wip

src/py/download.pyi

@@ -0,0 +1,8 @@
+from polars import DataFrame
+
+__all__ = [
+    "download_jpmaqs_indicators_as_df",
+]
+
+def download_jpmaqs_indicators_as_df(*args, **kwargs) -> DataFrame: 
+    ...

src/py/msyrs.pyi

@@ -0,0 +1,8 @@
+
+import .download # type: ignore
+import .qdf # type: ignore
+
+__all__ = [
+    "download",
+    "qdf",
+]

src/py/qdf.pyi

@@ -0,0 +1,24 @@
+from polars import DataFrame
+
+__all__ = [
+    "load_qdf",
+    "load_qdf_from_download_bank",
+    "reduce_dataframe",
+    "update_dataframe",
+]
+
+# qdf/load_qdf.pyi
+def load_qdf(*args, **kwargs) -> DataFrame: 
+    ...
+
+# qdf/load_qdf_from_download_bank.pyi
+def load_qdf_from_download_bank(*args, **kwargs) -> DataFrame: 
+    ...
+
+# qdf/reduce_dataframe.pyi
+def reduce_dataframe(*args, **kwargs) -> DataFrame: 
+    ...
+
+# qdf/update_dataframe.pyi
+def update_dataframe(*args, **kwargs) -> DataFrame: 
+    ...

src/utils/qdf/pivots.rs

@@ -4,10 +4,14 @@ use polars::prelude::*;
 use std::collections::HashMap;
 use std::error::Error;
 
+#[allow(unused_imports)]
+use std::f32::consts::E;
+
 /// The required columns for a Quantamental DataFrame.
 const QDF_INDEX_COLUMNS: [&str; 3] = ["real_date", "cid", "xcat"];
 
 /// Pivots a dataframe to a format where each ticker a column.
+#[allow(dead_code)]
 pub fn pivot_dataframe_by_ticker(
     df: DataFrame,
     metric: Option<String>,
@@ -24,7 +28,7 @@ pub fn pivot_dataframe_by_ticker(
         metric = df.get_column_names()[3].to_string();
     }
 
-    let mut new_df = df.clone();
+    // let mut new_df = df.clone();
     // keep only the index columns and the metric column
     let mut keep_cols = QDF_INDEX_COLUMNS
         .to_vec()
@@ -33,7 +37,9 @@ pub fn pivot_dataframe_by_ticker(
         .collect::<Vec<String>>();
     keep_cols.push(metric.clone());
 
-    new_df = new_df.select(keep_cols)?;
+    return Err("Not implemented".into());
+
+    // new_df = new_df.select(keep_cols)?;
     // let ticker_col = get_ticker_column_for_quantamental_dataframe(&new_df)?;
 
     // new_df.with_column(ticker_col)?;
@@ -42,9 +48,11 @@ pub fn pivot_dataframe_by_ticker(
 
     // let dates_col = df.column("real_date")?;
 
-    Ok(df)
+    // Ok(df)
 }
 
+/// Splits a dataframe by ticker.
+#[allow(dead_code)]
 fn split_df_by_tickers(df: &DataFrame) -> Result<HashMap<String, DataFrame>, Box<dyn Error>> {
     check_quantamental_dataframe(df)?;