def lyst(event, context):
keywords = event["keywords"]
discount_rate = event["discount_rate"]
print(f"*** This is lyst, {keywords}, {discount_rate} ***")
""" Pt.1 Lyst から検索ワード一覧を取得 """
lyst = Lyst()
c = Client(lyst)
c.search(keywords=keywords, discount_rate=discount_rate)
data, columns = c.collect()
path = "~/Desktop/%s&%s.collected.csv" % (
c.channel.name,
"+".join(keywords),
)
df_curator = c.to_df(data=data, columns=columns, save=path)
# path = "~/Desktop/Lyst.com&celine+bag.collected.csv"
# df_curator = pd.read_csv(path)
print(df_curator.head())
""" Pt.2 取得先のリテーラーから必要情報を取得 """
data_dict = {}
for index, row in df_curator.iterrows():
try:
retailer_name = exchange_retailer_name(row["retailer"])
if retailer_name in RETAILER_NAMES:
retailer = globals()[retailer_name](row["href"])
c = Client(retailer)
c.search()
data, columns = c.collect()
try:
data_dict[index] = data[0]
except KeyError:
data_dict[index] = [None for c in columns]
except Exception as e:
print("...Exception Occured...", index, row["title"])
print(e.args[0])
data_dict[index] = [None for c in columns]
path = "~/Desktop/%s&%s.retailer.csv" % (
c.channel.name,
"+".join(keywords),
)
df_retailer = c.to_df(data=data_dict, columns=columns, save=path)
""" Pt.3 キュレーターとリテーラーを結合 """
path = "~/Desktop/%s&%s.curator-retailer.csv" % (
c.channel.name,
"+".join(keywords),
)
df2 = pd.concat([df_curator, df_retailer], axis=1)
df2.to_csv(path)
# df2 = pd.read_csv(path)
df2 = df2.dropna()
""" Pt.4 BUYMA で価格チェック """
buymaItems = BuymaItems()
ptn = r".+[^\-A-Z0-9]([\-A-Z0-9]+$)"
active_dict = {}
for index, row in df2.iterrows():
# SKU を検索ワードに設定
sku = re.sub(ptn, r"\1", row["retailer_sku"])
cheapest_price = row["retailer_price"] if any(
row["retailer_price"]
) else "9999999999" # if "通貨" があるので str 型にしておく
cheapest_price = exchange_currency(cheapest_price)
c = Client(buymaItems)
c.search(keywords=[sku])
data, columns = c.collect()
prices = [v for k, values in data.items() for v in values]
active_dict[index] = [
BuymaItems.compare(cheapest_price, prices), cheapest_price
]
path = "~/Desktop/%s&%s.malls.csv" % (
c.channel.name,
"+".join(keywords),
)
mall_df = c.to_df(data=active_dict,
columns=["active", "active_price"],
save=path)
""" Pt.5 リサーチ結果を結合し、1 のものだけをフィルター """
df3 = pd.concat([df2, mall_df], axis=1)
active_df = df3[df3["active"] == 1]
path = "~/Desktop/%s&%s.researched.csv" % (
c.channel.name,
"+".join(keywords),
)
active_df.to_csv(path)
return True
def articture(event, context):
keywords = event["keywords"]
print(f"*** This is articture, {keywords} ***")
""" Pt.1 Articture の検索結果一覧を取得 """
artic = Art()
c = Client(artic)
data_dict = {}
while c.channel.next_page is not None:
c.search(keywords=keywords)
data, columns = c.collect()
data_dict.update(data)
path = "~/Desktop/%s&%s.collected.csv" % (
c.channel.name,
"+".join(keywords),
)
df_curator = c.to_df(data=data_dict, columns=columns, save=path)
# keywords = ["FURLA"]
# path = "~/Desktop/articture.com&light.collected.csv"
# df_curator = pd.read_csv(path)
print(df_curator.head())
""" Pt.2 取得先の href リンク先から必要情報を取得 """
data_dict = {}
for index, row in df_curator.iterrows():
try:
retailer = Articture(row["href"])
c = Client(retailer)
c.search()
data, columns = c.collect()
try:
data_dict[index] = data[0]
except KeyError:
data_dict[index] = [None for c in columns]
except Exception as e:
print("...Exception Occured...", index, row["title"])
print(e.args[0])
data_dict[index] = [None for c in columns]
path = "~/Desktop/%s&%s.retailer.csv" % (
c.channel.name,
"+".join(keywords),
)
df_retailer = c.to_df(data=data_dict, columns=columns, save=path)
""" Pt.3 キュレーターとリテーラーを結合 """
path = "~/Desktop/%s&%s.curator-retailer.csv" % (
c.channel.name,
"+".join(keywords),
)
df2 = pd.concat([df_curator, df_retailer], axis=1)
df2.to_csv(path)
# df2 = pd.read_csv(path)
df2 = df2.dropna()
""" Pt.4 BUYMA で価格チェック（出品がないためスキップ） """
ptn = r".+[^\-A-Z0-9]([\-A-Z0-9]+$)"
active_dict = {}
for index, row in df2.iterrows():
# SKU を検索ワードに設定
# sku = re.sub(ptn, r"\1", row["retailer_sku"])
cheapest_price = row["retailer_price"]
cheapest_price = exchange_currency(cheapest_price)
active_dict[index] = [1, cheapest_price] # 全て アクティブ 1 に設定
path = "~/Desktop/%s&%s.malls.csv" % (
c.channel.name,
"+".join(keywords),
)
mall_df = c.to_df(data=active_dict,
columns=["active", "active_price"],
save=path)
""" Pt.5 リサーチ結果を結合し、1 のものだけをフィルター """
df3 = pd.concat([df2, mall_df], axis=1)
active_df = df3[df3["active"] == 1]
path = "~/Desktop/%s&%s.researched.csv" % (
c.channel.name,
"+".join(keywords),
)
active_df.to_csv(path)
return True
