Python读取无表头CSV并将每行数据用于API脚本与正则处理

Hey there! No worries about the initial vague description—we’ve all been there when we’re just starting out with programming. Let’s walk through exactly what you need, with clear, actionable code snippets.

Since your CSV has no headers, we can use Python’s built-in csv module to read each row as a list of values. No fancy mapping needed—just grab each row directly.

Here’s a quick example:

import csv

# Path to your CSV file
csv_file_path = "your_file.csv"

# Open the file and read rows
with open(csv_file_path, mode='r', encoding='utf-8') as file:
    csv_reader = csv.reader(file)
    # Convert reader to a list of rows (each row is a list of strings)
    rows = list(csv_reader)

# Optional: Print first 5 rows to verify the data
for row in rows[:5]:
    print(row)

Next, we’ll wrap your API call in a reusable function, then loop through each CSV row to send the data. We’ll use the requests library for HTTP calls (install it first with pip install requests if you haven’t).

Example code:

import requests

def call_write_api(row_data):
    # Replace with your actual API endpoint
    api_url = "https://your-api-endpoint.com/write"
    
    # Adjust the payload to match what your API expects
    # Since row_data is a list, map values to API fields as needed
    payload = {
        "first_value": row_data[0],
        "second_value": row_data[1],
        # Add more fields based on your CSV columns
    }
    
    try:
        # Send POST request (switch to PUT if your API requires it)
        response = requests.post(api_url, json=payload)
        response.raise_for_status()  # Trigger error for HTTP codes >=400
        print(f"Successfully wrote data: {row_data}")
    except requests.exceptions.RequestException as e:
        print(f"Failed to write data {row_data}: {str(e)}")

# Loop through each row and trigger the API call
for row in rows:
    call_write_api(row)

Now let’s integrate regex to pull specific data from each row before sending it to the API. We’ll use Python’s built-in re module for this.

First, define your regex pattern. For example, if you want to extract a 6-digit ID that comes after "UserID:", your pattern might be r"UserID: (\d{6})".

Here’s how to wire it up:

import re

def extract_target_data(row):
    # Join row into a single string if your target data spans columns, or use a specific column
    row_text = " ".join(row)
    
    # Replace with your actual regex pattern
    regex_pattern = r"your-regex-pattern-here"
    match = re.search(regex_pattern, row_text)
    
    if match:
        # Extract the matched group (adjust index based on your pattern's capture groups)
        extracted_value = match.group(1)
        return extracted_value
    else:
        print(f"No match found in row: {row}")
        return None

# Updated loop: extract data first, then call API with the extracted variable
for row in rows:
    extracted_var = extract_target_data(row)
    if extracted_var:
        # Pass the extracted variable to your API function
        # Adjust the payload in call_write_api to use this variable as needed
        call_write_api([extracted_var])

• Test small first: Don’t run the full loop immediately—test with 2-3 rows to confirm your regex and API calls work as expected.
• Rate limit handling: If your API has rate limits, add a delay between calls with time.sleep(1) (import time first).
• Fix encoding issues: If your CSV has weird characters, try changing the encoding parameter in open() to 'latin-1' or 'utf-8-sig'.

内容的提问来源于stack exchange，提问作者madwheel