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Add token history and credit formatting helpers for analytics (#45741)
## What changed - Add daily text token history grouped by model or token type, with date-range and model filtering, freshness metadata, and validation of token counts. Support both grouped and per-model report data, including reported model totals when components are unavailable. - Add credit formatting helpers that preserve tiny signed adjustments and format integer millionths without floating-point rounding, plus a short date formatter. ## Testing Add unit tests for token groupings, model filtering, freshness, missing components, explicit zero totals, and credit formatting across tiny refunds and integer limits. GitOrigin-RevId: 706dcae7995e46707c2f1df9cdf3e06966459dd6
This commit is contained in:
Felipe Coury
@@ -1,5 +1,11 @@
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//! Account analytics data preparation, staged for the dashboard integration.
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mod data;
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mod models;
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mod normalize;
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mod report_data;
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mod tokens;
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#[cfg(test)]
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#[path = "analytics_tests.rs"]
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mod tests;
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79
codex-rs/tui/src/analytics/data.rs
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79
codex-rs/tui/src/analytics/data.rs
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@@ -0,0 +1,79 @@
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//! Precise signed credit amounts and dates for analytics presentation.
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/// Keep tiny refunds visible while avoiding noise on ordinary credit amounts.
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pub(super) fn amount(value: f64) -> String {
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if value == 0.0 {
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return "0".into();
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}
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if value.abs() < 0.000001 {
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return format!("{value:.2e}");
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}
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let rounded = if value.abs() < 0.01 {
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format!("{value:.6}")
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} else {
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format!("{value:.2}")
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};
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let (whole, fraction) = rounded.split_once('.').unwrap_or((&rounded, ""));
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let mut grouped = String::new();
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for (index, ch) in whole.chars().enumerate() {
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if index > 0
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&& ch.is_ascii_digit()
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&& (whole.len() - index).is_multiple_of(/*rhs*/ 3)
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&& !grouped.ends_with('-')
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{
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grouped.push(',');
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}
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grouped.push(ch);
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}
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let fraction = fraction.trim_end_matches('0');
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if !fraction.is_empty() {
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grouped.push('.');
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grouped.push_str(fraction);
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}
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grouped
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}
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/// Align ordinary credit amounts to two decimals without hiding tiny adjustments.
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pub(super) fn credit_amount(value: f64) -> String {
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let formatted = amount(value);
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if value != 0.0 && value.abs() < 0.01 {
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return formatted;
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}
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match formatted.split_once('.') {
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None => format!("{formatted}.00"),
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Some((_, fraction)) if fraction.len() == 1 => format!("{formatted}0"),
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Some(_) => formatted,
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}
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}
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/// Format integer millionths without floating-point rounding or hiding tiny adjustments.
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pub(super) fn credits(micros: i64) -> String {
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let magnitude = micros.unsigned_abs();
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if magnitude > 0 && magnitude < 10_000 {
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let fractional = format!("{magnitude:06}");
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return format!(
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"{}0.{}",
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if micros < 0 { "-" } else { "" },
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fractional.trim_end_matches('0')
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);
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}
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let cents = (magnitude + 5_000) / 10_000;
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let mut whole = (cents / 100).to_string();
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let digits = whole.len();
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for index in (1..digits).rev() {
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if (digits - index).is_multiple_of(/*rhs*/ 3) {
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whole.insert(index, ',');
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}
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}
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format!(
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"{}{whole}.{:02}",
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if micros < 0 { "-" } else { "" },
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cents % 100
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)
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}
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pub(super) fn date(date: &str) -> String {
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chrono::NaiveDate::parse_from_str(date, "%Y-%m-%d")
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.map(|date| date.format("%b %-d").to_string())
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.unwrap_or_else(|_| date.to_string())
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}
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@@ -25,6 +25,7 @@ pub(crate) enum AccountAnalyticsUnit {
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RelativeUsage,
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Credits,
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Count,
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Tokens,
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}
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#[derive(Debug, Clone, PartialEq)]
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135
codex-rs/tui/src/analytics/tokens.rs
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135
codex-rs/tui/src/analytics/tokens.rs
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@@ -0,0 +1,135 @@
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//! Enterprise text token history, independent of credit and allowance accounting.
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use super::models::*;
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use super::report_data::AnalyticsData;
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use chrono::NaiveDate;
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use std::collections::BTreeMap;
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pub(super) fn history(
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response: AnalyticsData,
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grouping: AccountAnalyticsGrouping,
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start: NaiveDate,
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end: NaiveDate,
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) -> Result<AccountAnalyticsHistory, String> {
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filtered_history(response, grouping, start, end, /*model_filter*/ None)
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}
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pub(super) fn filtered_history(
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response: AnalyticsData,
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grouping: AccountAnalyticsGrouping,
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start: NaiveDate,
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end: NaiveDate,
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model_filter: Option<&str>,
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) -> Result<AccountAnalyticsHistory, String> {
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let mut days: BTreeMap<NaiveDate, BTreeMap<String, f64>> = BTreeMap::new();
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for record in response.data {
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let date = record
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.date
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.parse::<NaiveDate>()
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.map_err(|_| "Invalid token report date.")?;
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if date < start || date > end {
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continue;
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}
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let groups = if let Some(groups) = record.groups {
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groups
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.into_iter()
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.map(|group| {
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(
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if group.is_other {
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"Other".into()
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} else {
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group
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.dimensions
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.get("model")
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.cloned()
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.unwrap_or_else(|| "Unknown".into())
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},
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[
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group.uncached_text_input_tokens,
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group.cached_text_input_tokens,
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group.text_output_tokens,
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],
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None,
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)
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})
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.collect::<Vec<_>>()
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} else if let Some(models) = record.models {
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models
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.into_iter()
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.map(|model| {
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(
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model.model,
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[
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model.uncached_text_input_tokens,
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model.cached_text_input_tokens,
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model.text_output_tokens,
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],
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model.text_total_tokens,
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)
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})
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.collect()
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} else {
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return Err("Token breakdown is not available in this report.".into());
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};
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let values = days.entry(date).or_default();
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for (model, counts, total) in groups {
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if model_filter.is_some_and(|selected| selected != model) {
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continue;
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}
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let missing_components = counts.iter().all(Option::is_none);
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if grouping == AccountAnalyticsGrouping::Model
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&& let Some(total) = total.filter(|total| *total != 0.0 || missing_components)
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{
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if !total.is_finite() || total < 0.0 || total.fract() != 0.0 {
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return Err("Invalid token count.".into());
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}
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*values.entry(model).or_default() += total;
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continue;
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}
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if missing_components {
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return Err("Token counts were not reported.".into());
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}
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for (label, count) in ["Uncached input", "Cached input", "Output"]
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.into_iter()
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.zip(counts)
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{
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let count = count.unwrap_or(/*default*/ 0.0);
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if !count.is_finite() || count < 0.0 || count.fract() != 0.0 {
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return Err("Invalid token count.".into());
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}
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let key = if grouping == AccountAnalyticsGrouping::Model {
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&model
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} else {
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label
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};
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*values.entry(key.to_string()).or_default() += count;
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}
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}
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}
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Ok(AccountAnalyticsHistory {
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unit: AccountAnalyticsUnit::Tokens,
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updated_at: response
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.data_freshness_ts
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.and_then(|time| chrono::DateTime::parse_from_rfc3339(&time).ok())
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.map(|time| time.timestamp()),
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data: days
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.into_iter()
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.map(|(date, values)| AccountAnalyticsDay {
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date,
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total: values.values().sum(),
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values: values
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.into_iter()
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.map(|(key, value)| AccountAnalyticsValue {
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label: key.clone(),
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key,
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value,
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})
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.collect(),
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})
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.collect(),
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})
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}
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#[cfg(test)]
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#[path = "tokens_tests.rs"]
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mod tests;
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131
codex-rs/tui/src/analytics/tokens_tests.rs
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131
codex-rs/tui/src/analytics/tokens_tests.rs
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@@ -0,0 +1,131 @@
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//! Enterprise token normalization across supported groupings.
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use super::*;
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use pretty_assertions::assert_eq;
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use serde_json::json;
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#[test]
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fn tokens_use_text_components_and_keep_daily_totals_across_groupings() {
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let response: AnalyticsData = serde_json::from_value(json!({"units":"credits", "data":[{
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"date":"2026-09-01", "groups":[{"dimensions":{"model":"gpt-5"}, "uncached_text_input_tokens":10, "cached_text_input_tokens":80, "text_output_tokens":10}]
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}]})).unwrap();
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let date = "2026-09-01".parse().unwrap();
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let by_type = history(
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response.clone(),
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AccountAnalyticsGrouping::TokenType,
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date,
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date,
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)
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.unwrap();
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let by_model = history(response, AccountAnalyticsGrouping::Model, date, date).unwrap();
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assert_eq!(
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(by_type.unit, by_type.data[0].total, by_model.data[0].total),
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(AccountAnalyticsUnit::Tokens, 100.0, 100.0)
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);
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assert_eq!(
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by_type.data[0]
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.values
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.iter()
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.map(|v| (v.label.as_str(), v.value))
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.collect::<Vec<_>>(),
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vec![
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("Cached input", 80.0),
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("Output", 10.0),
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("Uncached input", 10.0)
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]
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);
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}
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#[test]
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fn token_model_filter_retains_components_and_freshness() {
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let date = "2026-09-01".parse().unwrap();
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let response: AnalyticsData = serde_json::from_value(json!({"data_freshness_ts":"2026-09-02T00:00:00Z", "data":[{
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"date":"2026-09-01", "groups":[
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{"dimensions":{"model":"alpha"}, "uncached_text_input_tokens":10,"cached_text_input_tokens":20,"text_output_tokens":30},
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{"dimensions":{"model":"beta"}, "uncached_text_input_tokens":100,"cached_text_input_tokens":200,"text_output_tokens":300}
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], "models":[{"model":"ignored", "text_total_tokens":1000}]
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}]})).unwrap();
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let selected = filtered_history(
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response.clone(),
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AccountAnalyticsGrouping::TokenType,
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date,
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date,
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Some("alpha"),
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)
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.unwrap();
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let expected = history(serde_json::from_value(json!({"data_freshness_ts":"2026-09-02T00:00:00Z", "data":[{
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"date":"2026-09-01", "models":[{"model":"alpha", "uncached_text_input_tokens":10,"cached_text_input_tokens":20,"text_output_tokens":30}]
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}]})).unwrap(), AccountAnalyticsGrouping::TokenType, date, date).unwrap();
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assert_eq!(selected, expected);
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assert_eq!(
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history(response, AccountAnalyticsGrouping::TokenType, date, date)
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.unwrap()
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.data[0]
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.total,
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660.0
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);
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}
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#[test]
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fn model_totals_use_reported_total_and_missing_components_remain_unavailable() {
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let date = "2026-09-01".parse().unwrap();
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let response: AnalyticsData = serde_json::from_value(json!({"data":[{"date":"2026-09-01", "models":[{"model":"alpha", "text_total_tokens":123}]}]})).unwrap();
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assert_eq!(
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history(
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response.clone(),
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AccountAnalyticsGrouping::Model,
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date,
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date
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)
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.unwrap()
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.data,
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vec![AccountAnalyticsDay {
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date: "2026-09-01".parse().unwrap(),
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total: 123.0,
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values: vec![AccountAnalyticsValue {
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key: "alpha".into(),
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label: "alpha".into(),
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value: 123.0
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}]
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}]
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);
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assert_eq!(
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history(response, AccountAnalyticsGrouping::TokenType, date, date).unwrap_err(),
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"Token counts were not reported."
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);
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}
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#[test]
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fn explicit_zero_model_total_is_reported_without_components() {
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let date = "2026-09-01".parse().unwrap();
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let response: AnalyticsData = serde_json::from_value(json!({
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"data": [{"date": "2026-09-01", "models": [
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{"model": "idle", "text_total_tokens": 0},
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{"model": "active", "text_total_tokens": 0, "text_output_tokens": 5}
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]}]
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}))
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.unwrap();
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assert_eq!(
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history(response, AccountAnalyticsGrouping::Model, date, date).unwrap(),
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AccountAnalyticsHistory {
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unit: AccountAnalyticsUnit::Tokens,
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updated_at: None,
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data: vec![AccountAnalyticsDay {
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date: "2026-09-01".parse().unwrap(),
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total: 5.0,
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values: vec![
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AccountAnalyticsValue {
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key: "active".into(),
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label: "active".into(),
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value: 5.0,
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},
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AccountAnalyticsValue {
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key: "idle".into(),
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label: "idle".into(),
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value: 0.0,
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},
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],
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}],
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}
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);
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}
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55
codex-rs/tui/src/analytics_tests.rs
Normal file
55
codex-rs/tui/src/analytics_tests.rs
Normal file
@@ -0,0 +1,55 @@
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//! Credit formatting preserves tiny adjustments and integer precision.
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use super::data;
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use pretty_assertions::assert_eq;
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#[test]
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fn analytics_credit_display_retains_integer_precision() {
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assert_eq!(
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[753.71, 411.12, 47.4, 0.0, 1_212.224, -0.004, -0.000004].map(data::credit_amount),
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[
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"753.71",
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"411.12",
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"47.40",
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"0.00",
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"1,212.22",
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"-0.004",
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"-0.000004"
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]
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.map(str::to_string)
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);
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assert_eq!(
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[0, -4, 999_999_999, 19_350_041_555, i64::MIN, i64::MAX].map(data::credits),
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[
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"0.00",
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"-0.000004",
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"1,000.00",
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"19,350.04",
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"-9,223,372,036,854.78",
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"9,223,372,036,854.78"
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]
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.map(str::to_string)
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);
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assert_eq!(
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[
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12_746.441206,
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-1_000.125,
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999.999,
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0.0,
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-0.000004,
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0.009,
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7.5
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]
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.map(data::amount),
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[
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"12,746.44",
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"-1,000.12",
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"1,000",
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"0",
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"-0.000004",
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"0.009",
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"7.5"
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]
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.map(str::to_string)
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);
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}
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