clean up repr and str methods

README.md

@@ -21,14 +21,15 @@ Currently supports `SummarizedExperiment` & `RangedSummarizedExperiment` classes
 First create necessary sample data
 
 ```python
+from random import random
 import pandas as pd
 import numpy as np
-from genomicranges import GenomicRanges
+from biocframe import BiocFrame
 
 nrows = 200
 ncols = 6
 counts = np.random.rand(nrows, ncols)
-df_gr = pd.DataFrame(
+row_data = BiocFrame(
     {
         "seqnames": [
             "chr1",
@@ -51,9 +52,7 @@ df_gr = pd.DataFrame(
     }
 )
 
-gr = genomicranges.from_pandas(df_gr)
-
-colData = pd.DataFrame(
+col_data = pd.DataFrame(
     {
         "treatment": ["ChIP", "Input"] * 3,
     }
@@ -66,20 +65,41 @@ To create a `SummarizedExperiment`,
 from summarizedexperiment import SummarizedExperiment
 
 tse = SummarizedExperiment(
-    assays={"counts": counts}, row_data=df_gr, col_data=colData
+    assays={"counts": counts}, row_data=row_data, column_data=col_data
 )
 ```
 
+    ## output
+    class: SummarizedExperiment
+    dimensions: (200, 6)
+    assays(1): ['counts']
+    row_data columns(6): ['seqnames', 'starts', 'ends', 'strand', 'score', 'GC']
+    row_names(0):  
+    column_data columns(1): ['treatment']
+    column_names(0):  
+    metadata(0): 
+
 To create a `RangedSummarizedExperiment`
 
 ```python
 from summarizedexperiment import RangedSummarizedExperiment
+from genomicranges import GenomicRanges
 
 trse = RangedSummarizedExperiment(
-    assays={"counts": counts}, row_ranges=gr, col_data=colData
+    assays={"counts": counts}, row_data=row_data, row_ranges=GenomicRanges.from_pandas(row_data.to_pandas()), column_data=col_data
 )
 ```
 
+    ## output
+    class: RangedSummarizedExperiment
+    dimensions: (200, 6)
+    assays(1): ['counts']
+    row_data columns(6): ['seqnames', 'starts', 'ends', 'strand', 'score', 'GC']
+    row_names(0):  
+    column_data columns(1): ['treatment']
+    column_names(0):  
+    metadata(0): 
+
 For more examples, checkout the [documentation](https://biocpy.github.io/SummarizedExperiment/).
 
 <!-- pyscaffold-notes -->

src/summarizedexperiment/BaseSE.py

@@ -278,13 +278,48 @@ def dims(self) -> Tuple[int, int]:
     ##########################
 
     def __repr__(self) -> str:
-        pattern = (
-            f"Class {type(self).__name__} with {self.shape[0]} features and {self.shape[1]} samples \n"
-            f"  assays: {', '.join(list(self.assays.keys()))} \n"
-            f"  row_data: {self._rows.row_names if self._rows is not None else None} \n"
-            f"  column_data: {self._cols.column_names if self._cols is not None else None}"
-        )
-        return pattern
+        """
+        Returns:
+            A string representation.
+        """
+        output = f"{type(self).__name__}(number_of_rows={self.shape[0]}"
+        output += f", number_of_columns={self.shape[1]}"
+        output += ", assays=" + ut.print_truncated_list(self.assay_names)
+        output += ", row_data=" + self._rows.__repr__()
+        output += ", column_data=" + self._cols.__repr__()
+
+        if self._row_names is not None:
+            output += ", row_names=" + ut.print_truncated_list(self._row_names)
+
+        if self._column_names is not None:
+            output += ", column_names=" + ut.print_truncated_list(self._column_names)
+
+        if len(self._metadata) > 0:
+            output += ", metadata=" + ut.print_truncated_dict(self._metadata)
+
+        output += ")"
+        return output
+
+    def __str__(self) -> str:
+        """
+        Returns:
+            A pretty-printed string containing the contents of this object.
+        """
+        output = f"class: {type(self).__name__}\n"
+
+        output += f"dimensions: ({self.shape[0]}, {self.shape[1]})\n"
+
+        output += f"assays({len(self.assay_names)}): {ut.print_truncated_list(self.assay_names)}\n"
+
+        output += f"row_data columns({len(self._rows.column_names)}): {ut.print_truncated_list(self._rows.column_names)}\n"
+        output += f"row_names({0 if self._row_names is None else len(self._row_names)}): {' ' if self._row_names is None else ut.print_truncated_list(self._row_names)}\n"
+
+        output += f"column_data columns({len(self._cols.column_names)}): {ut.print_truncated_list(self._cols.column_names)}\n"
+        output += f"column_names({0 if self._column_names is None else len(self._column_names)}): {' ' if self._column_names is None else ut.print_truncated_list(self._column_names)}\n"
+
+        output += f"metadata({str(len(self.metadata))}): {ut.print_truncated_list(list(self.metadata.keys()), sep=' ', include_brackets=False, transform=lambda y: y)}\n"
+
+        return output
 
     ########################
     ######>> assays <<######

src/summarizedexperiment/RangedSummarizedExperiment.py

@@ -220,14 +220,51 @@ def copy(self):
     ##########################
 
     def __repr__(self) -> str:
-        pattern = (
-            f"Class  {type(self).__name__} with {self.shape[0]} features and {self.shape[1]} "
-            "samples \n"
-            f"  assays: {list(self.assays.keys())} \n"
-            f"  row_data: {self._rows.columns if self._rows is not None else None} \n"
-            f"  column_data: {self._cols.columns if self._cols is not None else None}"
-        )
-        return pattern
+        """
+        Returns:
+            A string representation.
+        """
+        output = f"{type(self).__name__}(number_of_rows={self.shape[0]}"
+        output += f", number_of_columns={self.shape[1]}"
+        output += ", assays=" + ut.print_truncated_list(self.assay_names)
+
+        output += ", row_data=" + self._rows.__repr__()
+        if self._row_names is not None:
+            output += ", row_names=" + ut.print_truncated_list(self._row_names)
+
+        output += ", column_data=" + self._cols.__repr__()
+        if self._column_names is not None:
+            output += ", column_names=" + ut.print_truncated_list(self._column_names)
+
+        if self._row_ranges is not None:
+            output += "row_ranges=" + self._row_ranges.__repr__()
+
+        if len(self._metadata) > 0:
+            output += ", metadata=" + ut.print_truncated_dict(self._metadata)
+
+        output += ")"
+        return output
+
+    def __str__(self) -> str:
+        """
+        Returns:
+            A pretty-printed string containing the contents of this object.
+        """
+        output = f"class: {type(self).__name__}\n"
+
+        output += f"dimensions: ({self.shape[0]}, {self.shape[1]})\n"
+
+        output += f"assays({len(self.assay_names)}): {ut.print_truncated_list(self.assay_names)}\n"
+
+        output += f"row_data columns({len(self._rows.column_names)}): {ut.print_truncated_list(self._rows.column_names)}\n"
+        output += f"row_names({0 if self._row_names is None else len(self._row_names)}): {' ' if self._row_names is None else ut.print_truncated_list(self._row_names)}\n"
+
+        output += f"column_data columns({len(self._cols.column_names)}): {ut.print_truncated_list(self._cols.column_names)}\n"
+        output += f"column_names({0 if self._column_names is None else len(self._column_names)}): {' ' if self._column_names is None else ut.print_truncated_list(self._column_names)}\n"
+
+        output += f"metadata({str(len(self.metadata))}): {ut.print_truncated_list(list(self.metadata.keys()), sep=' ', include_brackets=False, transform=lambda y: y)}\n"
+
+        return output
 
     ############################
     ######>> row_ranges <<######

src/summarizedexperiment/__init__.py

@@ -16,4 +16,4 @@
     del version, PackageNotFoundError
 
 from .SummarizedExperiment import SummarizedExperiment
-# from .RangedSummarizedExperiment import RangedSummarizedExperiment
+from .RangedSummarizedExperiment import RangedSummarizedExperiment