python imports working!

notebooks/main.rs

@@ -0,0 +1,200 @@
+use msyrs::download::{JPMaQSDownload, JPMaQSDownloadGetIndicatorArgs};
+// use msyrs::download::jpmaqsdownload::*;
+// use msyrs::utils::qdf::load::*;
+// use msyrs::utils::qdf::dftools::*;
+// use msyrs::utils::qdf::core::*;
+use msyrs::utils as msyrs_utils;
+use msyrs::utils::qdf as msyrs_qdf;
+use polars::frame::DataFrame;
+
+#[allow(dead_code)]
+fn download_stuff() {
+    println!("Authentication to DataQuery API");
+    let mut jpamqs_download = JPMaQSDownload::default();
+
+    println!("Checking connection to DataQuery API");
+    jpamqs_download.check_connection().unwrap();
+
+    println!("Retrieving catalogue of tickers");
+    let start = std::time::Instant::now();
+    let tickers = jpamqs_download.get_catalogue().unwrap();
+    println!(
+        "Retrieved catalogue with {} tickers in {:?}",
+        tickers.len(),
+        start.elapsed()
+    );
+
+    let num_ticks = 100;
+    let sel_tickers: Vec<String> = tickers
+        .iter()
+        .take(num_ticks)
+        .map(|s| s.to_string())
+        .collect();
+    // let mut df_deets = Vec::new();
+
+    println!("Retrieving indicators for {} tickers", sel_tickers.len());
+
+    let res_df = jpamqs_download
+        .get_indicators_qdf(JPMaQSDownloadGetIndicatorArgs {
+            tickers: sel_tickers.clone(),
+            start_date: "2024-11-05".to_string(),
+            ..Default::default()
+        })
+        .unwrap();
+
+    println!(
+        "Retrieved indicators for {} tickers in {:?}",
+        sel_tickers.len(),
+        start.elapsed()
+    );
+
+    if !msyrs_qdf::is_quantamental_dataframe(&res_df) {
+        println!("DataFrame is not a quantamental DataFrame");
+    } else {
+        println!("DataFrame is a quantamental DataFrame");
+    }
+}
+
+#[allow(dead_code)]
+fn load_mega_df() -> DataFrame {
+    let start = std::time::Instant::now();
+    let st_pth = "E:\\Work\\jpmaqs-data\\data";
+
+    let mega_df = msyrs_qdf::load::load_qdf_from_download_bank(
+        st_pth,
+        None,
+        None,
+        Some(vec![
+            "AUD_EQXR_NSA",
+            "USD_EQXR_NSA",
+            "GBP_EQXR_NSA",
+            "JPY_EQXR_NSA",
+            "AUD_RIR_NSA",
+            "USD_RIR_NSA",
+            "GBP_RIR_NSA",
+            "JPY_RIR_NSA",
+        ]),
+    )
+    .unwrap();
+
+    let end = start.elapsed();
+    println!("Loaded Mega DataFrame in {:?}", end);
+    mega_df
+}
+
+fn main() {
+    nb();
+}
+
+#[allow(dead_code)]
+fn nb() {
+    let cids_dm = vec![
+        "AUD", "CAD", "CHF", "EUR", "GBP", "JPY", "NOK", "NZD", "SEK", "USD",
+    ];
+    let cids_em = vec![
+        "CLP", "COP", "CZK", "HUF", "IDR", "ILS", "INR", "KRW", "MXN", "PLN", "THB", "TRY", "TWD",
+        "ZAR",
+    ];
+
+    // cids = cids_dm + cids_em
+    let cids: Vec<String> = cids_dm
+        .iter()
+        .chain(cids_em.iter())
+        .map(|s| s.to_string())
+        .collect();
+
+    let non_dux = ["IDR", "NZD"];
+    #[allow(unused_variables)]
+    let cids_dux: Vec<String> = cids
+        .iter()
+        .filter(|s| !non_dux.contains(&s.as_str()))
+        .map(|s| s.to_string())
+        .collect();
+    let ecos = vec![
+        "CPIC_SA_P1M1ML12",
+        "CPIC_SJA_P3M3ML3AR",
+        "CPIC_SJA_P6M6ML6AR",
+        "CPIH_SA_P1M1ML12",
+        "CPIH_SJA_P3M3ML3AR",
+        "CPIH_SJA_P6M6ML6AR",
+        "INFTEFF_NSA",
+        "INTRGDP_NSA_P1M1ML12_3MMA",
+        "INTRGDPv5Y_NSA_P1M1ML12_3MMA",
+        "PCREDITGDP_SJA_D1M1ML12",
+        "RGDP_SA_P1Q1QL4_20QMA",
+        "RYLDIRS02Y_NSA",
+        "RYLDIRS05Y_NSA",
+        "PCREDITBN_SJA_P1M1ML12",
+    ];
+    let mkts = vec![
+        "DU02YXR_NSA",
+        "DU05YXR_NSA",
+        "DU02YXR_VT10",
+        "DU05YXR_VT10",
+        "EQXR_NSA",
+        "EQXR_VT10",
+        "FXXR_NSA",
+        "FXXR_VT10",
+        "FXCRR_NSA",
+        "FXTARGETED_NSA",
+        "FXUNTRADABLE_NSA",
+    ];
+
+    let xcats: Vec<String> = ecos
+        .iter()
+        .chain(mkts.iter())
+        .map(|s| s.to_string())
+        .collect();
+
+    let cids_str: Vec<&str> = cids.iter().map(AsRef::as_ref).collect();
+    let xcats_str: Vec<&str> = xcats.iter().map(AsRef::as_ref).collect();
+    let download_tickers = msyrs_utils::misc::create_interesecting_tickers(&cids_str, &xcats_str);
+
+    let mut jpmaqs_client = JPMaQSDownload::default();
+    let downloaded_df = jpmaqs_client
+        .get_indicators_qdf(JPMaQSDownloadGetIndicatorArgs {
+            tickers: download_tickers,
+            ..Default::default()
+        })
+        .unwrap();
+
+    println!("Downloaded DF:\n{:?}", downloaded_df.head(Some(10)));
+
+    let eq_df = msyrs_qdf::reduce_dataframe(
+        downloaded_df.clone(),
+        None,
+        Some(vec!["EQXR_NSA", "EQXR_VT10"]),
+        None,
+        // None,
+        Some("2024-11-12"),
+        None,
+        false,
+    )
+    .unwrap();
+
+    println!("{:?}", eq_df.head(Some(10)));
+
+    let fx_df = msyrs_qdf::reduce_dataframe(
+        downloaded_df,
+        None,
+        Some(vec![
+            "FXXR_NSA",
+            "FXXR_VT10",
+            "FXCRR_NSA",
+            "FXTARGETED_NSA",
+            "FXUNTRADABLE_NSA",
+        ]),
+        None,
+        // None,
+        Some("2024-11-12"),
+        None,
+        true,
+    )
+    .unwrap();
+
+    println!("{:?}", fx_df.head(Some(10)));
+
+    let custom_df = msyrs_qdf::update_dataframe(&fx_df, &eq_df).unwrap();
+
+    println!("{:?}", custom_df.head(Some(20)));
+}