# 1.6 File Management

### File Input and Output

Open a file.

```python
f = open('foo.txt', 'rt')     # Open for reading (text)
g = open('bar.txt', 'wt')     # Open for writing (text)
```

Reading data.

```python
data = f.read()

# Read only up to 'maxbytes' bytes
data = f.read([maxbytes])
```

Writing text to a file.

```python
g.write('some text')
```

Close when you are done.

```python
f.close()
g.close()
```

Files should be properly closed. This is why the preferred approach is to use the `with` statement.

```python
with open(filename, 'rt') as f:
    # Use the file `f`
    ...
    # No need to close explicitly
...statements
```

This automatically closes the file when control leaves the indented code block.

### Common Idioms for Reading File Data

Reading an entire file all at once as a string.

```python
with open('foo.txt', 'rt') as f:
    data = f.read()
    # `data` is a string with all the text in `foo.txt`
```

Reading a file line-by-line

```python
with open(filename, 'rt') as f:
    for line in f:
        # Process the line `f`
```

Writing string data.

```python
with open('outfile', 'wt') as f:
    f.write('Hello World\n')
    ...
```

Redirecting the print function.

```python
with open('outfile', 'wt') as f:
    print('Hello World', file=f)
    ...
```

## Exercises

This exercise depends on a file `Data/portfolio.csv`.  The file contains a list of lines with information on a portfolio of stocks.
Locate the file and look at its contents:

### Exercise 1.26: File Preliminaries

*Note: Make sure you are running Python in a location where you can access the `portfolio.csv` file.
It's normally located in `Data/portfolio.csv`. 
You can find out where Python thinks it's running by doing this:

```pycon
>>> import os
>>> os.getcwd()
'/Users/beazley/Desktop/practical-python' # Output vary
>>>
```

First, try reading the entire file all at once as a big string:

```pycon
>>> with open('Data/portfolio.csv', 'rt') as f:
        data = f.read()
>>> data
'name,shares,price\n"AA",100,32.20\n"IBM",50,91.10\n"CAT",150,83.44\n"MSFT",200,51.23\n"GE",95,40.37\n"MSFT",50,65.10\n"IBM",100,70.44\n'
>>> print(data)
name,shares,price
"AA",100,32.20
"IBM",50,91.10
"CAT",150,83.44
"MSFT",200,51.23
"GE",95,40.37
"MSFT",50,65.10
"IBM",100,70.44
>>>
```

In the above example, it should be noted that Python has two modes of
output.  In the first mode where you type `data` at the prompt, Python
shows you the raw string representation including quotes and escape
codes.  When you type `print(data)`, you get the actual formatted
output of the string.

Although reading a file all at once is simple, it is often not the
most appropriate way to do it—especially if the file happens to be
huge or if contains lines of text that you want to handle one at a
time.

To read a file line-by-line, use a for-loop like this:

```pycon
>>> with open('Data/portfolio.csv', 'rt') as f:
    for line in f:
        print(line, end='')
name,shares,price
"AA",100,32.20
"IBM",50,91.10
...
>>>
```

When you use this code as shown, lines are read until the end of the
file is reached at which point the loop stops.

On certain occasions, you might want to manually read or skip a
*single* line of text (e.g., perhaps you want to skip the first line
of column headers).

```pycon
>>> f = open('Data/portfolio.csv', 'rt')
>>> headers = next(f)
>>> headers
'name,shares,price\n'
>>> for line in f:
    print(line, end='')

"AA",100,32.20
"IBM",50,91.10
...
>>> f.close()
>>>
```

`next()` returns the next line of text in the file. If you were to call it repeatedly, you would get successive lines. 
However, just so you know, the `for` loop already uses `next()` to obtain its data.
Thus, you normally wouldn’t call it directly unless you’re trying to explicitly skip or read a single line as shown.

Once you’re reading lines of a file, you can start to perform more processing such as splitting.
For example, try this:

```pycon
>>> f = open('Data/portfolio.csv', 'rt')
>>> headers = next(f).split(',')
>>> headers
['name', 'shares', 'price\n']
>>> for line in f:
    row = line.split(',')
    print(row)

['"AA"', '100', '32.20\n']
['"IBM"', '50', '91.10\n']
...
>>> f.close()
```

*Note: In these examples, `f.close()` is being called explicitly because the `with` statement isn’t being used.*

### Exercise 1.27: Reading a data file

Now that you know how to read a file, let’s write a program to perform a simple calculation.

The columns in `portfolio.csv` correspond to the stock name, number of
shares, and purchase price of a single share.  Write a program called
`pcost.py` that opens this file, reads all lines, and calculates how
much it cost to purchase all of the shares in the portfolio.

*Hint: to convert a string to an integer, use `int(s)`. To convert a string to a floating point, use `float(s)`.*

Your program should print output such as the following:

```bash
Total cost 44671.15
```

### Exercise 1.28: Other kinds of 'files'

What if you wanted to read a non-text file such as a gzip-compressed
datafile?  The builtin `open()` function won’t help you here, but
Python has a library module `gzip` that can read gzip compressed
files.

Try it:

```pycon
>>> import gzip
>>> with gzip.open('Data/portfolio.csv.gz') as f:
    for line in f:
        print(line, end='')

... look at the output ...
>>>
```

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