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118 lines
4.1 KiB
Python
118 lines
4.1 KiB
Python
# Generated by CodiumAI
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from pr_agent.algo.utils import convert_to_markdown
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"""
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Code Analysis
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Objective:
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The objective of the 'convert_to_markdown' function is to convert a dictionary of data into a markdown-formatted text.
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The function takes in a dictionary as input and recursively iterates through its keys and values to generate the
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markdown text.
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Inputs:
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- A dictionary of data containing information about a pull request.
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Flow:
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- Initialize an empty string variable 'markdown_text'.
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- Create a dictionary 'emojis' containing emojis for each key in the input dictionary.
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- Iterate through the input dictionary:
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- If the value is empty, continue to the next iteration.
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- If the value is a dictionary, recursively call the 'convert_to_markdown' function with the value as input and
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append the returned markdown text to 'markdown_text'.
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- If the value is a list:
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- If the key is 'code suggestions', add an additional line break to 'markdown_text'.
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- Get the corresponding emoji for the key from the 'emojis' dictionary. If no emoji is found, use a dash.
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- Append the emoji and key to 'markdown_text'.
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- Iterate through the items in the list:
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- If the item is a dictionary and the key is 'code suggestions', call the 'parse_code_suggestion' function with
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the item as input and append the returned markdown text to 'markdown_text'.
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- If the item is not empty, append it to 'markdown_text'.
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- If the value is not 'n/a', get the corresponding emoji for the key from the 'emojis' dictionary. If no emoji is
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found, use a dash. Append the emoji, key, and value to 'markdown_text'.
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- Return 'markdown_text'.
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Outputs:
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- A markdown-formatted string containing the information from the input dictionary.
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Additional aspects:
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- The function uses recursion to handle nested dictionaries.
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- The 'parse_code_suggestion' function is called for items in the 'code suggestions' list.
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- The function uses emojis to add visual cues to the markdown text.
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"""
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class TestConvertToMarkdown:
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# Tests that the function works correctly with a simple dictionary input
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def test_simple_dictionary_input(self):
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input_data = {
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'Main theme': 'Test',
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'Type of PR': 'Test type',
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'Relevant tests added': 'no',
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'Unrelated changes': 'n/a', # won't be included in the output
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'Focused PR': 'Yes',
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'General PR suggestions': 'general suggestion...',
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'Code feedback': [
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{
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'Code example': {
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'Before': 'Code before',
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'After': 'Code after'
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}
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},
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{
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'Code example': {
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'Before': 'Code before 2',
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'After': 'Code after 2'
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}
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}
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]
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}
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expected_output = """\
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- 🎯 **Main theme:** Test
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- 📌 **Type of PR:** Test type
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- 🧪 **Relevant tests added:** no
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- ✨ **Focused PR:** Yes
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- 💡 **General PR suggestions:** general suggestion...
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- 🤖 **Code feedback:**
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- **Code example:**
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- **Before:**
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```
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Code before
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```
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- **After:**
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```
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Code after
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```
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- **Code example:**
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- **Before:**
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```
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Code before 2
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```
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- **After:**
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```
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Code after 2
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```
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"""
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assert convert_to_markdown(input_data).strip() == expected_output.strip()
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# Tests that the function works correctly with an empty dictionary input
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def test_empty_dictionary_input(self):
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input_data = {}
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expected_output = ""
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assert convert_to_markdown(input_data).strip() == expected_output.strip()
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def test_dictionary_input_containing_only_empty_dictionaries(self):
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input_data = {
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'Main theme': {},
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'Type of PR': {},
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'Relevant tests added': {},
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'Unrelated changes': {},
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'Focused PR': {},
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'General PR suggestions': {},
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'Code suggestions': {}
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}
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expected_output = ""
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assert convert_to_markdown(input_data).strip() == expected_output.strip()
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