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import csv
import os
from collections import Counter
from itertools import islice
import sys
sys.path.append('..')
from core import build
youtube = build.build_youtube()
def batch(iterable, size):
"""
Split an iterable into chunks of specified size.
"""
it = iter(iterable)
while True:
chunk = list(islice(it, size))
if not chunk:
break
yield chunk
def get_channel_info_batch(video_ids):
"""
Batch retrieve channel IDs and names using video IDs.
"""
channel_info = []
try:
response = (
youtube.videos()
.list(part="snippet", id=",".join(video_ids))
.execute()
)
for item in response.get("items", []):
snippet = item["snippet"]
channel_info.append((snippet["channelId"], snippet["channelTitle"]))
except Exception as e:
print(f"Error fetching data for video_ids {video_ids}: {e}")
return channel_info
def process_single_csv(input_file):
"""
Process a single CSV file to:
1. Extract video IDs
2. Query YouTube API for channel info
3. Count channel occurrences
4. Return sorted results
"""
video_ids = []
with open(input_file, "r", encoding="utf-8") as infile:
reader = csv.DictReader(infile)
for row in reader:
video_ids.append(row["video_id"]) # Assuming CSV has video_id column
# Batch process channel info
channel_counter = Counter()
channel_details = {}
for video_batch in batch(video_ids, 50): # Process 50 video IDs per batch
channel_info_batch = get_channel_info_batch(video_batch)
for channel_id, channel_title in channel_info_batch:
channel_counter[channel_id] += 1
channel_details[channel_id] = channel_title
# Sort by occurrence count
sorted_channels = channel_counter.most_common()
return sorted_channels, channel_details
def process_folder(folder_path, output_file):
"""
Process all CSV files in a folder to:
1. Aggregate video IDs
2. Collect channel statistics
3. Merge results
4. Output sorted results to CSV
"""
all_channel_counter = Counter()
all_channel_details = {}
# Process each CSV file in folder
for filename in os.listdir(folder_path):
if filename.endswith(".csv"):
input_file = os.path.join(folder_path, filename)
print(f"Processing file: {input_file}")
# Process individual CSV
sorted_channels, channel_details = process_single_csv(input_file)
# Aggregate results
for channel_id, count in sorted_channels:
all_channel_counter[channel_id] += count
all_channel_details.update(channel_details)
# Write final results to CSV
with open(output_file, "w", encoding="utf-8", newline="") as outfile:
writer = csv.writer(outfile, quotechar='"', quoting=csv.QUOTE_ALL)
writer.writerow(["channel_id", "channel_name", "count"])
for channel_id, count in all_channel_counter.most_common():
writer.writerow(
[channel_id, all_channel_details[channel_id], count]
)
# Example execution
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"-i",
"--input-dir",
help="Path to folder containing CSV files",
required=True,
)
parser.add_argument(
"-o",
"--output-csv",
help="Output CSV file path",
default="output.csv",
)
args = parser.parse_args()
folder_path = args.input_dir # CSV files directory
output_csv = args.output_csv # Output file path
process_folder(folder_path, output_csv) |