def scraped_insert(db_client, l_race_key):
url = scraping.Scraping.url_program
scraping_client = scraping.Scraping(url, [l_race_key[0]], [l_race_key[1]],
[l_race_key[2]])
scraping_client.get_raceinfo_by_url_program()
# スクレイピング結果が格納されていなかった場合、エラー
if len(scraping_client.out_l_header) == 0:
return False
else:
# ヘッダー情報をDBへINSERT
l_param = l_race_key + scraping_client.out_l_header
db_client.execute_insert(sql.Sql.insert_W_RACE_HEAD, l_param)
# レース情報をDBへINSERT
for i in range(len(scraping_client.out_l_racer)):
l_param = l_race_key + [
i + 1, scraping_client.out_l_racer[i],
scraping_client.out_l_represent[i],
scraping_client.out_l_hande[i],
scraping_client.out_l_trialrun[i],
scraping_client.out_l_deviation[i],
scraping_client.out_l_position_x[i],
scraping_client.out_l_position_y[i]
]
db_client.execute_insert(sql.Sql.insert_W_RACE_INFO, l_param)
return True
def scraped_insert_result(db_client, l_race_key):
url = scraping.Scraping.url_result
scraping_client = scraping.Scraping(url, [l_race_key[0]], [l_race_key[1]],
[l_race_key[2]])
scraping_client.get_raceresult_by_url_result()
# スクレイピング結果が格納されていなかった場合、エラー
if len(scraping_client.out_l_rank) == 0:
return scraping_client.out_err_msg
else:
try:
# 払戻額をDBへINSERT（着順は7車制を考慮）
l_param = l_race_key + scraping_client.out_l_payoff + (
scraping_client.out_l_car_no + [None])[:8]
db_client.execute_insert(sql.Sql.insert_T_RACE_PAYOFF, l_param)
# レース結果をDBへINSERT
for i in range(len(scraping_client.out_l_car_no)):
l_param = l_race_key + [
scraping_client.out_l_car_no[i],
scraping_client.out_l_racetime[i],
scraping_client.out_l_starttime[i],
scraping_client.out_l_rank[i]
]
db_client.execute_insert(sql.Sql.insert_T_RACE_RESULT, l_param)
return ""
except Exception as e:
print(str(e))
return str(e)
def scraped_insert(db_client, dated):
url = scraping.Scraping.url_program
scraping_client = scraping.Scraping(url, [dated], ['isesaki','kawaguchi','hamamatsu','sanyou','iizuka'], ['1'])
scraping_client.get_place_by_url_program()
for place in scraping_client.out_list_place:
for i in range(12):
l_param = [dated, place, i+1, 0, None]
db_client.execute_insert(sql.Sql.insert_T_MONTHLY_LOG, l_param)
def scraped_insert(db_client, dated):
url = scraping.Scraping.url_program
scraping_client = scraping.Scraping(
url, [dated],
['isesaki', 'kawaguchi', 'hamamatsu', 'sanyou', 'iizuka'], ['1'])
scraping_client.get_place_by_url_program()
# スクレイピング結果が格納されていなかった場合、エラー
if len(scraping_client.out_list_place) == 0:
return False
else:
# レース場をDBへINSERT
for place in scraping_client.out_list_place:
l_param = [dated, place]
db_client.execute_insert(sql.Sql.insert_W_PLACE, l_param)
return True
def lambda_handler(event, context):
try:
# パラム取得
# dated = event["queryStringParameters"]["dated"]
place = event["queryStringParameters"]["place"]
round = event["queryStringParameters"]["round"]
# 今日を取得（日付はLambdaで取得するよう統一）
today = datetime.datetime.today()
dated = today.strftime("%Y-%m-%d")
# スクレイピング
url = scraping.Scraping.url_program
scraping_client = scraping.Scraping(url, [dated], [place], [round])
scraping_client.get_raceinfo_by_url_program()
# スクレイピング結果が格納されていなかった場合、エラー
if len(scraping_client.out_l_header) == 0:
err_msg = message.Message.ios_err01
raise Exception(err_msg)
else:
# エラーチェック
if scraping_client.out_l_header[7] != "8車制":
err_msg = message.Message.ios_err02
raise Exception(err_msg)
elif scraping_client.out_l_trialrun[0] == None:
err_msg = message.Message.ios_err03
raise Exception(err_msg)
elif scraping_client.out_l_header[6] != "良走路":
err_msg = message.Message.ios_err04
raise Exception(err_msg)
else:
# 分析開始
if int(max(scraping_client.out_l_position_x)) > 4:
anaylize_client = anaylize.Sklearn("RandomForestRegressor")
else:
anaylize_client = anaylize.Sklearn("LinearRegression")
l_d_result = []
train_count = 0
for i in range(len(scraping_client.out_l_racer)):
# S3から訓練データを準備
l_d_train_data = []
s3_client = awsmanagement.S3()
for d_train_data in csv.DictReader(
s3_client.get_file(
scraping_client.out_l_racer[i] + ".csv",
awsmanagement.S3.s3_bucket_data_train)):
l_d_train_data.append(d_train_data)
# 訓練データの件数取得
train_count += len(l_d_train_data)
# テストデータを準備
l_d_test_date = [{
"車番":
i + 1,
"ハンデ":
scraping_client.out_l_hande[i],
"試走タイム":
scraping_client.out_l_trialrun[i],
"試走偏差":
scraping_client.out_l_deviation[i],
"横ポジション":
scraping_client.out_l_position_x[i],
"縦ポジション":
scraping_client.out_l_position_y[i],
"気温":
scraping_client.out_l_header[3],
"湿度":
scraping_client.out_l_header[4],
"走路温度":
scraping_client.out_l_header[5]
}]
# 予測実行（訓練データはs3のcsvファイル）
result = anaylize_client.execute_anaylize(
l_d_train_data, l_d_test_date, "競争タイム",
["試走タイム", "横ポジション", "縦ポジション", "走路温度"])[0]
# 予測値整形
# 競争タイムから、ヨーイドンからゴールまでのタイムを計算
# 競争タイム ÷ 100 × (レース距離 + ハンデ)
result2 = result / 100 * (
int(scraping_client.out_l_header[1]) +
int(scraping_client.out_l_hande[i]))
# 着順を決める用に、辞書型でリストに格納
l_d_result.append({
"車番": str(i + 1),
"選手名": scraping_client.out_l_racer[i],
"競争タイム": str(result),
"並替用": result2
})
# ソートして着順に車番を取得する
l_d_result.sort(key=lambda x: x['並替用'])
# S3にcsvファイル出力
csv_value = ""
csv_value = csv_value + "訓練レース数" + ","
csv_value = csv_value + "車番" + ","
csv_value = csv_value + "選手名" + ","
csv_value = csv_value + "競争タイム" + "\n"
for i in range(len(l_d_result)):
csv_value = csv_value + str(train_count) + ","
csv_value = csv_value + str(l_d_result[i]["車番"]) + ","
csv_value = csv_value + l_d_result[i]["選手名"] + ","
csv_value = csv_value + str(l_d_result[i]["競争タイム"]) + "\n"
# S3にUP
if place == "kawaguchi":
place_kana = "川口"
elif place == "isesaki":
place_kana = "伊勢崎"
elif place == "hamamatsu":
place_kana = "浜松"
elif place == "iizuka":
place_kana = "飯塚"
elif place == "sanyou":
place_kana = "山陽"
else:
place_kana = "その他"
s3_client.put_file(place_kana + "/" + round + "R.csv",
csv_value,
awsmanagement.S3.s3_bucket_data_anaylize)
# レスポンス
return {
'statusCode':
200,
'body':
json.dumps({
"message": "ok",
"TrainCount": str(train_count),
"Anaylize": l_d_result
})
}
except Exception as e:
print(str(e))
# レスポンス
return {
"headers": {
"Access-Control-Allow-Origin": "*",
"Access-Control-Allow-Credentials": "true"
},
'statusCode': 400,
'body': json.dumps({"message": str(e)})
}
def lambda_handler(event, context):
try:
# 昨日分のレース情報ファイルを削除
s3_client = awsmanagement.S3()
l_file = s3_client.get_filelist(awsmanagement.S3.s3_bucket_data_daily)
for file_name in l_file:
s3_client.delete_file(file_name,
awsmanagement.S3.s3_bucket_data_daily)
# 昨日分のレース分析結果ファイルを削除
l_file = s3_client.get_filelist(
awsmanagement.S3.s3_bucket_data_anaylize)
for file_name in l_file:
s3_client.delete_file(file_name,
awsmanagement.S3.s3_bucket_data_anaylize)
# 今日を取得
today = datetime.datetime.today()
dated = today.strftime("%Y-%m-%d")
# レース会場取得
url = scraping.Scraping.url_program
scraping_client = scraping.Scraping(
url, [dated],
['isesaki', 'kawaguchi', 'hamamatsu', 'sanyou', 'iizuka'], ['1'])
scraping_client.get_place_by_url_program()
# レース会場をループし、レース情報を取得
for place in scraping_client.out_list_place:
for round in [
'1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11',
'12'
]:
scraping_client = scraping.Scraping(url, [dated], [place],
[round])
scraping_client.get_raceinfo_by_url_program()
# レース情報が取得できていて、
if len(scraping_client.out_l_header) != 0:
# 8車制であれば、
if scraping_client.out_l_header[7] == "8車制":
# S3にcsvファイル出力
csv_value = ""
csv_value = csv_value + "place" + ","
csv_value = csv_value + "round" + ","
csv_value = csv_value + "car_no" + ","
csv_value = csv_value + "hande" + ","
csv_value = csv_value + "position_x" + ","
csv_value = csv_value + "position_y" + "\n"
for i in range(8):
csv_value = csv_value + place + ","
csv_value = csv_value + round + ","
csv_value = csv_value + str(i + 1) + ","
csv_value = csv_value + str(
scraping_client.out_l_hande[i]) + ","
csv_value = csv_value + str(
scraping_client.out_l_position_x[i]) + ","
csv_value = csv_value + str(
scraping_client.out_l_position_y[i]) + "\n"
# S3にUP
if place == "kawaguchi":
place_kana = "川口"
elif place == "isesaki":
place_kana = "伊勢崎"
elif place == "hamamatsu":
place_kana = "浜松"
elif place == "iizuka":
place_kana = "飯塚"
elif place == "sanyou":
place_kana = "山陽"
else:
place_kana = "その他"
s3_client.put_file(
place_kana + "/" + round + "R.csv", csv_value,
awsmanagement.S3.s3_bucket_data_daily)
# レスポンス
return {'statusCode': 200, 'body': json.dumps("ok")}
except Exception as e:
print(str(e))
# レスポンス
return {'statusCode': 400, 'body': json.dumps("ng")}
