The standard way to avoid this problem is to use autoload instead of require.
This way ESS is not required to compile and run EIN and it is only loaded if the user actually uses it.
```
"http://localhost:8888"
"http://localhost:8888/"
"http://127.0.0.1:8888"
"http://127.0.0.1:8888/"
"8888"
8888
```
Ideally these should converge to the same thing. Since many hash
tables are keyed off `url-or-port`, forgetting to
normalize `url-or-port` with `ein:url` leads to missed cache hits and
general malaise. So we try to do that.
Address a FIXME: apply callbacks to `ein:notebook-list-login-and-open`.
Removed py3.5 from travis build matrix to reduce developer strain.
Use deferred and callbacks instead of `:sync t` for tkf requests which
is known to have issues. Query server attributes once on
notebooklist-open to avoid sequencing issue #176 (but allow Resync).
Under curl backend, a second request for the same "key" as a pending
request will abort the latter, which has resulted in a clobbered
curl-cookie-jar file, so merely warn and don't abort.
Fix#176
Not sure if it is really doing anything, but ein:use-company-jedi-backend is now
a valid setting for ein:completion-backends.
More useful is that connected buffers now use ein's company completeion backend,
so completion should now work across all backends all across ein. Now let's get
something working in org!
Defer the deferred...
A bit less cryptically - wrap call to ein:shared-output-eval-string in a
deferred construct to ensure proper sequential execution of autoexec cells.
Don't think we were handling https:// url's correctly.
Also some code cleanup in ein-connect; fix longstanding bug in ein:load-files,
and tweak default timeout for starting a jupyter session from within emacs.
Trying to increase reliability of starting a juptyer server from Emacs. Deferred
is cool, but a pain to understand for this old brain.
Fix some typos in ein-ob and be smarter selecting completion backend when
connecting a python buffer to a jupyter notebook.
It is pointless to execute code in notebook unless some change in
the connected buffer is imported into the IPython kernel. Therefore,
hooking auto-execution to run or eval makes more sense than hooking
it to save.
