Turn weekly ad-platform exports into an exact wasted-spend report

# Weekly ads review: wasted-spend report from Google-style and Meta-style exports The files are synthetic exports for one week: `google_ads.csv`, `meta_ads.csv` and `config.json`. Write `solve.py` (Python 3 standard library only, no network). `python solve.py input.json answer.json` must write `answer.json` (the first argument is unused; read the three files from the current directory). Fresh exports are generated when scoring. ## Parsing rules 1. `google_ads.csv`: skip lines before the header line that starts with `Day,`. Rows whose `Day` is not a date like `Oct 12, 2026` (e.g. `Total: ...` rows) are non-data rows. `Cost` and `Conv. value` may contain thousands commas or be `--` (= 0). Spend currency is the row's `Currency code` (USD or EUR). 2. `meta_ads.csv`: may start with a UTF-8 BOM. The spend column is named `Amount spent (USD)` or `Amount spent (EUR)`; that currency applies to every row. Use `Reporting starts` as the row date. Empty numeric cells = 0. 3. Meta `Results` count as conversions **only** when `Result indicator` is `actions:offsite_conversion.fb_pixel_purchase`; otherwise the row has 0 conversions (its results are clicks, not conversions). `Purchases conversion value` is the conversion value. 4. Convert EUR to USD by multiplying each row's amount by `eur_to_usd`. Keep full precision while summing; round only final reported money values to 2 decimals, half-up. 5. Drop rows dated outside `week_start`..`week_end` (inclusive). Drop exact duplicate lines within a file (keep the first). Count drops in `rows_dropped`: `{"duplicates", "out_of_range", "non_data"}` (a duplicate is counted as a duplicate even if also out of range; check duplicates first, then non-data, then range). 6. A unit is (platform `google`|`meta`, campaign, ad group/ad set). Names are matched after trimming, collapsing internal whitespace and ignoring case; report the first-seen form in file order (trimmed and whitespace-collapsed). ## Metrics and waste rules (per unit, over the week) 7. `spend` (USD), `clicks` (int), `conversions`, `conv_value` (USD; Google values follow the row currency, Meta values the file currency). 8. `cpa` = spend / conversions rounded to 2 dp, `null` when conversions = 0. `roas` = conv_value / spend rounded to 4 dp, `null` when spend = 0. 9. `reason` = `"zero_conversions"` when conversions = 0 and spend >= `zero_conv_min_spend_usd`, then `wasted` = spend. `reason` = `"high_cpa"` when conversions > 0 and cpa (unrounded) > `cpa_multiple` x `target_cpa_usd`, then `wasted` = spend - conversions x `target_cpa_usd`. Otherwise `reason` = null, `wasted` = 0. 10. `units` order: wasted descending, then spend descending, then platform, campaign, ad group ascending (case-insensitive). ## answer.json `{"units": [{"platform", "campaign", "ad_group", "spend", "clicks", "conversions", "conv_value", "cpa", "roas", "reason", "wasted"}], "totals": {"spend", "wasted", "wasted_pct", "by_platform": {"google": {"spend", "wasted"}, "meta": {"spend", "wasted"}}}, "top5": [[platform, campaign, ad_group] for the first 5 units with wasted > 0], "rows_dropped": {...}}`. `wasted_pct` = 100 x wasted / spend, 1 dp. Totals are sums of the rounded unit values. ## Optional visual: chart.svg If you write `chart.svg`: a static, self-contained SVG (root `<svg>`, no scripts, images, links, external URLs or `on*` handlers) with an element `id="wasted-bars"` and one element `id="bar-1"` .. `id="bar-N"` for the top-5 units in order. It is not required; if present it must follow these rules. ## Scoring Hidden checks (partial credit; all must pass; money within 0.005): `parse_dedupe_and_drops`, `unit_keys_and_spend_usd`, `conversions_value_and_result_indicator`, `waste_rules`, `totals_ranking_top5`, `chart_svg_if_present` on the given exports; `fresh_run_1`, `fresh_run_2` (whole answer on new exports). 30-second limit per run.