diff --git a/native/Cargo.lock b/native/Cargo.lock
index 8f977ff..4f5228e 100644
--- a/native/Cargo.lock
+++ b/native/Cargo.lock
@@ -638,7 +638,7 @@ checksum = "b90ca2580b73ab6a1f724b76ca11ab632df820fd6040c336200d2c1df7b3c82c"
 
 [[package]]
 name = "factor-expr"
-version = "0.2.3"
+version = "0.3.0"
 dependencies = [
  "anyhow",
  "arrow",
diff --git a/native/Cargo.toml b/native/Cargo.toml
index 42e02a2..1790b6d 100644
--- a/native/Cargo.toml
+++ b/native/Cargo.toml
@@ -2,7 +2,7 @@
 authors = ["Weiyuan Wu <weiyuan@crows.land>"]
 edition = "2018"
 name = "factor-expr"
-version = "0.2.3"
+version = "0.3.0"
 
 [lib]
 crate-type = ["rlib", "cdylib"]
diff --git a/native/src/ops/window/minmax.rs b/native/src/ops/window/minmax.rs
index b27f470..217ec09 100644
--- a/native/src/ops/window/minmax.rs
+++ b/native/src/ops/window/minmax.rs
@@ -84,10 +84,11 @@ macro_rules! impl_minmax {
 
                         self.window.push_back((self.seq, val));
 
-                        let val = if self.window.len() == self.win_size {
+                        let val = if self.i >= self.ready_offset() {
                             let val = ($($vfunc)+) (&self.window, self.seq, self.win_size);
                             val
                         } else {
+                            self.i += 1;
                             f64::NAN
                         };
                         results.push(val);
diff --git a/python/factor_expr/replay.py b/python/factor_expr/replay.py
index 0f7047a..2581159 100644
--- a/python/factor_expr/replay.py
+++ b/python/factor_expr/replay.py
@@ -7,7 +7,6 @@
 from tqdm.auto import tqdm
 
 import numpy as np
-import pandas as pd
 import pyarrow as pa
 import pyarrow.parquet as pq
 import pyarrow.compute as pc
diff --git a/python/factor_expr/tests/factors/test_arithmetic.py b/python/factor_expr/tests/factors/test_arithmetic.py
index 94b48ee..55b6496 100644
--- a/python/factor_expr/tests/factors/test_arithmetic.py
+++ b/python/factor_expr/tests/factors/test_arithmetic.py
@@ -16,13 +16,12 @@ def test_add():
             [FILENAME],
             [Factor("(+ :price_ask_l1_high :price_bid_l1_open)")],
             pbar=False,
-            index_col="time",
         )
     )
 
     assert np.isclose(
         df.price_ask_l1_high + df.price_bid_l1_open,
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
@@ -34,28 +33,23 @@ def test_sub():
             [FILENAME],
             [Factor("(- :price_ask_l1_open :price_bid_l1_open)")],
             pbar=False,
-            index_col="time",
         )
     )
 
     assert np.isclose(
         df.price_ask_l1_open - df.price_bid_l1_open,
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
 def test_mul():
     df = pd.read_parquet(FILENAME)
 
-    result = asyncio.run(
-        replay(
-            [FILENAME], [Factor("(* :price_ask_l1_open :price_bid_l1_low)")], pbar=False
-        )
-    )
+    result = asyncio.run(replay([FILENAME], [Factor("(* :price_ask_l1_open :price_bid_l1_low)")], pbar=False))
 
     assert np.isclose(
         df.price_ask_l1_open * df.price_bid_l1_low,
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
@@ -67,76 +61,65 @@ def test_div():
             [FILENAME],
             [Factor("(/ :price_ask_l1_close :price_bid_l1_high)")],
             pbar=False,
-            index_col="time",
         )
     )
 
     assert np.isclose(
         df.price_ask_l1_close / df.price_bid_l1_high,
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
 def test_power():
     df = pd.read_parquet(FILENAME)
 
-    result = asyncio.run(
-        replay([FILENAME], [Factor("(^ 3 :price_ask_l1_open)")], pbar=False)
-    )
+    result = asyncio.run(replay([FILENAME], [Factor("(^ 3 :price_ask_l1_open)")], pbar=False))
 
     assert np.isclose(
-        df.price_ask_l1_open ** 3,
-        result.iloc[:, 0],
+        df.price_ask_l1_open**3,
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
 def test_signed_power():
     df = pd.read_parquet(FILENAME)
 
-    result = asyncio.run(
-        replay([FILENAME], [Factor("(SPow 2 :price_ask_l1_low)")], pbar=False)
-    )
+    result = asyncio.run(replay([FILENAME], [Factor("(SPow 2 :price_ask_l1_low)")], pbar=False))
 
     assert np.isclose(
         np.sign(df.price_ask_l1_low) * df.price_ask_l1_low.abs() ** 2,
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
 def test_log():
     df = pd.read_parquet(FILENAME)
 
-    result = asyncio.run(
-        replay([FILENAME], [Factor("(LogAbs :volume_ask_l1_high)")], pbar=False)
-    )
+    result = asyncio.run(replay([FILENAME], [Factor("(LogAbs :volume_ask_l1_high)")], pbar=False))
 
     assert np.isclose(
         np.log(np.abs(df.volume_ask_l1_high)),
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
 def test_sign():
     df = pd.read_parquet(FILENAME)
 
-    result = asyncio.run(
-        replay([FILENAME], [Factor("(Sign :price_ask_l1_close)")], pbar=False)
-    )
+    result = asyncio.run(replay([FILENAME], [Factor("(Sign :price_ask_l1_close)")], pbar=False))
 
     assert np.isclose(
         np.sign(df.price_ask_l1_close),
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
 
 
 def test_abs():
     df = pd.read_parquet(FILENAME)
 
-    result = asyncio.run(
-        replay([FILENAME], [Factor("(Abs :price_ask_l1_open)")], pbar=False)
-    )
+    result = asyncio.run(replay([FILENAME], [Factor("(Abs :price_ask_l1_open)")], pbar=False))
 
     assert np.isclose(
         np.abs(df.price_ask_l1_open),
-        result.iloc[:, 0],
+        result.to_pandas().iloc[:, 0],
     ).all()
diff --git a/python/factor_expr/tests/factors/test_logic.py b/python/factor_expr/tests/factors/test_logic.py
index a31f2cc..cfda06b 100644
--- a/python/factor_expr/tests/factors/test_logic.py
+++ b/python/factor_expr/tests/factors/test_logic.py
@@ -16,11 +16,10 @@ def test_gt():
             [FILENAME],
             [Factor("(> :price_ask_l1_open 0)")],
             pbar=False,
-            index_col="time",
         )
     )
 
-    assert ((df.price_ask_l1_open > 0).values == result.iloc[:, 0].values).all()
+    assert ((df.price_ask_l1_open > 0).values == result.to_pandas().iloc[:, 0].values).all()
 
 
 def test_gte():
@@ -31,11 +30,10 @@ def test_gte():
             [FILENAME],
             [Factor("(>= :price_ask_l1_low 0)")],
             pbar=False,
-            index_col="time",
         )
     )
 
-    assert ((df.price_ask_l1_low >= 0).values == result.iloc[:, 0].values).all()
+    assert ((df.price_ask_l1_low >= 0).values == result.to_pandas().iloc[:, 0].values).all()
 
 
 def test_lt():
@@ -46,11 +44,10 @@ def test_lt():
             [FILENAME],
             [Factor("(< :price_ask_l1_high 0)")],
             pbar=False,
-            index_col="time",
         )
     )
 
-    assert ((df.price_ask_l1_high < 0).values == result.iloc[:, 0].values).all()
+    assert ((df.price_ask_l1_high < 0).values == result.to_pandas().iloc[:, 0].values).all()
 
 
 def test_lte():
@@ -61,11 +58,10 @@ def test_lte():
             [FILENAME],
             [Factor("(<= :price_ask_l1_close 0)")],
             pbar=False,
-            index_col="time",
         )
     )
 
-    assert ((df.price_ask_l1_close <= 0).values == result.iloc[:, 0].values).all()
+    assert ((df.price_ask_l1_close <= 0).values == result.to_pandas().iloc[:, 0].values).all()
 
 
 def test_or():
@@ -79,8 +75,7 @@ def test_or():
     )
 
     assert (
-        ((df.price_ask_l1_close < 0).values | (df.price_bid_l1_high > 0).values)
-        == result.iloc[:, 0].values
+        ((df.price_ask_l1_close < 0).values | (df.price_bid_l1_high > 0).values) == result.to_pandas().iloc[:, 0].values
     ).all()
 
 
@@ -95,8 +90,7 @@ def test_and():
     )
 
     assert (
-        ((df.price_ask_l1_open < 0).values & (df.price_bid_l1_low > 0).values)
-        == result.iloc[:, 0].values
+        ((df.price_ask_l1_open < 0).values & (df.price_bid_l1_low > 0).values) == result.to_pandas().iloc[:, 0].values
     ).all()
 
 
@@ -111,8 +105,7 @@ def test_not():
     )
 
     assert (
-        ~((df.price_ask_l1_close < 0).values & (df.price_bid_l1_low > 0).values)
-        == result.iloc[:, 0].values
+        ~((df.price_ask_l1_close < 0).values & (df.price_bid_l1_low > 0).values) == result.to_pandas().iloc[:, 0].values
     ).all()
 
 
@@ -122,13 +115,8 @@ def test_if():
     result = asyncio.run(
         replay(
             [FILENAME],
-            [
-                Factor(
-                    "(If (< :price_ask_l1_high 0) :price_ask_l1_close :price_bid_l1_open)"
-                )
-            ],
+            [Factor("(If (< :price_ask_l1_high 0) :price_ask_l1_close :price_bid_l1_open)")],
             pbar=False,
-            index_col="time",
         )
     )
 
@@ -138,5 +126,5 @@ def test_if():
             df.price_ask_l1_close.values,
             df.price_bid_l1_open.values,
         )
-        == result.iloc[:, 0].values
+        == result.to_pandas().iloc[:, 0].values
     ).all()
diff --git a/python/factor_expr/tests/factors/test_sanity.py b/python/factor_expr/tests/factors/test_sanity.py
index 9c59d0e..c5345c0 100644
--- a/python/factor_expr/tests/factors/test_sanity.py
+++ b/python/factor_expr/tests/factors/test_sanity.py
@@ -9,34 +9,11 @@
 
 
 def test_index():
-    f = Factor("(TSMean 10 :price_ask_l1_open)")
+    f = Factor("(Mean 10 :price_ask_l1_open)")
     asyncio.run(
         replay(
             [FILENAME],
             [f],
-            trim=False,
-            index_col="time",
             pbar=False,
         )
     )
-
-
-def test_trim():
-    f = Factor("(TSMean 10 :price_ask_l1_open)")
-    asyncio.run(replay([FILENAME], [f], trim=True, pbar=False))
-
-
-def test_predicate():
-    f = Factor("(TSMean 10 :price_ask_l1_open)")
-    predicate = Factor(
-        "(> (TSStd 60 (TSLogReturn 120 (+ :price_bid_l1_close :price_ask_l1_close))) 0.005)"
-    )
-    asyncio.run(replay([FILENAME], [f], predicate=predicate, pbar=False))
-
-
-def test_predicate_with_trim():
-    f = Factor("(TSMean 10 :price_ask_l1_open)")
-    predicate = Factor(
-        "(> (TSStd 60 (TSLogReturn 120 (+ :price_bid_l1_close :price_ask_l1_close))) 0.005)"
-    )
-    asyncio.run(replay([FILENAME], [f], predicate=predicate, trim=True, pbar=False))
diff --git a/python/factor_expr/tests/factors/test_window.py b/python/factor_expr/tests/factors/test_window.py
index fb81e5c..6d0041c 100644
--- a/python/factor_expr/tests/factors/test_window.py
+++ b/python/factor_expr/tests/factors/test_window.py
@@ -10,88 +10,71 @@
 
 def test_sum():
     df = pd.read_parquet(FILENAME)
-    f = Factor("(TSSum 10 :price_ask_l1_close)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
-
+    f = Factor("(Sum 10 :price_ask_l1_close)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
     assert np.isclose(
         df.price_ask_l1_close.rolling(10).sum().values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_mean():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSMean 10 :price_ask_l1_open)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Mean 10 :price_ask_l1_open)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
         df.price_ask_l1_open.rolling(10).mean().values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_correlation():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSCorr 10 :price_ask_l1_high :price_bid_l1_low)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Corr 10 :price_ask_l1_high :price_bid_l1_low)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     def func(sub):
         subdf = df.loc[sub.index]
         return np.corrcoef(subdf.price_ask_l1_high, subdf.price_bid_l1_low)[0, 1]
 
     assert np.isclose(
-        np.nan_to_num(
-            df.price_ask_l1_high.rolling(10)
-            .apply(func, raw=False)
-            .values[f.ready_offset() :]
-        ),
-        result.values.ravel(),
+        np.nan_to_num(df.price_ask_l1_high.rolling(10).apply(func, raw=False).values)[f.ready_offset() :],
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_min():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSMin 10 :price_ask_l1_close)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Min 10 :price_ask_l1_close)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
         df.price_ask_l1_close.rolling(10).min().values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_max():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSMax 10 :price_ask_l1_open)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Max 10 :price_ask_l1_open)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
         df.price_ask_l1_open.rolling(10).max().values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_argmax():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSArgMax 10 :price_ask_l1_close)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(ArgMax 10 :price_ask_l1_close)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     def func(sub):
         subdf = df.loc[sub.index]
@@ -99,17 +82,15 @@ def func(sub):
 
     assert np.isclose(
         df.price_ask_l1_close.rolling(10).apply(func).values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_argmin():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSArgMin 10 :price_ask_l1_low)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(ArgMin 10 :price_ask_l1_low)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     def func(sub):
         subdf = df.loc[sub.index]
@@ -117,21 +98,19 @@ def func(sub):
 
     assert np.isclose(
         df.price_ask_l1_low.rolling(10).apply(func).values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_std():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSStd 10 :price_ask_l1_high)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Std 10 :price_ask_l1_high)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
         df.price_ask_l1_high.rolling(10).std().values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
         atol=1e-5,
     ).all()
 
@@ -139,16 +118,12 @@ def test_std():
 def test_skew():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSSkew 10 :price_bid_l1_high)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Skew 10 :price_bid_l1_high)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
-        np.nan_to_num(
-            df.price_bid_l1_high.rolling(10).skew().values[f.ready_offset() :]
-        ),
-        result.values.ravel(),
+        np.nan_to_num(df.price_bid_l1_high.rolling(10).skew().values)[f.ready_offset() :],
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
@@ -156,80 +131,61 @@ def test_delay():
     df = pd.read_parquet(FILENAME)
 
     f = Factor("(Delay 10 :price_ask_l1_close)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
         df.price_ask_l1_close.shift(10).values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_rank():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSRank 10 :price_ask_l1_open)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Rank 10 :price_ask_l1_open)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     def func(sub):
         subdf = df.loc[sub.index]
-        return (
-            subdf.price_ask_l1_open.values[-1] > subdf.price_ask_l1_open.values
-        ).sum()
+        return (subdf.price_ask_l1_open.values[-1] > subdf.price_ask_l1_open.values).sum()
 
     assert np.isclose(
         df.price_ask_l1_open.rolling(10).apply(func).values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_logreturn():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSLogReturn 100 (Abs :price_ask_l1_high))")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(LogReturn 100 (Abs :price_ask_l1_high))")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
-        np.log(
-            np.abs(
-                df.price_ask_l1_high.values[f.ready_offset() :]
-                / df.price_ask_l1_high.values[: -f.ready_offset()]
-            )
-        ),
-        result.values.ravel(),
+        np.log(df.price_ask_l1_high.abs().pct_change(100) + 1)[f.ready_offset() :],
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_quantile():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSQuantile 30 0.3 :price_bid_l1_open)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Quantile 30 0.3 :price_bid_l1_open)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
-        df.price_bid_l1_open.rolling(30)
-        .quantile(0.3, "lower")
-        .values[f.ready_offset() :],
-        result.values.ravel(),
+        df.price_bid_l1_open.rolling(30).quantile(0.3, "lower").values[f.ready_offset() :],
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
 
 
 def test_median():
     df = pd.read_parquet(FILENAME)
 
-    f = Factor("(TSQuantile 37 0.5 :price_bid_l1_open)")
-    result = asyncio.run(
-        replay([FILENAME], [f], trim=True, pbar=False, index_col="time")
-    )
+    f = Factor("(Quantile 37 0.5 :price_bid_l1_open)")
+    result = asyncio.run(replay([FILENAME], [f], pbar=False))
 
     assert np.isclose(
         df.price_bid_l1_open.rolling(37).median().values[f.ready_offset() :],
-        result.values.ravel(),
+        result.to_pandas().values.ravel()[f.ready_offset() :],
     ).all()
diff --git a/python/poetry.lock b/python/poetry.lock
index 12266a3..fc7e93e 100644
--- a/python/poetry.lock
+++ b/python/poetry.lock
@@ -1,15 +1,5 @@
 # This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
-[[package]]
-name = "atomicwrites"
-version = "1.4.1"
-description = "Atomic file writes."
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
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 version = "23.2.0"
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 tomlkit = ["tomlkit (>=0.11.8)"]
 ujson = ["ujson (>=5.7.0)"]
 
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+
+[package.dependencies]
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+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -300,64 +354,64 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
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+    {file = "pyarrow-15.0.0.tar.gz", hash = "sha256:876858f549d540898f927eba4ef77cd549ad8d24baa3207cf1b72e5788b50e83"},
 ]
 
 [package.dependencies]
-numpy = ">=1.16.6"
+numpy = ">=1.16.6,<2"
+
+[[package]]
+name = "pycparser"
+version = "2.21"
+description = "C parser in Python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "pycparser-2.21-py2.py3-none-any.whl", hash = "sha256:8ee45429555515e1f6b185e78100aea234072576aa43ab53aefcae078162fca9"},
+    {file = "pycparser-2.21.tar.gz", hash = "sha256:e644fdec12f7872f86c58ff790da456218b10f863970249516d60a5eaca77206"},
+]
 
 [[package]]
 name = "pyright"
@@ -379,27 +433,23 @@ dev = ["twine (>=3.4.1)"]
 
 [[package]]
 name = "pytest"
-version = "6.2.5"
+version = "7.4.4"
 description = "pytest: simple powerful testing with Python"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
-    {file = "pytest-6.2.5-py3-none-any.whl", hash = "sha256:7310f8d27bc79ced999e760ca304d69f6ba6c6649c0b60fb0e04a4a77cacc134"},
-    {file = "pytest-6.2.5.tar.gz", hash = "sha256:131b36680866a76e6781d13f101efb86cf674ebb9762eb70d3082b6f29889e89"},
+    {file = "pytest-7.4.4-py3-none-any.whl", hash = "sha256:b090cdf5ed60bf4c45261be03239c2c1c22df034fbffe691abe93cd80cea01d8"},
+    {file = "pytest-7.4.4.tar.gz", hash = "sha256:2cf0005922c6ace4a3e2ec8b4080eb0d9753fdc93107415332f50ce9e7994280"},
 ]
 
 [package.dependencies]
-atomicwrites = {version = ">=1.0", markers = "sys_platform == \"win32\""}
-attrs = ">=19.2.0"
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
-py = ">=1.8.2"
-toml = "*"
 
 [package.extras]
-testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "python-dateutil"
@@ -548,17 +598,6 @@ files = [
     {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
 ]
 
-[[package]]
-name = "toml"
-version = "0.10.2"
-description = "Python Library for Tom's Obvious, Minimal Language"
-optional = false
-python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
-files = [
-    {file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
-    {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
-]
-
 [[package]]
 name = "tqdm"
 version = "4.66.1"
@@ -667,4 +706,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "8d2303ae8f3d5cc50dc9e6613ab75a7b2d553f6c4cbcb569541f4316aa88037f"
+content-hash = "92f329fedd56ea70f5b71d3479e80d5d47bd0296458d189e42176d5d32d60ff8"
diff --git a/python/pyproject.toml b/python/pyproject.toml
index a6fc48d..ee79321 100644
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -16,12 +16,11 @@ keywords = ["factor", "expression", "alpha", "S-expression", "quantative trading
 license = "MIT"
 name = "factor_expr"
 readme = "README.md"
-version = "0.2.3"
+version = "0.3.0"
 
 [tool.poetry.dependencies]
 numpy = "^1.26"
-pandas = "^2"
-pyarrow = "^14"
+pyarrow = {extras = ["cffi"], version = "^15.0.0"}
 python = "^3.11"
 tqdm = "^4"
 
@@ -30,7 +29,9 @@ ruff = "^0.1.13"
 python-lsp-ruff = "^2.0.2"
 pyright = "^1.1.347"
 docopt = "^0.6.2"
-pytest = "^6.2.3"
+cffi = "^1.16.0"
+pytest = "^7.4.4"
+pandas = "^2.2.0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]