Update README.md

README.md

@@ -12,7 +12,7 @@ size_categories:
 
 # Overview
 
-This dataset contains 25,000+ rows of code-docstring-ast data along with additional metadata. Data was gathered from various Python libraries and frameworks and their
+This dataset contains 22,000+ rows of code-docstring-ast data along with additional metadata. Data was gathered from various Python libraries and frameworks and their
 publicly available GitHub repos. This dataset was created for the purpose of training the [CodeT5+](https://arxiv.org/abs/2305.07922) transformer on AST-enhanced code-to-doc tasks.
 
 # Sources
@@ -61,55 +61,52 @@ An instance of the dataset is as follows:
   <docstring> : <The corresponding docstring of the code>,
   <type> : <Whether it's a function, method, or class>,
   <file_path> : <The relative path of the file containing the function>,
-  <ast_sequence> : <The ast sequence of the raw source code. Scroll down for more info about this>
+  <ast_data> : <A flattened representation of the parsed AST. For more info about this, see section below>
 }
 ```
 
-# The AST Sequence
+# The AST Data
 
-A function recursively converts the AST tree into a linear sequence. It uses depth markers (├1>, └2>, etc.) to show parent-child relationships. It also adds node identifiers by pairing
-each node type with a meaningful identifier. Furthermore, pruning is also applied to irrelevant and shallow identifiers to denoise the dataset. 
+An extractor only focuses on specific nodes relevant for docstring generation denoted by this set:
 
-Here's an example of how the AST sequence is generated:
+```
+KEEP_NODES = {
+        'FunctionDef', 'AsyncFunctionDef', 'ClassDef',
+        'arguments', 'arg', 'Return',
+        'If', 'For', 'While', 'Try', 'With',
+        'Assign', 'Call',
+        'Raise', 'ExceptHandler',
+        'decorator', 'bases',
+        'Compare', 'BoolOp'
+    }
+```
+
+Everything else is discarded. For example
 
-Example Code
+**Source Code**
 ```
-def calculate_area(radius):
-    """
-    Calculate the area of a circle.
-    
-    Parameters:
-        radius (float): The radius of the circle
-        
-    Returns:
-        float: The area of the circle
-    """
-    PI = 3.14159
-    area = PI * radius * radius
-    return area
+def tox_append_version_info() -> str: return '[toxfile]'
 ```
 
-Resulting AST Sequence
+**Resulting AST Dictionary**
 ```
-FunctionDef:calculate_area
-├1> args:[radius]
-├1> Assign:PI
-│ └2> Constant:
-├1> Assign:area
-│ └2> BinOp:
-│   ├3> BinOp:
-│   │ ├4> Name:PI
-│   │ └4> Name:radius
-│   └3> Name:radius
-└1> Return:
-  └2> Name:area
+"ast_data": {
+      "type": "FunctionDef",
+      "children": [
+        {
+          "type": "arguments",
+          "args": []
+        },
+        {
+          "type": "Return",
+          "has_value": true
+        }
+      ],
+      "name": "tox_append_version_info"
+    }
 ```
 
-1. The code is parsed via Python's `ast` module
-2. A method traverses this tree and linearizes the sequence
-3. Each node is then converted to a string with type-identifier keys
-4. Structural relationships are preserved using the depth markers
-5. Denoising of irrelevant and shallow nodes are applied
+This dictionary is then flattened via a helper function which would then look something like `FunctionDef name:tox_append_version_info arguments Return return:yes`.
 
 # Preprocessing
 
@@ -118,46 +115,53 @@ The dataset generally follows [CodeBERT's code2nl](https://github.com/microsoft/
 - Removed comments from the code
 - Removed examples where code cannot be parsed into an AST
 - Remove examples that codes cannot be parsed into an abstract syntax tree.
-- Remove examples where the number of tokens of documents is < 3 or >256
 - Remove examples that documents contain special tokens (e.g. <img ...> or https:...)
 - Remove examples that documents are not English
 
 Furthermore, the following cleaning steps specific to this dataset were applied:
-- Docstrings from source codes was stripped
-- Standard text cleaning procedures (normalized whitespaces and special characters)
-- Removed abnormally long AST sequences (>100)
-- Structural pruning of the AST sequence (removing irrelevant or shallow identifiers/nodes)
+- Removed examples where, using CodeT5+'s tokenizer, the combined tokens of the source_code + ast_data is > 512
+- Removed examples where, using CodeT5+'s tokenizer, the docstrings are > 512
+- Normalized the source code
 
 # Final Statistics
 
-## Final Count : 25,489
-
-## Average Docstring Length : 51
-
-## Average Source Code Length : 591
-
-## Average AST Sequence Length : 72
-
-## Type Distribution
-
-**Methods: 13,149(52.1%)**
-
-**Functions: 8,671(34.3%)**
-
-**Classes: 3,444(13.6%)**
-
-## Major Contributors
-
-**TensorFlow (5,455)**
-
-**PyTorch (5,448)**
-
-**Matplotlib (2,190)**
-
-**Django (2,138)**
+```
+{
+  "original_samples": 25481,
+  "processed_samples": 22099,
+  "filter_stats": {
+    "success": 22099,
+    "non_english": 44,
+    "input_too_short": 0,
+    "input_too_long": 3309,
+    "target_too_short": 0,
+    "target_too_long": 29,
+    "error": 0
+  },
+  "split_sizes": {
+    "train": 15469,
+    "val": 3314,
+    "test": 3316
+  },
+  "input_token_stats": {
+    "min": 18,
+    "max": 511,
+    "avg": 155.931
+  },
+  "target_token_stats": {
+    "min": 6,
+    "max": 426,
+    "avg": 67.264
+  },
+  "type_distribution": {
+    "method": 8625,
+    "class": 1434,
+    "function": 5410
+  }
+}
 
-**Scipy (1,715)**
+```
 
 # NOTE
 
-This dataset is *imperfect*. Due to the varying degrees of code complexity, some fields are inaccurate representations. 
+This dataset is *imperfect*. Use under your own volition.