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 # exorcist
 Daemonless campaign-scale simulation orchestration
+
+
+### Micro-dashboard (pandas DataFrame)
+
+Eventually, we expect to develop a useful dashboard. Until then, the most
+convenient way for users to get an overview of the task status database is by
+using `pandas` (version 2.0 or greater):
+
+```python
+import pandas as pd
+from exorcist import TaskStatusDB
+
+db = TaskStatusDB.from_filename("path/to/my/database.db")
+tasks = pd.read_sql_table("tasks", db.engine)
+deps = pd.read_sql_table("dependencies", db.engine)
+```
+
+NOTE: `pandas` is not in the `exorcist` requirement stack, so you may need to
+install it separately.
+
+The tasks table is the main thing you'll be interested in. It has columns for
+the task ID (a string labeling the task), the task status (see
+[models.py](https://github.com/OpenFreeEnergy/exorcist/blob/main/exorcist/models.py)),
+last modified (which will be not-a-time until the first update), the number of
+tries so far, and the maximum number tries allowed.
+
+The dependencies table gives details on the dependencies in the DAG. Each entry
+in this table has a task ID for the "from" side of the edge and the "to" side
+of the edge, as well as a boolean "blocking" column. The "from" task must be
+completed before the "to" task can begin. When the "from" task has been
+completed, the entry should be updated so the "blocking" is False.