Programming languages

Apr

2020

Minimal ESP-IDF UART transmit example for ESP32 & PlatformIO

The following example writes the string CAFE to UART continously, waiting for 100ms in between:

#include <driver/gpio.h>
#include <driver/uart.h>
// Include FreeRTOS for delay
#include <freertos/FreeRTOS.h>
#include <freertos/task.h>

int app_main() {
    uart_config_t uart_config = {
        .baud_rate = 115200,
        .data_bits = UART_DATA_8_BITS,
        .parity    = UART_PARITY_DISABLE,
        .stop_bits = UART_STOP_BITS_1,
        .flow_ctrl = UART_HW_FLOWCTRL_DISABLE
    };
    uart_driver_install(UART_NUM_1, 2048, 0, 0, NULL, 0);
    uart_param_config(UART_NUM_1, &uart_config);
    uart_set_pin(UART_NUM_1, 10, 9, UART_PIN_NO_CHANGE, UART_PIN_NO_CHANGE);

    // Main loop
    while(true) {
        uart_write_bytes(UART_NUM_1, "CAFE", 5);
        vTaskDelay(100 / portTICK_RATE_MS);
    }
}

Apr

2020

ESP-IDF equivalent to Arduino delay()

You can use the FreeRTOS API to provide a delay similar to the Arduino delay() function in the ESP-IDF framework. FreeRTOS is included in the PlatformIO ESP-IDF default configuration.

First, include the FreeRTOS headers

// Include FreeRTOS for delay
#include <freertos/FreeRTOS.h>
#include <freertos/task.h>

After that, you can use vTaskDelay(...) to perform the delay. This example delays by 500ms:

vTaskDelay(500 / portTICK_RATE_MS);

You can use vTaskDelay() even if not using FreeRTOS tasks.

For a full example, refer to PlatformIO ESP-IDF ESP32 blink example

Apr

2020

How to set pin to output mode using ESP-IDF

Use this snippet to define a pin as output using the ESP-IDF framework (e.g. using PlatformIO):

gpio_config_t io_conf;
io_conf.intr_type = GPIO_PIN_INTR_DISABLE;
io_conf.mode = GPIO_MODE_OUTPUT;
// Define the pin here (e.g. (1ULL << 2) for GPIO9)
io_conf.pin_bit_mask = (1ULL << 2);
io_conf.pull_down_en = 0;
io_conf.pull_up_en = 0;
gpio_config(&io_conf);

The example above configures GPIO2 as an output. Use (1ULL << 3) to configure GPIO3 as an output

Apr

2020

How to fix ESP-IDF ‘undefined reference to app_main’

Problem:

You are trying to compile your C/C++ ESP8266/ESP32 firmware using the ESP-IDF framework. Your source code looks like this:

int main() {
    // ...
}

but you only see an error message like this:

.platformio/packages/toolchain-xtensa32/bin/../lib/gcc/xtensa-esp32-elf/8.2.0/../../../../xtensa-esp32-elf/bin/ld.exe: .pio\build\nodemcu-32s\esp-idf\esp32\libesp32.a(cpu_start.c.o):(.literal.main_task+0x18): undefined reference to `app_main'
.platformio/packages/toolchain-xtensa32/bin/../lib/gcc/xtensa-esp32-elf/8.2.0/../../../../xtensa-esp32-elf/bin/ld.exe: .pio\build\nodemcu-32s\esp-idf\esp32\libesp32.a(cpu_start.c.o): in function `main_task':
.platformio\packages\framework-espidf\components\esp32/cpu_start.c:540: undefined reference to `app_main'
collect2.exe: error: ld returned 1 exit status
*** [.pio\build\nodemcu-32s\firmware.elf] Error 1

Solution:

For the ESP-IDF framework, the main() function needs to be named app_main():

int app_main() {
    // ...
}

See PlatformIO ESP-IDF ESP32 blink example for a complete example.

Apr

2020

PlatformIO ESP-IDF ESP32 blink example

This example is the equivalent of the simple Arduino blink example for ESP32 boards when using the ESP-IDF framework:

#include <driver/gpio.h>
// Include FreeRTOS for delay
#include <freertos/FreeRTOS.h>
#include <freertos/task.h>

#define LED 2 // LED connected to GPIO2

int app_main() {
    // Configure pin
    gpio_config_t io_conf;
    io_conf.intr_type = GPIO_PIN_INTR_DISABLE;
    io_conf.mode = GPIO_MODE_OUTPUT;
    io_conf.pin_bit_mask = (1ULL << LED);
    io_conf.pull_down_en = 0;
    io_conf.pull_up_en = 0;
    gpio_config(&io_conf);

    // Main loop
    while(true) {
        gpio_set_level(LED, 0);
        vTaskDelay(500 / portTICK_RATE_MS);
        gpio_set_level(LED, 1);
        vTaskDelay(500 / portTICK_RATE_MS);
    }
}

Apr

2020

How to auto-set Windows audio balance to a specific L-R difference using Python

When you can’t place your speakers equally far from your ears, you need to adjust the audio balance in order to compensate for the perceived difference in volume.

Windows allows you to compensate the audio volume natively using the system settings – however it has one critical issue: If you ever set your audio volume to zero, your balance settings get lost and you need to click through plenty of dialogs in order to re-configure it.

In our previous post How to set Windows audio balance using Python we showed how tp use the pycaw library to (see that post for installation instructions etc).

The following Python script can be run to set the audio balance to. It has been designed to keep the mean (i.e. L+R) audio level in dB when adjusting the volume (i.e. it will not change the overall volume and hence avoid blowing out your eardrums) and will not do any adjustment if the balance is already within 0.1 dB.

Set desiredDelta to your desired left-right difference in dB (positive values mean that the left speaker will be louder than the right speaker)!

from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume
import math

# Get default audio device using PyCAW
devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(
    IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))

# Get current volume of the left channel
currentVolumeLeft = volume.GetChannelVolumeLevel(0)
# Set the volume of the right channel to half of the volume of the left channel
volumeL = volume.GetChannelVolumeLevel(0)
volumeR = volume.GetChannelVolumeLevel(1)
print(f"Before adjustment: L={volumeL:.2f} dB, R={volumeR:.2f} dB")

desiredDelta = 6.0 # Desired delta between L and R. Positive means L is louder!

delta = abs(volumeR - volumeL)
mean = (volumeL + volumeR) / 2.

# Re-configure balance if delta is not 
if abs(delta - desiredDelta) > 0.1:
    # Adjust volume
    volume.SetChannelVolumeLevel(0, mean + desiredDelta/2., None) # Left
    volume.SetChannelVolumeLevel(1, mean - desiredDelta/2., None) # Right
    # Get & print new volume
    volumeL = volume.GetChannelVolumeLevel(0)
    volumeR = volume.GetChannelVolumeLevel(1)
    print(f"After adjustment: L={volumeL:.2f} dB, R={volumeR:.2f} dB")
else:
    print("No adjustment neccessary")

Apr

2020

How to set Windows audio balance using Python

In our previous post we showed how to set the Windows audio volume using pycaw.

First, we install the library using

pip install pycaw

Note: pycaw does not work with WSL (Windows Subsystem for Linux)! You actually need to install it using a Python environment running on Windows. I recommend Anaconda.

In order to set the audio balance, we can use volume.SetChannelVolumeLevel(...):

from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume
import math

# Get default audio device using PyCAW
devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(
    IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))

# Get current volume of the left channel
currentVolumeLeft = volume.GetChannelVolumeLevel(0)
# Set the volume of the right channel to half of the volume of the left channel
volume.SetChannelVolumeLevel(1, currentVolumeLeft - 6.0, None)
# NOTE: -6.0 dB = half volume !

Note that by convention, the left channel is channel 0 and the right channel is channel 1. Depending on the type of sound card, there might be as few as 1 channel (e.g. a mono headset) or many channels like in a multichannel USB audio interface. use volume.GetChannelCount() to get the number of channels.

Apr

2020

How to set Windows audio volume using Python

We can use the pycaw library to set the Windows Audio volume using Python.

First, we install the library using

pip install pycaw

Note: pycaw does not work with WSL (Windows Subsystem for Linux)! You actually need to install it using a Python environment running on Windows. I recommend Anaconda.

Now we can set the volume to half the current volume using this script:

from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume
import math

# Get default audio device using PyCAW
devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(
    IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))

# Get current volume 
currentVolumeDb = volume.GetMasterVolumeLevel()
volume.SetMasterVolumeLevel(currentVolumeDb - 6.0, None)
# NOTE: -6.0 dB = half volume !

Mar

2020

How to fix Python ‘ValueError: Namespace GnomeDesktop not available’ on Ubuntu

Problem:

On Ubuntu, you are trying to run a Python script using the gi package and GnomeDesktop but you are seeing this stacktrace:

Traceback (most recent call last):
  File "myscript.py", line 48, in <module>
    gi.require_version('GnomeDesktop', '3.0')
  File "/usr/lib/python3/dist-packages/gi/__init__.py", line 130, in require_version
    raise ValueError('Namespace %s not available' % namespace)
ValueError: Namespace GnomeDesktop not available

Solution

Install gir1.2-gnomedesktop-3.0:

sudo apt -y install gir1.2-gnomedesktop-3.0

and retry running your script.

Feb

2020

Computing the CRC8-ATM CRC in Python

The 8-bit CRC8-ATM polynomial is used in many embedded applications, including Trinamic UART-controlled stepper motor drivers like the TMC2209:

\text{CRC} = x^8 + x^2 + x^1 + x^0

The following code provides an example on how to compute this type of CRC in Python:

def compute_crc8_atm(datagram, initial_value=0):
    crc = initial_value
    # Iterate bytes in data
    for byte in datagram:
        # Iterate bits in byte
        for _ in range(0, 8):
            if (crc >> 7) ^ (byte & 0x01):
                crc = ((crc << 1) ^ 0x07) & 0xFF
            else:
                crc = (crc << 1) & 0xFF
            # Shift to next bit
            byte = byte >> 1
    return crc

This code has been field-verified for the TMC2209.

Feb

2020

MicroPython ESP32 minimal UART example

This example shows how to use UART on the ESP32 using MicroPython. In this example, we use UART1 which is mapped to pins GPIO9 (RX) and GPIO10 (TX).

from machine import UART
uart = UART(1, 115200) # 1st argument: UART number: Hardware UART #1

# Write
uart.write("test")

# Read
print(uart.read()) # Read as much as possible using

Don’t know how to upload the file to MicroPython so it is automatically run on boot?

To flash over USB, see How to upload files to MicroPython over USB/serial
To flash over the network (with WebREPL already enabled), see How to upload files to MicroPython using WebREPL using webrepl_cli.py

Feb

2020

How to fix ESP32 MicroPython ‘ValueError: pin can only be input’

Problem:

You are trying to initialize an ESP32 pin in MicroPython using

import machine
machine.Pin(34, machine.Pin.OUT)

but you see an error message like

>>> machine.Pin(34, machine.Pin.OUT)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: pin can only be input

Solution:

On the ESP32, pins with numbers >= 34 are input-only pins!

You need to use other pins < 34 if you need output capability!

For reference, see the relevant MicroPython source code section:

// configure mode
if (args[ARG_mode].u_obj != mp_const_none) {
    mp_int_t pin_io_mode = mp_obj_get_int(args[ARG_mode].u_obj);
    if (self->id >= 34 && (pin_io_mode & GPIO_MODE_DEF_OUTPUT)) {
        mp_raise_ValueError("pin can only be input");
    } else {
        gpio_set_direction(self->id, pin_io_mode);
    }
}

Feb

2020

How to upload files to MicroPython over USB/serial

In this post we will investigate how to connect to a wireless network on boot

First, install ampy – a tool to modify the MicroPython filesystem over a serial connection.

sudo pip3 install adafruit-ampy

Now prepare your script – we’ll use main.py in this example.

Upload the file to the board:

ampy -p /dev/ttyUSB* put main.py

This only takes about 2-4 seconds. In case ampy is still running after 10 seconds, you might need to

Stop ampy (Ctrl+C), reset the board using the RESET button and retry the command
Stop ampy (Ctrl+C). Detach USB and ensure the board is powered off (and not powered externally). Re-Attach USB and retry the command.
In case that doesn’t help, try re-flashing your board with the most recent version of MicroPython. See How to flash MicroPython to your ESP32 board in 30 seconds. This will also clear the internal filesystem and hence remove any file that might cause failure to boot properly.

Feb

2020

MicroPython ESP32 blink example

This MicroPython code blinks GPIO2 which is connected to the LED on most ESP32 boards.

import machine
import time
led = machine.Pin(2, machine.Pin.OUT)
while True:
    led.value(1)
    time.sleep(1)
    led.value(0)
    time.sleep(1)

Don’t know how to upload the file to MicroPython so it is automatically run on boot?

To flash over USB, see How to upload files to MicroPython over USB/serial
To flash over the network (with WebREPL already enabled), see How to upload files to MicroPython using WebREPL using webrepl_cli.py

Feb

2020

How to run WebREPL without webrepl_setup in MicroPython

Problem:

You want to enable WebREPL on your MicroPython board using

import webrepl
webrepl.start()

but it is only showing this error message:

WebREPL is not configured, run 'import webrepl_setup'

However, you want to configure WebREPL programmatically instead of manually running it on every single board.

Solution:

Use

import webrepl
webrepl.start(password="Rua8ohje")

This will circumvent webrepl_setup completely and is compatible with an automated setup process.

Note: At the time of writing this you can only use passwords with 8 characters max! (see How to fix MicroPython WebREPL ValueError in File „webrepl.py“, line 72, in start )

Feb

2020

How to fix MicroPython WebREPL ValueError in File “webrepl.py”, line 72, in start

Problem:

You want to configure your MicroPython WebREPL programmatically using webrepl.start(password="...") but you see a stacktrace like

>>> webrepl.start(password="Rua8ohjedo")
Traceback (most recent call last):
 File "<stdin>", line 1, in <module>
 File "webrepl.py", line 72, in start
ValueError:

Solution:

Use a shorter password with 8 characters max:

webrepl.start(password="Rua8ohje")

Feb

2020

How to autoconnect to Wifi using MicroPython on your ESP32 board

In this post we will investigate how to connect to a wireless network on boot

First, install ampy – a tool to modify the MicroPython filesystem over a serial connection.

sudo pip3 install adafruit-ampy

Now download main.py and save it in your current working directory and insert your wifi credentials:

import network
station = network.WLAN(network.STA_IF)
station.active(True)
station.connect("YourWifiName", "EnterYourWifiPasswordHere")

Upload the file to the board:

ampy -p /dev/ttyUSB* put main.py

In case ampy shows no output within 5 seconds, try resetting the board, waiting for 5-10 seconds and retrying the upload using ampy

Note: You can list the files on the board’s filesystem using

ampy -p /dev/ttyUSB0 ls

You can verify the content of main.py using

ampy -p /dev/ttyUSB0 get main.py

Feb

2020

How to fix Nextcloud Refused to send form data to /login/v2/grant because it violates the following Content Security Policy directive: form-action ‘self’

Problem:

When trying to connect using the Nextcloud client, during the Flow v2 authorization step where you open a page in the browser to authorize the client, you see an error message in the JS console like

Refused to send form data to 'http://nextcloud.mydomain.com/login/v2/grant' because it violates the following Content Security Policy directive: "form-action 'self'".

Solution:

Add

'overwriteprotocol' => 'https',

after this line:

'version' => '18.0.0.10',

in your nextcloud/config/config.php.

Feb

2020

How to read IDF diabetes statistics in Python using Pandas

The International Diabetes Foundation provides a Data portal with various statistics related to diabetes.

In this post we’ll show how to read the Diabetes estimates (20-79 y) / People with diabetes, in 1,000s data export in CSV format using pandas.

First download IDF (people-with-diabetes--in-1-000s).csv from the data page.

Now we can parse the CSV file:

import pandas as pd

# Download at https://www.diabetesatlas.org/data/en/indicators/1/
df = pd.read_csv("IDF (people-with-diabetes--in-1-000s).csv")
# Parse year columns to obtain floats and multiply by thousands factor. Pandas fails to parse values like "12,345.67"
for column in df.columns:
    try:
        int(column)
        df[column] = df[column].apply(lambda s: None if s == "-" else float(s.replace(",", "")) * 1000)
    except:
        pass

As you can see in the postprocessing step, the number of diabetes patients are given in 1000s in the CSV, so we multiply them by 1000 to obtain the actual numbers.

If you want to modify the data columns (i.e. the columns referring to year), you can use this simple template:

for column in df.columns:
    try:
        int(column) # Will raise ValueError() if column is not a year number
        # Whatever you do here will only be applied to year columns
        df[column] = df[column] * 0.75 # Example on how to modify a column
        # But note that if your code raises an Exception, it will be ignored!
    except:
        pass

Let’s plot some data:

regions = df[df["Type"] == "Region"] # Only regions, not individual countries

from matplotlib import pyplot as plt
plt.style.use("ggplot")
plt.gcf().set_size_inches(20,4)
plt.ylabel("Diabetes patients [millions]")
plt.xlabel("Region")
plt.title("Diabetes patients in 2019 by region")
plt.bar(regions["Country/Territory"], regions["2019"] / 1e6)

Note that if you use a more recent dataset than the version I’m using the 2019 column might not exist in your CSV file. Choose an appropriate column in that case.

Feb

2020

Parsing World Population Prospects (WPP) XLSX data in Python

The United Nations provides the Word Population Prospects (WPP) dataset on geographic and age distribution of mankind as downloadable XLSX files.

Reading these files in Python is rather easy. First we have to find out how many rows to skip. For the 2019 WPP dataset this value is 16 since row 17 contains all the column headers. The number of rows to skip might be different depending on the dataset. We’re using WPP2019_POP_F07_1_POPULATION_BY_AGE_BOTH_SEXES.xlsx in this example.

We can use Pandas read_excel() function to import the dataset in Python:

import pandas as pd

df = pd.read_excel("WPP2019_INT_F03_1_POPULATION_BY_AGE_ANNUAL_BOTH_SEXES.xlsx", skiprows=16, na_values=["..."])

This will take a few seconds until the large dataset has been processed. Now we can check if skiprows=16 is the correct value. It is correct if pandas did recognize the column names correctly:

>>> df.columns
Index(['Index', 'Variant', 'Region, subregion, country or area *', 'Notes',
       'Country code', 'Type', 'Parent code', 'Reference date (as of 1 July)',
       '0-4', '5-9', '10-14', '15-19', '20-24', '25-29', '30-34', '35-39',
       '40-44', '45-49', '50-54', '55-59', '60-64', '65-69', '70-74', '75-79',
       '80-84', '85-89', '90-94', '95-99', '100+'],
      dtype='object')

Now let’s filter for a country:

russia = df[df["Region, subregion, country or area *"] == 'Russian Federation']

This will show us the population data for multiple years in 5-year intervals from 1950 to 2020. Now let’s filter for the most recent year:

russia.loc[russia["Reference date (as of 1 July)"].idxmax()]

This will show us a single dataset:

Index                                                 3255
Variant                                          Estimates
Region, subregion, country or area *    Russian Federation
Notes                                                  NaN
Country code                                           643
Type                                          Country/Area
Parent code                                            923
Reference date (as of 1 July)                         2020
0-4                                                9271.69
5-9                                                9350.92
10-14                                              8174.26
15-19                                              7081.77
20-24                                               6614.7
25-29                                              8993.09
30-34                                              12543.8
35-39                                              11924.7
40-44                                              10604.6
45-49                                              9770.68
50-54                                              8479.65
55-59                                                10418
60-64                                              10073.6
65-69                                              8427.75
70-74                                              5390.38
75-79                                              3159.34
80-84                                              3485.78
85-89                                              1389.64
90-94                                              668.338
95-99                                              102.243
100+                                                 9.407
Name: 3254, dtype: object

How can we plot that data? First, we need to select all the columns that contain age data. We’ll do this by manually inserting the name of the first such column (0-4) into the following code and assuming that there are no columns after the last age column:

>>> df.columns[df.columns.get_loc("0-4"):]
Index(['0-4', '5-9', '10-14', '15-19', '20-24', '25-29', '30-34', '35-39',
       '40-44', '45-49', '50-54', '55-59', '60-64', '65-69', '70-74', '75-79',
       '80-84', '85-89', '90-94', '95-99', '100+'],
      dtype='object')

Now let’s select those columns from the russia dataset:

most_recent_russia = russia.loc[russia["Reference date (as of 1 July)"].idxmax()]
age_columns = df.columns[df.columns.get_loc("0-4"):]

russian_age_data = most_recent_russia[age_columns]

Let’s have a look at the dataset:

>>> russian_age_data
0-4      9271.69
5-9      9350.92
10-14    8174.26
15-19    7081.77
20-24     6614.7
25-29    8993.09
30-34    12543.8
35-39    11924.7
40-44    10604.6
45-49    9770.68
50-54    8479.65
55-59      10418
60-64    10073.6
65-69    8427.75
70-74    5390.38
75-79    3159.34
80-84    3485.78
85-89    1389.64
90-94    668.338
95-99    102.243
100+       9.407

That looks useable, note however that the values are in thousands, i.e. we have to multiply the values by 1000 to obtain the actual estimates of the population. Let’s plot it:

from matplotlib import pyplot as plt
plt.style.use("ggplot")

plt.title("Age composition of the Russian population (2020)")
plt.ylabel("People in age group [Millions]")
plt.xlabel("Age group")
plt.gcf().set_size_inches(15,5)
# Data is given in thousands => divide by 1000 to obtain millions
plt.plot(russian_age_data.index, russian_age_data.as_matrix() / 1000., lw=3)

The finished plot will look like this:

Here’s our finished script:

#!/usr/bin/env python3
import pandas as pd
df = pd.read_excel("WPP2019_POP_F07_1_POPULATION_BY_AGE_BOTH_SEXES.xlsx", skiprows=16)
# Filter only russia
russia = df[df["Region, subregion, country or area *"] == 'Russian Federation']

# Filter only most recent estimate (1 row)
most_recent_russia = russia.loc[russia["Reference date (as of 1 July)"].idxmax()]
# Retain only value columns
age_columns = df.columns[df.columns.get_loc("0-4"):]
russian_age_data = most_recent_russia[age_columns]

# Plot!
from matplotlib import pyplot as plt
plt.style.use("ggplot")

plt.title("Age composition of the Russian population (2020)")
plt.ylabel("People in age group [Millions]")
plt.xlabel("Age group")
plt.gcf().set_size_inches(15,5)
# Data is given in thousands => divide by 1000 to obtain millions
plt.plot(russian_age_data.index, russian_age_data.as_matrix() / 1000., lw=3)

# Export as SVG
plt.savefig("russian-demographics.svg")

Programming languages

Minimal ESP-IDF UART transmit example for ESP32 & PlatformIO

ESP-IDF equivalent to Arduino delay()

How to set pin to output mode using ESP-IDF

How to fix ESP-IDF ‘undefined reference to app_main’

Problem:

Solution:

PlatformIO ESP-IDF ESP32 blink example

How to auto-set Windows audio balance to a specific L-R difference using Python

How to set Windows audio balance using Python

How to set Windows audio volume using Python

How to fix Python ‘ValueError: Namespace GnomeDesktop not available’ on Ubuntu

Problem:

Solution

Computing the CRC8-ATM CRC in Python

MicroPython ESP32 minimal UART example

How to fix ESP32 MicroPython ‘ValueError: pin can only be input’

Problem:

Solution:

How to upload files to MicroPython over USB/serial

MicroPython ESP32 blink example

How to run WebREPL without webrepl_setup in MicroPython

Problem:

Solution:

How to fix MicroPython WebREPL ValueError in File “webrepl.py”, line 72, in start

Problem:

Solution:

How to autoconnect to Wifi using MicroPython on your ESP32 board

How to fix Nextcloud Refused to send form data to /login/v2/grant because it violates the following Content Security Policy directive: form-action ‘self’

Problem:

Solution:

How to read IDF diabetes statistics in Python using Pandas

Parsing World Population Prospects (WPP) XLSX data in Python

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