From 35b097469b8e4921f55785c90db522f1e8435878 Mon Sep 17 00:00:00 2001
From: Tyler Goodlet <jgbt@protonmail.com>
Date: Thu, 12 Jan 2023 01:32:30 -0500
Subject: [PATCH 1/3] Round spread (slap) offset to min tick digits

---
 piker/clearing/_ems.py | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/piker/clearing/_ems.py b/piker/clearing/_ems.py
index ad512c08..01de9822 100644
--- a/piker/clearing/_ems.py
+++ b/piker/clearing/_ems.py
@@ -46,6 +46,7 @@ from ..data._normalize import iterticks
 from ..data._source import (
     unpack_fqsn,
     mk_fqsn,
+    float_digits,
 )
 from ..data.feed import (
     Feed,
@@ -1249,6 +1250,7 @@ async def process_client_order_cmds(
 
                 spread_slap: float = 5
                 min_tick = flume.symbol.tick_size
+                min_tick_digits = float_digits(min_tick)
 
                 if action == 'buy':
                     tickfilter = ('ask', 'last', 'trade')
@@ -1257,12 +1259,18 @@ async def process_client_order_cmds(
                     # TODO: we probably need to scale this based
                     # on some near term historical spread
                     # measure?
-                    abs_diff_away = spread_slap * min_tick
+                    abs_diff_away = round(
+                        spread_slap * min_tick,
+                        ndigits=min_tick_digits,
+                    )
 
                 elif action == 'sell':
                     tickfilter = ('bid', 'last', 'trade')
                     percent_away = -0.005
-                    abs_diff_away = -spread_slap * min_tick
+                    abs_diff_away = round(
+                        -spread_slap * min_tick,
+                        ndigits=min_tick_digits,
+                    )
 
                 else:  # alert
                     tickfilter = ('trade', 'utrade', 'last')

From 7ef81113813339556e58b75d2e7e06b09805260e Mon Sep 17 00:00:00 2001
From: Tyler Goodlet <jgbt@protonmail.com>
Date: Thu, 12 Jan 2023 16:30:56 -0500
Subject: [PATCH 2/3] Provide `datetime`-sorted clears table iteration

Likely pertains to helping with stuff in issues #345 and #373 and just
generally is handy to have when processing ledgers / clearing event
tables.

Adds the following helper methods:
- `iter_by_dt()` to iter-sort an arbitrary `Transaction`-like table of
  clear entries.
- `Position.iter_clears()` as a convenience wrapper for the above.
---
 piker/pp.py | 43 +++++++++++++++++++++++++++++++++----------
 1 file changed, 33 insertions(+), 10 deletions(-)

diff --git a/piker/pp.py b/piker/pp.py
index 8fdaaa4d..48cf0daa 100644
--- a/piker/pp.py
+++ b/piker/pp.py
@@ -29,6 +29,7 @@ import re
 import time
 from typing import (
     Any,
+    Iterator,
     Optional,
     Union,
 )
@@ -116,6 +117,21 @@ class Transaction(Struct, frozen=True):
     # from: Optional[str] = None
 
 
+def iter_by_dt(
+    clears: dict[str, Any],
+) -> Iterator[tuple[str, dict]]:
+    '''
+    Iterate entries of a ``clears: dict`` table sorted by entry recorded
+    datetime presumably set at the ``'dt'`` field in each entry.
+
+    '''
+    for tid, data in sorted(
+        list(clears.items()),
+        key=lambda item: item[1]['dt'],
+    ):
+        yield tid, data
+
+
 class Position(Struct):
     '''
     Basic pp (personal/piker position) model with attached clearing
@@ -183,12 +199,7 @@ class Position(Struct):
         toml_clears_list = []
 
         # reverse sort so latest clears are at top of section?
-        for tid, data in sorted(
-            list(clears.items()),
-
-            # sort by datetime
-            key=lambda item: item[1]['dt'],
-        ):
+        for tid, data in iter_by_dt(clears):
             inline_table = toml.TomlDecoder().get_empty_inline_table()
 
             # serialize datetime to parsable `str`
@@ -301,6 +312,14 @@ class Position(Struct):
     # def lifo_price() -> float:
     #     ...
 
+    def iter_clears(self) -> Iterator[tuple[str, dict]]:
+        '''
+        Iterate the internally managed ``.clears: dict`` table in
+        datetime-stamped order.
+
+        '''
+        return iter_by_dt(self.clears)
+
     def calc_ppu(
         self,
         # include transaction cost in breakeven price
@@ -331,10 +350,9 @@ class Position(Struct):
         asize_h: list[float] = []  # historical accumulative size
         ppu_h: list[float] = []  # historical price-per-unit
 
-        clears = list(self.clears.items())
-
-        for i, (tid, entry) in enumerate(clears):
-
+        tid: str
+        entry: dict[str, Any]
+        for (tid, entry) in self.iter_clears():
             clear_size = entry['size']
             clear_price = entry['price']
 
@@ -344,6 +362,11 @@ class Position(Struct):
 
             sign_change: bool = False
 
+            if accum_size == 0:
+                ppu_h.append(0)
+                asize_h.append(0)
+                continue
+
             if accum_size == 0:
                 ppu_h.append(0)
                 asize_h.append(0)

From 51f4afbd88ddbca2bb18630dab670fefc8e402c1 Mon Sep 17 00:00:00 2001
From: Tyler Goodlet <jgbt@protonmail.com>
Date: Mon, 9 Jan 2023 14:24:39 -0500
Subject: [PATCH 3/3] Don't raise on quote feed lags to dark clearing loop

---
 piker/clearing/_ems.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/piker/clearing/_ems.py b/piker/clearing/_ems.py
index 01de9822..32a1cc36 100644
--- a/piker/clearing/_ems.py
+++ b/piker/clearing/_ems.py
@@ -173,6 +173,7 @@ async def clear_dark_triggers(
     # TODO:
     # - numba all this!
     # - this stream may eventually contain multiple symbols
+    quote_stream._raise_on_lag = False
     async for quotes in quote_stream:
         # start = time.time()
         for sym, quote in quotes.items():