Upgrade polars to 0.50

Cargo.toml

@@ -31,7 +31,7 @@ exclude = [
 ]
 
 [dependencies]
-polars = { version = "0.47.1", features = ["lazy", "strings", "temporal", "rolling_window", "parquet", "dtype-categorical", "dtype-struct"] }
+polars = { version = "0.53", features = ["lazy", "strings", "temporal", "rolling_window", "parquet", "dtype-categorical", "dtype-struct", "timezones", "regex"] }
 chrono = "0.4.34"
 thiserror = "2.0.11" # Consider updating if needed, check compatibility
 ndarray = "0.16.1" # Consider updating if needed, check compatibility
@@ -102,4 +102,4 @@ path = "examples/trend_adx_basic.rs"
 [lib]
 name = "rustalib"
 path = "src/lib.rs"
-doctest = false
+doctest = false

examples/bollinger_bands_basic.rs

@@ -13,7 +13,7 @@ fn main() -> Result<(), PolarsError> {
     );
 
     // Create DataFrame with price data
-    let df = DataFrame::new(vec![close_prices.clone().into()])?;
+    let df = DataFrame::new(close_prices.len(), vec![close_prices.clone().into()])?;
 
     // Calculate Bollinger Bands with standard parameters (20-period, 2 standard deviations)
     let (middle, upper, lower) = calculate_bollinger_bands(&df, 20, 2.0, "close")?;

examples/debug_array_lengths.rs

@@ -127,10 +127,10 @@ fn main() -> Result<(), PolarsError> {
     println!("  closes_series: {}", closes_series.len());
 
     // Create DataFrame
-    let mut df = DataFrame::new(vec![
-        dates_series.clone().into(),
-        closes_series.clone().into(),
-    ])?;
+    let mut df = DataFrame::new(
+        dates_series.len(),
+        vec![dates_series.clone().into(), closes_series.clone().into()],
+    )?;
 
     println!("\nDataFrame height: {}", df.height());
 
@@ -144,7 +144,7 @@ fn main() -> Result<(), PolarsError> {
     println!("DataFrame height: {}", df.height());
 
     // Try to add the test vector to the DataFrame
-    let test_series = Series::new("test".into(), test_vec);
+    let test_series = Column::new("test".into(), test_vec);
     match df.with_column(test_series) {
         Ok(new_df) => {
             println!("Success! New DataFrame height: {}", new_df.height());

examples/general/basic_indicators.rs

@@ -17,7 +17,7 @@ fn main() -> Result<(), PolarsError> {
     );
 
     // Create DataFrame with price data
-    let df = DataFrame::new(vec![close_prices.clone().into()])?;
+    let df = DataFrame::new(close_prices.len(), vec![close_prices.clone().into()])?;
 
     println!("Basic Technical Indicators Example\n");
 

examples/macd_basic.rs

@@ -13,7 +13,7 @@ fn main() -> Result<(), PolarsError> {
     );
 
     // Create DataFrame with price data
-    let df = DataFrame::new(vec![close_prices.clone().into()])?;
+    let df = DataFrame::new(close_prices.len(), vec![close_prices.clone().into()])?;
 
     // Calculate MACD with standard parameters
     // fast_period = 12, slow_period = 26, signal_period = 9

examples/mean_reversion_test.rs

@@ -21,7 +21,10 @@ fn main() -> Result<(), PolarsError> {
     let values = Series::new("value".into(), &[10.0, 11.0, 12.0, 13.0, 14.0]);
 
     // Create DataFrame
-    let mut df = DataFrame::new(vec![dates.clone().into(), values.clone().into()])?;
+    let mut df = DataFrame::new(
+        values.len(),
+        vec![dates.clone().into(), values.clone().into()],
+    )?;
 
     // Print information
     println!("Original DataFrame:");
@@ -45,7 +48,7 @@ fn main() -> Result<(), PolarsError> {
     let doubles_series = Series::new("doubles".into(), doubles);
 
     // Add the new column
-    df.with_column(doubles_series)?;
+    df.with_column(doubles_series.into_column())?;
     println!("\nDataFrame with new column:");
     println!("{}", df);
 

examples/moving_averages_basic.rs

@@ -13,7 +13,7 @@ fn main() -> Result<(), PolarsError> {
     );
 
     // Create DataFrame with price data
-    let df = DataFrame::new(vec![close_prices.clone().into()])?;
+    let df = DataFrame::new(close_prices.len(), vec![close_prices.clone().into()])?;
 
     // Calculate different moving averages
     let sma_10 = calculate_sma(&df, "close", 10)?;

examples/options/vertical_spreads.rs

@@ -54,7 +54,7 @@ fn main() -> Result<(), PolarsError> {
     let description = Series::new("description".into(), description_vec);
 
     // Create a DataFrame with our spread data
-    let mut df = DataFrame::new(vec![
+    let mut df = DataFrame::new(short_strike.len(), vec![
         short_strike.into(),
         long_strike.into(),
         short_price.into(),
@@ -123,11 +123,11 @@ fn main() -> Result<(), PolarsError> {
     }
 
     // Add calculated metrics to the dataframe
-    df.with_column(Series::new("max_profit".into(), max_profit))?;
-    df.with_column(Series::new("max_loss".into(), max_loss))?;
-    df.with_column(Series::new("breakeven".into(), breakeven))?;
-    df.with_column(Series::new("risk_reward".into(), risk_reward))?;
-    df.with_column(Series::new("strike_width".into(), strike_width))?;
+    df.with_column(Column::new("max_profit".into(), max_profit))?;
+    df.with_column(Column::new("max_loss".into(), max_loss))?;
+    df.with_column(Column::new("breakeven".into(), breakeven))?;
+    df.with_column(Column::new("risk_reward".into(), risk_reward))?;
+    df.with_column(Column::new("strike_width".into(), strike_width))?;
 
     // Display the results
     println!("Vertical Spread Metrics:");

examples/rsi_basic.rs

@@ -12,7 +12,7 @@ fn main() -> Result<(), PolarsError> {
     );
 
     // Create DataFrame with date and price data
-    let df = DataFrame::new(vec![close_prices.clone().into()])?;
+    let df = DataFrame::new(close_prices.len(), vec![close_prices.clone().into()])?;
 
     // Calculate RSI with 5-period setting for this short example
     let rsi = calculate_rsi(&df, 5, "close")?;

examples/simple_dataframe.rs

@@ -7,7 +7,7 @@ fn main() -> Result<(), PolarsError> {
     let values = Series::new("value".into(), &[10.0, 11.0, 12.0]);
 
     // Create DataFrame
-    let df = DataFrame::new(vec![dates.clone().into(), values.clone().into()])?;
+    let df = DataFrame::new(3, vec![dates.clone().into(), values.clone().into()])?;
 
     // Print information
     println!(

examples/stock/mean_reversion.rs

@@ -163,14 +163,17 @@ fn main() -> Result<(), PolarsError> {
     println!("  Volume count: {}", volumes.len());
 
     // Create DataFrame
-    let mut df = DataFrame::new(vec![
-        dates.into(),
-        opens.into(),
-        highs.into(),
-        lows.into(),
-        closes.clone().into(),
-        volumes.into(),
-    ])?;
+    let mut df = DataFrame::new(
+        opens.len(),
+        vec![
+            dates.into(),
+            opens.into(),
+            highs.into(),
+            lows.into(),
+            closes.clone().into(),
+            volumes.into(),
+        ],
+    )?;
 
     // Calculate indicators
     // 1. Calculate SMA
@@ -180,15 +183,15 @@ fn main() -> Result<(), PolarsError> {
         sma_20.len(),
         df.height()
     );
-    df.with_column(sma_20)?;
+    df.with_column(sma_20.into_column())?;
 
     // 2. Calculate Bollinger Bands
     let (middle, upper, lower) = calculate_bollinger_bands(&df, 20, 2.0, "close")?;
-    println!("Middle Band length: {}, Upper Band length: {}, Lower Band length: {}, DataFrame height: {}", 
+    println!("Middle Band length: {}, Upper Band length: {}, Lower Band length: {}, DataFrame height: {}",
              middle.len(), upper.len(), lower.len(), df.height());
-    df.with_column(middle)?;
-    df.with_column(upper)?;
-    df.with_column(lower)?;
+    df.with_column(middle.into_column())?;
+    df.with_column(upper.into_column())?;
+    df.with_column(lower.into_column())?;
 
     // 3. Calculate RSI
     let rsi = calculate_rsi(&df, 14, "close")?;
@@ -223,12 +226,12 @@ fn main() -> Result<(), PolarsError> {
             padded_rsi.len(),
             df.height()
         );
-        df.with_column(padded_rsi)?;
+        df.with_column(padded_rsi.into_column())?;
     } else {
         // Rename RSI column to ensure consistency
         let rsi_values = rsi.f64()?.to_vec();
         let renamed_rsi = Series::new("rsi".into(), rsi_values);
-        df.with_column(renamed_rsi)?;
+        df.with_column(renamed_rsi.into_column())?;
     }
 
     // 4. Calculate Z-Score (a simpler measure of mean reversion)
@@ -343,7 +346,7 @@ fn calculate_z_score(df: &mut DataFrame, window: usize) -> Result<(), PolarsErro
         z_scores.len(),
         height
     );
-    df.with_column(Series::new("z_score".into(), z_scores))?;
+    df.with_column(Column::new("z_score".into(), z_scores))?;
 
     Ok(())
 }
@@ -384,7 +387,7 @@ fn calculate_mean_reversion_signals(df: &mut DataFrame) -> Result<(), PolarsErro
     );
 
     // Add signals to dataframe
-    df.with_column(Series::new("signal".into(), signals))?;
+    df.with_column(Column::new("signal".into(), signals))?;
 
     Ok(())
 }

examples/stock/trend_following.rs

@@ -163,14 +163,17 @@ fn main() -> Result<(), PolarsError> {
     println!("  Volume count: {}", volumes.len());
 
     // Create DataFrame
-    let mut df = DataFrame::new(vec![
-        dates.into(),
-        opens.into(),
-        highs.into(),
-        lows.into(),
-        closes.clone().into(),
-        volumes.into(),
-    ])?;
+    let mut df = DataFrame::new(
+        dates.len(),
+        vec![
+            dates.into(),
+            opens.into(),
+            highs.into(),
+            lows.into(),
+            closes.clone().into(),
+            volumes.into(),
+        ],
+    )?;
 
     // Calculate indicators for trend following
     // 1. Calculate short and long SMAs
@@ -182,15 +185,15 @@ fn main() -> Result<(), PolarsError> {
     let sma_50_values = sma_50.f64()?.to_vec();
 
     // Add to dataframe
-    df.with_column(Series::new("sma_20".into(), sma_20_values))?;
-    df.with_column(Series::new("sma_50".into(), sma_50_values))?;
+    df.with_column(Column::new("sma_20".into(), sma_20_values))?;
+    df.with_column(Column::new("sma_50".into(), sma_50_values))?;
 
     // 2. Calculate MACD
     let (macd_line, signal_line) = calculate_macd(&df, 12, 26, 9, "close")?;
 
     // Add MACD and signal line to the dataframe
-    df.with_column(macd_line.with_name("macd".into()))?;
-    df.with_column(signal_line.with_name("macd_signal".into()))?;
+    df.with_column(macd_line.with_name("macd".into()).into_column())?;
+    df.with_column(signal_line.with_name("macd_signal".into()).into_column())?;
 
     // Calculate MACD histogram
     // First get the values as f64 arrays
@@ -206,7 +209,7 @@ fn main() -> Result<(), PolarsError> {
     }
 
     // Add the histogram to the dataframe
-    df.with_column(Series::new("macd_histogram".into(), histogram))?;
+    df.with_column(Column::new("macd_histogram".into(), histogram))?;
 
     // 3. Calculate ADX (Average Directional Index) for trend strength
     let adx = calculate_adx(&df, 14)?;
@@ -226,10 +229,10 @@ fn main() -> Result<(), PolarsError> {
             padded_adx.push(val);
         }
 
-        df.with_column(Series::new("adx".into(), padded_adx))?;
+        df.with_column(Column::new("adx".into(), padded_adx))?;
     } else {
         let adx_values = adx.f64()?.to_vec();
-        df.with_column(Series::new("adx".into(), adx_values))?;
+        df.with_column(Column::new("adx".into(), adx_values))?;
     }
 
     // 4. Calculate RSI
@@ -250,10 +253,10 @@ fn main() -> Result<(), PolarsError> {
             padded_rsi.push(val);
         }
 
-        df.with_column(Series::new("rsi".into(), padded_rsi))?;
+        df.with_column(Column::new("rsi".into(), padded_rsi))?;
     } else {
         let rsi_values = rsi.f64()?.to_vec();
-        df.with_column(Series::new("rsi".into(), rsi_values))?;
+        df.with_column(Column::new("rsi".into(), rsi_values))?;
     }
 
     // 5. Generate trend signals
@@ -359,7 +362,7 @@ fn calculate_trend_signals(df: &mut DataFrame) -> Result<(), PolarsError> {
     }
 
     // Add signals to dataframe
-    df.with_column(Series::new("signal".into(), signals))?;
+    df.with_column(Column::new("signal".into(), signals))?;
 
     Ok(())
 }

examples/stock_mr.rs

@@ -30,10 +30,13 @@ fn main() -> Result<(), PolarsError> {
     }
 
     // Create DataFrame
-    let mut df = DataFrame::new(vec![
-        Series::new("date".into(), dates).into(),
-        Series::new("close".into(), closes.clone()).into(),
-    ])?;
+    let mut df = DataFrame::new(
+        dates.len(),
+        vec![
+            Series::new("date".into(), dates).into(),
+            Series::new("close".into(), closes.clone()).into(),
+        ],
+    )?;
 
     println!("Price data created with {} days", df.height());
 
@@ -118,15 +121,15 @@ fn main() -> Result<(), PolarsError> {
     }
 
     // Add calculated columns to DataFrame
-    df.with_column(Series::new("sma".into(), sma_vals))?;
-    df.with_column(Series::new("upper_band".into(), upper_band))?;
-    df.with_column(Series::new("lower_band".into(), lower_band))?;
-    df.with_column(Series::new("rsi".into(), rsi_vals))?;
-    df.with_column(Series::new("z_score".into(), z_scores))?;
+    df.with_column(Column::new("sma".into(), sma_vals))?;
+    df.with_column(Column::new("upper_band".into(), upper_band))?;
+    df.with_column(Column::new("lower_band".into(), lower_band))?;
+    df.with_column(Column::new("rsi".into(), rsi_vals))?;
+    df.with_column(Column::new("z_score".into(), z_scores))?;
 
     // Clone signals before adding to DataFrame
     let signals_copy = signals.clone();
-    df.with_column(Series::new("signal".into(), signals))?;
+    df.with_column(Column::new("signal".into(), signals))?;
 
     // Print results
     println!("\nMean Reversion Analysis:");

examples/test_case_sensitive.rs

@@ -7,7 +7,7 @@ fn main() -> Result<(), Box<dyn Error>> {
     println!("=====================================\n");
 
     // Create a sample DataFrame with financial data with differently cased headers
-    let df = DataFrame::new(vec![
+    let df = DataFrame::new(3, vec![
         Series::new("DATE".into(), &["2024-01-01", "2024-01-02", "2024-01-03"]).into(),
         Series::new("Open".into(), &[150.0, 152.0, 151.0]).into(),
         Series::new("HIGH".into(), &[155.0, 156.0, 154.0]).into(),

examples/test_df.rs

@@ -8,7 +8,7 @@ fn main() -> Result<(), PolarsError> {
     let s2 = Series::new("b".into(), &[4, 5, 6]);
 
     // Create DataFrame
-    let df = DataFrame::new(vec![s1.into(), s2.into()])?;
+    let df = DataFrame::new(3, vec![s1.into(), s2.into()])?;
 
     // Print the DataFrame
     println!("Test DataFrame");

examples/test_headerless.rs

@@ -28,14 +28,17 @@ fn main() -> Result<(), Box<dyn Error>> {
     );
 
     // Create DataFrame
-    let mut df = DataFrame::new(vec![
-        dates.into(),
-        opens.into(),
-        highs.into(),
-        lows.into(),
-        closes.into(),
-        volumes.into(),
-    ])?;
+    let mut df = DataFrame::new(
+        5,
+        vec![
+            dates.into(),
+            opens.into(),
+            highs.into(),
+            lows.into(),
+            closes.into(),
+            volumes.into(),
+        ],
+    )?;
 
     println!("Original DataFrame with generic column names:");
     println!("{}\n", df);