494b3faa9b
Since each broker backend generally needs to define a specific
field-name-schema to determine the exact instantiation arguments to
`Transaction`, we generally need each backend to define an endpoint
function to conduct this transaction from an input `dict[str, Any]`
received either directly from provided ledger APIs or from previously
stored `.accounting._ledger` saved trades ledger TOML files.
To accomplish this we now require backends to declare a new routine:
```python
def norm_trade(
tid: str, # the uuid for the transaction
txdict: dict, # the input record-dict
# a table of mkt-symbols to backend
# struct objects which define the (meta-data) for the backend specific
# venue's symbology
pairs: dict[str, Struct],
) -> Transaction:
...
```
which implements that record conversion (at least for trades)
and can thus be used in `TransactionLedger.iter_txns()` which requires
"some code" to implement the loading from a serialization format (aka
the input `dict` record) to our local `Transaction` struct, normally
also using a `Pair`-struct table defined (and maybe previously cached)
by the specific backend such our (normalization layer's) `MktPair`'s
fields can be set.
For the case of our `.clearing._paper_engine` we def the routine to
simply extract the exact same fields from the TOML ledger records that
we previously had written (to it) and define it in that module.
Also, we always pass `pairs=SymbologyCache.pairs: dict[str, Struct]` on
norm trade calls such that offline ledger and accounting processing
clients can use a previously cached symbology set without having to
necessarily start the async-actor runtime to query the actual backend API
if the data has already been saved locally on the system B)
Other related:
- always passthrough kwargs in overridden `.to_dict()` method.
- only do fqme related trade record field name rewrites/names when
operating on a paper ledger; normally a backend's records don't
contain these.
- fix `pendulum.DateTime` type annots.
- just deliver `Transaction`s from `.iter_txns()`
|
||
|---|---|---|
| .github/workflows | ||
| config | ||
| dockering | ||
| docs | ||
| examples | ||
| piker | ||
| scripts | ||
| snippets | ||
| tests | ||
| .gitignore | ||
| LICENSE | ||
| MANIFEST.in | ||
| README.rst | ||
| develop.nix | ||
| notes_to_self.rst | ||
| pytest.ini | ||
| requirements-test.txt | ||
| requirements.txt | ||
| setup.py | ||
README.rst
piker
trading gear for hackers.
piker is a broker agnostic, next-gen FOSS toolset for real-time computational trading targeted at hardcore Linux users .
we use as much bleeding edge tech as possible including (but not limited to):
- latest python for glue
- trio & tractor for our distributed, multi-core, real-time streaming structured concurrency runtime B)
- Qt for pristine high performance UIs
- pyqtgraph for real-time charting
polarsnumpyandnumbafor fast numerics- apache arrow and parquet for time series history management persistence and sharing
- (prototyped) techtonicdb for L2 book storage
focus and features:
- 100% federated: your code, your hardware, your data feeds, your broker fills.
- zero web: low latency, native software that doesn't try to re-invent the OS
- maximal privacy: prevent brokers and mms from knowing your planz; smack their spreads with dark volume.
- zero clutter: modal, context oriented UIs that echew minimalism, reduce thought noise and encourage un-emotion.
- first class parallelism: built from the ground up on next-gen structured concurrency primitives.
- traders first: broker/exchange/asset-class agnostic
- systems grounded: real-time financial signal processing that will make any queuing or DSP eng juice their shorts.
- non-tina UX: sleek, powerful keyboard driven interaction with expected use in tiling wms
- data collaboration: every process and protocol is multi-host scalable.
- fight club ready: zero interest in adoption by suits; no corporate friendly license, ever.
fitting with these tenets, we're always open to new framework suggestions and ideas.
building the best looking, most reliable, keyboard friendly trading platform is the dream; join the cause.
sane install with poetry
TODO!
rigorous install on nixos using poetry2nix
TODO!
hacky install on nixos
NixOS is our core devs' distro of choice for which we offer a stringently defined development shell envoirment that can be loaded with:
nix-shell develop.nixthis will setup the required python environment to run piker, make sure to run:
pip install -r requirements.txt -e .once after loading the shell
install wild-west style via pip
piker is currently under heavy pre-alpha development and as such should be cloned from this repo and hacked on directly.
for a development install:
git clone git@github.com:pikers/piker.git
cd piker
virtualenv env
source ./env/bin/activate
pip install -r requirements.txt -e .check out our charts
bet you weren't expecting this from the foss:
piker -l info -b kraken -b binance chart btcusdt.binance --pdbthis runs the main chart (currently with 1m sampled OHLC) in in debug mode and you can practice paper trading using the following micro-manual:
order_mode(edge triggered activation by any of the following keys,
mouse-clickon y-level to submit at that price ):f/ctl-fto stage buyd/ctl-dto stage sellato stage alert
search_mode(ctl-lorctl-spaceto open,ctl-corctl-spaceto close ) :- begin typing to have symbol search automatically lookup symbols from all loaded backend (broker) providers
- arrow keys and mouse click to navigate selection
- vi-like
ctl-[hjkl]for navigation
you can also configure your position allocation limits from the sidepane.
run in distributed mode
start the service manager and data feed daemon in the background and connect to it:
pikerd -l info --pdbconnect your chart:
piker -l info -b kraken -b binance chart xmrusdt.binance --pdbenjoy persistent real-time data feeds tied to daemon lifetime. the next time you spawn a chart it will load much faster since the data feed has been cached and is now always running live in the background until you kill pikerd.
if anyone asks you what this project is about
you don't talk about it.
how do i get involved?
enter the matrix.
how come there ain't that many docs
suck it up, learn the code; no one is trying to sell you on anything. also, we need lotsa help so if you want to start somewhere and can't necessarily write serious code, this might be the place for you!