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BINREV SPYD3R last won the day on July 2 2020

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    I could have written a book with all of these posts

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  1. Why is there a lack of diverse voices and faces in the world of Linux and open source Free software but it's not made available to the very people who could really benefit from it Lack of training in schools when it comes to Linux and other open source software View the full article
  2. Hey guys I have been doing a lot of MS Teams it works on Linux not so I can have 365 on my ubuntu browser and MS teams installed. (Work complete from a linux box) (It's great) The Raspberry PI400 is a great box you should get it. Also I thought the Raspberry 4 8GB to be very solid. View the full article
  3. garage door part 2 tis teh season COUGH COUGH View the full article
  4. What is ReText? The ReText website on GitHub says that ReText is a simple but powerful editor for Markdown and reStructuredText markup languages. Doing a search on the HPR site returned the following two references to ReText. The excellent Markdown and Pandoc HPR 1832 episode by b-yeezi makes reference to ReText Dave Morriss mentioned using ReText as a possible tool when sending in shownotes as markdown is preferable to plain text. Refer to HPR 3167 Retext Version Info As of the 1st of January 2021 I am running ReText version 7.0.1 the latest version was 7.1.0 this was last updated on the 4th of April 2020. Why I am covering this I’m covering this because in HPR show 3167 Dave Morriss said that Markdown was a preferred way to submit shownotes. Prior to this I had supplied my shownotes in plain text. What is Markdown? I guess I first must cover what markdown is I found the following definitions:- Description of Markdown from Wikipedia Markdown is a lightweight markup language for creating formatted text using a plain-text editor. John Gruber and Aaron Swartz created Markdown in 2004 as a markup language that is appealing to the human users in its source form.[9] Markdown is widely used in blogging, instant messaging, online forums, collaboration software, documentation pages, and even readme files Link Description of Markdown from John Gruber's website, one of the co founders of Markdown. Markdown is a text-to-HTML conversion tool for web writers. Markdown allows you to write using an easy-to-read, easy-to-write plain text format, then convert it to structurally valid XHTML (or HTML). Example text used in the show and how it looks # This is a level 1 heading ## This is a level 2 heading ### This is a level 3 heading This is a level 1 heading This is a level 2 heading This is a level 3 heading List of useful links Finally here are useful links that are available from within the ReText program. They can be found within the Help / About ReText menu:- Link to ReText website Link to Markdown syntax Link to reStructuredText syntax Final thoughts Using ReText to pull these shownotes together disciplined me to hopefully put more meaningful titles within my shownotes. It helped my to create meaningful descriptive links which will hopefully help accessibility for the visually impaired. I edited the text on this occasion in live preview mode I found this made it very easy to see how the final version would look. I think I ended up with more polished shownotes that hopefully needs fewer and hopefully no input from our band of HPR volunteers working behind the scenes. View the full article
  5. NEW 'Off The Wall' ONLINE Posted 20 Jan, 2021 1:18:49 UTC The new edition of Off The Wall from 01/19/2021 has been archived and is now available online. "Off The Wall" - 01/19/2021 Download the torrent here View the full article
  6. Welcome to another episode of HPR I'm your host Enigma and today we are going to be talking about one of my favorite python modules Pandas This will be the first episode in a series I'm naming: For The Love of Python. First we need to get the module pip or pip3 install pandas This will install numpy as well Pandas uses an object called a dataframe which is a two-dimensional data structure, i.e., data is aligned in a tabular fashion in rows and columns. Think of a spreadsheet type object in memory Today we are going to talk about: 1) Importing data from various sources Csv, excel, sql. More advance topics like Json covered in another episode. df = pd.read_csv('file name') 2) Accessing data by column names or positionally print(df.head(5)) # print all columns only first 5 rows print(df.tail(5)) # print all columns only last 5 rows print(df.shape) # print number of rows and columns in dataframe print(df.columns) print column names print(df[0:1].head(5)) print first two columns first 5 values by column position print(df['field1].head(5)) print same column first five values by column name 3) Setting column types. df['FieldName'] = df['FieldName'].astype(int) # sets column as interger df['FieldName'] = df['FieldName'].astype(str) # sets column to string df['DateColumn'] = pd.to_datetime(df['DateColumn']) # sets column to Datetime 4) Some basic filtering/manipulation of data. Splits string at the @ for one split next two lines create 2 columns that use the pieces. new = df2["Email"].str.split("@", n = 1, expand = True) df2["user"]= new[0] df2["domain"]= new[1] df['col'] = df['Office'].str[:3] # creates a new column grabing the first 3 positions of Office column df = df[df['FieldName'] != 0] # Only keep rows that have a FieldName value not equal to zero See example code that you can run at: Pandas Working example View the full article
  7. JSON Json is a cool little data serialization language, that allows you to easily and clearly demarcate blocks of data by nesting data structures such as lists (enclosed by square brackets) and key-value pairs or "dictionaries" (enclosed by curly braces). So that in the end you get something that looks like this { "first list" : [ "element1", "element2", {"element3" : "is another k-v pair", "but contains" : ["a" , "list", "of", "words"]}] , "this value is a string" : "1" , "and this is a number" : 23 , "and floating point" : 1.413 } Aside from: Lists are enclosed in [] and each element is separated by , Key-value pair lists are enclosed in {} and have the key and value separated by : and each pair is separated by , Keys have to strings quoted with double quotes Numbers may be left unquoted (but just in value fields) There are no restrictions to what you can do with JSON. Given how explicit the syntax is then, it makes for very easy parsing, and there are plenty of good parser out there. My favourite JSON parser is jq(1). A canonical representation of the JSON example above can easily be obtained with jq by simply calling jq '' file.json (or piping the file through stdin, or even putting the contents properly quoted as the second argument). { "first list": [ "element1", "element2", { "element3": "is another k-v pair", "but contains": [ "a", "list", "of", "words" ] } ], "this value is a string": "1", "and this is a number": 23, "and floating point": 1.413 } You can also use jq in a shell script to obtain, for example the second element of the first list: $ jq '."first list"[1]' example.json "element2" So to get the value associated to a key you use the notation .key and to get the k-th element you use the notation [k-1]. To remove the quotes on the string you can use the -r flag which stands for raw output. jq(1) also gives you a few more functionalities that can be useful like getting the number of elements in a list with the length function. $ jq 'length' example.json 3 $ jq '."first list"[2]."but contains" | length' 4 Another useful feature is getting the list of keys from a key-value pair list which can be done with the function keys $ jq '."first list"[2] | keys[]' example.json "but contains", "element3" The query language is much much more flexible than this, but for most cases this should be enough for simple configuration querying. YAML and XML?? The yq project allows one to use the exact same syntax as jq to query, and emit (and therefore also transcode) yaml and XML, extending the usefulness of the query language. So for example looking at the previous file through yq gives: $ yq -y '' example.json first list: - element1 - element2 - element3: is another k-v pair but contains: - a - list - of - words this value is a string: '1' and this is a number: 23 and floating point: 1.413 And the output of this can be of course queried with yq itself, or can be used to feed into whatever application requires a yaml input (I guess it lacks the triple dash at the top, but that is actually the only warning I get from passing that abomination to yamllint) Similarly xq can be used to query XML files with the same language. However, to emit these files from json you need to use yq -x like so: $ yq -x '' example2.json <file> <first_list>element1</first_list> <first_list>element2</first_list> <first_list> <element3>is another k-v pair</element3> <but_contains>a</but_contains> <but_contains>list</but_contains> <but_contains>of</but_contains> <but_contains>words</but_contains> </first_list> <this_value_is_a_string>1</this_value_is_a_string> <and_this_is_a_number>23</and_this_is_a_number> <and_floating_point>1.413</and_floating_point> </file> where the original (modified) file example2.json looks like: { "file": { "first_list": [ "element1", "element2", { "element3": "is another k-v pair", "but_contains": [ "a", "list", "of", "words" ] } ], "this_value_is_a_string": "1", "and_this_is_a_number": 23, "and_floating_point": 1.413 } } So that the root dictionary has a single key-value pair and all the keys have no spaces in them (so that they can be made into xml tags). View the full article
  8. I discuss the subject of alcohol with my partner of sixteen years, Mrs. Honeyhume. While we agree on many subjects, alcohol is not one of them. She believes alcohol is an important experience, one to be shared with friends, and I dislike nearly everything about it. We discuss what we like/dislike about alcohol, our histories with it, and present our personal anecdotal evidence. View the full article
  9. Layers are the feature that does most of the heavy lifting in GIMP. After our previous introduction, we start to get hands-on with the controls that let us work with Layers Links: View the full article
  10. NEW 'Off The Hook' ONLINE Posted 14 Jan, 2021 2:29:56 UTC The new edition of Off The Hook from 01/13/2021 has been archived and is now available online. First show of the year, the insurrection was planned online, cries of censorship after Trump is banned from social media, reactions to the Jan 6 attack on the Capitol, Parler finds a new registrar, monitoring domain name registrations related to the insurrection, 70tb of Parler data leaked, information security consequences of the Capitol attack, contact info for Congress members who supported overturning the election available at "Off The Hook" - 01/13/2021 Download the torrent here View the full article
  11. Rust for the Linux kernel: Linus opinion on C++ in the Linux kernel: gdb: lldb: Novell's Netware: strace: ltrace: DTrace: ptrace: Capabilities: Extended attributes: inux eBPF: BCC: BCC toolchain: Linux kernel tracing: Cathy O'Neil's Weapons of Math Destruction: s_of_Math_Destruction Audacity: Jitsi (Meet): View the full article
  12. NEW 'Off The Wall' ONLINE Posted 13 Jan, 2021 2:14:21 UTC The new edition of Off The Wall from 01/12/2021 has been archived and is now available online. "Off The Wall" - 01/12/2021 Download the torrent here View the full article
  13. Basic Process Sample Collection Sample Transportation Nucleic Acid extraction and Purification Amplification and Detection Links View the full article
  14. The top ten are: Gas Tires Battery Hoses/Belts Fluids External Review dates Schedule replacement parts Clean up Choose for car wash A treat! Blog site: View the full article
  15. My review on the FP3 when it came out Two solutions for a free OS: lineage OS - free android with the Gapps removed the /e/ project !! A "de-googled" operating system - actually a fork of lineage OS - this is what I'm going to talk about here. The research paper on Google Data Collection by Professor Douglas C. Schmidt, Vanderbilt University (2018) - learn how and how often normal Android phones send your data to Google servers. Another background article on tracking (in German) based on research from a Norwegian journalist: MicroG services, a replacement for Google's libraries on /e/ with purely open-source implementations. The man behind the /e/ project: Gael Duval, pioneer of Open Source, Mandrake, Ulteo... His article outlining his vision for /e/ : You can buy a FP3 and an FP3 + with /e/ pre-installed here !! Installing on your phone: over 110 devices supported: from Asus to Google, to Oneplus and Xiaomi How to install it on the FP3 Install /e/ on FairPhone FP3 - FP3 | /e/ documentation Privacy ratings of apps: Alternative launchers: KISS launcher Simple launcher I recommended you add these apps: Antennapod - podcast client FairEmail or simple email Fennec (Firefox) Signal newpipe for watching youtube without being tracked Backup via adb is apparently broken | Not the fault of /e/!! You cannot simply flash a new recovery, such as TWRP, to flash images or backup, instead, you can use this method Donate or become a member to keep the project going: Feel free to add any comments below! Theme Music: Jazzhar, "Room with a View" CC-BY-SA, check him out on Jamendo and on Free Music Archive View the full article