csvresumable 0.0.3

adding tiny resume function, for csv reading iterator

# cssresumable

Adding tiny resume function for your csv reading iterator.

## examples

00main.py

```python
import sys
import os
import random
from io import StringIO
from csvresumable import DictReader

data = """\
id,name
1,foo
2,bar
3,boo
"""

random.seed(int(os.environ.get("SEED", "0")))
for row in DictReader(StringIO(data)):
n = random.random()
if n < 0.5:
print("fail {}".format(n), file=sys.stderr)
sys.exit(0)
print("\t", row["name"])
print("finished")

```

resuming until success.

```console
SEED=0 python 00main.py
fail 0.420571580830845
foo
bar
SEED=1 RESUME=1 python 00main.py
fail 0.13436424411240122
SEED=2 RESUME=1 python 00main.py
boo
finished
SEED=5 python 00main.py
foo
bar
boo
finished

```

or setting with `resume` option (run this script, such as `python 01main.py --resume`)

```diff
--- 00main.py 2018-06-16 04:19:51.573578443 +0900
+++ 01main.py 2018-06-16 04:20:04.760554103 +0900
@@ -4,17 +4,23 @@
from io import StringIO
from csvresumable import DictReader

-data = """\
+data = """
id,name
1,foo
2,bar
3,boo
"""

+import argparse
+parser = argparse.ArgumentParser()
+parser.add_argument("--seed", default=0, type=int)
+parser.add_argument("--resume", action="store_true")
+args = parser.parse_args()
+
random.seed(int(os.environ.get("SEED", "0")))
-for row in DictReader(StringIO(data)):
+for row in DictReader(StringIO(data), resume=args.resume):
n = random.random()
- if n < 0.5:
+ if n > 0.8:
print("fail {}".format(n), file=sys.stderr)
sys.exit(0)
print("\t", row["name"])

```

### with multi files

```python
from csvresumable import DictReader

files = ["a.csv", "b.csv"]
for f in files:
r = DictReader(f)
for row in r:
do_something(row)

```

## more

- [examples/01multisource](examples/01multisource)