azure-datalake-store 0.0.1

Convenient Filesystem interface to Azure Data-lake Store

azure-datalake-store is a file-system management system in python for the Azure Data-Lake Store.

To install from source instead of pip (for local testing and development):

> pip install -r dev_requirements.txt
> python setup.py develop

To run tests, you are required to set the following environment variables: azure_tenant_id, azure_username, azure_password, azure_data_lake_store_name

To play with the code, here is a starting point:

from azure.datalake.store import core, lib, multithread
token = lib.auth(tenant_id, username, password)
adl = core.AzureDLFileSystem(store_name, token)

# typical operations
adl.ls('')
adl.ls('tmp/', detail=True)
adl.cat('littlefile')
adl.head('gdelt20150827.csv')

# file-like object
with adl.open('gdelt20150827.csv', blocksize=2**20) as f:
    print(f.readline())
    print(f.readline())
    print(f.readline())
    # could have passed f to any function requiring a file object:
    # pandas.read_csv(f)

with adl.open('anewfile', 'wb') as f:
    # data is written on flush/close, or when buffer is bigger than
    # blocksize
    f.write(b'important data')

adl.du('anewfile')

# recursively download the whole directory tree with 5 threads and
# 16MB chunks
multithread.ADLDownloader(adl, "", 'my_temp_dir', 5, 2**24)

To interact with the API at a higher-level, you can use the provided command-line interface in “azure/datalake/store/cli.py”. You will need to set the appropriate environment variables as described above to connect to the Azure Data Lake Store.

To start the CLI in interactive mode, run “python azure/datalake/store/cli.py” and then type “help” to see all available commands (similiar to Unix utilities):

> python azure/datalake/store/cli.py
azure> help

Documented commands (type help <topic>):
========================================
cat    chmod  close  du      get   help  ls     mv   quit  rmdir  touch
chgrp  chown  df     exists  head  info  mkdir  put  rm    tail

azure>

While still in interactive mode, you can run “ls -l” to list the entries in the home directory (“help ls” will show the command’s usage details). If you’re not familiar with the Unix/Linux “ls” command, the columns represent 1) permissions, 2) file owner, 3) file group, 4) file size, 5-7) file’s modification time, and 8) file name.

> python azure/datalake/store/cli.py
azure> ls -l
drwxrwx--- 0123abcd 0123abcd         0 Aug 02 12:44 azure1
-rwxrwx--- 0123abcd 0123abcd   1048576 Jul 25 18:33 abc.csv
-r-xr-xr-x 0123abcd 0123abcd        36 Jul 22 18:32 xyz.csv
drwxrwx--- 0123abcd 0123abcd         0 Aug 03 13:46 tmp
azure> ls -l --human-readable
drwxrwx--- 0123abcd 0123abcd   0B Aug 02 12:44 azure1
-rwxrwx--- 0123abcd 0123abcd   1M Jul 25 18:33 abc.csv
-r-xr-xr-x 0123abcd 0123abcd  36B Jul 22 18:32 xyz.csv
drwxrwx--- 0123abcd 0123abcd   0B Aug 03 13:46 tmp
azure>

To download a remote file, run “get remote-file [local-file]”. The second argument, “local-file”, is optional. If not provided, the local file will be named after the remote file minus the directory path.

> python azure/datalake/store/cli.py
azure> ls -l
drwxrwx--- 0123abcd 0123abcd         0 Aug 02 12:44 azure1
-rwxrwx--- 0123abcd 0123abcd   1048576 Jul 25 18:33 abc.csv
-r-xr-xr-x 0123abcd 0123abcd        36 Jul 22 18:32 xyz.csv
drwxrwx--- 0123abcd 0123abcd         0 Aug 03 13:46 tmp
azure> get xyz.csv
2016-08-04 18:57:48,603 - ADLFS - DEBUG - Creating empty file xyz.csv
2016-08-04 18:57:48,604 - ADLFS - DEBUG - Fetch: xyz.csv, 0-36
2016-08-04 18:57:49,726 - ADLFS - DEBUG - Downloaded to xyz.csv, byte offset 0
2016-08-04 18:57:49,734 - ADLFS - DEBUG - File downloaded (xyz.csv -> xyz.csv)
azure>

It is also possible to run in command-line mode, allowing any available command to be executed separately without remaining in the interpreter.

For example, listing the entries in the home directory:

> python azure/datalake/store/cli.py ls -l
drwxrwx--- 0123abcd 0123abcd         0 Aug 02 12:44 azure1
-rwxrwx--- 0123abcd 0123abcd   1048576 Jul 25 18:33 abc.csv
-r-xr-xr-x 0123abcd 0123abcd        36 Jul 22 18:32 xyz.csv
drwxrwx--- 0123abcd 0123abcd         0 Aug 03 13:46 tmp
>

Also, downloading a remote file:

> python azure/datalake/store/cli.py get xyz.csv
2016-08-04 18:57:48,603 - ADLFS - DEBUG - Creating empty file xyz.csv
2016-08-04 18:57:48,604 - ADLFS - DEBUG - Fetch: xyz.csv, 0-36
2016-08-04 18:57:49,726 - ADLFS - DEBUG - Downloaded to xyz.csv, byte offset 0
2016-08-04 18:57:49,734 - ADLFS - DEBUG - File downloaded (xyz.csv -> xyz.csv)
>