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import os
import json
import pandas as pd
import re
def find_json_files(directory):
json_files = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith(".json"):
json_files.append(os.path.join(root, file))
return json_files
def clean_and_convert_data(json_data):
if "text" in json_data:
json_data["text"] = re.sub(r'[^\x00-\x7F]+', ' ', json_data["text"])
int_fields = ["minkilled", "mincaptured", "minleaderskilled", "minfacilitatorskilled", "minleaderscaptured", "minfacilitatorscaptured"]
bool_fields = ["killq", "captureq", "killcaptureraid", "airstrike", "noshotsfired", "dataprocessed", "flagged", "glossarymeta", "leaderq"]
for field in int_fields:
if field in json_data:
json_data[field] = int(json_data[field])
for field in bool_fields:
if field in json_data:
json_data[field] = json_data[field].lower() == "true"
return json_data
def load_json_to_dataframe(json_files):
data = []
skipped_files = []
for file in json_files:
try:
with open(file, "r") as f:
json_data = json.load(f)
json_data = clean_and_convert_data(json_data)
data.append(json_data)
except json.JSONDecodeError as e:
print(f"Skipping file {file} due to JSON decoding error: {str(e)}")
skipped_files.append(file)
return pd.DataFrame(data), skipped_files
def main():
# Directory containing the JSON files
directory = "../original_json_data"
# Find all JSON files recursively within the directory
json_files = find_json_files(directory)
# Load the contents of JSON files into a pandas DataFrame
df, skipped_files = load_json_to_dataframe(json_files)
# Export the DataFrame as a Parquet file
output_file = "../exported_press_releases_2024.parquet"
df.to_parquet(output_file)
print(f"Successfully exported {len(json_files) - len(skipped_files)} JSON files to {output_file}")
if skipped_files:
print(f"Skipped {len(skipped_files)} files due to JSON decoding errors.")
print("Skipped files:")
for file in skipped_files:
print(file)
if __name__ == "__main__":
main()
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