Unify CTable indexing around t[...]

 - Make CTable.getitem type-driven for rows, columns, and expressions
 - Return namedtuple-like rows for integer indexing
 - Keep slices, gathers, masks, and projections as CTable views
 - Add t["expr"] shorthand for boolean row filtering
 - Add where(..., columns=[...]) filtered projection
 - Add NumPy structured-array materialization via array()
 - Remove the legacy t.row[...] accessor
 - Update tests, docs, examples, and benches to the new API

Author: FrancescAlted

bench/ctable/row_access.py

@@ -5,7 +5,7 @@
 # SPDX-License-Identifier: BSD-3-Clause
 #######################################################################
 
-# Benchmark for measuring row[int] access (full row via _RowIndexer),
+# Benchmark for measuring row[int] access via CTable.__getitem__,
 # testing access at different positions across the array.
 
 from dataclasses import dataclass
@@ -54,7 +54,7 @@ class Row:
 
 for idx in indices:
     t0 = time()
-    row = ct.row[idx]
+    row = ct[idx]
     t_access = time() - t0
     position = f"{idx / N * 100:.0f}% into array"
     print(f"{idx:<15,} {position:>12}   {t_access:.6f}")

doc/reference/ctable.rst

@@ -153,9 +153,35 @@ or use string expressions when that reads better::
 
     t.where("amount > 100 and region == 'North'")
     t.where("not returned")
+    t["not returned"]
 
-The last two forms for negating a boolean column are equivalent: ``t.where(~t.returned)``
-and ``t.where("not returned")``.
+The last three forms for negating a boolean column are equivalent:
+``t.where(~t.returned)``, ``t.where("not returned")``, and
+``t["not returned"]``.
+
+Indexing & projection
+~~~~~~~~~~~~~~~~~~~~~
+
+CTable indexing is type-driven::
+
+    t["amount"]                 # column access
+    t[3]                        # one row as a namedtuple-like object
+    t[3:8]                      # row view
+    t[[1, 4, 7]]                # gathered-row view
+    t[mask]                     # filtered row view
+    t[["region", "amount"]]   # projected column view
+
+String keys first try exact column-name lookup.  If the string is not a
+column name, it is interpreted as a boolean expression and behaves like
+:meth:`CTable.where`.
+
+For explicit filtered projection, use::
+
+    t.where("amount > 100", columns=["region", "amount"])
+
+When a NumPy structured array is needed, materialize explicitly::
+
+    np.asarray(t[:10])
 
 .. autosummary::
 

examples/ctable/basics.py

@@ -5,7 +5,7 @@
 # SPDX-License-Identifier: BSD-3-Clause
 #######################################################################
 
-# CTable basics: creation, append, extend, head/tail, len.
+# CTable basics: creation, append, extend, row access, head/tail, len.
 
 from dataclasses import dataclass
 
@@ -41,7 +41,8 @@ class Row:
 arr["price"] = np.linspace(10.0, 14.0, 5)
 arr["active"] = [True, False, True, False, True]
 t.extend(arr)
-print(f"After numpy extend: {len(t)} rows\n")
+print(f"After numpy extend: {len(t)} rows")
+print(f"Row 0 via t[0]: {t[0]}\n")
 
 # -- display: head / tail / full table --------------------------------------
 print("head(3):")

examples/ctable/querying.py

@@ -5,7 +5,7 @@
 # SPDX-License-Identifier: BSD-3-Clause
 #######################################################################
 
-# Querying: where() filters, select() column projection, and chaining.
+# Querying: expression indexing, where() filters, projection, and chaining.
 
 from dataclasses import dataclass
 
@@ -40,7 +40,7 @@ class Sale:
 print(f"Sales > $200: {len(high_value)} rows")
 print(high_value)
 
-not_returned = t.where("not returned")
+not_returned = t["not returned"]
 print(f"Not returned: {len(not_returned)} rows")
 
 # -- chained filters (views are composable) ---------------------------------
@@ -49,12 +49,12 @@ class Sale:
 print(f"North region + amount > 100: {len(north_big)} rows")
 print(north_big)
 
-# -- select(): column projection (no data copy) -----------------------------
-slim = t.select(["id", "amount"])
+# -- column projection via [] (no data copy) --------------------------------
+slim = t[["id", "amount"]]
 print("id + amount only:")
 print(slim)
 
-# -- combined: select columns, then filter rows -----------------------------
-result = t.where("not returned").select(["region", "amount"])
+# -- combined filter + projection -------------------------------------------
+result = t.where("not returned", columns=["region", "amount"])
 print("Region + amount for non-returned sales:")
 print(result)