Использование переменных в качестве market_id и selection_id для place_order (используя betfairlightweight) - PullRequest
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Использование переменных в качестве market_id и selection_id для place_order (используя betfairlightweight)

0 голосов
/ 22 октября 2019

Я пытаюсь использовать переменные из предыдущей версии в проге как market_id и selection_id, когда я использую place_order с использованием Betfairlightweight. Размещение кода ставки работает, когда я выполняю тест с определенными идентификаторами, но я не могу заставить его работать с переменными.

Я попытался преобразовать selection_id (который, я думаю, был в формеnumpy.float64) в строку. Когда я выполняю тестовый прогон, я могу использовать переменные, которые я только что назначил, например, 

    # this is the test that works fine
    def bet():
        stake = 2
        selection = '12988828'
        market = '1.163978618'
        limit_order_filter = betfairlightweight.filters.limit_order(
            size=str(stake), 
            price=12,
            persistence_type='LAPSE')

        instructions_filter = betfairlightweight.filters.place_instruction(
            selection_id=str(selection),
            order_type="LIMIT",
            side="BACK",
            limit_order=limit_order_filter)

        order = trading.betting.place_orders(
            market_id=str(market),
            customer_strategy_ref='back_the_fav',
            instructions=[instructions_filter])

    # but this is the code that doesnt
    def placing_a_back_bet_on_the_favourite_horse():
        stake = 2

        limit_order_filter = betfairlightweight.filters.limit_order(
            size=str(stake), 
            price=12,
            persistence_type='LAPSE')

        instructions_filter = betfairlightweight.filters.place_instruction(
            selection_id=str(fav_selection_id),
            order_type="LIMIT",
            side="BACK",
            limit_order=limit_order_filter)

        order = trading.betting.place_orders(
            market_id=str(currentraceid), 
            customer_strategy_ref='back_the_fav',
            instructions=[instructions_filter] ) 

    def checking_the_odds_of_the_top(): # the code for how the variables are created...this is the fav_selection_id
        global fav_selection_id
        fav_selection_id = runners_df.iloc[0,1]

    def process_runner_books(runner_books):#from
        best_back_prices = [runner_book.ex.available_to_back[0].price
                            if runner_book.ex.available_to_back
                            else 100
                            for runner_book
                            in runner_books]
        best_lay_prices = [runner_book.ex.available_to_lay[0].price
                           if runner_book.ex.available_to_lay
                           else 1000.0
                           for runner_book
                           in runner_books]
        selection_ids = [runner_book.selection_id for runner_book in runner_books]
        last_prices_traded = [runner_book.last_price_traded for runner_book in runner_books]

        df = pd.DataFrame({
            'Last Price Traded': last_prices_traded,
            'Best Back Price': best_back_prices,
            'Selection ID': selection_ids,
            'Best Lay Price': best_lay_prices,
        }).set_index('Last Price Traded').sort_index()
        return df

    def getting_market_info_for_all_the_horses_in_a_race():
        global runners_df
        try:
            price_filter = betfairlightweight.filters.price_projection(price_data=['EX_BEST_OFFERS'])
            market_books = trading.betting.list_market_book(market_ids=[currentraceid],price_projection=price_filter)
            market_book = market_books[0]
            runners_df = process_runner_books(market_book.runners)            
            print(runners_df)

    def finding_the_races(): # and the currentraceid is from...  
        global currentraceid
        global marketfinishtime
        datetime_in_a_week = (datetime.datetime.utcnow() + datetime.timedelta(hours=1)).strftime("%Y-%m-%dT%TZ")
        market_catalogue_filter = betfairlightweight.filters.market_filter(event_ids=[currentmeetingid], market_start_time={'to': datetime_in_a_week})
        market_catalogues = trading.betting.list_market_catalogue(filter=market_catalogue_filter,
            market_projection=["MARKET_START_TIME"],
            max_results='10',
            sort='FIRST_TO_START'
        )
        market_types_mooney_valley = pd.DataFrame({
            'mst':[market_cat_object.market_start_time for market_cat_object in market_catalogues],
            'Market ID': [market_cat_object.market_id for market_cat_object in market_catalogues],
            'Market Name': [market_cat_object.market_name for market_cat_object in market_catalogues],
            'Total Matched': [market_cat_object.total_matched for market_cat_object in market_catalogues],
        }).set_index('Total Matched').sort_index(ascending=False)
        print(market_types_mooney_valley)
        marketfinishtime = market_types_mooney_valley.iloc[0,0]
        currentraceid = market_types_mooney_valley.iloc[0,1]

Извините за действительно длинный Q, но я слишком много обошел круг по этому вопросу слишком долго. Заранее спасибо за помощь

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