Allows building a `MktPair` from the backend specific `Pair` for
eventual use in the data feed layer. Also adds `Pair.price/tick_size` to
get to the expected tick precision info format.
Add a logic branch for now that switches on an instance check.
Generally swap over all `Position.symbol` and `Transaction.sym` refs to
`MktPair`. Do a wholesale rename of all `.bsuid` var names to
`.bs_mktid`.
Instead let's name it `.sys` for "system", the thing we use to conduct
the "transactions" ..
Also rename `.bsuid` -> `.bs_mktid` for "backend system market id`
which is more explicit, easier to remember and read.
Prepping to entirely replace `Symbol`; this adds a buncha docs/comments,
better implementation for representing and parsing the FQME: "fully
qualified market endpoint".
Deatz:
- make `.src` an optional field until we figure out how we're going
to support loading source assets from all backends sensibly..
- implement `MktPair.fqme: str` (what was previously called `fqsn`)
using a new util func: `maybe_cons_tokens()`.
- `Symbol.brokers` and expect only `.broker` usage.
- remap anything with `fqsn` in the name to `fqme` with aliases from the
old name.
- implement `unpack_fqme()` with `match:` syntax B)
- add `MktPair.tick_size_digits`, `.lot_size_digits`, `.fqsn`, `.key` for
backward compat.
- make all fqme generation related fields empty `str`s by default.
- add `MktPair.resolved: bool` a flag indicating whether or not `.dst`
is an `Asset` instance or just a string and, `.bs_mktid` the field
to hold the "backend system market id" per broker.
Try out using our new internal type for storing info about kraken's asset
infos now stored in the `Client.assets: dict[str, Asset]` table. Handle
a server error when requesting such info msgs.
Drop everything we can in terms of methods and attrs from `Symbol`:
- kill `.tokens()`, `.front_feed()`, `.tokens()`, `.nearest_tick()`,
`.front_fqsn()`, instead moving logic from these methods into
dependents (and obviously removing any usage from rest of code base,
coming in follow up commits).
- rename `.quantize_size()` -> `.quantize()`.
- re-implement `.brokers`, `.lot_size_digits`, `.tick_size_digits` as
`@property` methods; for the latter two, allows us to minimize to only
accepting min tick decimal values on alternative constructor class
methods and to drop the equivalent instance vars.
- map `_fqsn` related variable names to new and preferred `_fqme`.
We also juggle around some utility functions, moving limited precision
related `decimal.Decimal` routines to the top of module and soon-to-be
legacy `fqsn` related routines to the bottom.
`MktPair` draft type extensions:
- drop requirements for `src_type`, and offer the optional `.dst_type`
field as either a `str` or (new `typing.Literal`) `AssetTypeName`.
- define an equivalent `.quantize()` as (re)defined in `Symbol` but with
`quantity_type: str` field which specifies whether to use the price or
the size precision.
- add a lot more docs, a `.key` property for the "symbol" name, draft
property for a `.fqme: str`
- allow `.src` and `.dst` to be of type `str | Asset`
Add a new `Asset` to capture "things which can be used in markets and/or
transactions" XD
- defines a `.name`, `.atype: AssetTypeName` a financial category tag, `tx_tick:
Decimal` the precision limit for transactions and of course
a `.quantime()` method for doing accounting arithmetic on a given tech
stack.
- define the `atype: AssetTypeName` type as a finite set of `str`s
expected to be used in various ways for default settings in other
parts of the data and order control layers..
Our issue was not having the correct value set on each
`Symbol.lot_tick_size`.. and then doing PPU calcs with the default set
for legacy mkts..
Also,
- actually write `pps.toml` on broker mode exit.
- drop `get_likely_pair()` and import from pp module.
Not sure how this worked before but, the PPU calculation critically
requires that the order of clearing transactions are in the correct
chronological order! Fix this by sorting `trans: dict[str, Transaction]`
in the `PpTable.update_from_trans()` method.
Also, move the `get_likely_pair()` parser from the `kraken` backend here
for future use particularly when we revamp the asset-transaction
processing layer.
Apparently it will likely fix our `trio`-cancel-scopes-corrupted crash
when we try to let our `._web_bs.NoBsWs` do reconnect logic around
the asyn-generator implemented data-feed streaming routines in `binance`
and `kraken`. See the project docs for deatz; obvs we add the lib as
a dep.
Solve this by always scaling the y-range for the major/target curve
*before* the final overlay scaling loop; this implicitly always solve
the case where the major series is the only one in view.
Tidy up debug print formatting and add some loop-end demarcation comment
lines.
This is particularly more "good looking" when we boot with a pair that
doesn't have historical 1s OHLC and thus the fast chart is empty from
outset. In this case it's a lot nicer to be already zoomed to
a comfortable preset number of "datums in view" even when the history
isn't yet filled in.
Adjusts the chart display `Viz.default_view()` startup to explicitly
ensure this happens via the `do_min_bars=True` flag B)
Not sure how i missed this (and left in handling of `list.remove()` and
it ever worked for that?) after the `samplerd` impl in 5ec1a72 but, this
adjusts the remove-broken-subscriber loop to catch the correct
`set.remove()` exception type on a missing (likely already removed)
subscription entry.
For the purposes of eventually trying to resolve last-step indexing
synchronization (an intermittent but still existing) issue(s) that can
happen due to races during history frame query and shm writing during
startup. In fact, here we drop all `hist_viz` info queries from the main
display loop for now anticipating that this code will either be removed
or improved later.
Tyler Goodlet
goodboy