Agrego auto-replicación

data_transformers/default_transformers.py

@@ -24,4 +24,10 @@ def sort_values(df: DataFrame, how: str, by: list):
 @transformer.convert
 def cast_col(df: DataFrame, col: str, cast_to: type):
     df[col] = df[col].astype(cast_to)
+    return df
+
+
+@transformer.convert
+def rename_cols(df: DataFrame, map):
+    df = df.rename(columns=map)
     return df

data_transformers/dtransformers.py

@@ -113,12 +113,13 @@ def __init__(self, *fs: transformer):
 
         self.fs = fs
 
-    def transformers_source(self):
+    def transformers_source(self, hide_decorators=False):
         sources = []
         for f in self.fs:
             src, count = f.sourcelines
-            if src[0].startswith('@'):
-                src = src[1:]
+            if hide_decorators:
+                if src[0].startswith('@'):
+                    src = src[1:]
             sources.append(''.join(src))
         return sources
 

data_transformers/utils.py

@@ -7,7 +7,7 @@ def get_dataframe_info(df):
     return buf.getvalue()
 
 def dict_to_str(d):
-    return ','.join([f'{k}={v}' for k,v in d.items()])
+    return ', '.join([f'{k}={v!r}' for k,v in d.items()])
 
 def callstack_to_str(callstack):
     frames = []
@@ -28,4 +28,14 @@ def callstack_to_str(callstack):
         frames.append('-'*30)
         frames.append('')
 
-    return '\n'.join(frames)
+    return '\n'.join(frames)
+
+def callstack_to_program(callstack):
+    code = []
+    for i, (f, params, presult) in enumerate(callstack[1:]):
+        params.pop('df', None)
+        params_str = dict_to_str(params)
+        params_str = f'{f.name}({params_str})' + (',' if i < len(callstack) - 2 else '')
+        code.append(params_str)
+
+    return 'pipeline = chain(\n' + '\n\t'.join(code) + '\n)'