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Finding all the tables on that HTML page.Parsing the HTML content of the web page given its URL by constructing the BeautifulSoup object.Pd.DataFrame(rows, columns=headers).to_csv(f" tables.")įor i, table in enumerate(tables, start=1): The below function takes the table name, table headers, and all the rows and saves them as CSV format: def save_as_csv(table_name, headers, rows): The reason we used table.find_all("tr") and not all tr tags, is because the first tr tag corresponds to the table headers we don't wanna add it here.
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# can be found especially in wikipedia tables below the tableĪll the above function is doing, is to find tr tags (table rows) and extract td elements which then appends them to a list. """Given a table, returns all its rows"""
Html to csv converter how to#
Now that we know how to extract table headers, the remaining is to extract all the table rows: def get_table_rows(table): The above function finds the first row of the table and extracts all the th tags (table headers). """Given a table soup, returns all the headers"""įor th in table.find("tr").find_all("th"): Now we need a way to get the table headers, the column names, or whatever you want to call them: def get_table_headers(table): """Extracts and returns all tables in a soup object""" The following function does exactly that: def get_all_tables(soup): Since we want to extract every table in any page, we need to find the table HTML tag and return it. Related tutorial: How to Make an Email Extractor in Python. After that, we construct a BeautifulSoup object using html.parser. We first initialize a requests session, we use the User-Agent header to indicate that we are just a regular browser and not a bot (some websites block them), and then we get the HTML content using session.get() method. # set the User-Agent as a regular browser """Constructs and returns a soup using the HTML content of `url` passed""" We need a function that accepts the target URL and gives us the proper soup object: USER_AGENT = "Mozilla/5.0 (X11 Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/.157 Safari/537.36" Let's import the libraries: import requests Open up a new Python file and follow along. If you want to do the other way around, converting Pandas data frames to HTML tables, then check this tutorial.
Html to csv converter install#
If you haven't requests, BeautifulSoup and pandas installed, then install them with the following command: pip3 install requests bs4 pandas We will also be using pandas to easily convert to CSV format (or any format that pandas support). In this tutorial, we will be using requests and BeautifulSoup libraries to convert any table on any web page and save it on our disk. Have you ever wanted to automatically extract HTML tables from web pages and save them in a proper format on your computer? If that's the case, then you're in the right place. One enhancement for this script could be to add support for specifying a different line delimiter (or auto-calculate the platform-correct one), and a different column delimiter.Disclosure: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission. Self.buffer += space_re.sub(" ", data).strip() Worked like charm for me: $(document).ready(() => \"".format(self.buffer) (space_re.sub(' ', data).strip())Īssuming that you've designed an HTML page containing a table, I would recommend this solution. It doesn't handle colspan or rowspan.ĭef _init_(self, row_delim="\n", cell_delim="\t"): Not sure how it'll handle nested tables (probably it'll do bad stuff) or multiple tables (probably they'll just appear one after another). It was written in a couple of minutes, so it can probably be made better. Here's a short Python program I wrote to complete this task. Note that if any of the table cells contain commas, you may need to escape them first, or use a different delimiter. Remove TABLE and TR tags | sed 's/]*>//Ig' I only want Table elements (return only lines with TABLE,TR,TH,TD tags) | grep -i -e ' with newline | sed 's/]*>/\n/Ig' Get the Contents of the URL using cURL, dump stderr to null (no progress meter) curl "" 2>/dev/null curl "" 2>/dev/null | grep -i -e ']*>/\n/Ig' | sed 's/]*>//Ig' | sed 's/^]*>\|]*>$//Ig' | sed 's/]*>]*>/,/Ig'Īs you can see I've got the page source using curl, but you could just as easily feed in the table source from elsewhere. The below was bashed out very quickly, and so could be made much more elegant, but I'm just getting started really with sed/awk etc. So here's my solution using only grep and sed.
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Html to csv converter portable#
Sorry for resurrecting an ancient thread, but I recently wanted to do this, but I wanted a 100% portable bash script to do it.