I use Namecheap.com as a registrar, and they resale SSL Certs from a number of other companies, including Comodo.
These are the steps I went through to set up an SSL cert.
/** | |
* Retrieves all the rows in the active spreadsheet that contain data and logs the | |
* values for each row. | |
* For more information on using the Spreadsheet API, see | |
* https://developers.google.com/apps-script/service_spreadsheet | |
*/ | |
function readRows() { | |
var sheet = SpreadsheetApp.getActiveSheet(); | |
var rows = sheet.getDataRange(); | |
var numRows = rows.getNumRows(); |
I use Namecheap.com as a registrar, and they resale SSL Certs from a number of other companies, including Comodo.
These are the steps I went through to set up an SSL cert.
server { | |
server_name trailers.apple.com atv.plexconnect; | |
location / { | |
proxy_set_header Host $host; | |
proxy_set_header X-Real-IP $remote_addr; | |
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; | |
proxy_pass http://127.0.0.1:8091; | |
} |
One of the best ways to reduce complexity (read: stress) in web development is to minimize the differences between your development and production environments. After being frustrated by attempts to unify the approach to SSL on my local machine and in production, I searched for a workflow that would make the protocol invisible to me between all environments.
Most workflows make the following compromises:
Use HTTPS in production but HTTP locally. This is annoying because it makes the environments inconsistent, and the protocol choices leak up into the stack. For example, your web application needs to understand the underlying protocol when using the secure
flag for cookies. If you don't get this right, your HTTP development server won't be able to read the cookies it writes, or worse, your HTTPS production server could pass sensitive cookies over an insecure connection.
Use production SSL certificates locally. This is annoying
Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discuss around concrete examples, not hand-waving abstractions. Don't say you did something, provide a URL that proves it.
Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.
(This gist is pretty old; I've written up my current approach to the Pyramid integration on this blog post, but that blog post doesn't go into the transactional management, so you may still find this useful.)
I've created a Pyramid scaffold which integrates Alembic, a migration tool, with the standard SQLAlchemy scaffold. (It also configures the Mako template system, because I prefer Mako.)
I am also using PostgreSQL for my database. PostgreSQL supports nested transactions. This means I can setup the tables at the beginning of the test session, then start a transaction before each test happens and roll it back after the test; in turn, this means my tests operate in the same environment I expect to use in production, but they are also fast.
I based my approach on [sontek's blog post](http://sontek.net/blog/
class ReloaderEventHandler(FileSystemEventHandler): | |
""" | |
Listen for changes to modules within the Django project | |
On change, reload the module in the Python Shell | |
Custom logic required to reload django models.py modules | |
Due to the singleton AppCache, which caches model references. | |
For those models files, we must clear and repopulate the AppCache | |
""" | |
def __init__(self, *args, **kwargs): |
diff --git a/system/core/Kohana.php b/system/core/Kohana.php | |
index 271f917..287c271 100644 | |
--- a/system/core/Kohana.php | |
+++ b/system/core/Kohana.php | |
@@ -722,7 +722,7 @@ final class Kohana { | |
if (ob_get_level() >= self::$buffer_level) | |
{ | |
// Set the close function | |
- $close = ($flush === TRUE) ? 'ob_end_flush' : 'ob_end_clean'; | |
+ $close = ($flush === TRUE) ? 'ob_end_flush' : 'Kohana::_ob_end_clean'; |
Using Python's built-in defaultdict we can easily define a tree data structure:
def tree(): return defaultdict(tree)
That's it!