mirror of
https://github.com/NexVeridian/ark-invest-api-rust-data.git
synced 2025-09-02 09:59:12 +00:00
refactor: move format and data reader
This commit is contained in:
parent
817f3c9baf
commit
b344b9ac24
SSH key fingerprint:
SHA256:bsA1SKZxuEcEVHAy3gY1HUeM5ykRJl0U0kQHQn0hMg8
4 changed files with 199 additions and 188 deletions
195
src/util.rs
195
src/util.rs
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@ -1,19 +1,19 @@
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use anyhow::{anyhow, Error, Result};
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use chrono::{Duration, NaiveDate};
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use data_reader::Reader;
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use df::{DF, DFS};
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use glob::glob;
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use polars::datatypes::DataType;
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use polars::lazy::dsl::StrptimeOptions;
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use polars::prelude::*;
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use reqwest::blocking::Client;
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use serde_json::Value;
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use std::fs::{create_dir_all, File};
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use std::io::Cursor;
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use std::path::Path;
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use strum_macros::EnumString;
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use ticker::{DataSource, Ticker};
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pub mod data_reader;
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pub mod df;
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mod df_format;
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pub mod ticker;
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#[derive(Debug, Default, EnumString, Clone, Copy, PartialEq)]
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@ -154,154 +154,13 @@ impl Ark {
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Ok(self)
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}
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fn df_format_21shares(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df.get_column_names().contains(&"Weightings") {
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df = df
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.lazy()
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.rename(
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vec![
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"Date",
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"StockTicker",
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"CUSIP",
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"SecurityName",
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"Shares",
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"Price",
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"MarketValue",
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"Weightings",
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],
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vec![
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"date",
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"ticker",
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"cusip",
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"company",
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"shares",
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"share_price",
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"market_value",
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"weight",
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],
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)
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.collect()?;
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_ = df.drop_in_place("Account");
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_ = df.drop_in_place("NetAssets");
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_ = df.drop_in_place("SharesOutstanding");
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_ = df.drop_in_place("CreationUnits");
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_ = df.drop_in_place("MoneyMarketFlag");
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}
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Ok(df.into())
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}
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fn df_format_arkvx(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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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.get_column_names().contains(&"weight (%)") {
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df = df
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.lazy()
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.rename(vec!["weight (%)"], vec!["weight"])
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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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.with_columns([
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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fn df_format_europe(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df.get_column_names().contains(&"Currency") {
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_ = df.drop_in_place("Currency");
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df = df
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.lazy()
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.rename(
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vec!["name", "ISIN", "Weight"],
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vec!["company", "cusip", "weight"],
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)
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.with_columns([
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Series::new("date", [chrono::Local::now().date_naive()]).lit(),
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Series::new("ticker", [None::<String>]).lit(),
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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fn df_format_europe_arkfundsio(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df
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.get_column_names()
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.eq(&["company", "cusip", "date", "fund", "weight", "weight_rank"])
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{
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_ = df.drop_in_place("fund");
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_ = df.drop_in_place("weight_rank");
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df = df
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.lazy()
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.with_columns([
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Series::new("ticker", [None::<String>]).lit(),
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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fn df_format_europe_csv(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df.get_column_names().contains(&"_duplicated_0") {
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df = df.slice(2, df.height());
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df = df
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.clone()
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.lazy()
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.rename(df.get_column_names(), ["company", "cusip", "weight"])
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.with_columns([
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Series::new("date", [chrono::Local::now().date_naive()]).lit(),
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Series::new("ticker", [None::<String>]).lit(),
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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pub fn df_format(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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df = Self::df_format_europe_csv(df.into())?.collect()?;
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df = Self::df_format_europe_arkfundsio(df.into())?.collect()?;
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df = Self::df_format_21shares(df.into())?.collect()?;
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df = Self::df_format_arkvx(df.into())?.collect()?;
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df = Self::df_format_europe(df.into())?.collect()?;
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df = df_format::df_format_europe_csv(df.into())?.collect()?;
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df = df_format::df_format_europe_arkfundsio(df.into())?.collect()?;
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df = df_format::df_format_21shares(df.into())?.collect()?;
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df = df_format::df_format_arkvx(df.into())?.collect()?;
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df = df_format::df_format_europe(df.into())?.collect()?;
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if df.get_column_names().contains(&"market_value_($)") {
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df = df
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@ -706,44 +565,6 @@ impl Ark {
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}
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}
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#[derive(Debug, Clone, Copy, PartialEq)]
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pub enum Reader {
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Csv,
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Json,
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}
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impl Reader {
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pub fn get_data_url(&self, url: String) -> Result<DataFrame, Error> {
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let response = Client::builder()
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.user_agent("Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36")
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.gzip(true)
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.build()?
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.get(url)
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.send()?;
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if !response.status().is_success() {
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return Err(anyhow!(
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"HTTP request failed with status code: {:?}",
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response.status()
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));
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}
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let data = response.text()?.into_bytes();
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let df = match self {
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Self::Csv => CsvReader::new(Cursor::new(data))
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.has_header(true)
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.finish()?,
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Self::Json => {
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let json_string = String::from_utf8(data)?;
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let json: Value = serde_json::from_str(&json_string)?;
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JsonReader::new(Cursor::new(json.to_string())).finish()?
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}
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};
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Ok(df)
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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45
src/util/data_reader.rs
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45
src/util/data_reader.rs
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@ -0,0 +1,45 @@
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use anyhow::{anyhow, Error};
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use polars::frame::DataFrame;
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use polars::io::SerReader;
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use polars::prelude::{CsvReader, JsonReader};
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use reqwest::blocking::Client;
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use serde_json::Value;
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use std::io::Cursor;
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#[derive(Debug, Clone, Copy, PartialEq)]
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pub enum Reader {
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Csv,
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Json,
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}
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impl Reader {
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pub fn get_data_url(&self, url: String) -> anyhow::Result<DataFrame, Error> {
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let response = Client::builder()
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.user_agent("Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36")
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.gzip(true)
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.build()?
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.get(url)
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.send()?;
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if !response.status().is_success() {
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return Err(anyhow!(
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"HTTP request failed with status code: {:?}",
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response.status()
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));
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}
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let data = response.text()?.into_bytes();
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let df = match self {
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Self::Csv => CsvReader::new(Cursor::new(data))
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.has_header(true)
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.finish()?,
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Self::Json => {
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let json_string = String::from_utf8(data)?;
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let json: Value = serde_json::from_str(&json_string)?;
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JsonReader::new(Cursor::new(json.to_string())).finish()?
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}
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};
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Ok(df)
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}
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}
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@ -35,7 +35,7 @@ impl DF {
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}
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}
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#[allow(clippy::upper_case_acronyms)]
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#[allow(clippy::upper_case_acronyms, dead_code)]
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pub trait DFS {
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fn lazy(self) -> Vec<LazyFrame>;
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fn collect(self) -> Vec<DataFrame>;
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145
src/util/df_format.rs
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145
src/util/df_format.rs
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@ -0,0 +1,145 @@
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use anyhow::{Error, Result};
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use polars::prelude::*;
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use crate::util::df::DF;
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pub fn df_format_21shares(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df.get_column_names().contains(&"Weightings") {
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df = df
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.lazy()
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.rename(
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vec![
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"Date",
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"StockTicker",
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"CUSIP",
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"SecurityName",
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"Shares",
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"Price",
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"MarketValue",
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"Weightings",
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],
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vec![
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"date",
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"ticker",
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"cusip",
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"company",
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"shares",
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"share_price",
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"market_value",
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"weight",
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],
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)
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.collect()?;
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_ = df.drop_in_place("Account");
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_ = df.drop_in_place("NetAssets");
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_ = df.drop_in_place("SharesOutstanding");
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_ = df.drop_in_place("CreationUnits");
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_ = df.drop_in_place("MoneyMarketFlag");
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}
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Ok(df.into())
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}
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pub fn df_format_arkvx(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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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.get_column_names().contains(&"weight (%)") {
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df = df
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.lazy()
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.rename(vec!["weight (%)"], vec!["weight"])
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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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.with_columns([
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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pub fn df_format_europe(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df.get_column_names().contains(&"Currency") {
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_ = df.drop_in_place("Currency");
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df = df
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.lazy()
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.rename(
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vec!["name", "ISIN", "Weight"],
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vec!["company", "cusip", "weight"],
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)
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.with_columns([
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Series::new("date", [chrono::Local::now().date_naive()]).lit(),
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Series::new("ticker", [None::<String>]).lit(),
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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pub fn df_format_europe_arkfundsio(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df
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.get_column_names()
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.eq(&["company", "cusip", "date", "fund", "weight", "weight_rank"])
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{
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_ = df.drop_in_place("fund");
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_ = df.drop_in_place("weight_rank");
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df = df
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.lazy()
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.with_columns([
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Series::new("ticker", [None::<String>]).lit(),
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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pub fn df_format_europe_csv(df: DF) -> Result<DF, Error> {
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let mut df = df.collect()?;
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if df.get_column_names().contains(&"_duplicated_0") {
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df = df.slice(2, df.height());
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df = df
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.clone()
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.lazy()
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.rename(df.get_column_names(), ["company", "cusip", "weight"])
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.with_columns([
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Series::new("date", [chrono::Local::now().date_naive()]).lit(),
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Series::new("ticker", [None::<String>]).lit(),
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Series::new("market_value", [None::<i64>]).lit(),
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Series::new("shares", [None::<i64>]).lit(),
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Series::new("share_price", [None::<f64>]).lit(),
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])
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.collect()?;
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}
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Ok(df.into())
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}
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