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Melchior Reimers
2026-01-25 17:36:29 +01:00
parent 4f4d734643
commit 33f5c90fce
8 changed files with 996 additions and 355 deletions
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284
dashboard/server.py
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@@ -114,168 +114,46 @@ async def get_analytics(
"exchange_sector": f"concat({t_prefix}exchange, ' - ', coalesce({m_prefix}sector, 'Unknown'))" if needs_metadata else "'Unknown'"
}
# Determine table based on granularity and needs
# For day/month aggregation without ISIN specific filtering, use analytics_daily
# But analytics_daily doesn't have individual ISINs (except via another table)
# So if ISIN filter is off, use analytics_daily
selected_metric = metrics_map.get(metric, metrics_map["volume"])
selected_group = groups_map.get(group_by, groups_map["day"])
use_analytics_table = False
query = f"select {selected_group} as label"
# Check if we can use the pre-aggregated table
if not isins and not sub_group_by == "isin" and group_by != "isin" and group_by != "name":
use_analytics_table = True
table_name = "analytics_daily" if use_analytics_table else "trades"
# If using analytics table, columns might be named differently?
# analytics_daily: timestamp, exchange, sector, continent, volume, trade_count, avg_price
# We need to map our generic query builder to this table
# This might be tricky if column names don't align exactly or if we need dynamic mapping.
# To keep it safe for now, let's just stick to 'trades' but hint towards optimization.
# Actually, let's implement IT for the main view (Exchange/Continent breakdown)
if use_analytics_table:
# Simplified query for analytics table
# Note: timestamps are day-aligned in analytics table
# Adjust metric mapping for analytics table
metrics_map_opt = {
"volume": "sum(volume)",
"count": "sum(trade_count)",
"avg_price": "avg(avg_price)", # Not mathematically perfect but close for display
"all": "count(*) as value_count, sum(volume) as value_volume" # Wait, 'all' needs specific handling
}
if metric == 'all':
metric_expr = "sum(trade_count) as value_count, sum(volume) as value_volume"
else:
metric_expr = f"{metrics_map_opt.get(metric, 'sum(volume)')} as value"
# Group mapping logic
# analytics_daily has: timestamp, exchange, sector, continent
groups_map_opt = {
"day": "timestamp",
"month": "date_trunc('month', timestamp)",
"exchange": "exchange",
"continent": "continent",
"sector": "sector",
"exchange_continent": "concat(exchange, ' - ', continent)",
"exchange_sector": "concat(exchange, ' - ', sector)"
}
sel_group_expr = groups_map_opt.get(group_by, "timestamp")
query = f"select {sel_group_expr} as label"
if sub_group_by and sub_group_by in groups_map_opt:
query += f", {groups_map_opt[sub_group_by]} as sub_label"
query += f", {metric_expr} from analytics_daily where 1=1"
if date_from: query += f" and timestamp >= '{date_from}'"
if date_to: query += f" and timestamp <= '{date_to}'"
# Filters
if continents:
cont_list = ",".join([f"'{c.strip()}'" for c in continents.split(",")])
query += f" and continent in ({cont_list})"
query += f" group by {sel_group_expr}"
if sub_group_by: query += f", {groups_map_opt[sub_group_by]}"
query += " order by label asc"
if sub_group_by and sub_group_by in groups_map:
query += f", {groups_map[sub_group_by]} as sub_label"
if metric == 'all':
query += f", count(*) as value_count, sum({t_prefix}price * {t_prefix}quantity) as value_volume from trades"
else:
# Fallback to RAW TRADES query (existing logic)
# ... (keep existing logic but indented/wrapped)
selected_metric = metrics_map.get(metric, metrics_map["volume"])
selected_group = groups_map.get(group_by, groups_map["day"])
query = f"select {selected_group} as label"
if sub_group_by and sub_group_by in groups_map:
query += f", {groups_map[sub_group_by]} as sub_label"
if metric == 'all':
query += f", count(*) as value_count, sum({t_prefix}price * {t_prefix}quantity) as value_volume from trades"
else:
query += f", {selected_metric} as value from trades"
if needs_metadata:
query += " t left join metadata m on t.isin = m.isin"
query += " where 1=1"
if date_from:
query += f" and {t_prefix}timestamp >= '{date_from}'"
if date_to:
query += f" and {t_prefix}timestamp <= '{date_to}'"
if isins:
isins_list = ",".join([f"'{i.strip()}'" for i in isins.split(",")])
query += f" and {t_prefix}isin in ({isins_list})"
if continents and needs_metadata:
cont_list = ",".join([f"'{c.strip()}'" for c in continents.split(",")])
query += f" and {m_prefix}continent in ({cont_list})"
query += f" group by {selected_group}"
if sub_group_by and sub_group_by in groups_map:
query += f", {groups_map[sub_group_by]}"
query += " order by label asc"
query += f", {selected_metric} as value from trades"
if needs_metadata:
query += " t left join metadata m on t.isin = m.isin"
query += " where 1=1"
if date_from:
query += f" and {t_prefix}timestamp >= '{date_from}'"
if date_to:
query += f" and {t_prefix}timestamp <= '{date_to}'"
if isins:
isins_list = ",".join([f"'{i.strip()}'" for i in isins.split(",")])
query += f" and {t_prefix}isin in ({isins_list})"
if continents and needs_metadata:
cont_list = ",".join([f"'{c.strip()}'" for c in continents.split(",")])
query += f" and {m_prefix}continent in ({cont_list})"
query += f" group by {selected_group}"
if sub_group_by and sub_group_by in groups_map:
query += f", {groups_map[sub_group_by]}"
query += " order by label asc"
print(f"Executing Query: {query}")
try:
response = requests.get(f"http://{DB_HOST}:9000/exec", params={'query': query}, auth=DB_AUTH)
if response.status_code == 200:
return response.json()
print(f"DEBUG: Query Failed: {response.text}")
if use_analytics_table:
print("DEBUG: Analytics query failed, falling back to RAW trades query...")
selected_metric = metrics_map.get(metric, metrics_map["volume"])
selected_group = groups_map.get(group_by, groups_map["day"])
raw_query = f"select {selected_group} as label"
if sub_group_by and sub_group_by in groups_map:
raw_query += f", {groups_map[sub_group_by]} as sub_label"
if metric == 'all':
raw_query += f", count(*) as value_count, sum({t_prefix}price * {t_prefix}quantity) as value_volume from trades"
else:
raw_query += f", {selected_metric} as value from trades"
if needs_metadata:
raw_query += " t left join metadata m on t.isin = m.isin"
raw_query += " where 1=1"
if date_from: raw_query += f" and {t_prefix}timestamp >= '{date_from}'"
if date_to: raw_query += f" and {t_prefix}timestamp <= '{date_to}'"
if isins:
isins_list = ",".join([f"'{i.strip()}'" for i in isins.split(",")])
raw_query += f" and {t_prefix}isin in ({isins_list})"
if continents and needs_metadata:
cont_list = ",".join([f"'{c.strip()}'" for c in continents.split(",")])
raw_query += f" and {m_prefix}continent in ({cont_list})"
raw_query += f" group by {selected_group}"
if sub_group_by and sub_group_by in groups_map:
raw_query += f", {groups_map[sub_group_by]}"
raw_query += " order by label asc"
print(f"Executing Fallback Query: {raw_query}")
fb_response = requests.get(f"http://{DB_HOST}:9000/exec", params={'query': raw_query}, auth=DB_AUTH)
if fb_response.status_code == 200:
return fb_response.json()
throw_http_error(response)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@@ -292,6 +170,104 @@ async def search_metadata(q: str):
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/statistics/moving-average")
async def get_moving_average(days: int = 7, exchange: str = None):
"""
Gibt Moving Average Daten für Tradezahlen und Volumen je Exchange zurück.
Unterstützte Zeiträume: 7, 30, 42, 69, 180, 365 Tage
"""
if days not in [7, 30, 42, 69, 180, 365]:
raise HTTPException(status_code=400, detail="Invalid days parameter. Must be one of: 7, 30, 42, 69, 180, 365")
# Hole Daten aus der vorberechneten analytics_exchange_daily Tabelle
query = f"""
select
timestamp as date,
exchange,
trade_count,
volume,
ma{days}_count as ma_count,
ma{days}_volume as ma_volume
from analytics_exchange_daily
where timestamp >= dateadd('d', -{days}, now())
"""
if exchange:
query += f" and exchange = '{exchange}'"
query += " order by date asc, exchange asc"
try:
response = requests.get(f"http://{DB_HOST}:9000/exec", params={'query': query}, auth=DB_AUTH)
if response.status_code == 200:
return response.json()
throw_http_error(response)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/statistics/volume-changes")
async def get_volume_changes(days: int = 7):
"""
Gibt Änderungen in Volumen und Anzahl je Exchange zurück.
Unterstützte Zeiträume: 7, 30, 42, 69, 180, 365 Tage
"""
if days not in [7, 30, 42, 69, 180, 365]:
raise HTTPException(status_code=400, detail="Invalid days parameter. Must be one of: 7, 30, 42, 69, 180, 365")
query = f"""
select
timestamp as date,
exchange,
trade_count,
volume,
count_change_pct,
volume_change_pct,
trend
from analytics_volume_changes
where period_days = {days}
order by date desc, exchange asc
"""
try:
response = requests.get(f"http://{DB_HOST}:9000/exec", params={'query': query}, auth=DB_AUTH)
if response.status_code == 200:
return response.json()
throw_http_error(response)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/statistics/stock-trends")
async def get_stock_trends(days: int = 7, limit: int = 20):
"""
Gibt Trendanalyse für häufig gehandelte Aktien zurück.
Unterstützte Zeiträume: 7, 30, 42, 69, 180, 365 Tage
"""
if days not in [7, 30, 42, 69, 180, 365]:
raise HTTPException(status_code=400, detail="Invalid days parameter. Must be one of: 7, 30, 42, 69, 180, 365")
# Hole Top-Aktien nach Volumen für den Zeitraum
query = f"""
select
timestamp as date,
isin,
trade_count,
volume,
count_change_pct,
volume_change_pct
from analytics_stock_trends
where period_days = {days}
order by volume desc
limit {limit}
"""
try:
response = requests.get(f"http://{DB_HOST}:9000/exec", params={'query': query}, auth=DB_AUTH)
if response.status_code == 200:
return response.json()
throw_http_error(response)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
def throw_http_error(res):
raise HTTPException(status_code=res.status_code, detail=f"QuestDB error: {res.text}")