gspread-sheets#

Prerequisites#

bash

pip install gspread google-auth

Service account JSON key file required. Set path via:

• Environment variable: export GOOGLE_SERVICE_ACCOUNT_JSON=/path/to/key.json
• Or pass explicitly in scripts

Share the target spreadsheet with the service account email (found in the JSON key file).

Quick Start#

Initialize Client#

python

import gspread
from google.oauth2.service_account import Credentials

SCOPES = ['https://www.googleapis.com/auth/spreadsheets',
          'https://www.googleapis.com/auth/drive']

# Option 1: From JSON file path
creds = Credentials.from_service_account_file('key.json', scopes=SCOPES)
gc = gspread.authorize(creds)

# Option 2: From JSON string (e.g. env var)
import json, os
creds_info = json.loads(os.environ['GOOGLE_SERVICE_ACCOUNT_JSON'])
creds = Credentials.from_service_account_info(creds_info, scopes=SCOPES)
gc = gspread.authorize(creds)

Open Spreadsheet#

python

# By name
sh = gc.open("My Spreadsheet")

# By URL
sh = gc.open_by_url("https://docs.google.com/spreadsheets/d/SPREADSHEET_ID/edit")

# By key
sh = gc.open_by_key("SPREADSHEET_ID")

Core Operations#

Read Data#

python

ws = sh.sheet1  # or sh.worksheet("Sheet Name")

# All values as list of lists
data = ws.get_all_values()

# All records (first row = headers)
records = ws.get_all_records()

# Specific range
subset = ws.get("A1:D10")

# Single cell
val = ws.acell("B2").value
val = ws.cell(row=2, col=2).value

# Column or row as list
col_a = ws.col_values(1)
row_1 = ws.row_values(1)

Write Data (Batch)#

python

# Update a range (list of lists)
ws.update("A1:D3", [["a1","b1","c1","d1"],
                      ["a2","b2","c2","d2"],
                      ["a3","b3","c3","d3"]])

# Append rows (at the bottom)
ws.append_rows([["new1","row1"],["new2","row2"]])

# Append single row
ws.append_row(["val1","val2","val3"])

# Batch update multiple ranges at once (most efficient)
ws.batch_update([
    {"range": "A1:B2", "values": [["a","b"],["c","d"]]},
    {"range": "D1:E2", "values": [["x","y"],["z","w"]]},
])

Cell-Level Batch Update#

python

# Update specific cells by row/col
cell_list = ws.range("A1:C2")
for i, cell in enumerate(cell_list):
    cell.value = f"data_{i}"
ws.update_cells(cell_list)

Clear & Format#

python

# Clear specific range
ws.clear()

# Clear range
ws.batch_clear(["A1:D10", "F1:G5"])

# Format cells
ws.format("A1:D1", {"textFormat": {"bold": True}})

Worksheet Management#

python

# List all worksheets
worksheets = sh.worksheets()

# Add worksheet
new_ws = sh.add_worksheet(title="New Sheet", rows=100, cols=20)

# Delete worksheet
sh.del_worksheet(ws)

# Rename
ws.update_title("New Name")

# Duplicate
ws.duplicate(new_sheet_name="Copy")

Find & Replace#

python

# Find all matches
cells = ws.findall("search_term")

# Find with regex
import re
cells = ws.findall(re.compile(r"^prefix_.*"))

# Replace all
ws.replace("old_value", "new_value")

Batch Operation Patterns#

Pattern 1: Read-Modify-Write#

python

data = ws.get_all_records()  # list of dicts
for row in data:
    row["status"] = "processed"
# Write back (need headers + data as list of lists)
header = list(data[0].keys())
rows = [list(r.values()) for r in data]
ws.update("A1", [header] + rows)

Pattern 2: Efficient Large Upload (>1000 rows)#

python

import math
BATCH_SIZE = 1000
for i in range(0, len(all_rows), BATCH_SIZE):
    batch = all_rows[i:i+BATCH_SIZE]
    ws.append_rows(batch, value_input_option="USER_ENTERED")

Pattern 3: Multi-Sheet Batch Sync#

python

for ws_name in ["Sheet1", "Sheet2", "Sheet3"]:
    ws = sh.worksheet(ws_name)
    records = ws.get_all_records()
    # process...
    ws.batch_update(processed_ranges)

Pattern 4: Conditional Formatting#

python

ws.add_conditional_formatting("A1:A100", {
    "type": "NUMBER_GREATER",
    "value": 100,
    "format": {"backgroundColor": {"red": 0.8, "green": 0.2, "blue": 0.2}}
})

Error Handling#

python

import gspread
from gspread.exceptions import APIError, WorksheetNotFound

try:
    ws = sh.worksheet("NonExistent")
except WorksheetNotFound:
    ws = sh.add_worksheet("NonExistent", rows=100, cols=20)

# Rate limit handling
import time
from gspread.exceptions import APIError

def safe_batch_update(ws, data, retries=3):
    for attempt in range(retries):
        try:
            return ws.batch_update(data)
        except APIError as e:
            if "429" in str(e) and attempt < retries - 1:
                time.sleep(2 ** attempt)
            else:
                raise

Tips#

• Use batch_update over multiple update calls — fewer API requests
• value_input_option="USER_ENTERED" parses formulas and number formats
• value_input_option="RAW" writes literal strings
• Default include_empty=False in get_all_values omits trailing empty cells
• Service account has its own Drive; share sheets with its email to access
• For shared drives, use gc.open_by_key() (more reliable than name)