fixtests

Signed-off-by: Robert Kruszewski <github@robertk.io>

Author: robert3005

docs/api/python/expr.rst

@@ -57,11 +57,11 @@ the following expression represents the set of rows for which the `age` column l
       ...     {"x": 2, "y": {"yy": "b"}},
       ... ])
       >>>
-      >>> vx.io.write(vx.array(array), '/tmp/foo.vortex')
-      >>> (vx.file.open('/tmp/foo.vortex')
+      >>> session = vx.Session()
+      >>> vx.io.write(vx.array(array), '/tmp/foo.vortex', session=session)
+      >>> (vx.file.open('/tmp/foo.vortex', session=session)
       ...    .scan(expr=vx.expr.column("y")["yy"] == "a")
       ...    .read_all()
-      ...    .to_pylist()
+      ...    .to_pylist(session=session)
       ... )
       [{'x': 1, 'y': {'yy': 'a'}}]
-

docs/conf.py

@@ -58,7 +58,9 @@
 nitpicky = True  # ensures all :class:, :obj:, etc. links are valid
 nitpick_ignore = []
 
-doctest_global_setup = "import pyarrow; import vortex; import vortex as vx; import random; random.seed(a=0)"
+doctest_global_setup = (
+    "import pyarrow; import vortex; import vortex as vx; import random; random.seed(a=0); session = vx.Session()"
+)
 doctest_default_flags = (
     doctest.ELLIPSIS | doctest.IGNORE_EXCEPTION_DETAIL | doctest.DONT_ACCEPT_TRUE_FOR_1 | doctest.NORMALIZE_WHITESPACE
 )

docs/getting-started/python.rst

@@ -36,7 +36,8 @@ Use :func:`~vortex.io.write` to write the Vortex array to disk:
 .. doctest::
 
    >>> import vortex as vx
-   >>> vx.io.write(vtx, "example.vortex")  # doctest: +SKIP
+   >>> session = vx.Session()
+   >>> vx.io.write(vtx, "example.vortex", session=session)  # doctest: +SKIP
 
 Small Vortex files (this one is just 71KiB) currently have substantial overhead relative to their
 size. This will be addressed shortly. On files with at least tens of megabytes of data, Vortex is
@@ -56,7 +57,8 @@ Use :func:`~vortex.open` to open and read the Vortex array from disk:
 .. doctest::
 
    >>> import vortex as vx
-   >>> cvtx = vx.open("example.vortex").scan().read_all()  # doctest: +SKIP
+   >>> session = vx.Session()
+   >>> cvtx = vx.open("example.vortex", session=session).scan().read_all()  # doctest: +SKIP
 
 
 Vortex is architected to achieve fast random access, in many cases hundreds of times faster
@@ -68,7 +70,8 @@ IO and decoding and read just the data that is relevant to you:
 .. doctest::
 
     >>> import vortex as vx
-    >>> vf = vx.open("example.vortex")  # doctest: +SKIP
+    >>> session = vx.Session()
+    >>> vf = vx.open("example.vortex", session=session)  # doctest: +SKIP
     >>> # row indices must be ordered and unique
     >>> indices = vx.array([1, 2, 10])
     >>> result = vf.scan(indices=indices).read_all()  # doctest: +SKIP

docs/user-guide/pandas.md

@@ -10,10 +10,11 @@ convert:
 ```{doctest} pycon
 >>> import vortex as vx
 >>> import pyarrow.parquet as pq
->>> vx.io.write(pq.read_table("_static/example.parquet"), 'example.vortex')
+>>> session = vx.Session()
+>>> vx.io.write(pq.read_table("_static/example.parquet"), 'example.vortex', session=session)
 >>>
->>> f = vx.open('example.vortex')
->>> df = f.scan().read_all().to_pandas()
+>>> f = vx.open('example.vortex', session=session)
+>>> df = f.scan().read_all().to_pandas(session=session)
 >>> df[['tip_amount', 'fare_amount']].head(3)
    tip_amount  fare_amount
 0         0.0         61.8
@@ -36,7 +37,7 @@ convert:
 ... {'name': 'Angela', 'age': 33},
 ... {'name': 'Mikhail', 'age': 57},
 ... ])
->>> struct_arr.to_pandas()
+>>> struct_arr.to_pandas(session=session)
       age      name
    0   25    Joseph
    1   31  Narendra
@@ -49,7 +50,7 @@ convert:
 ```{doctest} pycon
 >>> import pandas as pd
 >>> df = pd.DataFrame({'age': [25, 31, 33, 57], 'name': ['Joseph', 'Narendra', 'Angela', 'Mikhail']})
->>> vx.array(df).to_arrow_table()
+>>> vx.array(df).to_arrow_table(session=session)
 pyarrow.Table
 age: int64
 name: string_view

docs/user-guide/polars.md

@@ -13,9 +13,10 @@ Vortex integrates with Polars via {meth}`.VortexFile.to_polars`, which returns a
 ```{doctest} pycon
 >>> import vortex as vx
 >>> import pyarrow.parquet as pq
->>> vx.io.write(pq.read_table("_static/example.parquet"), 'example.vortex')
+>>> session = vx.Session()
+>>> vx.io.write(pq.read_table("_static/example.parquet"), 'example.vortex', session=session)
 >>>
->>> lf = vx.open('example.vortex').to_polars()
+>>> lf = vx.open('example.vortex', session=session).to_polars()
 >>> lf = lf.select('tip_amount', 'fare_amount')
 >>> lf = lf.head(3)
 >>> lf.collect()

docs/user-guide/pyarrow.md

@@ -13,16 +13,17 @@ anything that implements `IntoArrayIterator`, including {class}`pyarrow.Table` a
 >>> import pyarrow.parquet as pq
 >>> import vortex as vx
 >>>
+>>> session = vx.Session()
 >>> table = pq.read_table("_static/example.parquet")
->>> vx.io.write(table, 'example.vortex')
+>>> vx.io.write(table, 'example.vortex', session=session)
 ```
 
 ## Reading Vortex Files
 
 Use {func}`~vortex.open` to lazily open a Vortex file:
 
 ```{doctest} pycon
->>> f = vx.open('example.vortex')
+>>> f = vx.open('example.vortex', session=session)
 >>> len(f)
 1000
 ```
@@ -75,7 +76,7 @@ int(64, nullable=True)
 {meth}`.Array.to_arrow_array` converts back:
 
 ```{doctest} pycon
->>> arr.to_arrow_array()
+>>> arr.to_arrow_array(session=session)
 <pyarrow.lib.Int64Array object at ...>
 [
 1,
@@ -94,7 +95,7 @@ Struct arrays convert to Arrow tables with {meth}`.Array.to_arrow_table`:
 ... {'name': 'Angela', 'age': 33},
 ... {'name': 'Mikhail', 'age': 57},
 ... ])
->>> struct_arr.to_arrow_table()
+>>> struct_arr.to_arrow_table(session=session)
 pyarrow.Table
 age: int64
 name: string

docs/user-guide/ray.md

@@ -11,14 +11,15 @@ and then run `make -C docs doctest` -->
 >>> import os
 >>> os.makedirs("ray_data", exist_ok=True)
 >>> table = pq.read_table("_static/example.parquet")
->>> vx.io.write(table, 'ray_data/example-01.vortex')
->>> vx.io.write(table, 'ray_data/example-02.vortex')
->>> vx.io.write(table, 'ray_data/example-03.vortex')
+>>> session = vx.Session()
+>>> vx.io.write(table, 'ray_data/example-01.vortex', session=session)
+>>> vx.io.write(table, 'ray_data/example-02.vortex', session=session)
+>>> vx.io.write(table, 'ray_data/example-03.vortex', session=session)
 >>>
 >>> from vortex.ray.datasource import VortexDatasource
 >>> from ray.data import read_datasource
 >>>
->>> ds = read_datasource(VortexDatasource(url='ray_data')) # doctest: +SKIP
+>>> ds = read_datasource(VortexDatasource(url='ray_data', session=session)) # doctest: +SKIP
 >>> ds.to_pandas() # doctest: +SKIP
       VendorID tpep_pickup_datetime  ... congestion_surcharge  Airport_fee
 0            1  2023-11-01 00:03:03  ...                  0.0         1.75

docs/user-guide/vortex-python.md

@@ -82,36 +82,37 @@ Available types: {func}`~vortex.null`, {func}`~vortex.bool_`,
 ### Element Access
 
 ```{doctest} pycon
+>>> session = vx.Session()
 >>> arr = vx.array([10, 20, 30, 40, 50])
->>> arr.scalar_at(0).as_py()
+>>> arr.scalar_at(0, session=session).as_py()
 10
->>> arr.to_arrow_array().to_pylist()
+>>> arr.to_arrow_array(session=session).to_pylist()
 [10, 20, 30, 40, 50]
 ```
 
 ### Slicing and Selection
 
 ```{doctest} pycon
->>> arr.slice(1, 3).to_arrow_array().to_pylist()
+>>> arr.slice(1, 3).to_arrow_array(session=session).to_pylist()
 [20, 30]
 >>> indices = vx.array([0, 2, 4])
->>> arr.take(indices).to_arrow_array().to_pylist()
+>>> arr.take(indices).to_arrow_array(session=session).to_pylist()
 [10, 30, 50]
 ```
 
 ### Filtering
 
 ```{doctest} pycon
 >>> mask = vx.array([True, False, True, False, True])
->>> arr.filter(mask).to_arrow_array().to_pylist()
+>>> arr.filter(mask, session=session).to_arrow_array(session=session).to_pylist()
 [10, 30, 50]
 ```
 
 ### Comparisons
 
 ```{doctest} pycon
 >>> other = vx.array([10, 25, 25, 45, 50])
->>> (arr > other).to_arrow_array().to_pylist()
+>>> (arr > other).to_arrow_array(session=session).to_pylist()
 [False, False, True, False, False]
 ```
 
@@ -129,7 +130,7 @@ applied directly:
 ...     {'name': 'Carol', 'age': 35},
 ... ])
 >>> expr = ve.column('age') > 28
->>> arr.apply(expr).to_arrow_array().to_pylist()
+>>> arr.apply(expr).to_arrow_array(session=session).to_pylist()
 [True, False, True]
 ```
 
@@ -139,9 +140,10 @@ applied directly:
 
 ```{doctest} pycon
 >>> import pyarrow.parquet as pq
->>> vx.io.write(pq.read_table("_static/example.parquet"), 'example.vortex')
+>>> session = vx.Session()
+>>> vx.io.write(pq.read_table("_static/example.parquet"), 'example.vortex', session=session)
 >>>
->>> f = vx.open('example.vortex')
+>>> f = vx.open('example.vortex', session=session)
 >>> len(f)
 1000
 ```
@@ -150,7 +152,7 @@ Use {meth}`.VortexFile.scan` to read data with optional projection, filtering, a
 
 ```{doctest} pycon
 >>> result = f.scan(['tip_amount'], limit=3).read_all()
->>> result.to_arrow_array()
+>>> result.to_arrow_array(session=session)
 <pyarrow.lib.StructArray object at ...>
 -- is_valid: all not null
 -- child 0 type: double