trading-daemon/dashboard/__pycache__/server.cpython-313.pyc

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Gibt aggregierte Analyse aller Trades zurück (nicht einzelne Trades).
Nutzt vorberechnete Daten aus analytics_exchange_daily.
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        select 
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            count(*) as trade_count,
            sum(price * quantity) as volume,
            avg(price) as avg_price
        from trades
        where isin = 'z('
        and timestamp > dateadd('d', -zB, now())
        group by date
        order by date desc
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        select 
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        from analytics_exchange_daily
        where timestamp >= dateadd('d', -z:, now())
        order by date desc, exchange asc
        r;r<00>Oanalytics_exchange_daily is empty. Analytics worker should calculate this data.r<00>date<74>exchange<67>trade_count<6E>volumer9)r6r+<00>len<65>logger<65>warningr<)r=r>r r7s    r<00>
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Gibt Zusammenfassung zurück. Nutzt analytics_daily_summary für total_trades.
Optional: days Parameter für Zeitraum-basierte Zusammenfassung.
z<EFBFBD>
        select 
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            sum(total_volume) as total_volume
        from analytics_daily_summary
        where timestamp >= dateadd('d', -z, now())
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Flexibler Analytics-Endpunkt für custom Graphen.
Nutzt vorberechnete Daten aus analytics_custom für bessere Performance.

Parameters:
- date_from: Startdatum (YYYY-MM-DD)
- date_to: Enddatum (YYYY-MM-DD)
- x_axis: X-Achse (date, exchange, isin) - aktuell nur "date" unterstützt
- y_axis: Y-Achse (volume, trade_count, avg_price)
- group_by: Gruppierung (exchange, isin, date)
- exchanges: Komma-separierte Liste von Exchanges (optional)
)rArBr=)rDrC<00>	avg_price)rBr=rA<00><>
z Invalid x_axis. Must be one of: r'z Invalid y_axis. Must be one of: z"Invalid group_by. Must be one of: rAzrx_axis must be 'date' for pre-calculated analytics. Other x_axis values are not supported for performance reasons.<2E>
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    select 
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    where timestamp >= 'z'
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    and exchange_filter = 'z2'
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Gibt Moving Average Daten für Tradezahlen und Volumen je Exchange zurück.
Unterstützte Zeiträume: 7, 30, 42, 69, 180, 365 Tage
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    select 
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        maz_count as ma_count,
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Gibt Änderungen in Volumen und Anzahl je Exchange zurück.
Unterstützte Zeiträume: 7, 30, 42, 69, 180, 365 Tage
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    select 
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        volume_change_pct,
        trend
    from analytics_volume_changes
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    order by timestamp desc
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Gibt Trendanalyse für häufig gehandelte Aktien zurück.
Unterstützte Zeiträume: 7, 30, 42, 69, 180, 365 Tage
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    select 
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    from analytics_stock_trends
    where period_days = z$
    and timestamp >= dateadd('d', -z,, now())
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)5u&Analytics Endpunkt für Report Builder<65>exchange_continent<6E>exchange_sector)rrM<00>sectorNzt.<2E>zm.zsum(zprice * z	quantity)zcount(*)zavg(zprice))rD<00>countr^zdate_trunc('day', z
timestamp)zdate_trunc('month', rBr=z	coalesce(zname, zisin)zcontinent, 'Unknown')z	'Unknown'zsector, 'Unknown')zconcat(zexchange, ' - ', coalesce(zcontinent, 'Unknown'))zsector, 'Unknown')))	<09>day<61>monthrBr=rrMr<>r<>r<>rDr<>zselect z	 as labelz, z
 as sub_labelrbz, count(*) as value_count, sum(z%quantity) as value_volume from tradesz as value from tradesz* t left join metadata m on t.isin = m.isinz
 where 1=1z and ztimestamp >= 'r~ztimestamp <= 'r`z	isin in (<28>
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