Update README.md

Author: alexcombessie

README.md

@@ -6,47 +6,53 @@ Use it and adapt it as you wish, and have fun with Dataiku!
 
 
 # How to test your plugin
-Development cycles should be supported with unit and integration tests. 
-To operate integration tests you will need the help of the `dataiku-plugin-tests-utils` pacakge in order
-to automate their executions while targeting DSS instances that should be dedicated to them.
 
-`dataiku-plugin-tests-utils` will be installed as a `pytest plugin`. So only install that package inside an environment dédicated for integration tests, otherwise `pytest` will complain about unused fixtures inside your unit tests.
+We recommend supporting your development cycle with unit and integration tests.
+To operate integration tests, you will need the help of the `dataiku-plugin-tests-utils` package to automate their executions while targeting dedicated DSS instances.
+
+`dataiku-plugin-tests-utils` will be installed as a `pytest plugin`. Install that package inside an environment dedicated to integration tests; otherwise, `pytest` will complain about unused fixtures inside your unit tests.
 
 # How to install in your plugin
-To install the `dataiku-plugin-tests-utils` package for your plugins use the
-following line depending on your prefered way to managed packages and situation
-you are in.
-## Using Requierement.txt
-### Development cycle
+
+To install the `dataiku-plugin-tests-utils` package for your plugins, use the following line depending on your preferred way to managed packages.
+
+## Using requirements.txt
+
+### Development
 
 ```
 git+git://github.com/dataiku/dataiku-plugin-tests-utils.git@<BRANCH>#egg=dataiku-plugin-tests-utils
 ```
 
-Replace `<BRANCH>` by the most accurate value
+Replace `<BRANCH>` with the most accurate value
 
-### Stable release (untested for now)
+### Stable release
 
 ```
 git+git://github.com/dataiku/dataiku-plugin-tests-utils.git@releases/tag/<RELEASE_VERSION>#egg=dataiku-plugin-tests-utils
 ```
 
-Replace `<RELEASE_VERSION>` by the most accurate value
+Replace `<RELEASE_VERSION>` with the most accurate value
+
+## Using pipfile
 
-## Using Pipfile
 Put the following line under `[dev-packages]` section
+
 ### Development cycle
+
 ```
 dku-plugin-test-utils = {git = "git://github.com/dataiku/dataiku-plugin-tests-utils.git", ref = "<BRANCH>"}
 ```
+
 ### Stable release
 TBD
 
 ## Dev env
+
 ### Config
 
-First, ensure that you have Personal Api Keys generated for the DSS you want to target.
-Secondly, define a config file which will give the DSS you will target.
+First, ensure that you have personal API Keys for the DSS you want to target.
+Secondly, define a config file that will give the DSS you will target.
 ```
 {
 	"DSSX":
@@ -80,18 +86,19 @@ Then, set the environment variable `PLUGIN_INTEGRATION_TEST_INSTANCE` to point t
 # How to use the package
 
 ## General information
+
 To use the package in your test files:
 ```python
 import dku_plugin_test_utils
 import dku_plugin_test_utils.subpakcage.subsymbol
 ```
-Look at the next section for more information about potential `subpackage` and `subsymbol`
+Look at the next section for more information about potential `subpackage` and `subsymbol`.
 
-The python integration tests files are indirections towards the "real" tests that are written as DSS scenarios on DSS instances.
-The python test function triggers the targeted DSS scenario and waits either for its sucessfull or failed completion.
+The python integration test files are indirections towards the "real" tests written as DSS scenarios on DSS instances.
+The python test function triggers the targeted DSS scenario and waits either for its successful or failed completion.
 Thence your test function should look like the following snippet :
 ```python
-# Mandatory imprts
+# Mandatory imports
 from dku_plugin_test_utils import dss_scenario
 
 def test_run_some_dss_scenario(user_dss_clients):
@@ -100,26 +107,27 @@ def test_run_some_dss_scenario(user_dss_clients):
 # [... other tests ...]
 ```
 With:
-- `user_dss_clients`: representing the dss client corresponding to the desired user.
+- `user_dss_clients`: representing the DSS client corresponding to the desired user.
 - `PROJECT_KEY`: The project that holds the test scenarios
 - `scenario_id`: The test scenario to run
-- `user`: Specify the user to run the scenario with. It is an optionnal argument, by default it equalt to "default".
+- `user`: Specify the user to run the scenario with. It is an optional argument. By default, it is "default".
 
 ## How to generate a graphical report with Allure for integration tests
 
-For each plugin, a folder named `allure_report` should exists inside the `test` folder, reports will be generated inside that folder.
-To generate the graphical report, you must have allure installed on your system as described [on their installation guide](https://docs.qameta.io/allure/#_manual_installation). Once the installation is done, run the following :
+For each plugin, a folder named `allure_report` should exist inside the `test` folder; reports will be generated inside that folder.
+To generate the graphical report, you must have Allure installed on your system as described [on their installation guide](https://docs.qameta.io/allure/#_manual_installation). Once the installation is done, run the following :
 ```shell
 allure serve path/to/the/allure_report/dir/inside/you/plugin/test/folder/
 ```
 
-# Package Hierarchy
-As it is a tooling package for integration test, it will aggregate different packages with different aim. 
+# Package hierarchy
+
+As it is a tooling package for integration tests, it will aggregate different packages with different goals. 
 The following hierarchy exposes the different sub-package contained in `dku_plugin_test_utils` with their aim 
 and the list of public symbols:
 
 - `run_config`:
-  - `ScenarioConfiguration`: Class exposing the parsed run configuration as a python dict.
-  - `PluginInfo`: Parse the plugin.json and the code-env desc.json files to extract plugin metadata as a python dict.
+  - `ScenarioConfiguration`: Class exposing the parsed run configuration as a python dictionary.
+  - `PluginInfo`: Parse the plugin.json and the code-env desc.json files to extract plugin metadata as a python dictionary.
 - `dss_scenario`: 
-  - `run`: Run the targetted DSS scenario and wait for it completion either success or failure.
+  - `run`: Run the target DSS scenario and wait for its completion (either success or failure).