aljaz/hummingbot-dashboard
1
0
Fork 0
mirror of https://github.com/aljazceru/hummingbot-dashboard.git synced 2026-02-14 17:46:10 +01:00
Code Issues Packages Projects Releases Wiki Activity

(feat) allow multiple pages code gen

Browse Source
This commit is contained in:
cardosofede
2023-07-21 11:52:05 +02:00
parent 2da66f5275
commit 181c962e5e
1 changed files with 25 additions and 24 deletions
Download Patch File Download Diff File Expand all files Collapse all files

49
pages/9_⚙️_Backtesting.py
View File

@@ -97,7 +97,7 @@ with optimize:
# TODO:
# * Add videos explaining how to use the optimization tool, quick intro to optuna, etc in a toggle
with st.container():
c1, c2 = st.columns([1, 1])
c1, c2, c3 = st.columns([1, 1, 1])
with c1:
strategies = load_directional_strategies(constants.DIRECTIONAL_STRATEGIES_PATH)
strategy_to_optimize = st.selectbox("Select strategy to optimize", strategies.keys())
@@ -106,26 +106,27 @@ with optimize:
# TODO: add hints about the study name
STUDY_NAME = st.text_input("Study name",
f"{strategy_to_optimize}_study_{today.day:02d}-{today.month:02d}-{today.year}")
c1, c2 = st.columns([4, 1])
with c1:
# TODO: every time that we save and run the optimizations, we should save the code in a file
# so the user then can correlate the results with the code
st.session_state.strategy_code = st_ace(key="create_code",
value=strategy_optimization_template(
strategy_info=strategies[strategy_to_optimize]),
language='python',
keybinding='vscode',
theme='pastel_on_dark')
with c2:
if st.button("Save optimizations"):
save_file(name=f"{STUDY_NAME}.py", content=st.session_state.strategy_code,
path=constants.OPTIMIZATIONS_PATH)
if st.button("Run optimizations"):
study = optuna.create_study(direction="maximize", study_name=STUDY_NAME,
storage="sqlite:///data/backtesting/backtesting_report.db",
load_if_exists=True)
objective = get_function_from_file(file_path=f"{constants.OPTIMIZATIONS_PATH}/{STUDY_NAME}.py",
function_name="objective")
with c3:
generate_optimization_code_button = st.button("Generate Optimization Code")
if generate_optimization_code_button:
c1, c2 = st.columns([4, 1])
with c1:
# TODO: every time that we save and run the optimizations, we should save the code in a file
# so the user then can correlate the results with the code.
optimization_code = st_ace(key="create_optimization_code",
value=strategy_optimization_template(strategy_info=strategies[strategy_to_optimize]),
language='python',
keybinding='vscode',
theme='pastel_on_dark')
with c2:
if st.button("Run optimization"):
save_file(name=f"{STUDY_NAME}.py", content=optimization_code, path=constants.OPTIMIZATIONS_PATH)
study = optuna.create_study(direction="maximize", study_name=STUDY_NAME,
storage="sqlite:///data/backtesting/backtesting_report.db",
load_if_exists=True)
objective = get_function_from_file(file_path=f"{constants.OPTIMIZATIONS_PATH}/{STUDY_NAME}.py",
function_name="objective")
def optimization_process():
@@ -134,9 +135,9 @@ with optimize:
optimization_thread = threading.Thread(target=optimization_process)
optimization_thread.start()
if st.button("Launch optuna dashboard"):
os_utils.execute_bash_command(f"optuna-dashboard sqlite:///data/backtesting/backtesting_report.db")
webbrowser.open("http://127.0.0.1:8080/dashboard", new=2)
if st.button("Launch optuna dashboard"):
os_utils.execute_bash_command(f"optuna-dashboard sqlite:///data/backtesting/backtesting_report.db")
webbrowser.open("http://127.0.0.1:8080/dashboard", new=2)
with analyze:
# TODO: