# The # symbol starts a comment — Python ignores it
# Comments are notes to yourself (and me)

company_name = "Vestas Wind Systems"   # a string (text)
employee_count = 400                    # an integer (whole number)
is_public = True                        # a boolean (True or False)

print(company_name)      # prints: Vestas Wind Systems
print(employee_count)    # prints: 400
print(is_public)         # prints: True

name = "Vestas"
employees = 400

# Without f-string — awkward
print("Company: " + name + ", Size: " + str(employees))

# With f-string — clean
print(f"Company: {name}, Size: {employees}")
# Both print: Company: Vestas, Size: 400

employees = 650

if employees > 500:
    print("Large company")     # runs if True
elif employees > 200:
    print("Mid-size company")  # runs if first was False
else:
    print("Smaller company")   # runs if all above False

# Prints: Large company

# A list — square brackets, comma-separated
clients = ["Vestas", "Ørsted", "Grundfos"]

# A for loop — runs once for each item
for client in clients:
    print(f"Processing: {client}")

# Prints:
# Processing: Vestas
# Processing: Ørsted
# Processing: Grundfos

# Access a specific item by index (starts at 0)
print(clients[0])   # Vestas
print(clients[2])   # Grundfos

# Define the function — this does NOT run it yet
def format_client(name, industry, size):
    summary = f"{name} | {industry} | {size} employees"
    return summary

# Call the function — this runs it
result = format_client("Vestas", "Energy", 400)
print(result)
# Prints: Vestas | Energy | 400 employees

# Call it again with different data
result2 = format_client("Ørsted", "Renewable energy", 800)
print(result2)

# open() accesses the file. "r" means read-only.
# The 'with' block ensures the file is closed when done.

with open("notes.txt", "r") as f:
    contents = f.read()

print(contents)   # prints the full file

# Reading line by line
with open("notes.txt", "r") as f:
    for line in f:
        print(line.strip())   # .strip() removes newlines

import csv   # import the csv module (built in, no install needed)

with open("clients.csv", "r") as f:
    reader = csv.DictReader(f)   # reads each row as a dictionary
    for row in reader:
        name = row["Name"]
        industry = row["Industry"]
        employees = row["Employees"]
        print(f"{name} — {industry} — {employees} staff")

# Create a dictionary with curly braces
client = {
    "name": "Vestas Wind Systems",
    "industry": "Energy",
    "employees": 400,
    "is_public": True
}

# Access values by key
print(client["name"])       # Vestas Wind Systems
print(client["employees"])  # 400

# Add or update a value
client["country"] = "Denmark"

# A list of dictionaries — one per client
all_clients = [
    {"name": "Vestas", "employees": 400},
    {"name": "Ørsted", "employees": 800}
]

for c in all_clients:
    print(c["name"])

import json

# A Python dictionary
data = {"name": "Vestas", "employees": 400}

# Convert to JSON string (for sending/storing)
json_string = json.dumps(data)
print(json_string)  # {"name": "Vestas", "employees": 400}

# Convert JSON string back to Python dictionary
back_to_dict = json.loads(json_string)
print(back_to_dict["name"])  # Vestas

# Without error handling — crashes if file missing
with open("clients.csv") as f:
    data = f.read()

# With error handling — fails gracefully
try:
    with open("clients.csv") as f:
        data = f.read()
    print("File read successfully")
except FileNotFoundError:
    print("Error: clients.csv not found — check the file path")

Traceback (most recent call last):
  File "summariser.py", line 12, in <module>
    result = format_client(row)
  File "summariser.py", line 6, in format_client
    summary = f"{row["name"]} | {row["industry"]}"
KeyError: 'name'