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Merged
gland78 merged 2 commits into from
Mar 13, 2025
Merged

fix_data_format #29

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3fa0eed
fix_data_format
gland78 Mar 13, 2025
0f91dd3
Automated format fixes
actions-user Mar 13, 2025
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33 changes: 23 additions & 10 deletions airflow/dags/Bugs_DAG.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import csv
import io
import json
from datetime import datetime, timedelta

Expand Down Expand Up @@ -53,24 +54,36 @@ def fetch_bugs_chart():
def convert_json_to_csv(**kwargs):
ti = kwargs["ti"]
data = ti.xcom_pull(task_ids="fetch_bugs_chart")
csv_data = [["rank", "title", "artist",
"lastPos", "peakPos", "image", "genre"]]

output = io.StringIO()
writer = csv.writer(
output, quoting=csv.QUOTE_ALL
) # ✅ 모든 필드를 자동으로 따옴표 처리

# 헤더 추가
writer.writerow(["rank", "title", "artist", "lastPos",
"peakPos", "image", "genre"])

# 데이터 추가
for entry in data["entries"]:
csv_data.append(
genres = json.dumps(
entry["genres"], ensure_ascii=False
) # 리스트를 문자열로 변환
# 이중 따옴표가 포함되면 한번만 보이도록 처리
genres = genres.replace('""', '"') # 이중 따옴표를 하나로 바꿈
writer.writerow(
[
entry["rank"],
entry["title"],
entry["artist"],
entry["lastPos"],
entry["peakPos"],
entry["image"],
json.dumps(
entry["genres"], ensure_ascii=False
), # ✅ 리스트를 문자열로 변환하여 저장
genres,
]
)
csv_string = "\n".join(",".join(map(str, row)) for row in csv_data)
return csv_string

return output.getvalue()


# 3. 로컬에 CSV 저장 (테스트용, 삭제 용이하도록 별도 함수)
Expand All @@ -83,7 +96,7 @@ def save_csv_locally(csv_string):
def upload_to_s3(**kwargs):
ti = kwargs["ti"]
csv_string = ti.xcom_pull(task_ids="convert_json_to_csv")
# save_csv_locally(csv_string) # 테스트용 로컬 저장
save_csv_locally(csv_string) # 테스트용 로컬 저장
s3_hook = S3Hook(aws_conn_id="S4tify_S3")
s3_hook.load_string(
csv_string,
Expand All @@ -106,7 +119,7 @@ def upload_to_s3(**kwargs):
"bugs_chart_dag",
default_args=default_args,
schedule_interval="10 0 * * *", # 매일 00:10 실행
catchup=False,
catchup=True,
) as dag:

get_spotify_token_task = PythonOperator(
Expand Down
41 changes: 30 additions & 11 deletions airflow/dags/Flo_DAG.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import csv
import io
import json
from datetime import datetime, timedelta

Expand Down Expand Up @@ -26,10 +27,12 @@ def fetch_flo_chart():
chart = ChartData(fetch=True)
chart_data = {"date": chart.date.strftime(
"%Y-%m-%d %H:%M:%S"), "entries": []}

for entry in chart.entries:
print(f"📊 차트 데이터 처리: {entry.rank}. {entry.title} - {entry.artist}")
artist_id = search_artist_id(entry.artist)
genre = get_artist_genre(artist_id)

chart_data["entries"].append(
{
"rank": entry.rank,
Expand All @@ -41,42 +44,58 @@ def fetch_flo_chart():
"genres": genre.split(", ") if genre else [],
}
)

return chart_data


# 2. JSON → CSV 변환
# 2. JSON → CSV 변환 (쉼표 포함된 데이터도 깨지지 않도록 수정)
def convert_json_to_csv(**kwargs):
ti = kwargs["ti"]
data = ti.xcom_pull(task_ids="fetch_flo_chart")
csv_data = [["rank", "title", "artist",
"lastPos", "isNew", "image", "genre"]]

output = io.StringIO()
writer = csv.writer(
output, quoting=csv.QUOTE_ALL
) # ✅ 모든 필드를 자동으로 따옴표 처리

# 헤더 추가
writer.writerow(["rank", "title", "artist",
"lastPos", "isNew", "image", "genre"])

# 데이터 추가
for entry in data["entries"]:
csv_data.append(
genres = json.dumps(
entry["genres"], ensure_ascii=False
) # 리스트를 문자열로 변환
# 이중 따옴표가 포함되면 한번만 보이도록 처리
genres = genres.replace('""', '"') # 이중 따옴표를 하나로 바꿈
writer.writerow(
[
entry["rank"],
entry["title"],
entry["artist"],
entry["lastPos"],
entry["isNew"],
entry["image"],
json.dumps(entry["genres"], ensure_ascii=False),
genres,
]
)
csv_string = "\n".join(",".join(map(str, row)) for row in csv_data)
return csv_string

return output.getvalue()

# 3. 로컬에 CSV 저장 (테스트용)

# 3. 로컬에 CSV 저장 (테스트용, 삭제 용이하도록 별도 함수)
def save_csv_locally(csv_string):
with open(LOCAL_FILE_PATH, "w", encoding="utf-8") as f:
f.write(csv_string)


# 4. AWS S3 업로드
# 3. AWS S3 업로드
def upload_to_s3(**kwargs):
ti = kwargs["ti"]
csv_string = ti.xcom_pull(task_ids="convert_json_to_csv")
# save_csv_locally(csv_string) # 테스트용 로컬 저장
save_csv_locally(csv_string) # 테스트용 로컬 저장

s3_hook = S3Hook(aws_conn_id="S4tify_S3")
s3_hook.load_string(
csv_string,
Expand All @@ -99,7 +118,7 @@ def upload_to_s3(**kwargs):
"flo_chart_dag",
default_args=default_args,
schedule_interval="20 0 * * *", # 매일 00:20 실행
catchup=False,
catchup=True,
) as dag:

get_spotify_token_task = PythonOperator(
Expand Down
41 changes: 30 additions & 11 deletions airflow/dags/Genie_DAG.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import csv
import io
import json
from datetime import datetime, timedelta

Expand Down Expand Up @@ -26,10 +27,12 @@ def fetch_genie_chart():
chart = ChartData(chartPeriod=GenieChartPeriod.Realtime, fetch=True)
chart_data = {"date": chart.date.strftime(
"%Y-%m-%d %H:%M:%S"), "entries": []}

for entry in chart.entries:
print(f"📊 차트 데이터 처리: {entry.rank}. {entry.title} - {entry.artist}")
artist_id = search_artist_id(entry.artist)
genre = get_artist_genre(artist_id)

chart_data["entries"].append(
{
"rank": entry.rank,
Expand All @@ -41,42 +44,58 @@ def fetch_genie_chart():
"genres": genre.split(", ") if genre else [],
}
)

return chart_data


# 2. JSON → CSV 변환
# 2. JSON → CSV 변환 (쉼표 포함된 데이터도 깨지지 않도록 수정)
def convert_json_to_csv(**kwargs):
ti = kwargs["ti"]
data = ti.xcom_pull(task_ids="fetch_genie_chart")
csv_data = [["rank", "title", "artist",
"peakPos", "lastPos", "image", "genre"]]

output = io.StringIO()
writer = csv.writer(
output, quoting=csv.QUOTE_ALL
) # ✅ 모든 필드를 자동으로 따옴표 처리

# 헤더 추가
writer.writerow(["rank", "title", "artist", "peakPos",
"lastPos", "image", "genre"])

# 데이터 추가
for entry in data["entries"]:
csv_data.append(
genres = json.dumps(
entry["genres"], ensure_ascii=False
) # 리스트를 문자열로 변환
# 이중 따옴표가 포함되면 한번만 보이도록 처리
genres = genres.replace('""', '"') # 이중 따옴표를 하나로 바꿈
writer.writerow(
[
entry["rank"],
entry["title"],
entry["artist"],
entry["peakPos"],
entry["lastPos"],
entry["image"],
json.dumps(entry["genres"], ensure_ascii=False),
genres,
]
)
csv_string = "\n".join(",".join(map(str, row)) for row in csv_data)
return csv_string

return output.getvalue()

# 3. 로컬에 CSV 저장 (테스트용)

# 3. 로컬에 CSV 저장 (테스트용, 삭제 용이하도록 별도 함수)
def save_csv_locally(csv_string):
with open(LOCAL_FILE_PATH, "w", encoding="utf-8") as f:
f.write(csv_string)


# 4. AWS S3 업로드
# 3. AWS S3 업로드
def upload_to_s3(**kwargs):
ti = kwargs["ti"]
csv_string = ti.xcom_pull(task_ids="convert_json_to_csv")
# save_csv_locally(csv_string) # 테스트용 로컬 저장
save_csv_locally(csv_string) # 테스트용 로컬 저장

s3_hook = S3Hook(aws_conn_id="S4tify_S3")
s3_hook.load_string(
csv_string,
Expand All @@ -99,7 +118,7 @@ def upload_to_s3(**kwargs):
"genie_chart_dag",
default_args=default_args,
schedule_interval="30 0 * * *", # 매일 00:30 실행
catchup=False,
catchup=True,
) as dag:

get_spotify_token_task = PythonOperator(
Expand Down
37 changes: 28 additions & 9 deletions airflow/dags/Melon_DAG.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import csv
import io
import json
from datetime import datetime, timedelta

Expand Down Expand Up @@ -26,10 +27,12 @@ def fetch_melon_chart():
chart = ChartData(fetch=True)
chart_data = {"date": chart.date.strftime(
"%Y-%m-%d %H:%M:%S"), "entries": []}

for entry in chart.entries:
print(f"📊 차트 데이터 처리: {entry.rank}. {entry.title} - {entry.artist}")
artist_id = search_artist_id(entry.artist)
genre = get_artist_genre(artist_id)

chart_data["entries"].append(
{
"rank": entry.rank,
Expand All @@ -48,25 +51,40 @@ def fetch_melon_chart():
def convert_json_to_csv(**kwargs):
ti = kwargs["ti"]
data = ti.xcom_pull(task_ids="fetch_melon_chart")
csv_data = [["rank", "title", "artist",
"lastPos", "isNew", "image", "genre"]]

output = io.StringIO()
writer = csv.writer(
output, quoting=csv.QUOTE_ALL
) # ✅ 모든 필드를 자동으로 따옴표 처리

# 헤더 추가
writer.writerow(["rank", "title", "artist",
"lastPos", "isNew", "image", "genre"])

# 데이터 추가
for entry in data["entries"]:
csv_data.append(
genres = json.dumps(
entry["genres"], ensure_ascii=False
) # 리스트를 문자열로 변환
# 이중 따옴표가 포함되면 한번만 보이도록 처리
genres = genres.replace('""', '"') # 이중 따옴표를 하나로 바꿈

writer.writerow(
[
entry["rank"],
entry["title"],
entry["artist"],
entry["lastPos"],
entry["isNew"],
entry["image"],
json.dumps(entry["genres"], ensure_ascii=False),
genres,
]
)
csv_string = "\n".join(",".join(map(str, row)) for row in csv_data)
return csv_string

return output.getvalue()

# 3. 로컬에 CSV 저장 (테스트용)

# 3. 로컬에 CSV 저장 (테스트용, 삭제 용이하도록 별도 함수)
def save_csv_locally(csv_string):
with open(LOCAL_FILE_PATH, "w", encoding="utf-8") as f:
f.write(csv_string)
Expand All @@ -76,7 +94,8 @@ def save_csv_locally(csv_string):
def upload_to_s3(**kwargs):
ti = kwargs["ti"]
csv_string = ti.xcom_pull(task_ids="convert_json_to_csv")
# save_csv_locally(csv_string) # 테스트용 로컬 저장
save_csv_locally(csv_string) # 테스트용 로컬 저장

s3_hook = S3Hook(aws_conn_id="S4tify_S3")
s3_hook.load_string(
csv_string,
Expand All @@ -99,7 +118,7 @@ def upload_to_s3(**kwargs):
"melon_chart_dag",
default_args=default_args,
schedule_interval="0 1 * * *", # 매일 01:00 실행
catchup=False,
catchup=True,
) as dag:

get_spotify_token_task = PythonOperator(
Expand Down
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