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https://github.com/NexVeridian/ark-invest-api-rust-data.git
synced 2025-09-02 01:49:12 +00:00
0.2.1
This commit is contained in:
parent
be08848b0d
commit
4074a97ae2
SSH key fingerprint:
SHA256:bsA1SKZxuEcEVHAy3gY1HUeM5ykRJl0U0kQHQn0hMg8
2 changed files with 135 additions and 127 deletions
11
src/main.rs
11
src/main.rs
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@ -8,7 +8,6 @@
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mod util;
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use util::*;
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// #[tokio::main]
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// async fn main() {
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// let mut scheduler = AsyncScheduler::new();
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@ -38,13 +37,13 @@ use util::*;
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// }
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fn main() {
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let dfn = df_format(Ticker::ARKF, read_parquet(Ticker::ARKF).unwrap()).unwrap();
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let dfn = df_format(read_parquet(Ticker::ARKVC).unwrap()).unwrap();
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println!("{:#?}", dfn);
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// update_parquet(Ticker::ARKF).unwrap();
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let update = df_format(Ticker::ARKF, get_csv(Ticker::ARKF).unwrap()).unwrap();
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// update_parquet(Ticker::ARKVC).unwrap();
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// let update = df_format(Ticker::ARKF, get_csv(Ticker::ARKF).unwrap()).unwrap();
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// let update = get_csv(Ticker::ARKF).unwrap().collect().unwrap();
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// let x = read_parquet(Ticker::ARKF).unwrap().collect().unwrap();
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println!("{:#?}", update);
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// let x = df_format(read_parquet(Ticker::ARKVC).unwrap()).unwrap();
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// println!("{:#?}", x);
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}
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251
src/util.rs
251
src/util.rs
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@ -44,7 +44,7 @@ pub fn merge_csv_to_parquet(folder: Ticker) -> Result<(), Box<dyn Error>> {
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let df = concat(dfs, false, true)?;
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write_parquet(folder, df_format(folder, df)?)?;
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write_parquet(folder, df_format(df)?)?;
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Ok(())
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}
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@ -53,7 +53,12 @@ pub fn update_parquet(ticker: Ticker) -> Result<(), Box<dyn Error>> {
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let mut df = read_parquet(ticker)?;
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df = concat(vec![df, update], false, true)?.unique_stable(None, UniqueKeepStrategy::First);
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df = concat(
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vec![df_format(df)?.lazy(), df_format(update)?.lazy()],
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false,
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true,
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)?
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.unique_stable(None, UniqueKeepStrategy::First);
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write_parquet(ticker, df.collect()?)?;
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Ok(())
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@ -74,127 +79,131 @@ pub fn write_parquet(ticker: Ticker, mut df: DataFrame) -> Result<(), Box<dyn Er
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Ok(())
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}
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pub fn df_format(ticker: Ticker, mut dfl: LazyFrame) -> Result<DataFrame, Box<dyn Error>> {
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match ticker {
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Ticker::ARKVC => {
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dfl = dfl.rename(vec!["CUSIP", "weight (%)"], vec!["cusip", "weight"]);
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pub fn df_format(df: LazyFrame) -> Result<DataFrame, Box<dyn Error>> {
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let mut df = df.collect()?;
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let df = dfl
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.with_columns(vec![
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col("date").str().strptime(StrpTimeOptions {
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date_dtype: DataType::Date,
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fmt: Some("%m/%d/%Y".into()),
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strict: false,
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exact: true,
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cache: false,
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tz_aware: false,
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utc: false,
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}),
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col("weight")
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.str()
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.extract(r"[0-9]*\.[0-9]+", 0)
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.cast(DataType::Float64),
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])
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.filter(col("date").is_not_null())
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.collect()?;
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Ok(df)
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}
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_ => {
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let mut df = dfl.collect()?;
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let col_names = df.get_column_names();
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if df.rename("market_value_($)", "market_value").is_ok() {}
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if df.rename("market value ($)", "market_value").is_ok() {}
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if df.rename("weight_(%)", "weight").is_ok() {}
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if df.rename("weight (%)", "weight").is_ok() {}
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if df.get_column_names().contains(&"fund") {
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_ = df.drop_in_place("fund");
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}
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if df.get_column_names().contains(&"weight_rank") {
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_ = df.drop_in_place("weight_rank");
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}
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let mut expressions: Vec<Expr> = vec![];
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if !df.fields().contains(&Field::new("date", DataType::Date)) {
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expressions.push(col("date").str().strptime(StrpTimeOptions {
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date_dtype: DataType::Date,
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fmt: Some("%m/%d/%Y".into()),
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strict: false,
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exact: true,
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cache: false,
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tz_aware: false,
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utc: false,
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}));
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}
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if df.fields().contains(&Field::new("weight", DataType::Utf8)) {
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expressions.push(
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col("weight")
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.str()
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.replace(lit("%"), lit(""), true)
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.cast(DataType::Float64),
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);
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}
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if df
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.fields()
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.contains(&Field::new("market_value", DataType::Utf8))
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{
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expressions.push(
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col("market_value")
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.str()
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.replace(lit("$"), lit(""), true)
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.str()
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.replace_all(lit(","), lit(""), true)
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.cast(DataType::Float64)
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.cast(DataType::Int64),
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);
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}
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if df.fields().contains(&Field::new("shares", DataType::Utf8)) {
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expressions.push(
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col("shares")
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.str()
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.replace_all(lit(","), lit(""), true)
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.cast(DataType::Int64),
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);
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}
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df = df
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.lazy()
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.with_columns(expressions)
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.filter(col("date").is_not_null())
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.collect()?;
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if !df.get_column_names().contains(&"share_price") {
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df = df
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.lazy()
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.with_column(
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(col("market_value").cast(DataType::Float64)
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/ col("shares").cast(DataType::Float64))
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.alias("share_price")
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.cast(DataType::Float64)
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.round(2),
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)
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.collect()?;
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}
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df = df.select([
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"date",
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"ticker",
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"cusip",
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"company",
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"market_value",
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"shares",
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"share_price",
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"weight",
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])?;
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Ok(df)
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}
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if df.get_column_names().contains(&"market_value_($)") {
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df = df
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.lazy()
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.rename(
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vec!["market_value_($), weight_(%)"],
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vec!["market_value, weight"],
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)
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.collect()?;
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}
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if df.get_column_names().contains(&"market value ($)") {
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df = df
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.lazy()
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.rename(
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vec!["market value ($), weight (%)"],
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vec!["market_value, weight"],
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)
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.collect()?;
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}
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if df.get_column_names().contains(&"CUSIP") {
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df = df
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.lazy()
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.rename(vec!["CUSIP", "weight (%)"], vec!["cusip", "weight"])
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.collect()?;
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}
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// if df.rename("market_value_($)", "market_value").is_ok() {}
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// if df.rename("market value ($)", "market_value").is_ok() {}
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// if df.rename("weight_(%)", "weight").is_ok() {}
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// if df.rename("weight (%)", "weight").is_ok() {}
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// if df.rename("CUSIP", "cusip").is_ok() {}
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if df.get_column_names().contains(&"fund") {
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_ = df.drop_in_place("fund");
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}
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if df.get_column_names().contains(&"weight_rank") {
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_ = df.drop_in_place("weight_rank");
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}
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let mut expressions: Vec<Expr> = vec![];
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if !df.fields().contains(&Field::new("date", DataType::Date)) {
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expressions.push(col("date").str().strptime(StrpTimeOptions {
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date_dtype: DataType::Date,
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fmt: Some("%m/%d/%Y".into()),
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strict: false,
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exact: true,
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cache: false,
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tz_aware: false,
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utc: false,
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}));
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}
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if df.fields().contains(&Field::new("weight", DataType::Utf8)) {
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expressions.push(
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col("weight")
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.str()
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.replace(lit("%"), lit(""), true)
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.cast(DataType::Float64),
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);
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}
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if df
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.fields()
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.contains(&Field::new("market_value", DataType::Utf8))
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{
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expressions.push(
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col("market_value")
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.str()
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.replace(lit("$"), lit(""), true)
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.str()
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.replace_all(lit(","), lit(""), true)
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.cast(DataType::Float64)
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.cast(DataType::Int64),
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);
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}
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if df.fields().contains(&Field::new("shares", DataType::Utf8)) {
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expressions.push(
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col("shares")
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.str()
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.replace_all(lit(","), lit(""), true)
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.cast(DataType::Int64),
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);
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}
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df = df
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.lazy()
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.with_columns(expressions)
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.filter(col("date").is_not_null())
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.collect()?;
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if !df.get_column_names().contains(&"share_price")
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&& df.get_column_names().contains(&"market_value")
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{
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df = df
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.lazy()
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.with_column(
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(col("market_value").cast(DataType::Float64)
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/ col("shares").cast(DataType::Float64))
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.alias("share_price")
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.cast(DataType::Float64)
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.round(2),
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)
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.collect()?
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}
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if df.get_column_names().contains(&"share_price") {
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df = df.select([
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"date",
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"ticker",
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"cusip",
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"company",
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"market_value",
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"shares",
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"share_price",
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"weight",
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])?;
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} else {
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df = df.select(["date", "ticker", "cusip", "company", "weight"])?;
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}
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Ok(df)
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}
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pub fn get_csv(ticker: Ticker) -> Result<LazyFrame, Box<dyn Error>> {
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