feat(Dataframe): save dataframe yml (#1443)

* feat(dataframe): save dataframe to path

* feat(dataframe): save dataframe to path

pandasai/__init__.py

@@ -4,6 +4,8 @@
 """
 
 from typing import List
+
+import pandas as pd
 from .agent import Agent
 from .helpers.cache import Cache
 from .dataframe.base import DataFrame
@@ -75,6 +77,11 @@ def load(dataset_path: str, virtualized=False) -> DataFrame:
     return _dataset_loader.load(dataset_path, virtualized)
 
 
+def read_csv(filepath: str) -> DataFrame:
+    data = pd.read_csv(filepath)
+    return DataFrame(data, filepath=filepath)
+
+
 __all__ = [
     "Agent",
     "clear_cache",

pandasai/dataframe/base.py

@@ -1,13 +1,18 @@
 from __future__ import annotations
+import os
+import shutil
 import pandas as pd
 from typing import TYPE_CHECKING, Optional, Union, Dict, Any, ClassVar
 
+import yaml
+
 from pandasai.config import Config
 import hashlib
 from pandasai.helpers.dataframe_serializer import (
     DataframeSerializer,
     DataframeSerializerType,
 )
+from pandasai.helpers.path import find_project_root
 
 
 if TYPE_CHECKING:
@@ -28,6 +33,7 @@ class DataFrame(pd.DataFrame):
     _metadata: ClassVar[list] = [
         "name",
         "description",
+        "filepath",
         "schema",
         "config",
         "_agent",
@@ -37,6 +43,7 @@ class DataFrame(pd.DataFrame):
     def __init__(self, *args, **kwargs):
         self.name: Optional[str] = kwargs.pop("name", None)
         self.description: Optional[str] = kwargs.pop("description", None)
+        self.filepath: Optional[str] = kwargs.pop("filepath", None)
         schema: Optional[Dict] = kwargs.pop("schema", None)
 
         super().__init__(*args, **kwargs)
@@ -157,3 +164,70 @@ def serialize_dataframe(
 
     def get_head(self):
         return self.head()
+
+    def _create_yml_template(self, name, description, output_yml_path: str):
+        """
+        Generate a .yml file with a simplified metadata template from a pandas DataFrame.
+
+        Args:
+            dataframe (pd.DataFrame): The DataFrame to document.
+            filepath (str): The path to the original data source file.
+            output_yml_path (str): The file path where the .yml file will be saved.
+            table_name (str): Name of the table or dataset.
+        """
+        # Metadata template
+        metadata = {
+            "name": name,
+            "description": description,
+            "columns": [
+                {"name": column, "type": str(self[column].dtype)}
+                for column in self.columns
+            ],
+            "source": {
+                "type": "csv",
+                "path": (
+                    "data.csv" if self.filepath.endswith(".csv") else "data.parquet"
+                ),
+            },
+        }
+
+        # Save metadata to a .yml file
+        with open(output_yml_path, "w") as yml_file:
+            yaml.dump(metadata, yml_file, sort_keys=False)
+
+        print(f"YML file created at: {output_yml_path}")
+
+    def save(self, path: str, name: str, description: str = None):
+        self.name = name
+        self.description = description
+
+        # Validate path format
+        path_parts = path.split("/")
+        if len(path_parts) != 2:
+            raise ValueError("Path must be in format 'organization/dataset'")
+
+        org_name, dataset_name = path_parts
+        if not org_name or not dataset_name:
+            raise ValueError("Both organization and dataset names are required")
+
+        # Validate dataset name format
+        if not dataset_name.islower() or " " in dataset_name:
+            raise ValueError(
+                "Dataset name must be lowercase and use hyphens instead of spaces (e.g. 'my-dataset')"
+            )
+
+        # Create full path with slugified dataset name
+        dataset_directory = os.path.join(
+            find_project_root(), "datasets", org_name, dataset_name
+        )
+
+        os.makedirs(dataset_directory, exist_ok=True)
+
+        # save csv file
+        new_file_path = os.path.join(dataset_directory, "data.csv")
+        shutil.copy(self.filepath, new_file_path)
+
+        # create schema yaml file
+        schema_path = os.path.join(dataset_directory, "schema.yaml")
+        self._create_yml_template(self.name, self.description, schema_path)
+        print(f"Dataset saved successfully to path: {dataset_directory}")

pandasai/helpers/utils.py

@@ -0,0 +1,27 @@
+import re
+import unicodedata
+
+
+def create_slug(text: str) -> str:
+    """
+    Generate a slug from a given text.
+
+    Args:
+        text (str): The input text to convert into a slug.
+
+    Returns:
+        str: A URL-friendly slug.
+    """
+    # Normalize text to remove accents and special characters
+    text = unicodedata.normalize("NFKD", text)
+    text = text.encode("ascii", "ignore").decode("ascii")
+
+    # Convert to lowercase
+    text = text.lower()
+
+    # Replace spaces and unwanted characters with a hyphen
+    text = re.sub(r"[^\w\s-]", "", text)
+    text = re.sub(r"[\s_]+", "-", text.strip())
+
+    # Remove leading or trailing hyphens
+    return text.strip("-")