diff --git a/docs/intro/install.rst b/docs/intro/install.rst index c90c1d2bf..e6c9a683b 100644 --- a/docs/intro/install.rst +++ b/docs/intro/install.rst @@ -37,7 +37,7 @@ Note that sometimes this may require solving compilation issues for some Scrapy dependencies depending on your operating system, so be sure to check the :ref:`intro-install-platform-notes`. -For more detailed and platform specifics instructions, as well as +For more detailed and platform-specific instructions, as well as troubleshooting information, read on. @@ -101,7 +101,7 @@ Windows ------- Though it's possible to install Scrapy on Windows using pip, we recommend you -to install `Anaconda`_ or `Miniconda`_ and use the package from the +install `Anaconda`_ or `Miniconda`_ and use the package from the `conda-forge`_ channel, which will avoid most installation issues. Once you've installed `Anaconda`_ or `Miniconda`_, install Scrapy with:: @@ -141,7 +141,7 @@ But it should support older versions of Ubuntu too, like Ubuntu 14.04, albeit with potential issues with TLS connections. **Don't** use the ``python-scrapy`` package provided by Ubuntu, they are -typically too old and slow to catch up with latest Scrapy. +typically too old and slow to catch up with the latest Scrapy release. To install Scrapy on Ubuntu (or Ubuntu-based) systems, you need to install @@ -170,7 +170,7 @@ macOS Building Scrapy's dependencies requires the presence of a C compiler and development headers. On macOS this is typically provided by Apple’s Xcode -development tools. To install the Xcode command line tools open a terminal +development tools. To install the Xcode command-line tools, open a terminal window and run:: xcode-select --install @@ -200,11 +200,6 @@ solutions: brew install python - * Latest versions of python have ``pip`` bundled with them so you won't need - to install it separately. If this is not the case, upgrade python:: - - brew update; brew upgrade python - * *(Optional)* :ref:`Install Scrapy inside a Python virtual environment `. diff --git a/docs/intro/overview.rst b/docs/intro/overview.rst index ef1294470..cd17b1968 100644 --- a/docs/intro/overview.rst +++ b/docs/intro/overview.rst @@ -65,7 +65,7 @@ When you ran the command ``scrapy runspider quotes_spider.py``, Scrapy looked fo Spider definition inside it and ran it through its crawler engine. The crawl started by making requests to the URLs defined in the ``start_urls`` -attribute (in this case, only the URL for quotes in *humor* category) +attribute (in this case, only the URL for quotes in the *humor* category) and called the default callback method ``parse``, passing the response object as an argument. In the ``parse`` callback, we loop through the quote elements using a CSS Selector, yield a Python dict with the extracted quote text and author, @@ -83,9 +83,9 @@ While this enables you to do very fast crawls (sending multiple concurrent requests at the same time, in a fault-tolerant way) Scrapy also gives you control over the politeness of the crawl through :ref:`a few settings `. You can do things like setting a download delay between -each request, limiting amount of concurrent requests per domain or per IP, and +each request, limiting the amount of concurrent requests per domain or per IP, and even :ref:`using an auto-throttling extension ` that tries -to figure out these automatically. +to figure these settings out automatically. .. note:: @@ -106,10 +106,10 @@ scraping easy and efficient, such as: * Built-in support for :ref:`selecting and extracting ` data from HTML/XML sources using extended CSS selectors and XPath expressions, - with helper methods to extract using regular expressions. + with helper methods for extraction using regular expressions. * An :ref:`interactive shell console ` (IPython aware) for trying - out the CSS and XPath expressions to scrape data, very useful when writing or + out the CSS and XPath expressions to scrape data, which is very useful when writing or debugging your spiders. * Built-in support for :ref:`generating feed exports ` in @@ -124,7 +124,7 @@ scraping easy and efficient, such as: well-defined API (middlewares, :ref:`extensions `, and :ref:`pipelines `). -* Wide range of built-in extensions and middlewares for handling: +* A wide range of built-in extensions and middlewares for handling: - cookies and session handling - HTTP features like compression, authentication, caching