Metadata-Version: 2.1
Name: metapost
Version: 0.0.2
Summary: Tools for interpreting MetaPost
Home-page: https://github.com/thitta/Python-MetaPost
Author: Hsufeng Lee
Author-email: thittalee@gmail.com
License: MIT License
Description: This Python package helps developers parse `Metapost` file.
        
        `Metapost` is a customized `Markdown` format which is meant to support blogs based on local file systems. Metapost allows writer append meta on the markdown file, such as `title` for a post; or `on_index` which denotes whether the post should be placed on the index page - in a most human `readable` and `manageable` way.
        
        `Metapost` file is devised to support my personal micro blog project [blog.someone.tw](http://blog.someone.tw), in which I can write some stuff on my local markdown files, append meta and publish them via console tools. The process is extremely productive since it prevents writer from using unreliable online editors, or spending tons of time on exporting content from source file to HTML. With the help of `Metapost`, writing could become very similar to coding.
        
        # How Metapost Works
        
        - `Metapost` file is a standard `Markdown` file with `.md` extension. 
        - Except one thing - `Metapost` is expected to star with a `code block`, which will be parsed as metas of the file.
        - The content of the `code block` should be neither json nor YAML, it's a special but easy to learn format, which is meant to optimize the readability and manageability.
        - This package provides necessary tools for manipulating Metapost files, such as reading and exporting.
        - The markdown parser in this project is based on John Gruber's [Markdown](https://github.com/Python-Markdown/markdown)
        
        Metapost is extremely simple and powerful. The examples below will demonstrate how to implement it.
        
        # Examples
        
        ## The First Example
        
        In this section, we are going to demonstrate how to parse a Metapost(markdown) file into useful formats that can interact with our application. Be aware that the meta content is neither json nor YAML, it's a key-value pair separated by a colon.
        
        Assuming we have a MetaPost(.md) file like this. The file starts with a code block containing metas, which is embraced by triple consecutive backtick(\`\`\`).
        
        ```
        ` ` `
        title: Example post
        ranking: 999
        on_top: true
        keywords: ["markdown", "meta", "microblog"]
        work_hours: 35.6
        ` ` `
        
        --- ↑↑↑    Meta Block    ↑↑↑ ---
        --- ↓↓↓ Markdown Content ↓↓↓ ---
        
        Be careful we use ` ` ` here just because we can't escape backtick in the code block of github. 
        
        You should always use ``` in your markdown file.
        ```
        
        Now, we are going to parse the file with `MetaPostReader` in our package:
        
        ``` python
        # import package
        from metapost import MetaPostReader
        
        # set file path
        path = ".\myMetaPostFilepath.md"
        
        # instantiate MetaPostReader
        mtpr = MetaPostReaser()
        mtpr.set_strict_mode(False)
        
        # read and export to python dict
        result = mtpr.read_file(path).to_dict()
        print(result)
        ```
        
        The out put will be:
        
        ```
        [{
            "meta":{"title":"Example post",
                    "rank":"999",
                    "on_top":"true",
                    "keywords":'["markdown", "meta", "microblog"]',
                    "work_hours": "35.6"}
            "html":"<p>......</p>"
        }]
        ```
        
        Well, it's not that impressive, right? All values are parsed as string instead of boolean, integer or other useful datatype.
        
        ## Set Meta Configs
        
        Set `meta_configs` on the `MetaPostReader` can help us parse value precisely. We can also set `required` and `df_val` on it to declare whether a meta is required or have default value.
        
        The five lines of meta in the source markdown file are mapping to five acceptable datatype in the meta, they are string(`str`), boolean(`bool`), integer(`int`),  float(`float`) and json(`json`).
        
        Let's set meta configs and parse it again
        
        ``` python
        from metapost import MetaPostReader
        
        path = ".\ExampleMetaPost.md"
        mtpr = MetaPostReaser()
        
        # add_meta_config()
        # key: str, datatype: str = "str", required: bool = True, df_val: Any = None
        mtpr.add_meta_config("title",      "str",   True        )
        mtpr.add_meta_config("ranking",    "int",   False, 0    )
        mtpr.add_meta_config("on_top",     "bool",  False, False)
        mtpr.add_meta_config("keywords",   "json",  False       )
        mtpr.add_meta_config("work_hours", "float", True        )
        
        result = mtpr.to_dict()
        print(result)
        ```
        
        Now, we can get the content of the file in the format of python `dict`:
        
        ```
        [{
            "meta":{"title":"Example post",
                    "rank":999,
                    "on_top":true,
                    "keywords":["markdown", "meta", "microblog",
                    "work_hours":35.6,
                    ......}
            "html":"<p>......</p>"
        }]
        ```
        
        If the parameter `required` is `True` while your file does not contain that meta key, the reader will report error. This feature can make sure some required metas, such as the title of a post won't be missing. 
        
        We can compare these three lines of code which clearly demonstrate how `required` and `df_val` works
        
        ```python
        # meta required, default value not necessary
        mtpr.add_meta_config("title",      "str",   True       )
        
        # meta not required, it is defaulted to be 999 if not provided
        mtpr.add_meta_config("ranking",    "int",   False, 999 )
        
        # meta not required, no default value
        mtpr.add_meta_config("keywords",   "json",  False      )
        ```
        
        Another thing worth mention is that `MetaPostReader` adopt elastic approach to parse `bool` meta. That's to say, values like `False`, `false`, `No`, `n`, `0`, etc., will be parsed to `False` as long as the meta config expects a boolean. The rule is __case insensitive__ and is also applies to `True` parsing.
        
        ## Set Strict Mode
        
        We can set the property `strict_mode` on `MetaPostReader`. The defaulted value is `True`, which means the reader won't parse metas that are not defined in configs. Set it to `False` if you wish to parse as many valid metas as possible.
        
        ```python
        mtpr = MetaPostReaser()
        
        # strict mode on 
        mtpr = MetaPostReaser().set_strict_mode(True)
        
        # strict mode off
        mtpr = MetaPostReaser().set_strict_mode(False)
        ```
        
        ## Default Meta
        
        Except for metas we have defined in config, you can find some default ones. They are `_filepath_`, `_filename_` and `_last_update_`. These are meant to provide more information about the source file. For example, I adopt the value of `_last_update_` as the update time of posts on my blog, so that I don't have to key it in by hand.
        
        ## Read Multiple Files & Read from Directory
        
        `MetaPostReader` can accommodate and parse multiple files at the same time. All the files loaded will be stored in `MetaPostReader.mtp_list`.
        
        ```python
        # read three files into MetaPostReader
        mtpr = MetaPostReader()
        mtpr.read_file(my_path_1)
        mtpr.read_file(my_path_2)
        mtpr.read_file(my_path_3)
        
        # now, the length will be 3
        print(len(mtpr.mtp_list))
        
        # set reset to True if you wish to reset list before read
        mtpr.read_file(my_path_4, reset=True)
        
        # now, the length will be 1
        print(len(mtpr.mtp_list))
        ```
        
        You can also read from a directory, which is often the writing space of users. `MetaPostReader.read_dir()` will automatically load all files with `.md` extensions under a directory. If you wish to load all `.md` files in the directory tree, set `walk` to `True`.
        
        ```python
        mtpr = MetaPostReader()
        
        # Read .md from directory
        mtpr.read_file(my_dirpath)
        
        # Read .md from whole directory tree
        mtpr.read_file(my_dirpath, walk=True)
        ```
        
        That's all! If you have any advice, feel free to contact me via email(thittalee@gmail.com) or github. The following API document provides some short description of all the (expected) public methods. Happy coding! 
        
        ## API Document
        
        ### Init
        - `MetaPostReader.__init__(self)`
        
        Create a MetaPostReader
        
        ### Add Meta Configs
        - `.add_meta_cfg(self, key: str, datatype: str = "str", required: bool = True, df_val: Any = None)`
        
        Add meta config. `datatype` can be `str`, `bool`, `int`, `float` and `json`.
        
        ### Methods of Read
        - `.read_dir(self, dirpath: str, reset: bool = False, walk: bool = False)`
        
        Read all the `.md` files under `dirpath` into reader. Set `reset` to `True` if you wish to clean the former loading. Set `walk` to `True` if you wish to read all the `.md` files in the directory tree.
        
        - `.read_file(self, filepath: str, reset: bool = False)`
        
        Read one single file from `filepath`. Set `reset` to `True` if you wish to clean the former loading.
        
        - `.read_text(self, source_text: str, reset: bool = False)`
        
        Read from a string. Set `reset` to `True` if you wish to clean the former loading.
        
        ### Methods of Output
        
        - `.to_dict(self) -> List[dict]`
        
        Export a list of dict from data read . Use `dict["meta"]` and `dict["html"]` to fetch values.
        
        - `.to_json(self) -> str`
        
        Export a string of json from data read.
        
        - `.to_meta(self) -> List[dict]`
        
        Export a list of dict of meta from data read.s
        
        - `.to_html(self) -> List[str]`
        
        Export a list of string of html from data read.
        
        ### Methods of Setter
        
        - `.set_strict_mode(self, strict_mode: bool)`
        
        Set `.strict_mode` to `True` if you wish to parse metas defined in configs only.
        
        - `.set_markdown_extensions(self, extensions: list)`
        
        Customize your markdown extensions. Visit [Markdown](https://github.com/Python-Markdown/markdown) for more information.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
