Stack of updates to docs in preparation for 1.0

docs/quickstart.rst

@@ -17,7 +17,7 @@ $ gcc --version
 
 Parsl has been tested on Linux and MacOS.
 
-.. note:: As of Parsl v0.7.2 we are switching to an opt-in model for anonymous usage tracking. To help support the
+.. note:: Parsl uses an opt-in model for anonymous usage tracking. To help support the
    Parsl project we request that users opt-in where possible by setting ``PARSL_TRACKING=true`` in their environment
    or by setting ``usage_tracking=True`` in the configuration object (`parsl.config.Config`). To read more about
    what information is collected and how it is used see :ref:`label-usage-tracking`.
@@ -26,7 +26,7 @@ Installation using Pip
 ^^^^^^^^^^^^^^^^^^^^^^
 
 While ``pip`` and ``pip3`` can be used to install Parsl we suggest the following approach
-for reliable installation when many Python environments are avaialble.
+for reliable installation when many Python environments are available.
 
 1. Install Parsl::
 
@@ -53,9 +53,9 @@ Installation using Conda
 2. Install Parsl::
 
      $ python3 -m pip install parsl
-     
+
      or
-     
+
      $ conda config --add channels conda-forge
      $ conda install parsl
 
@@ -71,11 +71,15 @@ can be installed easily via `pip` using a pip extras option.
 Here's a list of the components and their extras option:
 
 * Amazon Web Services (Cloud) : `aws`
+* OAuth based SSH : `oauth_ssh`
+* Logging monitoring data to a database: `monitoring`
+* Extreme Scale Executor (Supercomputing) : `extreme_scale`
 * Google Cloud : `google_cloud`
+* Python GSSAPI for SSH : `gssapi`
+* Azure (Cloud) : `azure`
 * Kubernetes : `kubernetes`
-* Extreme Scale Executor (Supercomputing) : `extreme_scale`
-* Logging monitoring data to a database: `monitoring`
-* Jetstream (NSF Cloud) : `jetstream`
+* Work Queue execution framework : `workqueue`
+
 
 Optional extras can be installed using the following syntax::
 

docs/userguide/app_caching.rst

@@ -53,6 +53,7 @@ two invocations are the same. This can be useful when generating log file
 names automatically based on time or run information. The names of keyword
 arguments to ignore can be specified as an ``ignore_for_cache``
 parameter to the decorator:
+
 .. code-block:: python
 
    @bash_app(cache=True, ignore_for_cache=['stdout'])

docs/userguide/examples/config.py

@@ -1,7 +1,18 @@
-import parsl
 from parsl.config import Config
-from parsl.executors.threads import ThreadPoolExecutor
+from parsl.channels import LocalChannel
+from parsl.executors import HighThroughputExecutor
+from parsl.providers import LocalProvider
 
-local_threads = Config(
-  executors=[ThreadPoolExecutor(max_threads=4)]
+htex_config = Config(
+    executors=[
+        HighThroughputExecutor(
+            label="htex_local",
+            cores_per_worker=1,
+            provider=LocalProvider(
+                channel=LocalChannel(),
+                init_blocks=1,
+                max_blocks=1,
+            ),
+        )
+    ],
 )

docs/userguide/examples/library.py

@@ -1,5 +1,6 @@
 from parsl import python_app
 
+
 @python_app
 def increment(x):
     return x + 1

docs/userguide/examples/run_increment.py

@@ -1,9 +1,8 @@
 import parsl
-from config import local_threads
+from config import htex_config
 from library import increment
 
-parsl.load(local_threads)
+parsl.load(htex_config)
 
 for i in range(5):
     print('{} + 1 = {}'.format(i, increment(i).result()))
-

docs/userguide/exceptions.rst

@@ -26,7 +26,7 @@ Failures might occur for various reasons:
 
 Since Parsl tasks are executed asynchronously, it can be difficult to determine
 where to place exception handling code in the workflow.
-In Parsl all exceptions are associated with the task futures. 
+In Parsl all exceptions are associated with the task futures.
 These exceptions are raised only when a result is called on the future
 of a failed task. For example:
 
@@ -64,12 +64,11 @@ The following example shows how the number of retries can be set to 2:
 
 .. code-block:: python
 
-   from parsl import load
-   from parsl.tests.configs.local_threads import config
+   import parsl
+   from parsl.configs.htex_local import config
    config.retries = 2
 
-   load(config)
-
+   parsl.load(config)
 
 
 
@@ -79,7 +78,7 @@ Lazy fail
 Parsl implements a lazy failure model through which a workload will continue
 to execute in the case that some tasks fail. That is, the workflow
 does not halt as soon as it encounters a failure, but continues execution of every
-app that is unaffected. 
+app that is unaffected.
 
 For example:
 
@@ -100,5 +99,3 @@ For example:
       (F)           (F)           (!F)
 
       time ----->
-
-

docs/userguide/modularizing.rst

@@ -13,11 +13,6 @@ benefits to be obtained by modularizing the workflow, including:
    3. Ease of reuse of components
 
 
-.. note::
-   Support for isolating configuration loading and app definition is available since 0.6.0.
-   Refer: `Issue#50 <https://github.com/Parsl/parsl/issues/50>`_
-
-
 The following example illustrates how a Parsl project can be organized into modules.
 
 The configuration(s) can be defined in a module or file (e.g., ``config.py``)