Welcome to Tubing’s documentation!¶
Tubing is a Python I/O library. What makes tubing so freakin’ cool is the gross abuse of the bit-wise OR operator (|). Have you ever been writing python code and thought to yourself, “Man, this is great, but I really wish it was a little more like bash.” Whelp, we’ve made python a little more like bash.If you are a super lame nerd-kid, you can replace any of the bit-wise ORs with the tube() function and pray we don’t overload any other operators in future versions. Here’s how you install tubing:
$ pip install tubing
Tubing is pretty bare-bones at the moment. We’ve tried to make it easy to add your own functionality. Hopefully you find it not all that unpleasant. There are three sections below for adding sources, tubes and sink. If you do make some additions, think about committing them back upstream. We’d love to have a full suite of tools.
Now, witness the power of this fully operational I/O library.
from tubing import sources, tubes, sinks
objs = [
dict(
name="Bob Corsaro",
birthdate="08/03/1977",
alignment="evil",
),
dict(
name="Tom Brady",
birthdate="08/03/1977",
alignment="good",
),
]
sources.Objects(objs) \
| tubes.JSONDumps() \
| tubes.Joined(by=b"\n") \
| tubes.Gzip() \
| sinks.File("output.gz", "wb")
Then in our old friend bash.
$ zcat output.gz
{"alignment": "evil", "birthdate": "08/03/1977", "name": "Bob Corsaro"}
{"alignment": "good", "birthdate": "08/03/1977", "name": "Tom Brady"}
$
You can find more documentation on readthedocs
Catalog¶
Sources¶
| Objects | Takes a list of python objects. |
| File | Creates a stream from a file. |
| Bytes | Takes a byte string. |
| IO | Takes an object with a read function. |
| Socket | Takes an addr, port and socket() args. . |
| HTTP | Takes an method, url and any args that can be passed to requests library. |
Tubes¶
| Gunzip | Unzips a binary stream. |
| Gzip | Zips a binary stream. |
| JSONLoads | Parses a byte string stream of raw JSON objects. Will try to use ujson, then built-in json. |
| JSONDumps | Serializes an object stream using json.dumps. Will try to use ujson, then built-in json. |
| Split | Splits a stream that supports the split method. |
| Joined | Joins a stream of the same type as the by argument. |
| Tee | Takes a sink and passes chunks along apparatus. |
| Map | Takes a transformer function for single items in stream. |
| Filter | Takes a filter test callback and only forwards items that pass. |
| ChunkMap | Takes a transformer function for batch of stream items. |
Sinks¶
| Objects | A list that stores all passed items to self. |
| Bytes | Saves each chunk self.results. |
| File | Writes each chunk to a file. |
| HTTPPost | Writes data via HTTPPost. |
| Hash | Takes algorithm name, updates hash with contents. |
| Debugger | Writes each chunk to the tubing.tubes debugger with level DEBUG. |
Extensions¶
| s3.S3Source | Create stream from an S3 object. |
| s3.MultipartUploader | Stream data to S3 object. |
| elasticsearch.BulkSink | Stream elasticsearch.DocUpdate objects to the elasticsearch _bulk endpoint. |
Sources¶
To make your own source, create a Reader class with the following interface.
class MyReader(object):
"""
MyReader returns count instances of data.
"""
def __init__(self, data="hello world\n", count=10):
self.data = data
self.count = count
def read(self, amt):
"""
read(amt) returns $amt of data and a boolean indicating EOF.
"""
if not amt:
amt = self.count
r = self.data * min(amt, self.count)
self.count -= amt
return r, self.count <= 0
The important thing to remember is that your read function should return an iterable of units of data, not a single piece of data. Then wrap your reader in the loving embrace of MakeSourceFactory.
from tubing import sources
MySource = sources.MakeSourceFactory(MyReader)
Now it can be used in a apparatus!
from __future__ import print_function
from tubing import tubes
sink = MySource(data="goodbye cruel world!", count=1) \
| tubes.Joined(by=b"\n") \
| sinks.Bytes()
print(sinks.result)
# Output: goodbye cruel world!
Tubes¶
Making your own tube is a lot more fun, trust me. First make a Transformer.
class OptimusPrime(object):
def transform(self, chunk):
return list(reversed(chunk))
chunk is an iterable with a len() of whatever type of data the stream is working with. In Transformers, you don’t need to worry about buffer size or closing or exception, just transform an iterable to another iterable. There are lots of examples in tubes.py.
Next give Optimus Prime a hug.
from tubing import tubes
AllMixedUp = tubes.MakeTranformerTubeFactory(OptimusPrime)
Ready to mix up some data?
from __future__ import print_function
import json
from tubing import sources, sinks
objs = [{"number": i} for i in range(0, 10)]
sink = sources.Objects(objs) \
| AllMixedUp(chunk_size=2) \
| sinks.Objects()
print(json.dumps(sink))
# Output: [{"number": 1}, {"number": 0}, {"number": 3}, {"number": 2}, {"number": 5}, {"number": 4}, {"number": 7}, {"number": 6}, {"number": 9}, {"number": 8}]
Sinks¶
Really getting tired of making documentation... Maybe I’ll finish later. I have real work to do.
Well.. I’m this far, let’s just push through.
from __future__ import print_function
from tubing import sources, tubes, sinks
class StdoutWriter(object):
def write(self, chunk):
for part in chunk:
print(part)
def close(self):
# this function is optional
print("That's all folks!")
def abort(self):
# this is also optional
print("Something terrible has occurred.")
Debugger = sinks.MakeSinkFactory(StdoutWriter)
objs = [{"number": i} for i in range(0, 10)]
sink = sources.Objects(objs) \
| AllMixedUp(chunk_size=2) \
| tubes.JSONDumps() \
| tubes.Joined(by=b"\n") \
| Debugger()
# Output:
#{"number": 1}
#{"number": 0}
#{"number": 3}
#{"number": 2}
#{"number": 5}
#{"number": 4}
#{"number": 7}
#{"number": 6}
#{"number": 9}
#{"number": 8}
#That's all folks!
Table of Contents¶