AttributeError: module ‘paramiko’ has no attribute ‘SSHClient’

I have a simple Python 3 script (I’m running Python 3.6.1, compiled from source) that does the following 3 things:

  1. Connects to remote server(s) and using scp to get files
  2. Processes the files.
  3. Connects to another remote server and uploads the processed files.

I moved this script from a soon-to-be-retired CentOS 6 host to a CentOS 7 host, and when I ran it there I received the following error message:

AttributeError: module 'paramiko' has no attribute 'SSHClient'

The line number specified in the stack trace led me to:

ssh = paramiko.SSHClient()

First things first: Google the error. Someone else has seen this before. Sure enough, on StackOverflow I found Paramiko: Module object has no attribute error ‘SSHClient’

But no, that’s not the problem I’m having.

I tried to create the the simplest possible script that would reproduce the error:


import paramiko

def main():
        ssh = paramiko.SSHClient()

if __name__ == "__main__":

I ran it as a super-user and received no errors:

$ sudo /usr/bin/python3

I ran it as myself, though, and it reproduced the error message. Maybe something with the user permissions?

$ ls -l /usr/local/lib/python3.6/site-packages/
total 1168
drwxr-x---.  3 root root   4096 May 29 14:25 paramiko

Oh! From that you can see that unless you are the root user, or a member of the root group, there’s no way you can even see the files within the paramiko directory.

What’s the default umask on the system?

$ umask

That explains it. Now, to fix it. I could probably just run:

$ sudo chmod -R 0755 /usr/local/lib/python3.6/site-packages/*

That should have been the end of that, problem solved! But in my case, installation of the pip modules had been handled by Ansible. I needed to fix the Ansible tasks to account for restrictive umask settings on future deployments. See the umask parameter in the documentation for the Ansible pip module. I updated the task:

- name: Install specified python requirements
    executable: /usr/local/bin/pip3
    requirements: /tmp/pip3-packages
    umask: 0022

Running the playbook with that task, I received an error:

fatal: []: FAILED! => {"changed": false, "details": "invalid literal for int() with base 8: '18'", "msg": "umask must be an octal integer"}

Another helpful StackOverflow post suggested the value needed to be in quotes:

- name: Install specified python requirements
    executable: /usr/local/bin/pip3
    requirements: /tmp/pip3-packages
    umask: "0022"

Now the playbook runs without error, but it doesn’t change the existing permissions. The task does nothing, since the Python pip modules are already installed. To really test the playbook, I need to clear out the existing modules first.

Warning: this breaks things!:

$ sudo rm -rf /usr/local/lib/python3.6/site-packages/*

I tried running the playbook again and received this error message:

stderr: Traceback (most recent call last):\n  File "/usr/local/bin/pip3", line 7, in <module>\n    from pip import main\nModuleNotFoundError: No module named 'pip'\n

I wasn’t able to run pip at all:

$ pip3
Traceback (most recent call last):
  File "/usr/local/bin/pip3", line 7, in <module>
    from pip import main
ModuleNotFoundError: No module named 'pip'

Clearly, I had deleted something important! I reinstalled Python from the gzipped source tarball for Python 3.6.1 (newer versions available from Python source releases) and then everything worked as expected.

Python Flask and VirtualBox networking

I had been using the Python socket module to create a very basic client-server for testing purposes, but soon I wanted to have something slightly more standard, like an HTTP server. I decided to try the Python Flask framework.

First I set up a Flask server on a CentOS 7 Linux VM running on VirtualBox:

# yum install python-pip
# pip install Flask
# mkdir flask-server && cd flask-server

I created the file as described on the Flask homepage:

from flask import Flask
app = Flask(__name__)

def hello():
    return "Hello World!"

Likewise, I started running Flask:

# flask run
 * Serving Flask app "hello"
 * Running on (Press CTRL+C to quit)

Then I set up port forwarding in VirtualBox on my desktop host so that I could communicate with the virtual machine, using the following settings:

Name: flask
Protocol: TCP
Host IP:
Host Port: 9500
Guest IP:
Guest Port: 5000

VirtualBox port forwarding rules
VirtualBox port forwarding rules

I tested it in a browser (Firefox) on my desktop at

No connection. Firefox endlessly tries to load the file.

I tried from the local machine itself:

# curl http://localhost:5000/
Hello World!

I tried running tcpdump to see what the network traffic to that port looked like:

# tcpdump -n -i enp0s3 port 5000
14:54:11.938625 IP > Flags [S], seq 3067208705, win 65535, options [mss 1460], length 0

Over and over I saw the same SYN packet from the client host, but the server never replied with a SYN-ACK.

I also noted that the local port was labeled commplex-main. This label is from /etc/services:

# grep commplex /etc/services
commplex-main   5000/tcp                #
commplex-main   5000/udp                #
commplex-link   5001/tcp                #
commplex-link   5001/udp                #

I don’t know what commplex-main is, but since I’m not running anything else on port 5000 other than Flask, it shouldn’t matter.

It turned out there were 2 separate problems:

  1. Flask was listening only on localhost
  2. firewalld was blocking the requests from external hosts

To fix the first, run Flask with the host flag:

# flask run --host=
 * Serving Flask app "hello"
 * Running on (Press CTRL+C to quit)

(This is mentioned in the Flask Quickstart guide, under Externally Visible Server.)

You can also specify an alternative port, e.g.:

# flask run --host= --port=56789
 * Serving Flask app "hello"
 * Running on (Press CTRL+C to quit)

To fix the latter temporarily, I disabled firewalld:

systemctl stop firewalld
systemctl disable firewalld

Obviously, if you are dealing with a machine connected directly to the Internet, this would be a terrible solution. You’d want to add rules allowing only the hosts and ports from which you expect to receive connections. But for testing communications between my desktop and a virtual host running on it, this seemed like a quick solution.

After those 2 changes, I was able to load the sample “hello” Flask app in a browser:

The text "Hello World!" loaded in Firefox
The text “Hello World!” loaded in Firefox

Analyzing text to find common terms using Python and NLTK

I just recently started playing with the Python NLTK (Natural Language ToolKit) to analyze text. The book Natural Language Processing with Python is available online and is very helpful if you’re just getting started.

At the beginning of the book the examples cover importing and analyzing text (primarily books) that you import from nltk (Getting Started with NLTK). It includes texts like Moby-Dick and Sense and Sensibility.

But you will probably want to analyze a source of your own. For example, I had text from a series of tweets debating political issues. The third chapter (Accessing Text from the Web and from Disk) has the answers:

First you need to turn raw text into tokens:

tokens = word_tokenize(raw)

Next turn your tokens into NLTK text:

text = nltk.Text(tokens)

Now you can treat it like the book examples in chapter 1.

I was analyzing a number number of tweets. One of the things I wanted to do was find common words in the tweets, to see if there were particular keywords that were common.

I was using the Python interpreter for my tests, and I did run into a couple errors with word_tokenize and later FreqDist, such as:

>>> fdist1 = FreqDist(text)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'FreqDist' is not defined

You can address this by importing the specific libraries:

>>> from nltk import FreqDist

Here are the commands, in order, that I ran to produce my list of common words — in this case, I was looking for words that appeared at least 3 times and that were at least 5 characters long:

>>> import nltk
>>> from nltk import word_tokenize
>>> from nltk import FreqDist

>>> with open("corpus-twitter", "r") as myfile:
...     raw ="utf8")

>>> tokens = word_tokenize(raw)
>>> text = nltk.Text(tokens)

>>> fdist = FreqDist(text)
>>> sorted(w for w in set(text) if len(w) >= 5 and fdist[w] >= 3)

[u'Americans', u'Detroit', u'Please', u'TaxReform', u'Thanks', u'There', u'Trump', u'about', u'against', u'always', u'anyone', u'argument', u'because', u'being', u'believe', u'context', u'could', u'debate', u'defend', u'diluted', u'dollars', u'enough', u'every', u'going', u'happened', u'heard', u'human', u'ideas', u'immigration', u'indefensible', u'logic', u'never', u'opinion', u'people', u'point', u'pragmatic', u'problem', u'problems', u'proposed', u'public', u'question', u'really', u'restricting', u'right', u'saying', u'school', u'scope', u'serious', u'should', u'solution', u'still', u'talking', u'their', u'there', u'think', u'thinking', u'thread', u'times', u'truth', u'trying', u'tweet', u'understand', u'until', u'welfare', u'where', u'world', u'would', u'wrong', u'years', u'yesterday']

It turns out the results weren’t as interesting as I’d hoped. A few interesting items–Detroit for example–but most of the words aren’t surprising given I was looking at tweets around political debate. Perhaps with a larger corpus there would be more stand-out words.

Twitter Status IDs and Direct Message IDs

twitter-birdI recently created a Magic Eight Ball twitter-bot as a demo. Written in Python using the python-twitter API wrapper, it runs every 2 minutes and polls twitter for new replies (status updates containing @osric8ball) and direct messages (DMs) to osric8ball. If there are any, it replies with a random 8-Ball response.

Every status update and DM has an associated numeric ID. Initially, I stored the highest ID in a log file and used that when I polled twitter (i.e. “retrieve all replies and DMs with ID > highest ID”). However, I discovered that status updates and DMs apparently are stored in separate tables on twitter’s backend, as they have a separate set of IDs. Since the highest status ID was an order of magnitude larger than the highest DM ID, my bot completely ignored all DMs. This was not entirely obvious at first, as the IDs looked very similar, other than an extra digit: 2950029179 and 273876291.

My fix for this was to store both the highest status update ID and the highest DM ID is separate log files.

Another interesting twist: you have to be a follower of a user in order to send that user a DM. Continue reading Twitter Status IDs and Direct Message IDs