the configuration. Because this code will do nothing with the configuration, this is the simplest way to show parsing logic.
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Imagine the configuration for a file processor: it includes an input directory, an output directory, and which files to pick up.
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The abstract definition for the configuration class might look something like:
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```
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`from __future__ import annotations`[/code] [code]
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import attr
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@attr.frozen
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class Configuration:
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@attr.frozen
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class Files:
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input_dir: str
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output_dir: str
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files: Files
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@attr.frozen
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class Parameters:
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patterns: List[str]
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parameters: Parameters
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```
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To make the format-specific code simpler, you will also write a function to parse this class out of dictionaries. Note that this assumes the configuration will use dashes, not underscores. This kind of discrepancy is not uncommon.
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```
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def configuration_from_dict(details):
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files = Configuration.Files(
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input_dir=details["files"]["input-dir"],
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output_dir=details["files"]["output-dir"],
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)
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parameters = Configuration.Paraneters(
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patterns=details["parameters"]["patterns"]
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)
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return Configuration(
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files=files,
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parameters=parameters,
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)
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```
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### JSON
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JSON (JavaScript Object Notation) is a JavaScript-like format.
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Here is an example configuration in JSON format:
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```
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json_config = """
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{
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"files": {
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"input-dir": "inputs",
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"output-dir": "outputs"
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},
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"parameters": {
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"patterns": [
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"*.txt",
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"*.md"
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]
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}
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}
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"""
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```
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The parsing logic parses the JSON into Python's built-in data structures (dictionaries, lists, strings) using the `json` module and then creates the class from the dictionary:
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```
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import json
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def configuration_from_json(data):
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parsed = json.loads(data)
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return configuration_from_dict(parsed)
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```
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### INI
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The INI format, originally popular on Windows, became a de facto configuration standard.
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Here is the same configuration as an INI:
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```
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ini_config="""
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[files]
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input-dir = inputs
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output-dir = outputs
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[parameters]
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patterns = ['*.txt', '*.md']
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"""
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```
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Python can parse it using the built-in `configparser` module. The parser behaves as a `dict`-like object, so it can be passed directly to `configuration_from_dict`:
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```
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import configparser
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def configuration_from_ini(data):
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parser = configparser.ConfigParser()
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parser.read_string(data)
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return configuration_from_dict(parser)
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```
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### YAML
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YAML (Yet Another Markup Language) is an extension of JSON that is designed to be easier to write by hand. It accomplishes this, in part, by having a long specification.
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Here is the same configuration in YAML:
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```
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yaml_config = """
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files:
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input-dir: inputs
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output-dir: outputs
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parameters:
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patterns:
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- '*.txt'
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- '*.md'
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"""
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```
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For Python to parse this, you will need to install a third-party module. The most popular is `PyYAML` (`pip install pyyaml`). The YAML parser also returns built-in Python data types that can be passed to `configuration_from_dict`. However, the YAML parser expects a stream, so you need to convert the string into a stream.
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```
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import io
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import yaml
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def configuration_from_yaml(data):
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fp = io.StringIO(data)
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parsed = yaml.safe_load(fp)
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return configuration_from_dict(parsed)
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```
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### TOML
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TOML (Tom's Own Markup Language) is designed to be a lightweight alternative to YAML. The specification is shorter, and it is already popular in some places (for example, Rust's package manager, Cargo, uses it for package configuration).
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Here is the same configuration as a TOML:
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```
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toml_config = """
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[files]
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input-dir = "inputs"
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output-dir = "outputs"
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[parameters]
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patterns = [ "*.txt", "*.md",]
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"""
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```
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In order to parse TOML, you need to install a third-party package. The most popular one is called, simply, `toml`. Like YAML and JSON, it returns basic Python data types.
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```
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import toml
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def configuration_from_toml(data):
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parsed = toml.loads(data)
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return configuration_from_dict(parsed)
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```
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### Summary
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Choosing a configuration format is a subtle tradeoff. However, once you make the decision, Python can parse most of the popular formats using a handful of lines of code.
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--------------------------------------------------------------------------------
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via: https://opensource.com/article/21/6/parse-configuration-files-python
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作者：[Moshe Zadka][a]
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选题：[lujun9972][b]
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译者：[译者ID](https://github.com/译者ID)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]: https://opensource.com/users/moshez
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[b]: https://github.com/lujun9972
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[1]: https://opensource.com/sites/default/files/styles/image-full-size/public/lead-images/python_programming_question.png?itok=cOeJW-8r (Python programming language logo with question marks)
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@ -0,0 +1,205 @@
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[#]: subject: "Use Python to parse configuration files"
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[#]: via: "https://opensource.com/article/21/6/parse-configuration-files-python"
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[#]: author: "Moshe Zadka https://opensource.com/users/moshez"
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[#]: collector: "lujun9972"
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[#]: translator: "zepoch"
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[#]: reviewer: " "
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[#]: publisher: " "
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[#]: url: " "
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使用Python解析配置文件
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======
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第一步是选择配置文件的格式：INI、JSON、YAML 或 TOML。
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![Python programming language logo with question marks][1]
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有时，程序需要足够的参数，将它们全部作为命令行参数或环境变量既不让人愉快也不可行。 在这些情况下，您将需要使用配置文件。
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有几种流行的配置文件格式。 其中包括古老的（虽然偶尔定义不足）`INI`格式，虽然流行但有时难以手写的`JSON`格式，广泛但偶尔在细节方面令人惊讶的`YAML`格式，以及最新添加的`TOML `，很多人还没有听说过。
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您的首要任务是选择一种格式，然后记录该选择。 解决了这个简单的部分之后就是时候解析配置了。
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有时，在配置中拥有一个与“抽象“数据相对应的类是一个不错的想法。 因为这段代码不会对配置做任何事情，所以这是展示解析逻辑最简单的方式。
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想象一下文件处理器的配置：它包括一个输入目录、一个输出目录和要提取的文件。
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配置类的抽象定义可能类似于：
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```
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`from __future__ import annotations`[/code] [code]
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import attr
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@attr.frozen
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class Configuration:
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@attr.frozen
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class Files:
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input_dir: str
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output_dir: str
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files: Files
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@attr.frozen
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class Parameters:
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patterns: List[str]
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parameters: Parameters
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```
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为了使特定于格式的代码更简单，您还将编写一个函数来从字典中解析此类。 请注意，这假设配置将使用破折号，而不是下划线。 这种差异并不少见。
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```
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def configuration_from_dict(details):
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files = Configuration.Files(
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input_dir=details["files"]["input-dir"],
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output_dir=details["files"]["output-dir"],
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)
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parameters = Configuration.Paraneters(
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patterns=details["parameters"]["patterns"]
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)
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return Configuration(
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files=files,
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parameters=parameters,
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)
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```
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### JSON
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JSON（JavaScript Object Notation）是一种类似于 JavaScript 的格式。
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以下是 JSON 格式的示例配置：
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```
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json_config = """
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{
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"files": {
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"input-dir": "inputs",
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"output-dir": "outputs"
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},
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"parameters": {
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"patterns": [
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"*.txt",
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"*.md"
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]
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}
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}
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"""
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```
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解析逻辑使用 `json` 模块将 JSON 解析为 Python 的内置数据结构（字典、列表、字符串），然后从字典中创建类：
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```
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import json
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def configuration_from_json(data):
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parsed = json.loads(data)
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return configuration_from_dict(parsed)
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```
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### INI
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INI 格式，最初只在 Windows 上流行，之后成为配置标准格式。
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这是与 INI 相同的配置：
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```
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ini_config="""
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[files]
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input-dir = inputs
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output-dir = outputs
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[parameters]
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patterns = ['*.txt', '*.md']
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"""
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```
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Python 可以使用内置的 `configparser` 模块解析它。解析器充当类似 `dict` 的对象，因此可以直接传递给 `configuration_from_dict`：
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```
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import configparser
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def configuration_from_ini(data):
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parser = configparser.ConfigParser()
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parser.read_string(data)
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return configuration_from_dict(parser)
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```
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### YAML
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YAML (Yet Another Markup Language) 是 JSON 的扩展，旨在更易于手动编写。 部分 YAML 需要通过具有较长的规范来实现这一点。
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以下是 YAML 中的相同配置：
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```
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yaml_config = """
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files:
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input-dir: inputs
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output-dir: outputs
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parameters:
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patterns:
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- '*.txt'
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- '*.md'
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"""
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```
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要让 Python 解析它，您需要安装第三方模块。 最受欢迎的是`PyYAML`（`pip install pyyaml`）。 YAML 解析器还返回可以传递给 `configuration_from_dict` 的内置 Python 数据类型。 但是，YAML 解析器需要一个字节流，因此您需要将字符串转换为字节流。
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```
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import io
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import yaml
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def configuration_from_yaml(data):
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fp = io.StringIO(data)
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parsed = yaml.safe_load(fp)
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return configuration_from_dict(parsed)
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```
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### TOML
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TOML（Tom's Own Markup Language）旨在成为 YAML 的轻量级替代品。 规范比较短，已经在一些地方流行了（比如 Rust 的包管理器 Cargo 就用它来进行包配置）。
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这是与 TOML 相同的配置：
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```
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toml_config = """
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[files]
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input-dir = "inputs"
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output-dir = "outputs"
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[parameters]
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patterns = [ "*.txt", "*.md",]
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"""
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```
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为了解析 TOML，您需要安装第三方包。 最流行的一种被简单地称为 `toml`。 与 YAML 和 JSON 一样，它返回基本的 Python 数据类型。
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```
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import toml
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def configuration_from_toml(data):
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parsed = toml.loads(data)
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return configuration_from_dict(parsed)
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```
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### Summary总结
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选择配置格式是一种微妙的权衡。 但是，一旦您做出决定，Python 就可以使用少量代码来解析大多数流行的格式。
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--------------------------------------------------------------------------------
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via: https://opensource.com/article/21/6/parse-configuration-files-python
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|
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作者：[Moshe Zadka][a]
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选题：[lujun9972][b]
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译者：[zepoch](https://github.com/zepoch)
|
||||
校对：[校对者ID](https://github.com/校对者ID)
|
||||
|
||||
本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
|
||||
|
||||
[a]: https://opensource.com/users/moshez
|
||||
[b]: https://github.com/lujun9972
|
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[1]: https://opensource.com/sites/default/files/styles/image-full-size/public/lead-images/python_programming_question.png?itok=cOeJW-8r "Python programming language logo with question marks"
|
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