Build a Streaming Markdown Code Fence Parser

Question

This question asks the candidate to design and implement a parser that can handle Markdown code fences in a streaming manner.

Codemia · Accepted Answer

To build a streaming Markdown code fence parser, we need to identify the key requirements:
1. **Input Handling**: The parser should accept a stream of text as input.
2. **Code Fence Detection**: It must recognize the start and end of code fences, which are typically marked by triple backticks (```).
3. **Content Extraction**: The parser should extract the content within the code fences, preserving formatting.
4. **Performance**: It should process the input efficiently, ideally in a single pass.

The high-level design of the parser can be broken down into the following components:
- **State Management**: Use a state machine to track whether we are inside or outside a code fence.
- **Buffering**: Maintain a buffer to store characters until a complete code fence is detected.
- **Output Handling**: Once a code fence is closed, output the extracted content for further processing.

Data structures involved might include a simple list for buffering and a string for storing the final output.

Here is a Python implementation of the streaming Markdown code fence parser:
```python
def parse_markdown_code_fences(stream):
    inside_fence = False
    buffer = []
    output = []

for line in stream:
        if line.strip() == '```':  # Check for code fence
            if inside_fence:
                output.append(''.join(buffer))  # Save the buffer content
                buffer = []  # Reset buffer
            inside_fence = not inside_fence
        elif inside_fence:
            buffer.append(line)  # Collect lines inside the fence

return output
```
This code reads lines from the input stream, toggles the `inside_fence` state when it encounters a code fence, and collects lines accordingly.

When implementing the parser, consider the following edge cases:
- **Empty Code Fences**: Handle cases where there are consecutive code fences without content.
- **Improperly Nested Fences**: Decide how to handle situations where fences are not properly closed.
- **Mixed Content**: Ensure that the parser can handle text outside of code fences without issues.

The time complexity of this parser is O(n), where n is the number of characters in the input stream. Each character is processed once. The space complexity is O(m), where m is the maximum size of the buffered content at any time. To optimize, we could implement a more sophisticated buffering strategy or use a generator to yield results incrementally.

Build a Streaming Markdown Code Fence Parser

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