docs: document v7.13.0 features

- Live formulas (HARDFORMULA/SOFTFORMULA) in dcc-validations with operator-friendly explanations - MPE_VALIDATIONS table doc: add HARDFORMULA/SOFTFORMULA to RULE_TYPE values - Roadmap: mark Frontend Formulae and Regex Rules as delivered - SAS VA Embed: document Live vs Confirm filter modes - ViewBoxes: document edge/corner drag resizing - Licensing: combined-key paste, key preview, protocol warning - CAS Tables: REPLACE load type support and temp table cleanup - Editor: native date/time pickers, paste-validation overlay, row status indicators - Stage page: Formatted/Unformatted toggle on the approvals screen - Viya deploy: configurator improvements, deploy checks, login page UX - Index page: add live formulas and VA embed to features list
2026-09-03 17:20:48 +00:00
36 changed files with 133 additions and 810 deletions
@@ -31,22 +31,19 @@ jobs:
          apt install -y ./google-chrome*.deb;
          export CHROME_BIN=/usr/bin/google-chrome
      # Deploy tooling is pinned to exact versions: the workflow builds whatever
      # is committed, and an unpinned `latest` would let a breaking or
      # compromised upstream release ship straight to the live site.
      - name: Install Surfer
        run: |
-          npm -g install cloudron-surfer@6.4.1
+          npm -g install cloudron-surfer
      - name: build site
        run: |
-          pip install mkdocs==1.6.1
+          pip install mkdocs
-          pip install mkdocs-material==9.7.7
+          pip install mkdocs-material
-          pip install fontawesome_markdown==0.2.6
+          pip install fontawesome_markdown
-          pip install mkdocs-redirects==1.2.3
+          pip install mkdocs-redirects
          mkdocs build --clean
          mkdir site/slides
-          npx @marp-team/marp-cli@4.5.1 slides/innovation/innovation.md -o ./site/slides/innovation/index.html
+          npx @marp-team/marp-cli slides/innovation/innovation.md -o ./site/slides/innovation/index.html
-          npx @marp-team/marp-cli@4.5.1 slides/if/if.md -o site/if.pdf --allow-local-files --html=true
+          npx @marp-team/marp-cli slides/if/if.md -o site/if.pdf --allow-local-files --html=true
      - name: Deploy docs
        run: surfer put --token ${{ secrets.SURFERKEY }} --server docs.datacontroller.io site/* /
@@ -1,11 +0,0 @@
 # npm configuration for this repo's CI and local installs.
 #
 # ignore-scripts keeps package install scripts (an arbitrary-code execution
 # point) from running during the deploy workflow. Both npm packages the
 # workflow installs - cloudron-surfer and @marp-team/marp-cli - ship no
 # install, preinstall or postinstall hook, so nothing is skipped.
 #
 # save-exact pins anything installed from here to an exact version rather than
 # a caret range.
 ignore-scripts=true
 save-exact=true
@@ -1,11 +0,0 @@
 # Hooks for the pre-commit framework - https://pre-commit.com
 #
 # This repo carries no native git hooks, so this is the route for a secret scan
 # at commit time: install the framework once with `pre-commit install`, and the
 # scan then runs on every commit. The hook is pinned to an exact gitleaks
 # release tag.
 repos:
  - repo: https://github.com/gitleaks/gitleaks
    rev: v8.30.1
    hooks:
      - id: gitleaks
@@ -22,3 +22,11 @@ Button info as follows:
 |Update Licence Key| Link to the screen for providing a new Data Controller licence key|
 |Export DC Library DDL|COMING SOON!!  <br>Exports the data controller control library in DB specific DDL (eg SAS, PGSQL, TSQL) and allows an optional schema name to be included|
 ## Licence Key Screen
 The licence key screen is where you apply or update your Data Controller licence key.  Three improvements have been made to make this easier:
 * **Paste both keys at once** - if you have received a combined key, simply paste it into the licence key field and both the licence key and activation key fields are filled in automatically.  You can toggle between the combined-key input and the traditional two-field layout.
 * **Preview before applying** - as soon as both fields are populated, the key details (expiry date, number of users, active features) are displayed so you can confirm the key is correct before clicking Apply.
 * **Protocol warning** - if you paste a key that was generated for a different connection type than the one you are using (http vs https), a warning is shown and the Apply button is blocked, preventing a key that will not work from being saved.
@@ -39,6 +39,10 @@ Note that since the CAS connection is using a shared account, the CASUSER librar
 It can happen that a CAS table is configured in Data Controller but not loaded into memory. In this case, when a user selects the table, it will be automatically loaded.
 ### REPLACE Load Type
 The REPLACE load type (which replaces all rows in the target table with the staged data) is now fully supported on CAS tables.  This works the same way as it does for regular SAS datasets - see [MPE_TABLES](/dcc-tables/#loadtype) for general REPLACE documentation.
 ## Unloading
 After an approval, the in-memory version of the CAS Table will be updated.  To apply this to the underlying file on disk, the following code must be executed (eg in a POST APPROVE HOOK):
@@ -54,3 +58,7 @@ quit;
 ## Special Variables
 Processing of data in Data Controller is performed in SPRE with SAS datasets - and as such, it is not possible to process character variables longer than 32k or other CAS specific data types.
 ## Temporary Table Cleanup
 If a CAS load fails partway through, any temporary tables created during the process are cleaned up automatically - no manual intervention is required.
@@ -1,45 +0,0 @@
 /*
 * Data Controller brand overrides for the Material theme.
 *
 * The values below mirror the marketing site (https://datacontroller.io): the
 * slate used for its navbar and hero, and the green used for its logo accent.
 * They are wired up through the `custom` palette in mkdocs.yml, which leaves
 * these CSS variables for us to define.
 */
 /* Primary - the brand slate, used for the header, the mobile drawer title and body links. */
 :root,
 [data-md-color-primary='custom'] {
  --md-primary-fg-color: #314351;
  --md-primary-fg-color--light: #3d5468;
  --md-primary-fg-color--dark: #263542;
  --md-primary-bg-color: #fff;
  --md-primary-bg-color--light: #ffffffb3;
  --md-typeset-a-color: #314351;
 }
 /* Accent - the brand green, used for link hover, focus rings and the active search hit. */
 [data-md-color-accent='custom'] {
  --md-accent-fg-color: #79a843;
  --md-accent-fg-color--transparent: #79a8431a;
  --md-accent-bg-color: #fff;
  --md-accent-bg-color--light: #ffffffb3;
 }
 /*
 * Dark scheme. Material derives its dark greys from a hue variable, so pointing
 * that at the brand slate (206deg) gives the whole scheme the same cast as the
 * header instead of Material's neutral default.
 */
 [data-md-color-scheme='slate'] {
  --md-hue: 206deg;
 }
 /*
 * The brand slate is only readable on a light background, so the dark scheme
 * uses a light tint of it for body links. Green stays the accent, which keeps
 * link hover visible in both schemes.
 */
 [data-md-color-scheme='slate'][data-md-color-primary='custom'] {
  --md-typeset-a-color: #9fb5c6;
 }
@@ -42,7 +42,7 @@ The Editor screen lets users who have been pre-authorised (via the `DATACTRL.MPE
 2 - *Upload*.  If you have a lot of data, you can [upload it directly](files).  The changes are then approved in the usual way.
-3 - *Edit*.  This is the main interface, data is displayed in tabular format.  The first column is always "Delete?", as this allows you to mark rows for deletion.  This column is created by Data Controller and is not part of your table.  Note that removing a row from display does not mark it for deletion!  It simply means that this row is not part of the changeset being submitted.
+3 - *Edit*.  This is the main interface, data is displayed in tabular format.  The first column is always "Delete?", as this allows you to mark rows for deletion.  Note that removing a row from display does not mark it for deletion!  It simply means that this row is not part of the changeset being submitted.
 The next set of columns are the Primary Key, and are shaded grey.  If the table has a surrogate / retained key, then it is the Business Key that is shown here (the RK field is calculated / updated at the backend).  For SCD2 type tables, the 'validity' fields are not shown.  It is assumed that the user is always working with the current version of the data, and the view is filtered as such.
 After this, remaining columns are shown.  Dates / datetime fields have appropriate datepickers.  Other fields may also have dropdowns to ensure entry of standard values, these can be configured in the `DATACTRL.MPE_SELECTBOX` table.
@@ -50,7 +50,7 @@ New rows can be added using the right click context menu, or the 'Add Row' butto
 #### Native Date and Time Pickers
-Date, time, and datetime columns use native browser pickers when editing a cell.  This provides a familiar calendar and time selector, and respects your browser's locale settings for date and time formats.
+Date, time, and datetime columns now use native browser pickers when editing a cell.  This provides a familiar calendar and time selector, and respects your browser's locale settings for date and time formats.
 #### Paste Validation Overlay
@@ -72,11 +72,13 @@ Data Controller supports special missing numerics, ie - a single letter or under
 The Data Controller only permits BiTemporal data uploads at a single point in time - so for convenience, when viewing data in the edit screen, only the most recent records are displayed.  To edit earlier records, either use file upload, or apply a filter.
 ### Submitted
-This page shows a list of the changes you have submitted (that are not yet approved).  When you open a submitted change for review, you can toggle between viewing the data with SAS formats applied (eg formatted dates and currency) or as raw underlying values.  This is useful when you need to verify the exact value being submitted rather than its display representation.
+This page shows a list of the changes you have submitted (that are not yet approved).
 ### Approvals
 This shows the list of changes that have been submitted to you (or your groups) for approval.
 When you open a submitted change for review, you can toggle between viewing the data with SAS formats applied (eg formatted dates and currency) or as raw underlying values.  This is useful when you need to verify the exact value being submitted rather than its display representation.
 ### History
 View the list of changes to each table, who made the change, when, etc.
@@ -20,23 +20,16 @@ Currently used scopes include:
 ### DC_EMAIL_ALERTS
 Set to YES or NO to enable email alerts. This requires email options to be preconfigured (mail server etc).
 ### DC_MAXCELLS_WEBEDIT
 By default, a maximum of 200,000 cells (observations multiplied by variables) can be edited in the browser at one time.  This limit is applied together with [DC_MAXOBS_WEBEDIT](#dc_maxobs_webedit) - whichever is reached first.
 The cell count matters because the cost of an EDIT screen load tracks the number of cells, not the number of rows.  A 10 column table is comfortable at 250 rows, but 250 rows of a 1000 column table is 250,000 cells.
 ### DC_MAXOBS_WEBEDIT
-By default, a maximum of 250 observations can be edited in the browser at one time.  This number can be increased, but note that the following factors will impact performance:
+By default, a maximum of 100 observations can be edited in the browser at one time.  This number can be increased, but note that the following factors will impact performance:
 * Number of configured [Validations](/dcc-validations)
 * Browser type and version (works best in Chrome)
 * Number (and size) of columns
 * Speed of client machine (laptop/desktop)
 A wide table can reach the [DC_MAXCELLS_WEBEDIT](#dc_maxcells_webedit) limit well before this one, so increase both together.
 ### DC_MAXOBS_WEBVIEW
-By default, a maximum of 2000 observations can be viewed in the browser at one time. Please see previous section for items to consider if increasing this value.
+By default, a maximum of 500 observations can be viewed in the browser at one time. Please see previous section for items to consider if increasing this value.
 ### DC_REQUEST_LOGS
 On SASjs Server and SAS9 Server types, at the end of each DC SAS request, a record is added to the [MPE_REQUESTS](/tables/mpe_requests) table.  In some situations this can cause table locks.  To prevent this issue from occuring, the `DC_REQUEST_LOGS` option can be set to `NO` (Default is `YES`).
@@ -16,9 +16,6 @@ Adding tables to the Data Controller is a matter of configuration, specifically
 ![screenshot](img/configtable.png)
 !!! note
    `_____DELETE__THIS__RECORD_____` is a reserved name. The editor creates that column itself - it is the **Delete?** column - and never reads it from the table, so a target table must not contain a column of that name. The editor refuses to open a table that does, rather than let the two collide.
 ## MPE_TABLES Configuration Details
 Each table to be edited in the Data Controller is represented by one record in `DATACTRL.MPE_TABLES`. The fields should be populated as follows:
@@ -23,17 +23,17 @@ It is possible to configure a number of other rules by updating the MPE_VALIDATI
 ## Configurable Checks
-Check back frequently as we keep growing this list of checks.  For how each rule treats a special missing value (`.A`-`.Z`, `._`), see [Special Missing Values](#special-missing-values).
+Check back frequently as we keep growing this list of checks.
 |Rule Type|Example Value |Description|
 |---|---|---|
 |CASE|UPCASE|Will enforce the case of cell values.  Valid values: UPCASE, LOWCASE, PROPCASE|
-|NOTNULL|(defaultval)|Will prevent submission if null values are present - a special missing counts as null.  Optional - provide a default value.|
+|NOTNULL|(defaultval)|Will prevent submission if null values are present.  Optional - provide a default value.|
-|MINVAL|1|Defines a minimum value for a numeric cell.  A special missing value sorts below every number, so it fails a numeric floor, and the floor itself may be a special missing - see [Special Missing Values](#special-missing-values).|
+|MINVAL|1|Defines a minimum value for a numeric cell|
-|MAXVAL|1000000|Defines a maximum value for a numeric cell.  A special missing value sorts below every number, so it passes a numeric ceiling, and the ceiling itself may be a special missing - see [Special Missing Values](#special-missing-values).|
+|MAXVAL|1000000|Defines a maximum value for a numeric cell|
 |READONLY|(defaultval) |Renders the column read-only in the editor.  The defaultval is used when rows are added. |
 |HIDDEN|(defaultval) |Hides the column from the editor grid while still submitting its data. The defaultval is used when rows are added. |
-|ROUND|2 |Rounds numeric input on paste/edit. Positive digits round to number of decimal places (eg 2 rounds to 0.01) Negative digits round to the nearest ten/hundred etc.  Half-away-from-zero rounding is applied so `-0.5 -> -1` and `2.5 -> 3`. |
+|ROUND|2 |Rounds numeric input on paste/edit. Positive digits round to number of decimal places (eg 2 rounds to 0.01) Negative digits round to the nearest ten/hundred etc.  Half-away-from-zero rounding is applied so `-0.5 → -1` and `2.5 → 3`. |
 |NUMBER_FORMAT|`{"style":"currency","currency":"GBP"}` |Display-only [`Intl.NumberFormat` renderer](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Intl/NumberFormat).  RULE_VALUE is the JSON options object passed straight to `Intl.NumberFormat`.  Does not change the stored value. |
 |HARDFORMULA|`= PRICE * VOLUME`|The cell displays a value computed from a formula, using other columns in the same row.  The column is read-only - the user cannot override the result.  See [Formula Rules](#formula-rules) below.|
 |SOFTFORMULA|`= if( DC.ROW_STATUS != 'U', DC.USER_NAME, DC.ORIG_VALUE )`|Like HARDFORMULA, but the user can override the computed value and type their own.  See [Formula Rules](#formula-rules) below.|
@@ -45,34 +45,6 @@ Check back frequently as we keep growing this list of checks.  For how each rule
 |[SOFTSELECT_HOOK](/dynamic-cell-dropdown)|/physical/path/program.sas|A SAS service (STP or Viya Job) or a path to a SAS program on the filesystem.  User-provided values may (or may not) be in this list.  Cannot be used alongside a HARDSELECT_HOOK.|
 ## Special Missing Values
 A SAS numeric variable has 28 missing values: the regular `.` and 27 special ones (`.A`-`.Z` and `._`).  Data Controller accepts them in a numeric cell as a letter - `a` to `z` - or an underscore, with or without a leading period (`a`, `.a`, `_`, `._`), and stores the matching special missing in SAS.  The period is optional, and a plain `.` stores the regular missing.
 A numeric column that carries a date, datetime or time format is the exception.  Those cells are edited through a date picker rather than the numeric editor, and the picker accepts only a date - so a special missing cannot be typed into one of them.
 The rules treat a special missing as a value for some checks and as a missing value for others - and the range rules compare it in the order SAS gives it, below every number but ordered among the other missing values:
 |Rule|What happens to a special missing|
 |---|---|
 |NOTNULL|Fails.  A special missing is a missing value, so a NOT NULL (or primary key) constraint rejects it, and a real SAS NOT NULL constraint on the target table rejects it too.|
 |MINVAL|Fails if the minimum is a number - a missing sorts below every number, so it is below any numeric floor.  A minimum that is itself a special missing is compared in the order the missing values have among themselves, and can accept one.|
 |MAXVAL|Passes - a missing sorts below every number, so it is below any numeric ceiling.  A ceiling that is itself a special missing is compared in the missing values' own order, and can reject one.|
 |CASE|Not applicable - it is a character rule.|
 |ROUND|Ignored - ROUND only rounds values that are numbers, so a special missing is left as typed.|
 |HARDREGEX / SOFTREGEX|Checked against the pattern like any other value.  Unlike blanks and the plain `.`, special missings are **not** exempt.  See [Regex Rules](#regex-rules).|
 |SOFTSELECT|Supports special missings - a soft dropdown never blocks a value.|
 |HARDSELECT|Supports special missings - the value is matched against the dropdown list like any other value.|
 |HARDFORMULA / SOFTFORMULA|The formula returns `#VALUE!` for that row instead of a number, and that is what gets submitted.|
 In short, a special missing is rejected by NOTNULL, by a primary key column, and by a MINVAL whose floor is a number; a formula returns `#VALUE!` for it.  It is fine in a column that carries a MAXVAL, a regex, a dropdown, or ROUND - and it can satisfy a MINVAL when the floor is expressed as a special missing.
 A range rule compares in the order SAS itself uses, so a range written in special missings means what SAS would mean by it.  That order puts every missing below every non-missing value, and orders the missing values as `._`, then the regular missing, then `.A` through `.Z`.  So `MINVAL .A` with `MAXVAL .C` accepts `.B` and rejects `.D`, and a blank - the regular missing - fails a floor of `.A` because it sorts below it.  A number sorts above every missing, so it passes a floor of `.A` and fails a ceiling of `.C`.
 A primary key column is treated as NOT NULL whether or not the target table carries a physical constraint, and whether or not MPE_VALIDATIONS has a NOTNULL rule for it - a key identifies the row, so a blank and a special missing are both rejected there.
 A range rule's own value is read as a number when it looks like one and as a missing value when it is a special missing.  A value that is neither - a typo such as `..` or `AB` - satisfies nothing, so every cell in the column fails until the rule is corrected.
 ## Formula Rules
 HARDFORMULA and SOFTFORMULA let you configure a column so that its value is automatically calculated from other columns in the same row - just like a spreadsheet formula.  When a user opens the editor, the formula is evaluated live and the result is shown in each cell.
@@ -88,7 +60,7 @@ Formulas use column names, not cell references, so there is no need to know the
 Each row calculates its own result - the PRICE in row 1 is multiplied by the VOLUME in row 1, the PRICE in row 2 by the VOLUME in row 2, and so on.
 !!! note
-    Each column name in the formula must be surrounded by spaces (eg ` PRICE ` not `PRICE`) so it is recognised as a column reference rather than part of a function name.  For example, `=MATCH( PRICE )` resolves the column reference, but `=MATCH(PRICE)` does not - PRICE is left unrecognised and the formula will error rather than using the column's value.  Text inside quotes is left as-is.
+    Each column name in the formula must be surrounded by spaces (eg ` PRICE ` not `PRICE`) so it is recognised as a column reference rather than part of a function name.  Text inside quotes is left as-is.
 ### HARDFORMULA vs SOFTFORMULA
@@ -98,18 +70,18 @@ Each row calculates its own result - the PRICE in row 1 is multiplied by the VOL
 ### Editor behaviour
 * When you paste a formula into the grid, column names are automatically translated so the formula works in its new position.
-* A cell that is overwritten by a formula is flagged so you can revert it.
+* A cell that has been overwritten by a formula is flagged so you can revert it.
 * Formula-looking values pasted from Excel are treated as plain data (not evaluated), unless you explicitly choose "Apply as formula".
 ### Special values
 Formulas can reference three special values that are resolved at runtime:
-* `DC.ROW_STATUS` - the current state of the row: `M` (Modified), `A` (Added), `D` (Deleted), or `U` (Unchanged).  A newly-added row is `A` from the moment it is created - there is no transient state before that.
+* `DC.ROW_STATUS` - the current state of the row: `M` (Modified), `A` (Added), `D` (Deleted), or `U` (Unchanged).
 * `DC.USER_NAME` - the logged-in user id.
 * `DC.ORIG_VALUE` - the original cell value before the current edit.
-Example - show the current user id if the row is changed, otherwise keep the original value:
+Example - show the current user id if the row has been changed, otherwise keep the original value:
 ```
 = if( DC.ROW_STATUS != 'U', DC.USER_NAME, DC.ORIG_VALUE )
@@ -14,8 +14,6 @@ There are two ways to deploy Data Controller on SAS 9:
 * Full Deployment (preferred)
 * Streaming (for quick demos)
 Both fetch a deployment program from the [releases page](https://git.datacontroller.io/dc/dc/releases) - see the [downloads page](/downloads) for what each asset contains and how to verify it.
 ### Full Deployment
 #### 1 - Deploy Stored Processes
@@ -29,16 +27,16 @@ filename dc url "https://git.datacontroller.io/dc/dc/releases/download/latest/sa
 %inc dc;
 ```
-If you don't have internet access from SAS, download `sas9.sas` from [here](https://git.datacontroller.io/dc/dc/releases), verify it against the release `SHA256SUMS` file ([downloads page](/downloads/#verifying-a-download)), and change the initial `compiled_apploc` and `compiled_serverName` macro variable assignments as necessary.
+If you don't have internet access from SAS, download `sas9.sas` from [here](https://git.datacontroller.io/dc/dc/releases), and change the initial `compiled_apploc` and `compiled_serverName` macro variable assignments as necessary.
 #### 2 - Deploy the Frontend
-The Data Controller frontend comes pre-built, and ready to deploy to the SAS Web Server (mid-tier).
+The Data Controller frontend comes pre-built, and ready to deploy to the root of the SAS Web Server (mid-tier).
 Deploy as follows:
-1.  Download the `frontend.zip` file from: [https://git.datacontroller.io/dc/dc/releases](https://git.datacontroller.io/dc/dc/releases) (verify it against the release `SHA256SUMS` file - see the [downloads page](/downloads/#verifying-a-download))
+1.  Download the `frontend.zip` file from: [https://git.datacontroller.io/dc/dc/releases](https://git.datacontroller.io/dc/dc/releases)
-2. Create a folder for Data Controller in the [htdocs folder of your SAS Web Server](https://sasjs.io/frontend-deployment/#sas9-deploy) - typically a subdirectory of: `!SASCONFIG/LevX/Web/WebServer/htdocs` - and unzip the archive **into** that folder. The archive holds the frontend files at its root, so `index.html` sits directly inside your folder (alongside the `images` folder and the compiled asset files) - for example `htdocs/dc/index.html`.
+2. Unzip and place in the [htdocs folder of your SAS Web Server](https://sasjs.io/frontend-deployment/#sas9-deploy) - typically a subdirectory of: `!SASCONFIG/LevX/Web/WebServer/htdocs`.
 3. Open the `index.html` file and update the values in the `<sasjs>` tag as follows:
  * `appLoc` - same as per SAS code in the section above
@@ -49,7 +47,7 @@ Deploy as follows:
 The remaining properties are not relevant for a SAS 9 deployment and can be **safely ignored**.
-You can now open the app at `https://YOURWEBSERVER/<yourfoldername>`  (the folder created in step 2 above) and follow the configuration steps (DC Physical Location and Admin Group) to complete deployment.
+You can now open the app at `https://YOURWEBSERVER/unzippedfoldername`  (step 2 above) and follow the configuration steps (DC Physical Location and Admin Group) to complete deployment.
 #### 3 - Run the Configurator
@@ -95,7 +93,7 @@ filename dc url "https://git.datacontroller.io/dc/dc/releases/download/vX.X.X/de
 %inc dc;
 ```
-If you don't have internet access from SAS, download `demostream_sas9.sas` from [https://git.datacontroller.io/dc/dc/releases](https://git.datacontroller.io/dc/dc/releases) (verify it against the release `SHA256SUMS` file - see the [downloads page](/downloads/#verifying-a-download)) and modify the `appLoc` on line 2, as follows:
+If you don't have internet access from your SAS environment, just download `demostream_sas9.sas` from [https://git.datacontroller.io/dc/dc/releases](https://git.datacontroller.io/dc/dc/releases) and modify the `appLoc` on line 2, as follows:
 ![](img/sas9_apploc.png)
@@ -108,131 +108,8 @@ This can happen if you enter the wrong `serverName` when deploying the SAS progr
 The error may also be thrown due to an encoding issue - changing to a UTF-8 server has helped at least one customer.
 ## Displayed timestamps are in UTC (or the wrong timezone)
 Data Controller records timestamps (such as the SUBMITTED column on the Submitted screen, and the audit history) using the SAS session clock, via the `datetime()` function. That function returns the time of the operating system, adjusted by the [TIMEZONE= system option](https://documentation.sas.com/doc/en/pgmsascdc/default/lesysoptsref/p15siqs0s00e50n1wuuvygzkr14r.htm) if it is set. The value is then displayed in the frontend exactly as stored, without conversion.
 On Viya, the SAS compute sessions that run Data Controller jobs are started inside Kubernetes containers whose clock is UTC by default, and which inherit no timezone from the host machine. If the TIMEZONE= option is not set for the compute context used by Data Controller, every timestamp DC records and displays is UTC. Other SAS products can appear unaffected because clients such as SAS Studio create their own compute sessions and pass the browser timezone / locale, whereas Data Controller submits jobs to its own shared compute context, which gets the raw container clock.
 To confirm the current state, run the following in a SAS session under the Data Controller compute context (or check the DC job log, where `_DEBUG` output shows the same values):
 ```sas
 proc options option=timezone;
 run;
 %put &=SYSTIMEZONEIDENT &=SYSTIMEZONEOFFSET;
 ```
 If TIMEZONE is blank (and SYSTIMEZONEOFFSET is 0), the session is on UTC. To fix it, ask your Viya administrator to set the timezone for the compute context used by Data Controller (in SAS Environment Manager, edit the context's Autoexec, or set the context's SAS options):
 ```sas
 options timezone='Europe/Berlin';
 ```
 Then recycle any existing compute sessions - hot sessions keep the old setting until they terminate.
 !!! note
    Use a region/area time zone ID such as `Europe/Berlin` rather than a fixed offset such as `GMT+2`. Fixed offsets do not follow daylight saving time, so the display would be 1 hour off in winter (CET = UTC+1).
 !!! note
    Changing the timezone affects new timestamps only. Previously recorded submissions keep the UTC values that were stored when they were created.
 ## Determining Application Version
 The app version is bundled into the frontend during the release, and is visible by clicking your username in the top right.
 You can also determine the app version (and SASjs Version, and build time) by opening browser Development Tools and running `appinfo()` in the console.
 ## Support Diagnostics
 The frontend sends two input tables with the startup service and with the services that execute customer-provided code - the [hook scripts](macros.md) (pre/post edit and approve hooks) and the dynamic cell dropdown programs. They are available in those services as `work.browser_info` and `work.browser_url_vars`, so a support ticket can be diagnosed from the job log without asking the user follow-up questions, and a hook can adapt to its context. Other services do not receive them.
 The services that receive the tables are: `public/startupservice`, `editors/getdata`, `editors/getdynamiccolvals`, `editors/stagedata`, `editors/loadfile`, `editors/restore` and `auditors/postdata`.
 `editors/loadfile` is the exception in practice: the app reaches it through the adapter's file-upload call (multipart), which carries no input tables, so the service - and the post edit hook it runs - does not receive them in normal use. It is on the list for completeness, and would receive them if the service were ever invoked through the ordinary request path.
 ### browser_info
 A single-row table with these columns:
 | Column | Description |
 |---|---|
 | `url` | The URL of the Data Controller page itself (the iframe), not the document embedding it. When the editor is embedded in a report, the embedding URL is visible here. |
 | `referrer` | The embedding document, from `document.referrer`. For an embedded report this is the report URL, so the embedding report can be told apart from the editor URL. |
 | `timezone` | The browser's IANA timezone name, e.g. `Europe/Berlin`. |
 | `tz_offset` | The browser's UTC offset in minutes, as `Date.getTimezoneOffset()` returns it (positive west of UTC, so `Europe/Berlin` in summer is -120). |
 | `locale` | The browser locale, e.g. `en-GB`. |
 | `dc_version` | The Data Controller build, as shown by `appinfo()`. |
 | `adapter_version` | The `@sasjs/adapter` version the client was built with. |
 | `browser` | The browser family, parsed from the user agent. |
 | `browser_version` | The browser version. |
 | `platform` | The operating system, parsed from the user agent. |
 | `user_agent` | The raw `navigator.userAgent` string. |
 ### browser_url_vars
 The page URL parameters as one row per parameter, so a SAS program can read a parameter by name rather than parse the `url` string:
 | Column | Description |
 |---|---|
 | `name` | The URL parameter name. |
 | `value` | The URL parameter value. |
 Parameters from both the search string and the hash query string (Angular routes carry them after the `#`) are included; on a name collision the search string value wins. The table is sent only when the page URL has at least one parameter.
 On SAS 9 and Viya the app is reached through the platform's own job URL, so the platform's parameters (`_FILE`, `_program`, `_debug`, `_webout` and friends) are in the table alongside DC's. Read a parameter by name rather than assuming every row belongs to Data Controller - `embed` and `labels` are DC's, `_FILE` and `_program` are the platform's.
 The values in both tables are supplied by the client, so treat them as diagnostics hints rather than a security boundary.
 To see the tables, run any of the services above with debug on. The debug value depends on the path: `&_debug=131` on the Compute API and SAS 9, or `&_debug=128` on the Viya web (JES) path with `runAsTask` enabled - which is what the frontend sends there, so turning debug on in the app is enough. Either value makes the session initialisation write the tables to the job log:
 ```
 NOTE: MPEINIT: work.browser_url_vars:
 name=embed value=va
 NOTE: MPEINIT: work.browser_info:
 url=... referrer=... timezone=Europe/Berlin tz_offset=-120 locale=en-GB
 dc_version=7.15.0 adapter_version=4.19.0 browser=Chrome browser_version=120.0
 platform=Linux user_agent=...
 ```
 A service called directly (for instance from a URL, or by a script), or by an older frontend, has no `work.browser_info` - the log then records that fact instead.
 ### Reading the tables from a hook
 A [hook script](macros.md) is `%include`d into the running service, so it shares the service's WORK library and can read the tables directly. Take an embedded editor opened at:
 ```
 https://datacontroller.io/#/editor/SASHELP.CLASS?labels=true&embed=va
 ```
 `browser_url_vars` then holds a row per parameter - `labels=true` and `embed=va` - so a hook can pick up either by name:
 ```sas
 %let labels=N;
 %let embed=N;
 %if %sysfunc(exist(work.browser_url_vars)) %then %do;
  proc sql noprint;
    select value into :labels
    from work.browser_url_vars
    where name = 'labels';
    select value into :embed
    from work.browser_url_vars
    where name = 'embed';
  quit;
 %end;
 ```
 To branch on what the client reports:
 ```sas
 %if %sysfunc(exist(work.browser_info)) %then %do;
  data _null_;
    set work.browser_info;
    call symputx('dc_timezone', timezone);
    call symputx('dc_locale', locale);
  run;
 %end;
 ```
 !!! warning
    Guard with `%sysfunc(exist())` before reading. A service called directly, or by a frontend older than this feature, has no `work.browser_info` at all, so an unguarded `set` or `select` fails the job.
@@ -16,18 +16,6 @@ Row and Column level security can also be applied in VIEW mode, as can additiona
 A single search box can be used to make a full table search on any character or numeric value, using this [macro](https://core.sasjs.io/mp__searchdata_8sas.html).
 The search covers **every** column of the table at once, so you do not need to know which column holds the value you are looking for:
 - **Character search** (the default) is a case sensitive CONTAINS match against every character column, so `Smith` finds `Smithson` and `smith` finds `Goldsmith`, but `smith` will not find `Smithson`.
 - **Numeric search** (tick the Numeric box) is an exact match against every numeric column, so `42` will not find `420` or `4210`.
 - If a filter is applied, the search runs within the filtered rows rather than the whole table.
 - The grid is capped by the [`DC_MAXOBS_WEBVIEW`](/dcc-options/#dc_maxobs_webview) option (500 rows by default).
 - For a search, the cap applies to the row count as well: a search that matches more rows than the cap returns 500 of them, and the count shown next to the table name is the number of rows returned, not the total number of matches.
 - Without a search, the count shown next to the table name is the full number of rows in the filtered view, so it can be higher than the number of rows displayed - a table of 1,200 rows reports `1,200 rows` above a grid holding the first 500.
 - A search that matches nothing shows a "No data found with given conditions" panel rather than an empty grid.
 ![Full table search](img/full-table-search.png)
 <iframe width="560" height="315" src="https://www.youtube.com/embed/i27w-xq85WQ" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
 ## Options
@@ -130,6 +130,20 @@ Now the services are deployed (including the service which creates the staging a
 * Admin Group - the members of this group will have full access to Data Controller
 * Compute Context - the context configured in Step 1
 !!! note
    The first-launch configuration screen has been improved.  The **Groups** dropdown now shows your own groups first, the **Contexts** dropdown groups contexts by their batch user, and a new **Verify** button lets you confirm the startup service is running before continuing.  If no admin groups are found, a clear message is shown instead of the screen hanging silently.
 !!! note
    The login page has been improved with better input contrast and validation.  Submitting empty fields no longer produces an infinite spinner.
 ### Deploy Checks
 The deploy process now runs additional checks during installation to catch configuration issues early.  For larger Viya environments, the deploy script is chunked for reliability.  The compute context is also automatically corrected during deploy if needed.
 !!! note
    A debug comment is added to the compute context during deploy.  This is permanent - it is not removed by subsequent deploys.
 ### Optimisation
 At this point, every DC request will read the `services/public/settings.sas` file to get the DC library (and other) settings.  To avoid these API calls (which will speed up the app) we can simply move this code to the autoexec.  Steps as follows:
@@ -1,131 +0,0 @@
 ---
 layout: article
 title: Derived Variables
 description: Derived variables are computed columns that appear in the EDIT screen and can be filtered on, without being stored in the target table.
 ---
 # Derived Variables
 A derived variable is a column that does not exist in the target table, but is computed when the table is loaded into the [EDIT screen](/dc-userguide/#editor). It is read-only, it appears after the physical columns, and it can be filtered on like any other column.
 Derived variables are useful when users need to work with a value that is a function of the stored data - a banding, a concatenation, a calculation - without changing the table, the load process, or the ETL.
 The values are **not stored**. They are computed on every read, and nothing derived is written back when a change is submitted or approved.
 ## What it looks like
 The table below is shown in the EDIT screen. `LINE_VALUE` is `QTY * PRICE` and `REGION` is derived from `STATE`; neither exists in the table itself, and both are read-only.
 ![](./img/derived-grid.png)
 Because the derived columns are created before the filter is applied, they can be filtered like any other column. Here `REGION = 'West'` selects the two western states, and the filter bar names the derived variable:
 ![](./img/derived-filter-region.png)
 A numeric derived column works the same way - `LINE_VALUE > 50` leaves the one row that satisfies it:
 ![](./img/derived-filter-value.png)
 ## How it works
 The statements are written into a DATA step view over the target table, and the filter is applied to that view rather than to the table:
 ```sas
 data work.vw_derived / view=work.vw_derived;
  set &libds;
  attrib REGION length=$8 label='...' format=$8.;
  REGION = ifc(STATE in ('CA','OR','WA'),'West','East');
 run;
 data out;
  set work.vw_derived;
  where %inc filtref;;
 run;
 ```
 A `WHERE` statement applies to the data set named on the `SET` statement, so in a single step it cannot see a variable created later in the same step. Putting the derived variables on the view means they are on the input to the step that filters, which is what makes them filterable at all.
 ## Configuration
 Derived variables are configured per table in the [MPE_DERIVED](/tables/mpe_derived/) control table, which is itself a Data Controller table - so it is maintained through the EDIT screen with the usual review and approve workflow. The three variables shown above, and nothing else, are the three rows below:
 ![](./img/derived-config.png)
 Each row defines one variable:
 - `LIBREF` / `DSN` - the target table
 - `VAR_NM` - the name of the new column
 - `VAR_DEPS` - every input the expression uses: the physical columns and any derived variables, space separated
 - `VAR_TYPE` - `C` for character, `N` for numeric
 - `VAR_LEN` - character length, or numeric length (1-8)
 - `VAR_FMT` - optional, eg `DATE9.` or `DOLLAR12.2`
 - `VAR_LABEL` - optional; when blank the label is `<VAR_NM>=<expression>`
 - `VAR_LOGIC` - the SAS expression that produces the value
 - `ACTIVE` - set to 1 to apply the variable
 A simple example, deriving a region from a state:
 ```
 VAR_NM      REGION
 VAR_DEPS    STATE
 VAR_TYPE    C
 VAR_LEN     8
 VAR_FMT     (blank)
 VAR_LABEL   (blank)
 VAR_LOGIC   ifc(STATE in ('CA','OR','WA'),'West','East')
 ACTIVE      1
 ```
 A second variable can build on it - its dependencies include the physical column and the derived one:
 ```
 VAR_NM      REGION_LABEL
 VAR_DEPS    REGION STATE
 VAR_TYPE    C
 VAR_LEN     14
 VAR_FMT     (blank)
 VAR_LABEL   Region and state
 VAR_LOGIC   cats(REGION,'-',STATE)
 ACTIVE      1
 ```
 There is no sequence number to maintain. The statements are emitted in dependency order, so `REGION` is always assigned before `REGION_LABEL`, however the rows are ordered in the table.
 For each row, Data Controller generates the following statements when the table is read:
 ```sas
 attrib REGION length=$8 label='REGION=ifc(STATE in (''CA'',''OR'',''WA''),''West'',''East'')' format=$8.;
 REGION = ifc(STATE in ('CA','OR','WA'),'West','East');
 ```
 The label is `VAR_LABEL` when one is supplied, otherwise the variable name, an equals sign and the expression - `REGION=ifc(...)` - so the column shows both what it is and where it comes from when labels are switched on. Either way the label is truncated to the maximum label length, on a boundary that cannot split a doubled quote.
 The type and length are declared, not inferred, so a value is truncated exactly as you specify. If `VAR_FMT` is left blank, character variables default to `$<length>.` and numeric variables to `<length>.`; a date, time or datetime format makes the column render (and filter) as a date, time or datetime, the same way a stored column does.
 ## Filtering
 The derived variable is created before the filter is applied, so it can be used in the [filter](/filter/) like any other column - including its list of values. A filter on a derived column is stored and re-applied in the normal way, and the value list for a derived column is built from the table under the rest of the filter, exactly as for a stored column.
 Derived columns themselves are an EDIT screen feature: the VIEW screen and the download services do not show them. A saved filter that references a derived column still applies there, and is evaluated the same way.
 ## Rules and limits
 - **Expressions only.** `VAR_LOGIC` must be a single SAS expression - no semicolons, macro triggers (`%`, `&`) or comments. Conditional logic is available through functions such as `ifc()`, `choosec()`, `cats()`, `catx()`, `put()`, `input()` and `intnx()`.
 - **Dependencies declared.** `VAR_DEPS` lists every input the expression uses - physical columns and derived variables alike. Statements are generated in dependency order, so no sequence number is maintained, and the declaration is checked in both directions: every reference must be declared, and every declared name must be referenced and must exist. Circular references are rejected.
 - **No collisions.** `VAR_NM` must not match an existing column of the target table, or `_____DELETE__THIS__RECORD_____`.
 - **Read-only.** Derived columns cannot be edited in the grid, and any value submitted for them is discarded before the approval package is created.
 - **Recomputed on every read.** The value always reflects the current data and the current definition, and there is no history of previous derived values.
 A configuration error - a bad name, an invalid type or length, a name collision, or a reference to a derived variable that is not declared in `VAR_DEPS` - stops the EDIT screen with a message naming the variable. A syntax error or an unknown column in the expression itself is caught when the view is compiled, and stops the screen with a message naming the table.
 Most of these rules are also applied when a row is submitted for approval, through a post edit hook on `MPE_DERIVED`. A bad name, type, length, format or expression - or a reference to a derived variable that is not declared in `VAR_DEPS` - is rejected at submit time, while the error can still be corrected, rather than breaking the EDIT screen afterwards. The collision between `VAR_NM` and a physical column of the target table is only checked at read time, as the hook does not have the target library assigned.
 The simple rules are also configured as validation rules on the table itself, so they show up in the grid before submission: `VAR_TYPE` is a dropdown of `C` and `N`, `VAR_LEN` carries minimum and maximum values, and `VAR_NM`, `VAR_DEPS`, `VAR_FMT` and `VAR_LOGIC` are pattern checked. Validation rules are evaluated in the browser, so the post edit hook remains the authoritative check.
 !!! warning "Derived values can expose hidden data"
    An expression can reference a column that is hidden from the user by [Column Level Security](/column-level-security/), and the derived column will show the result. Configure derived variables with the same care as any other data exposure.
 ## Performance
 The expression is evaluated for each row read, before the filter. The filter already requires a scan of the table, so this adds per-row arithmetic rather than a second pass - but keep expressions cheap (no lookups, no subqueries), and expect the cost to be paid on every load of the EDIT screen, including each request for filter values.
@@ -1,153 +0,0 @@
 ---
 layout: article
 title: Updating the Filter in a Pre-Edit Hook
 description: Read the filter a user applied, and hand back a modified one, from a Data Controller pre-edit hook - including changing the rows the editor shows.
 ---
 # Updating the Filter in a Pre-Edit Hook
 A [pre-edit hook](/dcc-tables/#pre_edit_hook) can read the filter a user applied and return a modified one. This is useful when the editor should widen a user's selection behind the scenes - for example, when a user filters for the current quarter and the grid should also show the previous one.
 The hook runs inside the `editors/getdata` service, so both the applied filter and the filtered rows are in scope. This page describes what is available at that point and works through an example.
 ## What the editor receives
 When a filtered editor loads, `editors/getdata` returns the filter to the client in two forms:
 - `sasparams.FILTER_TEXT` - the resolved WHERE clause, which the editor shows above the grid.
 - `query` - the filter's clauses as structured rows (`variable_nm`, `operator_nm`, `raw_value`), which the editor renders as the filter chips.
 The response does not carry the filter key (`FILTER_RK`). That is an *input* to `getdata`, not an output - the editor already holds it in the URL (`/editor/<table>/<FILTER_RK>`), so there is nothing to return.
 ## When the hook runs
 `getdata` builds the filter, applies it, and sorts the result, all before the pre-edit hook runs. In order:
 1. the WHERE clause is written to a temporary fileref, `filtref`;
 2. `work.OUT` is populated with `where %inc filtref` - the filter is applied here;
 3. the pre-edit hook runs;
 4. `FILTER_TEXT` is read back out of `filtref`, and the response is streamed.
 So the hook sits between "the rows are filtered" and "the filter is returned". Two consequences follow:
 - It can change what the editor is told the filter was, by rewriting `filtref` and, if the chips must match, `work.query`.
 - It cannot change which rows came back *that* way, because the data step has already run. To return different rows, the hook must re-read the table itself.
 ## Take the value from the data
 A hook that wants to extend a date filter needs the date the user is working with. It does not have to parse the filter text for it - the filtered rows are already in `work.OUT`, so the value can be read from there.
 ## Example: widen a date filter to the previous quarter
 The hook below is registered in `MPE_TABLES.PRE_EDIT_HOOK` for a table with a date column `ORDER_DATE`. When a user opens the editor with a filter that includes `ORDER_DATE`, it extends the filter to also cover the previous quarter, re-reads the table so the grid shows both quarters, and returns the widened filter text.
 ```sas
 /* PRE_EDIT_HOOK: widen the user's ORDER_DATE filter by one quarter */
 %if &filter_rk > 0 %then %do;
  /* the date the user is looking at, taken from the rows already returned */
  %let refdt=;
  proc sql noprint;
    select max(ORDER_DATE) into :refdt from work.out;
  quit;
  %if &refdt ne %then %do;
    /* the previous quarter, relative to that date */
    %let pq_from=%sysfunc(putn(%sysfunc(intnx(quarter,&refdt,-1,b)),date9.));
    %let pq_to  =%sysfunc(putn(%sysfunc(intnx(quarter,&refdt,-1,e)),date9.));
    /* the user's own clauses, as a standalone WHERE */
    %mp_filtergenerate(work.query,outref=userref)
    /* Data Controller's own clause - current-record validity, plus RLS */
    %mpe_filtermaster(EDIT,&orig_libds,
      dclib=&mpelib,
      filter_rk=-1,
      outref=ctlref,
      outds=work.ctlq
    )
    /* read each clause (which may span several lines) into a macro variable */
    %let usertext=;
    data _null_;
      infile userref end=eof;
      input;
      length t $32767;
      retain t;
      t=catx(' ',t,_infile_);
      if eof then call symputx('usertext',t);
    run;
    %let ctltext=;
    data _null_;
      infile ctlref end=eof;
      input;
      length t $32767;
      retain t;
      t=catx(' ',t,_infile_);
      if eof then call symputx('ctltext',t);
    run;
    /* ( user's filter OR previous quarter ) AND ( validity + RLS ) */
    filename newfilt temp;
    data _null_;
      file newfilt lrecl=32767;
      length f $32767;
      f='(( '!!trim(symget('usertext'))!!' ) OR (ORDER_DATE between "&pq_from"d and "&pq_to"d))'
        !!' AND ('!!trim(symget('ctltext'))!!' )';
      put f;
    run;
    /* re-read the table, so the grid shows both quarters */
    data work.out (drop=&var_txfrom &var_txto &var_processed &drop_rk);
      set &orig_libds;
      where %inc newfilt;
    run;
    /* keep the order the editor first showed */
    proc sort data=work.out;
      by &sortpk;
    run;
    /* hand the widened filter back to the editor */
    data _null_;
      file filtref lrecl=32767;
      infile newfilt;
      input;
      put _infile_;
    run;
  %end;
 %end;
 ```
 ### What the hook does
 - **The reference date.** `work.OUT` holds the rows the user's filter returned, so the latest `ORDER_DATE` on screen is read straight from it. Nothing has to be parsed out of the filter text.
 - **The previous quarter.** `INTNX` moves back one quarter from that date and returns its first and last day, formatted as SAS date literals (`01APR2026` and `30JUN2026`, for example).
 - **The user's clause.** `work.QUERY` is the filter's clauses as structured rows, and `%mp_filtergenerate` turns them back into a WHERE clause. This is the user's filter on its own, with no Row Level Security or validity clause mixed in.
 - **Data Controller's clause.** Calling `%mpe_filtermaster` with `filter_rk=-1` produces the part of the filter that is not the user's: the current-record validity clause and any Row Level Security, or `1=1` when there is neither.
 - **The combined filter.** The two clauses are combined as `( user OR previous-quarter ) AND ( validity + RLS )`, so the previous quarter is added to the user's selection without widening anything the user is not entitled to see.
 - **The rows.** `work.OUT` is rebuilt with the combined filter, using the same drop list as the data step `getdata` runs itself - the transaction and processing columns, plus `&drop_rk`, the surrogate key that `getdata` hides when a table is registered with `RK_UNDERLYING` - and sorted on `&sortpk`, because `getdata` sorts before the hook runs and does not sort again afterwards. On a bitemporal table `getdata` also deduplicates to the latest record per primary key (`by &pk &var_busfrom`); add that step too, or the re-read returns every temporal version rather than the current one. The delete column is **not** re-added: `_____DELETE__THIS__RECORD_____` is created by the editor itself and is never a column of the dataset, so a hook must not introduce it (a response that carries that name is refused by the editor).
 - **The returned text.** `filtref` is overwritten with the combined filter, so the clause the editor shows is the one that was actually applied.
 ### What it looks like
 The captures below are the editor for a table with an `ORDER_DATE` column, opened with a filter for the current quarter. In the first, no hook is configured, so the filter is the user's own and the grid holds one quarter of rows. In the second, the hook has run: the filter above the grid carries both quarters, and the rows have grown to match.
 ![The editor with the user's own filter, one quarter of rows](/img/pre-edit-hook-before.png)
 ![The same editor after the hook widened the filter to the previous quarter](/img/pre-edit-hook-after.png)
 ## Row Level Security
 The user's clause and Data Controller's clause have to be kept apart, because Row Level Security lives in the second one. Combining them as `( user OR previous-quarter ) AND ( validity + RLS )` keeps RLS applied to both branches. Wrapping the whole existing filter instead - `( existing OR previous-quarter )` - would let the previous-quarter rows through without their RLS condition, so do not take that shortcut.
 ## The row cap
 `getdata` refuses a result larger than `DC_MAXOBS_WEBEDIT` (500 by default) with *Table is too big*. Widening a filter widens the result, so a hook that adds a quarter can push a table over the cap. Check the count before handing the data back, or raise the option for that table in `MPE_CONFIG`.
 ## Matching the filter chips
 The clause above the grid comes from `FILTER_TEXT`, so overwriting `filtref` is what updates it. The filter chips are rendered from the `query` output instead, so if they must reflect the widened filter too, amend `work.QUERY` in the same hook - append the extra clause as a new subgroup with `group_logic='OR'` before the response is built.
@@ -1,122 +0,0 @@
 ---
 layout: article
 title: One Table, Two Rule Sets
 description: A single physical table can carry only one set of Data Controller validation rules. Two librefs over the same data - or a pair of hook scripts - give you as many rule sets as you need.
 ---
 # One Table, Two Rule Sets
 Most Data Controller sites settle into an obvious mapping: one table, one edit screen, one set of validation rules. But that is not always what the business wants. A table of orders might be edited from a finance report that only tolerates small adjustments, and from an operations report where much larger ones are routine. Same table, same columns, same approvers - different rules.
 Data Controller's validation rules are configured per table, so this takes a little thought. There are two ways to do it: the one we recommend, and the one to reach for when the first is not available.
 ## Why one table is one rule set
 Two configuration tables decide this.
 `MPE_TABLES` is the list of editable tables, and its primary key is `(tx_from, libref, dsn)`. One physical table is one editable table.
 `MPE_VALIDATIONS` holds the rules, and its primary key is `(tx_from, base_lib, base_ds, base_col, rule_type)`. Rules hang off a physical `libref.dataset`. There is no per-menu or per-report scoping anywhere in the schema, and the editor is handed exactly the rules whose `base_lib` and `base_ds` match the table being opened.
 So two rule sets on one table need two distinct `libref.dataset` identities. The question is how to get them without copying the data.
 ## Option 1 (recommended): two librefs over the same data
 A libref is just a name pointing at a location. Nothing stops you assigning two of them to the same place, and Data Controller will treat the two as separate tables:
 ```sas
 libname ORDERS_EU '/data/orders';
 libname ORDERS_US '/data/orders';
 ```
 `ORDERS_EU.ORDERS` and `ORDERS_US.ORDERS` are now the same physical file, but they are different rows in `MPE_TABLES` and can therefore carry different rows in `MPE_VALIDATIONS`. Register both, give each its own rules, and point each report at its own editor URL - `#/editor/ORDERS_EU.ORDERS` and `#/editor/ORDERS_US.ORDERS`.
 ![The first report rejects an amount of 5000](/img/rule-set-1.png)
 ![The second report accepts the same value](/img/rule-set-2.png)
 Everything else works exactly as it always did. Filtering, search, the row cap, the approval diff and the audit trail all operate on the table as normal, because as far as Data Controller is concerned these are ordinary tables. The only difference is that the two names resolve to the same file, so an approval in either report updates the same data - and that one difference has a consequence for concurrency, which is covered below.
 There is no copy to keep in sync, no hook to write and nothing to maintain. That is why it is the option we recommend.
 ### Things worth knowing
 - Where the librefs are defined depends on your platform. On Viya, in the compute context's `autoexec.sas` (or `[DC Drive Path]/services/settings.sas`); on SAS 9, as metadata libraries or in the Data Controller Settings stored process; on SASjs Server, in `services/public/settings.sas`. The one requirement is that each library has a unique libref.
 - `mp_lockanytable` keys on `libref.dataset`, so the two menus do not serialise against each other. That has consequences beyond a collision - see *The concurrency caveat* below.
 - The audit trail and approval queue record which libref a change came through, so `ORDERS_EU.ORDERS` and `ORDERS_US.ORDERS` stay distinguishable in history. For most people that is a feature - you can see which report a change originated from.
 ### The concurrency caveat
 Data Controller serialises its writes with `mp_lockanytable`, and the control table it uses, `MPE_LOCKANYTABLE`, has a primary key of `(lock_lib, lock_ds)`. That is the *registration*, not the physical file. At approve time, `postdata` takes the lock on the base table named in the submit record, and the same service runs its "has this table been updated since the diff screen was shown" check against `MPE_DATALOADS`, keyed on that same `libref` and `dsn`.
 Two librefs over one location are two different `(libref, dsn)` pairs, so:
 - two approvals arriving through different reports take two different locks, and neither one blocks the other;
 - a load through one report writes its `MPE_DATALOADS` entry against its own name, so the other report's staleness check does not see it either.
 So two people editing the same rows through different reports can both be approved, and the second write wins, silently. The lock is advisory to begin with - `mp_lockanytable` is, in its own words, "only useful if every update uses the macro" - so this is not a new class of risk, but registering one file twice is a new way to fall into it.
 The hook route does not have this problem. Both mirrors route their submit to the same base table, so every approval locks, loads and logs against one identity.
 If you do use two librefs, and concurrency matters to you, the cleanest fix is to keep the two registrations for the edit screen and give each one a `POST_EDIT_HOOK` that re-points the changeset at a single canonical registration - then every approval is keyed on the same table regardless of which report raised it. Register that canonical name as well. The alternative, an explicit shared lock taken in `PRE_APPROVE_HOOK` and released in `POST_APPROVE_HOOK`, works too, but a failed run leaves the sentinel locked and `MPE_LOCKANYTABLE` is then a table you have to unpick by hand.
 ## Option 2: an empty mirror and a pair of hook scripts
 Sometimes two librefs over one location are not available: a database library where the platform will not let you define the same object twice, or a site where adding a library definition is a change nobody wants to make. Then you can reach the same result with a mirror table and two hook scripts.
 The idea is that the thing Data Controller edits is not the real table at all, but an empty table of the same shape, with hooks moving data in and out of it:
 - a `PRE_EDIT_HOOK` fills the editor with the live rows of the real table, so the mirror never has to hold a copy
 - a `POST_EDIT_HOOK` re-points the submitted changeset at the real table, so the approval is raised against the real table and the load writes there
 The mirror exists purely to carry the rule set, and never stores any data.
 ### The pre-edit hook
 `PRE_EDIT_HOOK` runs inside the `getdata` service, after the user's filter has been applied and the rows sorted, with the data in `work.OUT`. It may replace that dataset, which is all this needs:
 ```sas
 data work.out;
  set ORDERS.ORDERS;
 run;
 ```
 The registered table is `ORDERS.MIRROR`, which is empty - so without the hook the editor would show nothing at all. With it, the grid shows the live rows:
 ![An empty mirror displaying the live rows of the real table](/img/mirror-live.png)
 Note the title bar: the mirror really is empty. Everything on screen came from the hook, and the grid is validated against the mirror's own rules rather than the real table's.
 ### The post-edit hook
 This is the part that surprises people. `POST_EDIT_HOOK` runs inside the `mpe_loader` macro at submit time, on the staged rows, before the submit record is written. It cannot choose the target table directly - but at that point `LIBREF` and `DS` are still ordinary macro variables, and the submit record is built from them. Reassigning them re-points the whole changeset:
 ```sas
 data _null_;
  call symputx('libref','ORDERS');
  call symputx('ds','ORDERS');
 run;
 ```
 From that moment the changeset is an approval against `ORDERS.ORDERS`. The approver sees a diff against the real table, the load writes to the real table, and the mirror is never touched.
 ![A change submitted against the mirror, raised against the real table](/img/approval-routed.png)
 ### Reassigning LIBREF and DS
 `LIBREF` and `DS` are ordinary macro variables inside `mpe_loader`, which creates them with `%let` and then updates them from the staged row. A `%let libref=ORDERS;` reassigns them just as well as the `call symputx` above: both statements assign to the *existing* variable, because it lives in an enclosing symbol table (`mpe_loader`'s local table) and SAS only creates a new local when the name is absent from every enclosing table. `call symputx` is used above because it is explicit about which variable is being set, and because it does not depend on the enclosing scope still holding the name - a wrapper macro that declared `%local libref` would turn a bare `%let` into an assignment to that shadow instead.
 ### Other things to watch
 - Concurrency behaves correctly here. Both mirrors route their submit to the same base table, so every approval locks, loads and logs against one identity - unlike the two-libref route above.
 - The filter has already been applied to the empty mirror by the time the pre-edit hook runs, so a hook that reads the real table ignores the user's filter unless it re-applies it (`where %inc filtref`). On a small table you will not notice; on a large one the `DC_MAXOBS_WEBEDIT` cap will stop the edit screen with "Table is too big". [Updating the Filter in a Pre-Edit Hook](/developer-guide/filter-pre-edit-hook/) works through extending that filter.
 - The hook's output must have the same columns the editor expects - the real table, minus any transaction or processing columns that Data Controller drops on load.
 - The real table must itself be registered in `MPE_TABLES`. The approval screen resolves the table's audit settings from that row, so a changeset routed to a table with no registration cannot be reviewed - the submit is refused up front, naming the table.
 - The mirror's `MPE_TABLES` row is read for the edit screen and the real table's for the load, so keep their `buskey`, `loadtype` and temporal column settings identical.
 - At approval time the access checks run against the real table, so editors need `EDIT` on the mirror while approvers need `EDIT` and `APPROVE` on the real table.
 ## Which should you use?
 If you can define two librefs over the same data, do that. It is configuration only, it leaves every other behaviour of the editor untouched, and there is nothing to maintain.
 Reach for the hook scripts when the platform will not let you duplicate the library definition, or when you specifically want the rule set to be a property of the application rather than of the data.
@@ -1,52 +0,0 @@
 ---
 layout: article
 title: DC Downloads
 description: Data Controller release assets and how to verify them
 ---
 # Downloads
 Data Controller releases are published on the [releases page](https://git.datacontroller.io/dc/dc/releases) of the source repository. Every release carries the same set of assets:
 | Asset | Use |
 |---|---|
 | `frontend.zip` | The pre-built web frontend, for deployments that serve the frontend from a web server (SAS 9 full deploy, Viya separated deploy) |
 | `sas9.sas` | SAS 9 full deployment program (stored processes + frontend registration) |
 | `demostream_sas9.sas` | SAS 9 streaming deployment program (demos and evaluations) |
 | `viya.sas` | Viya streaming deployment program (backend + frontend) |
 | `viya_noweb.sas` | Viya separated deployment program (backend only) |
 | `viya_noweb.json` | The Viya backend services as a SASjs Drive JSON deployment bundle |
 | `sasjs_server.json.zip` | SASjs Server deployment bundle (all services, for [SASjs Server](https://server.sasjs.io) deployments) |
 | `SHA256SUMS` | SHA-256 checksums for every asset above |
 Which asset you need depends on the deployment route - see [SAS 9 Deployment](/dci-deploysas9) or [SAS Viya Deployment](/deploy-viya).
 ## Verifying a download
 Every asset is covered by the `SHA256SUMS` file, which the release pipeline generates over the exact files it uploads. To verify a download:
 1. Download the asset (for example `frontend.zip`) from the [releases page](https://git.datacontroller.io/dc/dc/releases).
 2. Download `SHA256SUMS` from the same release into the same folder.
 3. Run the check:
 ```bash
 sha256sum --check SHA256SUMS --ignore-missing
 ```
 Each asset that matches reports `OK`. The `--ignore-missing` flag means you only need the files you actually downloaded - the check skips assets you did not fetch.
 On Windows, `certutil` can compute the hash of a single file for comparison against the value listed in `SHA256SUMS`:
 ```
 certutil -hashfile frontend.zip SHA256
 ```
 ### What the checksum proves
 A matching checksum confirms the asset is byte-for-byte the file the release pipeline uploaded. It catches corrupted and tampered downloads - interrupted transfers, proxies or mirrors that altered the file in transit.
 It is not a cryptographic signature. The hashes travel in the same release as the files they cover, so they protect the download path, not the release itself: a compromise of the forge would allow both the asset and its checksum to be altered together. For download integrity - the typical concern when fetching deployment artifacts over the internet - it is the standard check.
 ## Integrity inside SAS
 The SAS deployment programs embed the frontend and services as generated SAS code. Once `%inc`'d, their integrity is established by the check above at download time. They deploy the stored processes or jobs into the SAS Folder you nominate (`appLoc`) - a metadata location, not physical disk - and the only physical location they write to is the Data Controller location (`dcLoc`) you configure. The programs can be [reviewed in full](https://code.datacontroller.io) (or in the [source repository](https://git.datacontroller.io/dc/dc)) before you run them.
@@ -9,8 +9,6 @@ og_image:  https://docs.datacontroller.io/img/filter_dynamic_on.png
 Data Controller for SAS&reg; enables you to create complex table filters. The "dynamic" setting enables the dropdown values to be pre-filtered by previous filter clauses.  Filtered views are shareable!  They are also used when [embedded in VA.](/embed-va)
 The clause shown above the grid is the resolved WHERE clause that was applied, so it uses SAS syntax - a date, datetime or time filter reads as a SAS literal, eg `SOME_DATE = '20APR2042'd`, rather than the internal day or second count.
 ## Shared Filters
 When filters are submitted, the query is stored, and a unique URL is generated.  This means you can share the link to a filtered view of a table!  This can be used for VIEW, for EDIT and also for downloading data.
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@@ -20,9 +20,76 @@ When features are requested, we will describe the work to be performed in the se
 The following features are currently requested:
 * Additional Validations
 * Ability to set 'number of approvals' to zero, enabling instant updates (4 days)
 * Ability to make automated submissions using an API
 ### Additional Validations
 The following additional features are necessary:
 * ~~Frontend Formulae~~ - **Delivered** in v7.13.0.  See [Formula Rules](/dcc-validations/#formula-rules).
 * Regex Rules - **Delivered**.  See [Regex Rules](/dcc-validations/#regex-rules).
 The above rules will apply only at frontend, and will be configurable in the MPE_VALIDATIONS table.  The values will appear as part of the [editors/getdata](https://code.datacontroller.io/getdata_8sas_source.html) service response in the `dqrules` object.
 **Frontend Formulae**
 The plan here will be to introduce [hyperformula](https://hyperformula.handsontable.com/guide/demo.html) into HandsOnTable.  It will allow a library of ~400 functions and advanced excel-like behaviour.  It integrates natively [as a plugin with HandsOnTable](https://handsontable.com/docs/javascript-data-grid/formula-calculation/#available-functions).
 The initial challenge will be that HyperFormula requires cell references to operate, eg:
 |ITEM|PRICE|VOLUME|REVENUE|
 |---|---|---|---|
 |PAPER|4.20|100|`= B1 * C1`|
 |PEN|61.02|1,971|`= B2 * C2`|
 Whereas end users cannot know these references ahead of time.  Therefore the references will be made using variable names, eg:
 |ITEM|PRICE|VOLUME|REVENUE|
 |---|---|---|---|
 |PAPER|4.20|100|`= PRICE * VOLUME`|
 |PEN|61.02|1,971|`= PRICE * VOLUME`|
 The frontend can then perform replacement of the variables for each Formula cell.  For instance, replacing ` PRICE ` with ` B1 ` and ` VOLUME ` with ` C1 ` in the first row (and with ` B2 ` and ` C2 ` in the second row respectively).
 To avoid clashes with names that match function names (eg, `MATCH()`) each named variable **must have a leading and trailing blank**, and we should be sure to ignore variables inside of single or double quoted strings - eg ` ITEM & " string ITEM "` (would resolve to `A1 & "string ITEM "`).
 There would be two types applied:
 * `HARDFORMULA` -> Column is readonly 
 * `SOFTFORMULA` -> Column can be changed by the user
 To enable conditional logic (eg, show the current user id if row is changed), we also need a new column in the EDIT grid, to show the edit status (Modified, Added, Deleted, Unchanged).  This should be the first column, and should NOT be submitted to backend.  We could display these values as icons, rather than letters.
 These properties can be accessed using the following literals:
 * DC.ROW_STATUS - replaced at runtime with the cell reference, eg A1 or A2.  Values would be M, A, D, or U.
 * DC.USER_NAME - replaced at runtime with the logged-in user id
 * DC.ORIG_VALUE - replaced at runtime with the original cell value
 An example of a rule value that intends to show the current user id if the row is changed:
 ```
 RULE_VALUE= if( DC.ROW_STATUS != 'U', DC.USER_NAME, DC.ORIG_VALUE )
 ```
 Which would translate to the following formula, after the page is loaded:
 ```
 =if(A1!='U',"sasdemo","sasinstaller")
 ```
 **Regex Rules**
 There are two types of rule we can apply in the form of regular expressions:
 * `HARDREGEX` -> If the value fails the rule, the data cannot be submitted (turns red)
 * `SOFTREGEX` -> If the value fails the rule we change the cell colour to yellow (as a warning), but can still submit
 ### Set Approvals to Zero
 The following changes are necessary to implement this feature:
@@ -45,10 +112,6 @@ Described [here](https://docs.datacontroller.io/api/).
 Below are some examples of Features that have been requested (and delivered) into Data Controller.
 ### Derived Variables
 Columns that do not exist in the table - a banding, a concatenation, a calculation - can be configured per table and appear in the EDIT screen, read-only and filterable, without changing the table or the load process. Nothing derived is stored.  See [docs](/derived-variables)
 ### Column Level Security
 The columns that can be VIEWed or EDITed are now configurable.  See [docs](/column-level-security)
@@ -174,11 +237,3 @@ It is now possible to restore any change by heading to the particular staged dat
 This will submit a NEW change (which must first be approved) that will revert the table to state it was in just prior to the selected upload.
 Note that Data Controller can only track (and revert) changes that are made using the Data Controller tool itself! It does not / cannot track changes made externally to a table, by other tools.
 ### Frontend Formulae
 Delivered in v7.13.0.  Formula columns (HARDFORMULA / SOFTFORMULA) are computed live in the editor using HyperFormula, with variable-name references resolved to row-relative cell references.  See [Formula Rules](/dcc-validations/#formula-rules).
 ### Regex Rules
 Delivered.  HARDREGEX (blocking) and SOFTREGEX (warning) rules validate cell values against a Perl-style regular expression.  See [Regex Rules](/dcc-validations/#regex-rules).
@@ -1,26 +0,0 @@
 ---
 layout: article
 title: MPE_DERIVED
 description: The MPE_DERIVED table is used to configure computed columns that appear in the EDIT screen and can be filtered on without being stored in the table.
 ---
 # MPE_DERIVED
 The MPE_DERIVED table is used to configure derived (computed) variables - columns that are created when a table is loaded into the EDIT screen, so that they can be displayed and filtered on without being stored.  More details are available in the [user guide](/derived-variables/)
 The table is itself registered in [MPE_TABLES](/tables/mpe_tables/), so it is maintained through the EDIT screen with the usual review and approve workflow.
 ## Columns
 - `TX_FROM num`: SCD2 open datetime
 - 🔑 `TX_TO num`: SCD2 close datetime
 - 🔑 `LIBREF char(8)`: The libref of the target table
 - 🔑 `DSN char(32)`: The target table
 - 🔑 `VAR_NM char(32)`: The name of the derived column
 - `VAR_DEPS char(4000)`: Every input the expression uses - physical columns and derived variables, space separated
 - `VAR_TYPE char(1)`: `C` for character, `N` for numeric
 - `VAR_LEN num`: Character length, or numeric length (1-8)
 - `VAR_FMT char(32)`: Optional SAS format, eg `DATE9.`
 - `VAR_LABEL char(256)`: Optional label; defaults to `<VAR_NM>=<expression>`
 - `VAR_LOGIC char(4000)`: The SAS expression that produces the value
 - `ACTIVE num`: Set to 1 to apply the variable
@@ -17,5 +17,5 @@ The `MPE_FILTERSOURCE` table stores the individual query lines of each filter cr
 - `SUBGROUP_ID num`: Identifier of the subgroup to which this line belongs
 - `VARIABLE_NM char(32)`: The variable being filtered
 - `OPERATOR_NM char(12)`: The filter operator (e.g. `=`, `>`, `IN`)
- - `RAW_VALUE char(4000)`: The filter value. A date, datetime or time is stored as a SAS literal (for example `'20APR2042'd`, `'01JAN1960:00:00:42'dt`, `'00:00:42't`), so the clause shown above the grid reads as a date rather than the internal day or second count.
+ - `RAW_VALUE char(4000)`: The filter value
 - `PROCESSED_DTTM num`: Datetime the filter line was created
@@ -17,7 +17,7 @@ A collection of videos made in relation to Data Controller.  Some of them were r
 ### Data Controller - a Customer Story
 An illustration of the utility of Data Controller for Data & Analytics teams in regulated industries.
-<iframe title="Data Controller - a Customer Story" width="560" height="315" src="https://vid.4gl.io/videos/embed/kpSGoNE26FSif8X9A6pUfe?peertubeLink=0" frameborder="0" allowfullscreen="" sandbox="allow-same-origin allow-scripts allow-popups"></iframe>
+<iframe width="560" height="315" src="https://www.youtube.com/embed/M8hafkS4zY4" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
 ### Use Case Video - Manual Overrides
@@ -14,9 +14,6 @@ nav:
    - Table Viewer: dcu-tableviewer.md
    - ViewBoxes: viewboxes.md
    - Admin Services: admin-services.md
 - Developer Guide:
    - Filter in a Pre-Edit Hook: developer-guide/filter-pre-edit-hook.md
    - One Table, Two Rule Sets: developer-guide/two-rule-sets-one-table.md
 - Table Guide:
    - MPE_AUDIT: tables/mpe_audit.md
    - MPE_COLUMN_LEVEL_SECURITY: tables/mpe_column_level_security.md
@@ -32,7 +29,6 @@ nav:
    - MPE_DATASTATUS_TABS: tables/mpe_datastatus_tabs.md
    - MPE_DATADICTIONARY: tables/mpe_datadictionary.md
    - MPE_DATALOADS: tables/mpe_dataloads.md
    - MPE_DERIVED: tables/mpe_derived.md
    - MPE_EMAILS: tables/mpe_emails.md
    - MPE_EXCEL_CONFIG: tables/mpe_excel_config.md
    - MPE_FILTERANYTABLE: tables/mpe_filteranytable.md
@@ -59,7 +55,6 @@ nav:
    - CAS Tables: cas-tables.md
    - Column Level Security: column-level-security.md
    - Dates / Datetimes: dcc-dates.md
    - Derived Variables: derived-variables.md
    - Dynamic Cell Dropdown: dynamic-cell-dropdown.md
    - Emails: emails.md
    - Excel: excel.md
@@ -76,7 +71,6 @@ nav:
 - Macros: macros.md
 - Installation:
    - System Requirements: dci-requirements.md
    - Downloads: downloads.md
    - SAS Viya: deploy-viya.md
    - SAS 9 EBI: dci-deploysas9.md
    - SAS 9 STP Hardening: dci-stpinstance.md
@@ -101,9 +95,7 @@ markdown_extensions:
 extra:
  manifest: manifest.webmanifest
-extra_css:
+extra_css: ['font-awesome.css']
  - font-awesome.css
  - dc-brand.css
 plugins:
  - search:
@@ -119,22 +111,12 @@ repo_url: 'https://git.datacontroller.io/dc/docs.datacontroller.io'
 theme:
  name: material
-  logo: 'img/dc-logo.svg'
+  logo: 'img/favicon.ico'
  palette:
-    - scheme: slate
+    primary: 'White'
-      primary: custom
+    accent: 'Amber'
      accent: custom
      toggle:
        icon: material/weather-sunny
        name: Switch to light mode
    - scheme: default
      primary: custom
      accent: custom
      toggle:
        icon: material/weather-night
        name: Switch to dark mode
  font:
-    text: 'Montserrat'
+    text: 'Open Sans'
    code: 'Ubuntu Mono'
  favicon: img/favicon.ico
  custom_dir: 'theme'