Tools/Services

Scheduling Cron Jobs From Python

Inevitably, you’ll have to write a post-install routine in Python that has to schedule a Cron job. For this, python-crontab is a great solution.

Create the job using the following. This will not commit the changes, yet.

from crontab import CronTab    
cron = CronTab()
job = cron.new(command='/usr/bin/tool')

There are at least three ways to configure the schedule:

Using method calls:

job.minute.during(5,50).every(5)
job.hour.every(4)

Using an existing crontab row:

job.parse("* * * * * /usr/bin/tool")

Obviously in the last case, you can omit the command when we created the job.

Using an alias:

job.special = '@daily'

You can commit your changes by then calling:

job.write()

This is a very limited introduction that elaborates on how to use aliases and parsing to schedule, since the documentation doesn’t go into it, but omits other features such as:

  • indicating the user to schedule for (the default is “root”)
  • finding existing jobs by command or comment
  • enumerating jobs
  • enumerating the schedule that a particular job will follow
  • enumerating the logs for a particular job
  • removing jobs
  • editing a crontab file directly, or building one in-memory
  • enabling/disabling jobs

The official documentation (follow the link, above) describes all of the features on this list.

A Console-Based Form

I just uploaded a Python tool called “text-prompts” that takes a dictionary, presents a list of prompts to the user, and returns a dictionary.

For more detail, go here: text_prompts.txt

Example:

    from text_prompts import text_prompts
    text_prompts({ 'prompt1': ('Prompt 1', True, None), 
                   'prompt2': ('Prompt 2', False, 'default')})

Output:

    Prompt 1 (req): first response
    Prompt 2 [CTRL+D for "default"]: second response

Result:

    {'prompt1': 'first response', 'prompt2': 'second response'}

Listing SSL Certificates for a Hostname

If you’ve configured new SSL certificates on a server, you might want to watch for them to take effect and/or verify that they’re configured correctly. You can use an OpenSSL tool to do this (there is supposed to be an underscore: “s_client”):

openssl s_client -connect <hostname>:443 -servername <hostname>

This will print a barrage of information. For the purpose indicated above, you might only be interested in the very top portion:

$ openssl s_client -connect www.google.com:443 -servername www.google.com
CONNECTED(00000003)
depth=2 C = US, O = GeoTrust Inc., CN = GeoTrust Global CA
verify error:num=20:unable to get local issuer certificate
verify return:0
---
Certificate chain
 0 s:/C=US/ST=California/L=Mountain View/O=Google Inc/CN=www.google.com
   i:/C=US/O=Google Inc/CN=Google Internet Authority G2
 1 s:/C=US/O=Google Inc/CN=Google Internet Authority G2
   i:/C=US/O=GeoTrust Inc./CN=GeoTrust Global CA
 2 s:/C=US/O=GeoTrust Inc./CN=GeoTrust Global CA
   i:/C=US/O=Equifax/OU=Equifax Secure Certificate Authority
---

Under “Certificate chain”, there will be a list of all the certificates you’ve configured for the hostname. For example, if you configure one certificate (for a well-known authority) there will be one item, or if you configure a regular and an IA certificate (for lesser known authorities), there will be two.

The item (0) applies to your hostname, and each subsequently higher certificate represents a higher certificate authority. The last line of each item matches the first of the next item.

Password Strength Checking in Python

I’ve recently uploaded a tool to check password strength in Python. Prior, it seems like the only options that existed were to call cracklib via ctypes or using django-passwords, which, obviously, only works in the context of Django.

I took django-passwords and modified it to work as a library. It works as four separate validation classes:

  • LengthValidator: Check if between minimum and maximum lengths.
  • ComplexityValidator: Check for a minimum of certain character classes.
  • DictionaryValidator: Check if a password exists within a predefined list.
  • CommonSequenceValidator: Check is a password is a alphabetic, numeric, etc.. sequence.

Example of usage:

# See example for more information.

from password_check import ComplexityValidator, ValidationError

complexity = { # A minimum of N upper-case letters.
               "UPPER": 2,
               
               # A minimum of N lower-case letters.
               "LOWER": 2,
               
               # A minimum of N digits.
               "DIGITS": 2,
              
               # A minimum of N punctuation characters.
               "PUNCTUATION": 2,

               # A minimum of N non-ASCII characters ("\xx")
               "NON ASCII": 0,

               # A minimum of N space-separated, unique words.
               "WORDS": 0 }

complexity_validator = ComplexityValidator(complexity)

# Throws ValidationError due to several violations.
complexity_validator('simplepassword')

For more examples, go to the link, above, and look at the example script.

A Pure-Python Implementation of “pytz”

There is a problem with the standard “pytz” package: It’s awesome, but can’t be used on systems that don’t allow direct file access. I created “pytzpure” to account for this. It allows you to build-out data files as Python modules. As long as these modules are put into the path, the “pytzpure” module will provide the same exports as the original “pytz” package.

For export:

PYTHONPATH=. python pytzpure/tools/tz_export.py /tmp/tzppdata

Output:

Verifying export path exists: /tmp/tzppdata
Verifying __init__.py .
Writing zone tree.
(578) timezones written.
Writing country timezones.
Writing country names.

To use:

from datetime import datetime
from pytzpure import timezone
utc = timezone('UTC')
detroit = timezone('America/Detroit')
datetime.utcnow().replace(tzinfo=utc).astimezone(detroit).\
strftime('%H:%M:%S %z')
'16:34:37 -0400'

Dumping Raw Python from Dictionary

I wrote a simple tool to generate a Python string-representation of the given data. Note that this renders data very similar to JSON, with the exception of the handling of NULLs.

Example usage:

get_as_python({ 'data1': { 'data22': { 'data33': 44 }},
                'data2': ['aa','bb','cc'],
                'data3': ('dd','ee','ff',None) })

Output (notice that a dict does not carry order, as expected):

data1 = {"data22":{"data33":44}}
data3 = ["dd","ee","ff",None]
data2 = ["aa","bb","cc"]

https://raw.github.com/dsoprea/RandomUtility/master/get_as_python.py