Import a stacked branch of values onto the model. Default mode creates a BranchDefinition (scenario branch) and writes the supplied entries as input rows tagged with the new dataset_id. Optionally set branch.actuals_through to mark its real/forecast cutover. Pass replace: true together with branch.id to atomically refresh an existing branch instead: its id and created_at are preserved, its mutable metadata is patched with any value you supply (display_name is optional here — omit it to keep the current name; supplying it is an explicit rename), the previous input rows are wiped and the new entries written — all in one persist call. Carry-forward: for a period the new entries do NOT cover, the prior value is retained (so a narrower re-sync never silently zeroes the uncovered tail). To actually clear a period, send it explicitly with value 0. The result warnings flag any line the import left all-zero though it had values before. Entries reference items by item_uid (existing) or item_label (matched by display_name, else created as assumption). Instead of entries, pass file_id (from layerz_create_upload_url) to import a spreadsheet server-side: the file is parsed, each row is classified with THIS model's mapping set (the same rules layerz_list_mappings shows — no need to copy them), aggregated per (item, period), and written. A rule targeting a LIST-MODE item resolves each row's list entry from its category/dimension column (cost center / BU — e.g. the DATEV Kostenstelle) matched against the list entries by label; a row whose dimension matches no entry is skipped per-row, never a whole-import failure. A raw DATEV EXTF/Buchungsstapel export is detected natively (metadata line skipped, Umsatz signed by the Soll/Haben mark, compact Belegdatum dated from the fiscal-year header) — pair it with the Germany (SKR03) or (SKR04) mapping template matching the ledger's chart. Add sheet_name for a multi-sheet workbook and structure_override to fix a misdetected ledger (e.g. a Débit/Crédit split, an S/H sign_column, or an account-code column taken as the label). Re-importing an existing source? Pass replace_source_id (id from layerz_list_integrations) to refresh that file source's staged transactions in place instead of creating a second one; a legacy empty file source bound to the branch is adopted automatically. Exactly one of entries or file_id is required; the result then also carries skipped (rows that produced no entry) and mapping_drift (rules whose target item no longer exists). Each entry's timeline_ref must match the target item's native grain exactly (or be constant, which broadcasts to any grain). Any other grain — finer or coarser — is rejected to avoid corrupting other periods, because rows resolve cell-by-cell by raw array index. Aggregate (or split) the source to the item's grain before importing. Targeting a formula or balance item writes a per-period override (actual): on covered periods the imported value replaces the computed one and feeds downstream periods (e.g. actuals-then-forecast). Compute resolves cells by branch priority at load time. Result: entries_written counts supplied entries; inputs_written counts persisted rows after per-period compaction (≤ entries_written) and mirrors delete_branch.inputs_removed. Pass dry_run: true to preview the impact WITHOUT persisting: the model is left untouched and the result carries would_persist:false, the same inputs_written/inputs_removed/created_items/matched_items counts, overridden_items (existing items whose value this branch would overlay), and validation_errors_new (errors the import would introduce). Audit it, then re-call without dry_run to commit. Deterministic. Prefer the file_id path for spreadsheets (server-side parse + classify); build entries by hand only for values you compute yourself. Not available for read-only API keys.