18
Nov
2019

How to just show HTTP headers using wget

Use --server-response -qO /dev/null:

wget --server-response -qO /dev/null [URL]

Example:

wget --server-response -qO /dev/null https://techoverflow.net

Example output:

HTTP/1.1 200 OK
Server: nginx/1.14.0 (Ubuntu)
Date: Mon, 18 Nov 2019 02:15:19 GMT
Content-Type: text/html; charset=UTF-8
Transfer-Encoding: chunked
Connection: keep-alive
Vary: Accept-Encoding
Set-Cookie: cookielawinfo-checkbox-necessary=yes; expires=Mon, 18-Nov-2019 03:15:18 GMT; Max-Age=3600; path=/
Set-Cookie: cookielawinfo-checkbox-non-necessary=yes; expires=Mon, 18-Nov-2019 03:15:18 GMT; Max-Age=3600; path=/
Link: <https://techoverflow.net/wp-json/>; rel="https://api.w.org/"

 

Posted by Uli Köhler in Shell
16
Nov
2019

gzip-compress in-memory in Go

In Go, you can use the built-in gzip library together with bytes.Buffer to compress a []byte to obtain a []byte containing gzip-compressed data:

content := "Hello World!"
buf := &bytes.Buffer{}
gzWriter := gzip.NewWriter(buf)
gzWriter.Write([]byte(content))
gzWriter.Close()

This full example compresses the data in-memory and writes it to a file called text.txt.gz afterwards. Note that you can also gzip directly into a file and if you don’t need to do anything else with the compressed data, you might as well have a look at our previous post How to write to gzipped file in Go.

package main

import (
    "compress/gzip"
    "os"
)

func main() {
    content := "Hello World!"
    // Initialize gzip
    buf := &bytes.Buffer{}
    gzWriter := gzip.NewWriter(buf)
    gzWriter.Write([]byte(content))
    gzWriter.Close()
    // Convert buffer to
    ioutil.WriteFile("test.txt.gz", buf.Bytes(), 0644)
}

You can use zcat test.txt.gz to see that the content has been written to the file correctly.

Posted by Uli Köhler in Go
16
Nov
2019

How to write to gzipped file in Go

This example shows you how to directly write gzip-compressed data using Go’s gzip library.

First, open the file and use gzip.NewWriter() to create a new io.Writer on it:

// Open file
f, _ := os.Create("test.txt.gz")
defer f.Close()
// Create gzip writer
gzWriter := gzip.NewWriter(f)

Now you can gzWriter.Write(). Don’t forget to gzWriter.Close()

content := "Hello World!"
gzWriter.Write([]byte(content))
gzWriter.Close()

Full example:

package main

import (
    "compress/gzip"
    "os"
)

func main() {
    // Open file
    f, _ := os.Create("test.txt.gz")
    defer f.Close()
    // Create gzip writer
    gzWriter := gzip.NewWriter(f)
    // Write content and close
    content := "Hello World!"
    gzWriter.Write([]byte(content))
    gzWriter.Close()
}

You can use zcat test.txt.gz to see that the content has been written to the file correctly.

Posted by Uli Köhler in Go
16
Nov
2019

Go minimal ‘Write file’ example

This is the minimal example that writes a string (Hello World! in this example) to a file (test.txt in this example) using Go.

package main

import "io/ioutil"

func main() {
    content := "Hello World!"
    ioutil.WriteFile("test.txt", []byte(content), 0644)
}

Note that this example:

  • Creates the file with permission mode 0644, i.e. only the owner can write but others can read.
  • Encodes the text as UTF-8
Posted by Uli Köhler in Go
16
Nov
2019

Go equivalent of Python’s io.BytesIO

io.BytesIO in Python 3.x provides a convenient way of having a file-like object that actually streams to/from memory.

In Go, the equivalent problem is to have a io.Reader and/or and io.Writer (i.e. the equivalent of Python’s file-like object) that is backed by a []byte or a string.

Solution: Use bytes.Buffer !

// Initialize an empty buffer (e.g. for writing)
buf := &bytes.Buffer{}

// Initialize a buffer with a []byte content (e.g. for reading)
myBytes := ...
buf := bytes.NewBuffer(myBytes)

// Initialize a buffer with string
myStr := "test 123"
buf := bytes.NewBufferString(myStr)
Posted by Uli Köhler in Go
16
Nov
2019

How to download and parse HTML page in Go

This example uses goquery to request a HTML page (https://techoverflow.net) via the Go net/http client and then uses goquery and a simple CSS-style query to select the <title>...</title> HTML tag and print it’s content.

package main

import (
    "fmt"
    "log"
    "net/http"

    "github.com/PuerkitoBio/goquery"
)

func main() {
    // Perform request
    resp, err := http.Get("https://techoverflow.net")
    if err != nil {
        print(err)
        return
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read & parse response data
    doc, err := goquery.NewDocumentFromReader(resp.Body)
    if err != nil {
        log.Fatal(err)
    }
    // Print content of <title></title>
    doc.Find("title").Each(func(i int, s *goquery.Selection) {
        fmt.Printf("Title of the page: %s\n", s.Text())
    })
}

Example output:

Title of the page: TechOverflow

 

Posted by Uli Köhler in Go
16
Nov
2019

A simple reverse proxy example in Go

This example shows you a Go HTTP Server that forwards requests to an upstream Server using a HTTP client. Note that this example does not stream the upstream server’s responses but downloads them to RAM and then serves them to the client (hence you might need to improve upon this example if you intend to serve large files).

Also, note that this example does not implement proper error handling for the upstream request since it’s only intended to serve as a basic starting point for you to develop your own reverse proxy implementation.

package main

import (
    "fmt"
    "io/ioutil"
    "log"
    "net/http"
)

func main() {
    client := &http.Client{}
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
        // Perform request
        url := "https://techoverflow.net" + r.URL.Path
        req, _ := http.NewRequest(r.Method, url, r.Body)
        req.Header = r.Header
        resp, _ := client.Do(req)
        // Cleanup when this function ends
        defer resp.Body.Close()
        // Copy headers from request to response
        header := w.Header()
        for name, headers := range resp.Header {
            // Iterate all headers with one name (e.g. Content-Type)
            for _, hdr := range headers {
                header.Add(name, hdr)
            }
        }
        // Read all the response data into a []byte
        body, _ := ioutil.ReadAll(resp.Body)
        // Write header & body
        w.WriteHeader(resp.StatusCode)
        w.Write(body)
    })
    // log.Fatal shows you if there is an error like the
    //  port already being used
    fmt.Println("Listening on port 8080")
    log.Fatal(http.ListenAndServe(":8080", nil))
}

Further reading:

Posted by Uli Köhler in Go
16
Nov
2019

Iterating HTTP client response headers in Go

In this example we iterate all the HTTP headers the server sends back after a HTTP request made with the net/http Go library.

for name, headers := range resp.Header {
    // Iterate all headers with one name (e.g. Content-Type)
    for _, hdr := range headers {
        println(name + ": " + hdr)
    }
}

Full example:

package main

import (
    "net/http"
)

func main() {
    // Perform request
    resp, err := http.Get("https://ipv4.techoverflow.net/api/get-my-ip")
    if err != nil {
        print(err)
        return
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the headers
    for name, headers := range resp.Header {
        // Iterate all headers with one name (e.g. Content-Type)
        for _, hdr := range headers {
            println(name + ": " + hdr)
        }
    }
}

This example will print, for example:

Content-Type: application/octet-stream
Content-Type: text/plain charset=UTF-8
Content-Length: 11
Access-Control-Allow-Origin: *
Access-Control-Allow-Methods: GET, OPTIONS
Server: nginx/1.14.0 (Ubuntu)
Date: Sat, 16 Nov 2019 00:27:05 GMT

 

Posted by Uli Köhler in Go
16
Nov
2019

Go HTTP Server minimal example

package main

import (
    "fmt"
    "log"
    "net/http"
)

func main() {
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
        fmt.Fprintf(w, "Hello world!")
    })

    // log.Fatal shows you if there is an error like the
    //  port already being used
    log.Fatal(http.ListenAndServe(":8080", nil))
}

Save this file as Main.go in a directory called GoHTTPServer, run go build && ./GoHTTPServer. Then, open http://localhost:8080 in your browser and see the result for yourself.

Posted by Uli Köhler in Allgemein
16
Nov
2019

How to get external IPv4/IPv6 address in Go

You can use TechOverflow’s IPv4 HTTP API & IPv6 HTTP API within Go:

import (
    "io/ioutil"
    "net/http"
)

func GetExternalIPv4Address() (string, error) {
    // Perform request
    resp, err := http.Get("https://ipv4.techoverflow.net/api/get-my-ip")
    if err != nil {
        return "", err
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the response data into a []byte
    body, err := ioutil.ReadAll(resp.Body)
    // Decode & print
    return string(body), nil
}

func GetExternalIPv6Address() (string, error) {
    // Perform request
    resp, err := http.Get("https://ipv6.techoverflow.net/api/get-my-ip")
    if err != nil {
        return "", err
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the response data into a []byte
    body, err := ioutil.ReadAll(resp.Body)
    // Decode & print
    return string(body), nil
}

Usage example:

package main

func main() {
    v4, _ := GetExternalIPv4Address()
    v6, _ := GetExternalIPv6Address()
    println(v4)
    println(v6)
}

If you save both files in a directory named GoIPAddress, you can run

$ go build
$ ./GOIPAddress
31.190.168.110
2a03:4012:2:1022::1

 

 

Posted by Uli Köhler in Go
15
Nov
2019

Go HTTP client minimal example

This example gets the current IPv4 address from TechOverflow’s IP address HTTP API How to get your current IPv4 address using wget.

package main

import (
    "io/ioutil"
    "net/http"
)

func main() {
    // Perform request
    resp, err := http.Get("https://ipv4.techoverflow.net/api/get-my-ip")
    if err != nil {
        print(err)
        return
    }
    // Cleanup when this function ends
    defer resp.Body.Close()
    // Read all the response data into a []byte
    body, err := ioutil.ReadAll(resp.Body)
    // Decode & print
    println(string(body))
}

Save as Main.go in a new project directory (e.g. GoHttpTest) and run go build in that directory.
After that, you can run ./GoHttpTest which should print your IPv4 adress. Example:

uli@server ~/GoHttpTest % go build
uli@server ~/GoHttpTest % ./GoHttpTest 
91.59.80.56

 

Posted by Uli Köhler in Allgemein, Go
12
Nov
2019

Simulating survival data for Kaplan-Meier plots in Python

Libraries like lifelines provide a plethora of example datasets that one can work with. However, for many tasks you need to simulate specific behaviour in survival curves.

In this post, we demonstrate a simple algorithm to generate survival data in a format comparable to the one used in the lifelines example datasets like load_leukemia().

The generation algorithm is based on the following assumptions:

  • There is a strict survival plateau with a given survival probability starting at a given point in time
  • The progression from 100% survival, t=0 to the survival plateau is approximately linear (i.e. if you would generate an infinite number of datapoints, the survival curve would be linear)
  • No censoring events shall be generated except for censoring all surviving participants at the end point of the timeline.

Code:

import numpy as np
import random
from lifelines import KaplanMeierFitter

def simulate_survival_data_linear(N, survival_plateau, t_plateau, t_end):
    """
    Generate random simulated survival data using a linear model
    
    Keyword parameters
    ------------------
    N : integer
        Number of entries to generate
    survival_plateau : float
        The survival probability of the survival plateau
    t_plateau : float
        The time point where the survival plateau starts
    t_end : float
        The time point where all surviving participants will be censored.
    
    Returns
    -------
    A dict with "Time" and "Event" numpy arrays: 0 is censored, 1 is event
    """
    data = {"Time": np.zeros(N), "Event": np.zeros(N)}

    for i in range(N):
        r = random.random()
        if r <= survival_plateau:
            # Event is censoring at the end of the time period
            data["Time"][i] = t_end
            data["Event"][i] = 0
        else: # Event occurs
            # Normalize where we are between 100% and the survival plateau
            p = (r - survival_plateau) / (1 - survival_plateau)
            # Linear model: Time of event linearly depends on uniformly & randomly chosen position
            #  in range (0...tplateau)
            t = p * t_plateau
            data["Time"][i] = t
            data["Event"][i] = 1
    return data

# Example usage
data1 = simulate_survival_data_linear(250, 0.2, 18, 24)
data2 = simulate_survival_data_linear(250, 0.4, 17.2, 24)

Given data1 and data2 (see the usage example at the end of the code) you can plot them using

# Plot bad subgroup
kmf1 = KaplanMeierFitter()
kmf1.fit(data1["Time"], event_observed=data1["Event"], label="Bad subgroup")
ax = kmf1.plot()

# Plot good subgroup
kmf2 = KaplanMeierFitter()
kmf2.fit(data2["Time"], event_observed=data2["Event"], label="Good subgroup")
ax = kmf2.plot(ax=ax)

# Set Y axis to fixed scale
ax.set_ylim([0.0, 1.0])

Thi

Do not want a survival plateau?

Just set t_end = t_survival:

# Example usage
data1 = simulate_survival_data_linear(250, 0.2, 24, 24)
data2 = simulate_survival_data_linear(250, 0.4, 24, 24)
# Code to plot: See above

What happens if you have a low number of participants?

Let’s use 25 instead of 250 as above:

# Example usage
data1 = simulate_survival_data_linear(25, 0.2, 24, 24)
data2 = simulate_survival_data_linear(25, 0.4, 24, 24)
# Plot code: See above

Although we generated the data with the same data, the difference is much less clear in this example, especially towards the end of the timeline (note however that the data is generated randomly, so you might see a different result). You can see a large portion of the confidence intervals overlappings near t=24. In other words, based on this data it is not clear that the two groups of patients are significantly different (in other words, P \geq 0.05)

Posted by Uli Köhler in Python, Statistics
12
Nov
2019

How to use custom legend label in lifelines Kaplan-Meier plot?

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you want a custom label instead of KM_estimates to appear in the legend?

Use kmf.fit(..., label='Your label'). Since we use the leukemias dataset for this example, we use the label 'Leukemia'

Full example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
# Load datasets
df_leukemia = load_leukemia()

# Fit & plot leukemia dataset
kmf_leukemia = KaplanMeierFitter()
kmf_leukemia.fit(df_leukemia['t'], df_leukemia['Rx'], label="Leukemia")
ax = kmf_leukemia.plot()
# Set Y axis to fixed scale
ax.set_ylim([0.0, 1.0])

Posted by Uli Köhler in Python, Statistics
12
Nov
2019

How plot multiple Kaplan-Meier curves using lifelines

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you want to plot multiple survival curves?

The call to kmf.plot() returns a Matplotlib ax object which you can use on a second kmf2.plot() call als argument: kmf2.plot(ax=ax).

Full example (note that we also set a fixed Y range of [0.0, 1.0], see How to make Y axis start from 0 in lifelines Kaplan-Meier plots):

from lifelines.datasets import load_leukemia, load_lymphoma
from lifelines import KaplanMeierFitter
# Load datasets
df_leukemia = load_leukemia()
df_lymphoma = load_lymphoma()

# Fit & plot leukemia dataset
kmf_leukemia = KaplanMeierFitter()
kmf_leukemia.fit(df_leukemia['t'], df_leukemia['Rx'], label="Leukemia")
ax = kmf_leukemia.plot()

# Fit & plot lymphoma dataset
kmf_lymphoma = KaplanMeierFitter()
kmf_lymphoma.fit(df_lymphoma['Time'], df_lymphoma['Censor'], label="Lymphoma")
ax = kmf_lymphoma.plot(ax=ax)

# Set Y axis to fixed scale
ax.set_ylim([0.0, 1.0])

Posted by Uli Köhler in Python, Statistics
12
Nov
2019

How to make Y axis start from 0 in lifelines Kaplan-Meier plots

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you want to make the Y axis start from 0.0 and not from approx. 0.2 as in this example?

Remember that lifelines just calls matplotlib internally and km.plot() returns the ax object that you can use to manipulate the plot. In this specific case, you can use

ax.set_ylim([0.0, 1.0])

to stop autoranging the Y axis and set its range to fixed [0.0, 1.0].

Full example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
ax = kmf.plot()
# Set Y axis range to [0.0, 1.0]
ax.set_ylim([0.0, 1.0])

Posted by Uli Köhler in Python, Statistics
12
Nov
2019

How to hide confidence interval in lifelines Kaplan-Meier plots

Using the lifelines library, you can easily plot Kaplan-Meier plots, e.g. as seen in our previous post Minimal Python Kaplan-Meier Plot example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot()

What if you just want to show the dark blue curve and hide the light-blue confidence interval?

Easy: Just use km.plot(ci_show=False). ci in ci_show means confidence interval. Example:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
df = load_leukemia()

kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
kmf.plot(ci_show=False)

Posted by Uli Köhler in Python, Statistics
12
Nov
2019

Minimal Python Kaplan-Meier Plot example

Install the lifelines library:

sudo pip3 install lifelines

Now you can use this snippet to create a basic Kaplan-Meier plot from an example dataset included with the library:

from lifelines.datasets import load_leukemia
from lifelines import KaplanMeierFitter
# Load example dataset
df = load_leukemia()

# Create model from data
kmf = KaplanMeierFitter()
kmf.fit(df['t'], df['Rx']) # t = Timepoints, Rx: 0=censored, 1=event
# Plot model's survival curve
kmf.plot()

Note that different datasets might have different names for the time column (t in this example) and the event/censoring column (Rx in this example)

We exported the plot using

import matplotlib.pyplot as plt 
plt.savefig("Kaplan-Meier-Example-Leukemias.svg")

 

Posted by Uli Köhler in Python, Statistics
10
Nov
2019

How to sort files by modification date in Python

You can use sorted() to sort the files, and use key=lambda t: os.stat(t).st_mtime to sort by modification time. This will sort with ascending modification time (i.e. most recently modified file last).

In case you want to sort with descending modification time (i.e. most recently modified file first), use key=lambda t: -os.stat(t).st_mtime

Full example:

# List all files in the home directory
files = glob.glob(os.path.expanduser("~/*"))

# Sort by modification time (mtime) ascending and descending
sorted_by_mtime_ascending = sorted(files, key=lambda t: os.stat(t).st_mtime)
sorted_by_mtime_descending = sorted(files, key=lambda t: -os.stat(t).st_mtime)

 

Posted by Uli Köhler in Python
09
Nov
2019

How to read str from binary file in Python

When you have a file-like object in Python, .read() will always return bytes. You can use any of the following solutions to get a str from the binary file.

Option 1: Decode the bytes

You can call .decode() on the bytes. Ensure to use the right encoding. utf-8 is often correct if you don’t know what the encoding is, but

binary = myfile.read() # type: bytes
text = binary.decode("utf-8")

# Short version
text = myfile.read().decode("utf-8")

Option 2: Wrap the file so it appears like a file in text mode

Use io.TextIOWrapper like this:

import io

text_file = io.TextIOWrapper(myfile, encoding="utf-8")
text = text_file.read()
Posted by Uli Köhler in Python
09
Nov
2019

Wrap binary file-like object to get decoded text file-like object in Python

Problem:

In Python, you have a file-like object that reads binary data (e.g. if you open a file using open("my-file", "rb"))

You want to pass that file-like object to a function that expects a file-like object that expects a file-like object in text mode (i.e. where you can read str from, not bytes).

Solution:

Use io.TextIOWrapper:

with open("fp-lib-table", "rb") as infile:
    # infile.read() would return bytes
    text_infile = io.TextIOWrapper(infile)
    # text-infile.read() would return a str

In case you need to use a specific encoding, use encoding=...:

text_infile = io.TextIOWrapper(infile, encoding="utf-8")

 

Posted by Uli Köhler in Python

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