backing off – extending the wait for server response via python

TL;DR; Add a decorator to avoid server timeouts

When getting swisstopo altitude profiles the response time is in general quite good but just sometimes I ran into timeouts, be it due to my bad connection or too many requests to the server. To amend I added this decorator that you can get as the most up-to-date version from my GitHub gists to the original swisstopo function (or other functions that might run into some form of timeout)

def exponential_retry(max_retries, delay):
    """Retry a request with exponentially increasing (slightly random) time in between tries"""
    """Usage before def of another function via @exponential_retry(5, 1) """
    def decorator_exponential_retry(func):
        import functools
        @functools.wraps(func)
        def wrapper_exponential_retry_decorator(*args, **kwargs):
            import random
            retries = 0
            while retries <= max_retries:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    print(f"Attempt {retries + 1} failed: {e}")
                    retries += 1
                    sleeptime = (delay * 2 ** retries + random.uniform(0, 1))
                    print(f"Retrying in {sleeptime:.2f} seconds...")
                    time.sleep(sleeptime)
            raise Exception("Maximum amount of retries reached, too many timeouts/errors.")
        return wrapper_exponential_retry_decorator
    return decorator_exponential_retry
    
 
@exponential_retry(5, 1)
def get_swisstopo_elevation_profile(...):
    .# source code of get_swisstopo_elevation_profile
    ...

My implementation of a touchdown event via javascript

TL;DR; The below code can be added as a script to your page to implement a touchdown event detection and directly attach it to a “menu” element

async function swipedetect(el, callback, threshold=50, minimumTime=150, allowedTime=2000){

    var touchsurface = el,
    swipedir,
    startX,
    startY,
    distX,
    distY,
    threshold = threshold, //required min distance traveled to be considered swipe in X
//    restraintX = restraintX, // maximum distance allowed at the same time in perpendicular direction in X
//    thresholdY = thresholdY, //required min distance traveled to be considered swipe in Y
//    restraintY = restraintY, // maximum distance allowed at the same time in perpendicular direction in Y
    minimumTime = minimumTime, // maximum time allowed to travel that distance
    allowedTime = allowedTime, // maximum time allowed to travel that distance
    elapsedTime,
    startTime,
    handleswipe = callback || function(swipedir){}

    touchsurface.addEventListener('touchstart', function(e){
        var touchobj = e.changedTouches[0]
        swipedir = 'none'
        dist = 0
        startX = touchobj.pageX
        startY = touchobj.pageY
        startTime = new Date().getTime() // record time when finger first makes contact with surface
        // e.preventDefault()
    }, false)

    touchsurface.addEventListener('touchmove', function(e){
        e.preventDefault() // prevent scrolling when inside DIV
    }, false)

    touchsurface.addEventListener('touchend', function(e){
        var touchobj = e.changedTouches[0]
        distX = touchobj.pageX - startX; // get horizontal dist traveled by finger while in contact with surface
        distY = touchobj.pageY - startY; // get vertical dist traveled by finger while in contact with surface
        dist = distY * distY + distX * distX;
        dist = Math.sqrt(dist);
        elapsedTime = new Date().getTime() - startTime; // get time elapsed
        // calculate the angle of the movement
        angle = (Math.atan2(distY, distX) / Math.PI * 180)
        // convert angle to a sector of the movement
        // offsetting it by 45 degreees to get the movement easier.
        // and ensuring its positive
        sector = (angle + 45 + 360) % 360;
        sector = Math.floor(sector/90);
        if (elapsedTime >= minimumTime && elapsedTime <= allowedTime && dist >= threshold){ // first condition for a swipe met
            switch (sector) {
               case 0: swipedir = "right"; break;
               case 1: swipedir = "up"; break;
               case 2: swipedir = "left"; break;
               case 3: swipedir = "down"; break;
            }
        }
        handleswipe(swipedir)
        if (dist >= threshold) {
          e.preventDefault()
        }
    }, false)
}

async function swipe_enable(elementid='menu', table={'right':'a', 'up':'w', 'left':'d', 'down':'s', 'none': null}) {
  var el = document.getElementById(elementid);
  if (el) {
    swipedetect(el, async function(swipedir){
      //swipedir contains either "none", "left", "right", "top", or "down"
      let key = table[swipedir];
      document.dispatchEvent(new KeyboardEvent('keypress', {'key': key}));
    })
  }
}

Handling a touchdown event via vanilla JS is nothing new, and I also took the initial implementation from a website I cannot find anymore. The structure was similar to this gist and the related discussion, as in initially I simply added a touchdown but the detection of right/left/up/down was patchy until I also added the direction sector. Additionally, I did not want to attach it all the time to each element etc. but instead added another function that handles the attaching.

Now I can simply have the above in a js-lib file and source it on our data visualisation page, then call swipe_enable() in the doc.ready function and be certain that swiping is handled on the corresponding element (with selects in this case). This makes usage of the page far easier on mobile devices; highly relevant if you are in the field like in CLOUDLAB and your phone is the only thing available due to the windy/rainy/snowy weather.

Get the most recent census data from the Basler Atlas

TL;DR;

Get the census data (and more) from the Basler Atlas that are updated by the Statistisches Amt Basel. The up-to-date version can be found on my GitHub Gists. Don’t forget to add the data source, i.e. the Stat. Amt Basel when you use their data. – it is being added automatically to the “meta” part in the datacontainer (in addition to the URL, the name and short name of the dataset).

import datetime


headers = {'User-Agent': 'Mozilla/5.0'}


def data2csv(data,
             outpath='./',
             prefix='',
             suffix='',
             filesep='_',
             datasep=',',
             ext='.csv',
             quiet=True,
             ):

    import os
    if isinstance(data, dict) and 'data' not in data.keys():
        of = []
        for key in data.keys():
            _of = data2csv(data[key],
                           outpath=outpath,
                           prefix=prefix,
                           filesep=filesep,
                           datasep=datasep,
                           ext=ext,
                           quiet=quiet,
                           )
            if isinstance(_of, list):
                of += _of
            else:
                of.append(_of)
        return of

    outpath = os.path.expanduser(outpath)
    filename = filesep.join([prefix,
                             data['meta']['theme'],
                             data['meta']['subtheme'],
                             _nivgeo2nicename(data['meta']['nivgeo']),
                             suffix,
                             ])
    filename = filename.lstrip(filesep).rstrip(filesep) + ext
    os.makedirs(outpath, exist_ok=True)
    if not quiet:
        print('Saving as', outpath+filename)
    with open(outpath+filename, 'w') as file_obj:
        file_obj.writelines(datasep.join(data['header']) + '\n')

        datalines = [datasep.join(map(lambda x: str(x), line))
                     for line in data['data']]
        file_obj.writelines('\n'.join(datalines) + '\n')
    return outpath+filename


def _get_topic_url():
    url = 'https://www.basleratlas.ch/GC_listIndics.php?lang=de'
    return url


def _get_data_url():
    # used to be the first url at around 2018
    # "https://www.basleratlas.ch/GC_ronds.php?lang=de&js=1&indic=bevstruk.alter0&nivgeo=wge&ts=1&serie=2015"
    url = 'https://www.basleratlas.ch/GC_ronds.php'
    url = 'https://www.basleratlas.ch/GC_indic.php'
    return url


def _get_references_url():
    # e.g. https://www.basleratlas.ch/GC_refdata.php?nivgeo=wbl&extent=extent1&lang=de
    url = 'https://www.basleratlas.ch/GC_refdata.php'
    return url


def get_ref_data(nivgeo, slimmed=True):
    import requests
    payload = {'nivgeo': nivgeo,
               'lang': 'de', 'extent': 'extent1'}
    refs = requests.get(_get_references_url(),
                        params=payload,
                        headers=headers)
    refdata = refs.json()['content']['territories']
    # contains the actual numbering in the main geographical administrative
    # dataset that it can be linked against
    if slimmed:
        return refdata['libgeo'], refdata['codgeo']
    else:
        return refdata


def _replace_error_value(value, error_value, replace_value):
    return replace_value if value <= error_value else value


def get_basler_atlas_data(nivgeo,
                          theme,
                          subtheme,
                          year,
                          quiet=True,
                          error_value=-9999,
                          replace_value=0,
                          empty_value='',
                          ):
    import requests
    from requests.exceptions import JSONDecodeError

    payload = _params2payload(nivgeo, theme, subtheme, year=year)

    response = requests.get(_get_data_url(),
                            params=payload,
                            headers=headers)
    if response.ok:

        try:
            data = response.json()['content']['distribution']
        except JSONDecodeError:
            print(f'issues with {response.url} and the payload {payload}')
            return None, None
        if not quiet:
            print(f'Got data from {response.url}, transforming ...')

        values = data['values']

        if 'sortIndices' in data:
            # reported values are to be sorted, usual case?
            indices = data['sortIndices']
        else:
            # reported values are sorted already, usual case for Bezirk?
            indices = range(len(values))
        if isinstance(values, dict):
            keys = list(values.keys())
            indices = range(len(values[keys[0]]))
            values = [[_replace_error_value(values[key][i],
                                            error_value,
                                            replace_value,
                                            )
                      for key in keys]
                      for i in sorted(indices)
                      ]
            data = values
            return keys, data
        else:
            data = [str(_replace_error_value(values[i],
                                             error_value,
                                             replace_value,
                                             )
                        )
                    for i in sorted(indices)]
            return None, data
    else:
        if not quiet:
            print(f'Request for {payload} failed')
        return None, None


def _nivgeo2map(nivgeo):
    lookuptable = {'block': 'map5',
                   'wbl': 'map5',
                   'bezirk': 'map6',
                   'wbe': 'map6',
                   'viertel': 'map2',
                   'wvi': 'map2',
                   'gemeinde': 'map3',
                   'wge': 'map3',
                   # 'wahlkreis': 'map7',
                   # 'pwk': 'map7',
                   }

    return lookuptable[nivgeo]


def _get_nivgeos():
    return 'wbe', 'wvi', 'wge', 'wbl'  # , 'pwk'


def _nicename2nivgeo(nivgeo=None):
    nicenames = _nivgeo2nicename(nivgeo=nivgeo)
    if nivgeo is None:
        return {v: k for k, v in nicenames.items()}
    else:
        return {nicenames: nivgeo}


def _nivgeo2nicename(nivgeo=None):
    names = {'wbe': 'bezirk',
             'wvi': 'viertel',
             'wge': 'gemeinde',
             'wbl': 'block',
             # 'pwk': 'wahlkreis',
             }

    if nivgeo is None:
        return names
    else:
        return names[nivgeo]


def _params2payload(nivgeo,
                    theme,
                    subtheme,
                    year=None):

    payload = {'lang': 'de',
               'dataset':  theme,
               'indic': subtheme,
               'view': _nivgeo2map(nivgeo),
               }

    if year is not None:
        payload['filters'] = 'jahr='+str(year)

    return payload


def get_basler_atlas(start_year=1998,
                     end_year=datetime.date.today().year,
                     # population has different ages,
                     # men m , women w and a grand total
                     themes={'bevstruk': ['alter0',
                                          'alter20',
                                          'alter65',
                                          'w',
                                          'm',
                                          'gesbev'],
                             'bevheim': ['anteil_ch',
                                         'anteil_bs',
                                         'anteil_al',
                                         'anteil_bsanch',
                                         # "gesbev" has been replaced by
                                         'gesbev_f',
                                         ],
                             'bau_lwg': ['anzahl_lwg',
                                         ],
                             },
                     geographical_levels='all',
                     error_value=-9999,
                     replace_value=0,
                     testing=False,
                     quiet=True,
                     ):
    _nicenames = _nicename2nivgeo()

    if geographical_levels == 'all':
        nivgeos = _get_nivgeos()
    else:
        if isinstance(geographical_levels, str):
            geographical_levels = [geographical_levels]
        _nivgeos = _get_nivgeos()

        nivgeos = [i if i in _nivgeos else _nicenames[i]
                   for i in geographical_levels]

        assert all([i in _nivgeos or i in _nicenames
                    for i in nivgeos])

    # the defaults that we know of - there is wahlbezirke too on the
    # atlas but we don't particularly care about that one...
    data = {}
    
    # mapping of information from topic url to meta information entries
    info2meta = {'url': 'c_url_indicateur',
                 'name': 'c_lib_indicateur',
                 'short_name': 'c_lib_indicateur_court',
                 'unit': 'c_unite',
                 'source': 'c_source',
                 'description': 'c_desc_indicateur',
    }
    for nivgeo in nivgeos:
        refname, refnumber = get_ref_data(nivgeo)
        refdata = [[_refname, _refnumber]
                   for _refname, _refnumber in zip(refname, refnumber)]
        # ids of the nivgeo is in refdata['codgeo']
        # names of the nivgeo is in refdata['libgeo']
        nicename = _nivgeo2nicename(nivgeo)

        for theme in themes:
            if not quiet:
                print(f'Working on {theme} for {_nivgeo2nicename(nivgeo)}')
            for subtheme in themes[theme]:
                if not quiet:
                    print(f'Working on {theme}.{subtheme} for ',
                          f'{_nivgeo2nicename(nivgeo)}')
                # force a copy of refdata otherwise we keep updating the old list of lists.
                container = {'data': [i.copy() for i in refdata],
                             'meta': {'theme': theme,
                                      'nivgeo': nivgeo,
                                      'subtheme': subtheme,
                                      'theme': theme, },
                             'header': ['referencename', 'referencenumber'],
                             }
                topicinfo = get_basler_atlas_topics(theme=theme,
                                                    subtheme=subtheme,
                                                    fullinfo=True)
                for key, value in info2meta.items():
                    container['meta'][key] = topicinfo[theme][subtheme][value]

                # values will be nested, adjust header line with extra
                for year in range(start_year, end_year+1):

                    if not quiet:
                        print(f'Getting data for {year} for {theme}',
                              f'{subtheme} for {_nivgeo2nicename(nivgeo)}')

                    keys, thisdata = get_basler_atlas_data(nivgeo,
                                                           theme,
                                                           subtheme,
                                                           year,
                                                           quiet=quiet,
                                                           )
                    if thisdata is None:
                        if not quiet:
                            print(f'Failure to get data for {year} for {theme}',
                                  f'{subtheme} for {_nivgeo2nicename(nivgeo)}')
                        thisdata = [''] * len(container['data'])

                    if keys is None:
                        container['header'] += [f'{year}']
                    else:
                        container['header'] += [f'{year}_{key}'
                                                for key in keys]

                    for i, value in enumerate(thisdata):
                        if not isinstance(value, list):
                            value = [value]
                        container['data'][i] += value

                    if testing:
                        break  # year

                data[nicename+'_'+theme+'_'+subtheme] = container

                if testing:
                    break  # specific theme
            if testing:
                break  # theme
        if testing:
            break  # nivgeo

    return data


def get_basler_atlas_topics(theme=None,
                            subtheme=None,
                            fullinfo=False):
    import requests
    if subtheme is not None and isinstance(subtheme, str):
        subtheme = [subtheme]
    payload = {"tree": "A01", 'lang': 'de'}
    if theme is not None:
        payload['theme'] = theme
    response = requests.get(_get_topic_url(),
                            params=payload,
                            headers=headers)
    topiclist = response.json()['content']['indics']

    data = {}
    for topicinfo in topiclist:
        maintopic, subtopic = (topicinfo['c_id_dataset'],
                               topicinfo['c_id_indicateur'])
        if maintopic not in data:
            if fullinfo:
                data[maintopic] = {}
            else:
                data[maintopic] = []

        if subtheme is not None and subtopic not in subtheme:
            continue
        if fullinfo:
            data[maintopic][subtopic] = topicinfo
        else:
            data[maintopic] += [subtopic]

    return data
  
if __name__ == '__main__':
  print("""
        Some example usages:
        # get some information for the population for the years 200 to 2003
        data = get_basler_atlas(end_year=2003, 
                                start_year=2000, 
                                themes={'bevheim': ['anteil_ch','anteil_bs', ]},
                                geographical_levels='wvi',
                                quiet=True)
        # just get everything that is a predefined topic: 
        themes={'bevstruk': ['alter0',
                             'alter20',
                             'alter65',
                             'w',
                             'm',
                             'gesbev'],
                'bevheim': ['anteil_ch',
                            'anteil_bs',
                            'anteil_al',
                            'anteil_bsanch',
                            # "gesbev" has been replaced by
                            'gesbev_f',
                            ],
                'bau_lwg': ['anzahl_lwg',
                            ],
        }
        # limit just by years
        data = get_basler_atlas(themes=themes, start_year=2000, end_year=2010)
        # also save the data to csv files (by theme and subtheme)
        data2csv(data)
        # get some information regarding the available topics
        themes = get_basler_atlas_topics()
        """)

In the years of 2014 to 2020 or so I was teaching “An introduction to Geoinformatics” at the University of Basel. As a starter, students were supposed to load data of the administrative units of Basel in the form of shapefiles into a GIS (ArcMap or QGIS, I gave support in both) and connect these with population data (age groups or similar). These data can be downloaded from the Statistisches Amt Basel, usually in the form of Excel sheets – which is doable for a GIS but not great to be used: Sometimes I even struggled with getting the right separator in the excel sheet to be automatically recognised for the later import (which is just one reason why I prefer QGIS). However, the updated numbers were sometimes published later than when I’d like to use them – even though the Basler Atlas already had them. So I went to work to scrape the data directly from this source, because I did not want to manually download the data each and every semester again and for several dataset individually. We can do better than that.

In the back, the Basler Atlas uses geoclip, a product from a French company (you also see their logo when opening the Atlas). Relevant for me was that with the browser inspect feature you can get the requests being made in the back and see where the data are coming from (you can of course also click on the request to see the direct answer)

As you can see there is a listIndics and a indic API endpoint. ListIndics gives an overview of datasets, indic gives the data of the “indices”. Both require some specific payload to work, the most important being {‘lang’: ‘de’}. There is however a third endpoint that gives the crucial reference information, namely the name/id of the administrative feature at GC_refdata.php. Initially, I only used the indic endpoint to collect the data directly and the ref to get the reference frame. Combining requests to both, the data can be collected automatically, either to update or for the first time and come back in dict, including a headerline and meta information for the later export (also included above). Now you can get your up-to-date data from the Basler Atlas as well and have a better time using it for temporal analysis by running the above code and then calling this or something like this

data = get_basler_atlas(geographical_levels='block',
                        themes={'bevstruk': ['alter0',
                                             'alter20',
                                             'alter65',
                                             'w',
                                             'm',
                                             'gesbev'], },
                        quiet=True)

This gives you the population data on the block level of the years from 1998 until today (2024 as of this writing). Calling the below saves the data to your home directory, namely 6 CSV files.

data2csv(data, outpath='~/')

Today I extended the code above to also get the available topics (i.e. the categories). Which allows us to discover topics or download data that would require some time to find otherwise.

geolevel = 'block'

for key, values in topics.items():
    if key != 'bevstruk':
        continue
    data = get_basler_atlas(themes={key: values},
                         quiet=True,
                         geographical_levels=geolevel)
    of = data2csv(data, outpath='~/')
    break

As always, I hope this helps someone to discover data or save some time for themselves. And maybe at some point, I’ll find the time to document everything a bit better. Don’t forget to add the data source, i.e. the Stat. Amt Basel when you use their data.

Update/Fix

As I noticed today, there was some issue with the previous version of this script, namely a “deepcopy” issue that led to the fact, that the datacontainer had data from all connected subthemes when more than one was requested. Ups. But it should be fine now, the gist on top is updated and some usage information is added as well. 🙂

GIF frame extraction made easy (sci. vis. util)

TL;DR;Summary

Extract the single frames of a GIF to repurpose them (for example to create a video) with the below code. As always, the most up-to-date version can be found in the GitHub gist

def gif2imgs(file,
             save=False,
             outpath='same',
             outfilename='same',
             ):
    """
    Extract image array from a GIF file.

    Based on PIL, frames of a GIF file are extracted to a numpy array. If
    more than one frame is present in the GIF, a list of numpy arrays is 
    returned. It is possible to save the images directy, by default in the 
    same path as the GIF and the same basename.
    Parameters
    ----------
    file : str
        The GIF file containing one or more image frames.
    save : bool, optional
        Whether to save the image frames directy. The default is False, i.e.
        the function returns a list of the image frames as seperate numpy arrays
    outpath : str, optional
        Where to save the extracted image frames.
        The default is 'same', i.e. same folder
    outfilename : str, optional
        How to name the extracted image as files.
        The default is 'same', i.e. taking the basename and adding _frameX
        to it. If a string is passed, the same suffix is added but the basename
        is taken as the passed in string.

    Returns
    -------
    list of frames or two lists (of filenames of extracted image and images)
        The extracted frames from the GIF and if saving was turned on also 
        the filenames of written out frames.

    """

    import PIL
    import numpy as np
    import os
    import matplotlib.image as img

    pilIm = PIL.Image.open(file)
    pilIm.seek(0)

    # Read all images inside
    images = []
    try:
        while True:
            # Get image as numpy array
            tmp = pilIm.convert()  # Make without palette
            a = np.asarray(tmp)
            if len(a.shape) == 0:
                continue
            # Store, and next
            images.append(a)
            pilIm.seek(pilIm.tell()+1)
    except EOFError:
        pass

    if save:
        if outpath == 'same':
            outpath = os.path.dirname(file) + os.sep
        if outfilename == 'same':
            outfilename = os.path.basename(file)

            outfiles = []
        for frameno, frame in enumerate(images):
            _ = outpath+outfilename.rstrip('.gif') + f'_frame{frameno}.png'
            img.imsave(_, frame, vmin=0, vmax=255)
            outfiles.append(_)

        return outfiles, images
    else:
        return images
      

if __name__ == '__main__':
    import requests
    import matplotlib.pyplot as plt
    fileurl = 'https://gifdb.com/images/high/jumping-cat-typing-on-keyboard-2b15r60jnh8hn5sv.gif'
    response = requests.get(fileurl)
    filename = './example.gif'
    with open(filename, 'wb') as fo:
      fo.write(response.content)
    frames = gif2imgs(filename)
    plt.imshow(frames[0])

Recently I wanted to make a video for a talk. And that is where the trouble started.

Initially, I thought to place a video and GIF side by side. However, getting a synchronous playback was tricky because there are few to no control options for GIFs in most presentation software. As a result, I had to extract the frames from the GIF instead and had to convert them into a video. While I could do this with any of many online services I specifically needed a synchronised playback as the timing of the content needed to match. The code above does exactly these frame extractions and pairs up nicely with another utility, the img2vid (which converts image files to a video with a choosable frame rate.

Simply set the option to save the frames and then run the img2vid on the single images to make the video and you can use it with controls in your presentation software, be it PowerPoint, or anything else.

The above main part gets you an example GIF (it had to be a cat, right?) and shows you the first frame. Enjoy!

Minor SVG hack

TL;DR; Summary and code

This little script replaces certain properties in an SVG. By default, it only looks first at the file you pass in. Be aware that the wrong replacement can break your SVG. For this reason, the script makes a new SVG by default. As always, the GitHub gist should be the up-to-date version.

Python
#!/usr/bin/env python3
# -*- coding: utf-8 -*-

# ********** Careful, you may break SVG graphics with this************
# ********************** READ THE BELOW FIRST ************************
# ********************** No warranty is taken ************************
# By default nothing other than finding RGB codes in the SVG is done
# and only if you want to change something you can change what you want
# to change (inprop) to what it should be (outprop). For this to work
# set inspect to False.

def svg_property_replacer(file, 
                          path='',
                          inspect='rgb',
                          inprop='rgb(0%,0%,0%)',
                          outprop='rgb(100%,0%,0%)',
                          outfile='',
                          force=False):
    import os

    if not outfile:
        outfile = file[:-4]+'_replaced.svg'

    # does the file even exist?
    if not os.path.exists(path+file):
        # answer no, it doesn't, report it, return False
        print('File does not exist')
        return False
    elif not (path+file).endswith('.svg'):
        # answer yes, it does, but isn't an svg, report False
        print('File is not an SVG')
        return False
    else:
        # yes the file exists
        # read the file in
        with open(path+file) as fo:
            img = [line for line in fo.readlines()]

        if 'svg' not in img[0] and 'svg' not in img[1]:
            # it seemed like a svg, but is not a proper one, this may be
            # a mistake by the program that produced it in the first place
            print('Warning! No SVG tag has been found at the start of', file)
            print('For safety reasons only inspection is done.',
                  'Set force to override.')
            print('First lines were', img[0], img[1])
            if not force:
                inspect = 'svg'

        if inspect:
            # look for the inspect string in the lines and print them to stdout
            found = 0
            for _ in img:
                if inspect in _:
                    print(inspect+_.split(inspect)[1].split(';')[0])
                    found = 1
            return found

        else:
            # look for the inprop string in the lines and replace with outprop
            for _ in range(len(img)):
                img[_] = img[_].replace(inprop, outprop)

            # write the outfile as _replaced
            with open(path+outfile, 'w') as fo:
                fo.writelines(img)
        return outfile

if __name__ == '__main__':
    ###### EXAMPLE ###### 
    
    # This example turns the SVG into "darkmode", but be careful
    # the results may vary, depending on the original file, i.e. if there is 
    # some text in black it'll be white and that may not always make sense
    # the same for big white areas. Just try it out
    
    path = '~'
    file = 'test.svg'
    file = path+file
    props = [['rgb(0%,0%,0%)','REPLACEMEAGAIN'],
             ['rgb(100%,100%,100%)', 'rgb(0%,0%,0%)'],
             ['REPLACEMEAGAIN', 'rgb(100%,100%,100%)'],
             ['<svg ', '<svg style="background-color: rgb(15%,15%,15%);" '],
             ]
    
    # file will be named the same with appended _dark
    outfile = file.split('.svg')
    outfile = outfile[0] + '_dark.svg'
    
    for inprop, outprop in props:
        # make another file first, so we can try out different things
        if [inprop,outprop] == props[0]:
            infile = file
        else:
            # then overwrite the same file always to just have one
            infile = outfile
    
        svg_property_replacer(infile,
                              outfile=outfile,
                              inprop=inprop,
                              outprop=outprop,
                              inspect=False,
                              )

Background & motivation

Say you have an SVG, either made by yourself, from a colleague or by extracting from a PDF. This is a great starting point and editing vector graphics is often far more comfortable than raster graphics as you won’t have to edit single pixels. Now you could edit this file in Inkscape, illustrator, or any of the many other software solutions. But if all you want to do is change a certain color, or remove some part of the graphics, you can do that without installing any other software. Instead, you can open the SVG file with your text editor of choice and search for the colour you want to replace (note that colours in SVG files are generally in the hexadecimal form, i.e. #RRGGBB, a search for “colour picker” will generally help you figure out what to look for/pick as replacement). It might be a good idea to back up your file beforehand as well. So let’s say you have the following rectangle in your SVG:

<rect
       style="opacity:0.89;fill:#ffffff;stroke-width:0.264583;stroke:#000000;stroke-opacity:1"
       id="rect165"
       width="50"
       height="35"
       x="90"
       y="80" />

This will be a bit transparent, white filled with a black solid border (I added another rectangle just for show):

You can first search for “fill:” or for “stroke:” to see the occurrences of colour uses in your file and in other places. As you can see, it can also be useful and simple to change the opacity or similar by simply editing the file and changing that one value, for example, the red to light blue (replacing #ff0000 with #3399ff):

But most likely you want to do more/change more than one occurrence and/or more than one property. This is where the above script comes in, as you can run it like the example at the bottom of the script and change many properties in a row (note that the REPLACEME is so that we don’t just change everything from white to black and then both previous ones back to black.

Enjoy using it and easily changing your SVGs!

Images to video (sci. vis. util)

TL;DR; Summary & Code

Use the below Python snippet to create an mp4/webm video based on images in a path that all have a prefix (which can be an empty string too of course). It requires you to have setup ffmpeg to be found on the command line (there would be ways to use the Python version too but this way you can also simply create a link to the standalone version if you are on *nix). The gist version on my github should always be up to date.

Python
# -*- coding: utf-8 -*-
"""
At some point in time

@author: elbarto
"""

def img2vid(path,
            prefix,
            moviename='auto',
            movietype='mp4',
            outrate=15,
            inrate=15,
            imgtype='auto',
            width=1280,
            height=960,
            preset='fast',
            quiet=True,
            )
    """
    Create a movie (mp4 or webm) from a series of images from a folder.

    Parameters
    ----------
    path : str
        Where the images are located.
    prefix : str
        The prefix the images have, e.g., img_XX.png
    moviename : str
        The name of the movie that should be written out e.g., img_XX.png
        The default is movie_XX.mp4 where XX is checked avoid overwriting.
    movietype : str
        The format of the movie to be created e.g., mp4 or webm
        The default is mp4, see also parameter moviename.
    outrate : int, optional
        The framerate of the input. The default is 15.
    inrate : int, optional
        The framerate of the output video. The default is 15.
    imgtype : str, optional
        The imagetype to use as input. The default is 'auto',
        which means that jpg, jpeg, png, gif are looked at and collected
    width : int, optional
        The width of the output video. The default is 1280.
    height : int, optional
        The height of the output video. The default is 960.
    preset : str, optional
        The preset for video creation, determining the creation speed.
        The default is 'fast', other options are very_fast, medium, slow...
    quiet : bool, optional
        Whether to print progress to stdout or not. The default is True.

    Returns
    -------
    None.

    """
    import os
    import subprocess

    # cheap implementation of natsort to avoid dependency
    def natsorted(listlike):
        import re
        convert = lambda x: int(x) if x.isdigit() else x.lower()
        alphanum_key = lambda key: [convert(c) 
                                    for c in re.split('([0-9]+)', key)]
        return sorted(listlike, key=alphanum_key)

    # for convenience move to the path where the images are located
    # will change at the end to the original path again
    curdir = os.path.abspath(os.curdir)
    os.chdir(path)

    filelist = []

    for entry in os.scandir(path):
        if (not entry.name.startswith('.')
           and entry.is_file()
           and entry.name.startswith(prefix)):
            pass
        else:
            continue

        if imgtype == 'auto':
            imgtypes = ['png', 'jpeg', 'jpg', 'gif']
            chk = [entry.name.lower().endswith(_) for _ in imgtypes]
            if max(chk):
                filelist.append(entry.name)
                _imgtype = [_
                            for _ in imgtypes
                            if entry.name.lower().endswith(_)]
        else:
            if entry.name.lower().endswith(imgtype):
                filelist.append(entry.name)

    filelist = natsorted(filelist)

    if imgtype == 'auto':
        if len(_imgtype) != 1:
            print('Issues with autodetection of image format.',
                  'We found the formats', _imgtype,
                  'Please pass in type directly via imgtype=...')
            return False
        imgtype = _imgtype[0]

    if filelist == []:
        print('No files found with these parameters')

    else:

        if not imgtype.startswith('.'):
            imgtype = '.' + imgtype

        cmd = "ffmpeg -r "
        cmd += f'{inrate} '
        cmd += " -f concat "

        tmpfile = 'temp_filelist.txt'
        with open(path + tmpfile, 'w') as fo:
            for file in filelist:
                fo.writelines('file ' + (file).replace('/', "\\") + '\n')

        cmd += f' -i {tmpfile}'
        cmd += ' -vcodec libx264'
        cmd += f' -preset {preset} '
        cmd += '-pix_fmt yuv420p -r '
        cmd += str(outrate)
        cmd += ' -y -s ' + f'{width}x{height} '

        # may be an issue if you have 1382195208752376502350 movie files in
        # the same folder which we hope is unlikely!
        startnumber = 0
        while os.path.exists(path+f'movie_{startnumber}.mp4'):
            startnumber += 1

        if moviename == 'auto':
            moviename = (f'movie_{startnumber}.{movietype}').replace('/', os.sep)

        cmd += moviename

        try:
            if not quiet:
                print('Calling', cmd)
            subprocess.check_call(cmd.split())
            print(f'Successfully made movie {path+os.sep + moviename}')
        except subprocess.CalledProcessError:
            print('Calling ffmpeg failed!',
                  'Make sure it is installed on your system via conda/pip/...')
        finally:
            pass
            os.chdir(curdir)
            os.remove(tmpfile)

        return path + os.sep + moviename

Background & motivation

Who doesn’t know it? You have to give a talk, illustrate your findings or simply want to show something extra on your poster at a conference with a tablet or linked via QR code. Now you can upload your image sequence to many online pages that will convert it into a format of your choice. After you made the video, you notice a mistake in the images and you have to redo it – maybe more than once even. If you want several videos, repeat the process even more often.

Instead, you could use video software suites that render the images into videos, but this is essentially the same tedious process and often requires you to learn the software (which has its own merit but maybe you are lacking the time). Why not program it instead?

The requirements are actually quite easy to meet, especially if we are using ffmpeg and Python. This requires you to have setup ffmpeg so it can be found on the command line.

Development process

To simplify the process, let’s look at the requirements for the function that were important for me at the time:

  • Call ffmpeg on the command line
  • Name the movie and do not overwrite existing movies
  • Pass in a path of images or a list of files (handy if you store the output from another script)
  • Which kind of move to make (mp4 usually is compatible the most, but webm is also useful when making videos for the web/browsers – I tend to go with mp4 for powerpoint presentations, but webm is also supported by MS Office 365 nowadays)
  • How fast the movie should play (in/outrate)
  • Which image type the images are (read jpeg, jpg, png gif are fine)
  • The dimensions the video should have (width, height), per default the first image dimension is taken
  • How the rendering by ffmpeg should be done (fast is usually good enough quality, there is a tradeoff, see documentation of ffmpeg)
  • Whether to report some progress during the making – aka the quiet option

Some things to consider are:

  • You could use natsorted, to get a natural sort of the files as that is usually how we humans would sort them. Usually, this makes little difference but natural sorting works better with mixed naming conventions (0001, 0010, 0100 … vs 1, 10, 100 …). Instead of another dependency, a cheap natsort is implemented as well. Replace the function if you actually have natsort installed and want to use it instead.
  • Instead you can also directly run the video command via ffmpeg on the command line – this is just a thin wrapper to keep some default options in place that made sense to me. You could also write files out to a file and load them via ffmpeg instead …

Other than that, the process is straightforward. Pass in your directory and the prefix that the images might have (tune some things if you want to). Otherwise, enjoy your video making and as a teaser, the following timelapse is made via the above script on a regular basis and linked here

Further reading and resources

Conversion swisstopo, CH1903 (LV95/LV03) and WGS83

TL;DR; Summary and code

Pass in either Latitude/Longitude to wgs84_to_ch1903 (which by default converts to CH1903+) or “Rechtswert” (x) and “Hochwert” (y) to ch1903_to_wgs84 (which detects if its CH1903+ based on the length/value of the passed digits. The most recent version is available as a github gist from me.

Python
import numpy as np

def deci2sexa(angle):

    angle = np.asarray(angle)
    # Extract DMS
    degrees = angle.astype(int)
    minutes = (angle-degrees*60).astype(int)
    seconds = (((angle-degrees)*60)-minutes)*60
    # Result sexagesimal seconds
    return seconds + minutes * 60.0 + degrees * 3600.0

def wgs84_to_ch1903(lat, lon, plus=True):

    lat, lon = deci2sexa(lat), deci2sexa(lon)
    # Auxiliary values (% Bern)
    lat_aux = (lat - 169028.66) / 10000
    lng_aux = (lon - 26782.5) / 10000

    x = (200147.07 +
         308807.95 * lat_aux  +
         3745.25 * np.power(lng_aux, 2) +
         76.63 * np.power(lat_aux, 2) -
         194.56 * np.power(lng_aux, 2) * lat_aux +
         119.79 * np.power(lat_aux, 3))

    y = (600072.37 +
         211455.93 * lng_aux -
         10938.51 * lng_aux * lat_aux -
         0.36 * lng_aux * np.power(lat_aux, 2) -
         44.54 * np.power(lng_aux, 3))

    if plus:
        x += 1000000
        y += 2000000

    return x, y
    
  def ch1903_to_wgs84(x, y, plus='auto'):

    if plus == 'auto':
        if np.nanmax(x) > 1200000 or np.nanmax(y) > 2600000:
            plus = True
        else:
            plus = False

    #  Auxiliary values (% Bern)
    y_aux = (y - 600000)/1000000 # would be 2200000 for ch1903plus
    x_aux = (x - 200000)/1000000 # would be 1200000 for ch1903plus

    if plus:
        x_aux -= 1 # new ch1903plus system has another digit to distinguish it
        y_aux -= 2 # new ch1903plus system has another digit to distinguish it
    # Process lat
    lat = (16.9023892 +
           3.238272 * x_aux -
           0.270978 * np.power(y_aux, 2) -
           0.002528 * np.power(x_aux, 2) -
           0.0447 * np.power(y_aux, 2) * x_aux -
           0.0140 * np.power(x_aux, 3))

    # Process lng
    lon = (2.6779094 +
           4.728982 * y_aux +
           0.791484 * y_aux * x_aux +
           0.1306 * y_aux * np.power(x_aux, 2) -
           0.0436 * np.power(y_aux, 3))

	# Unit 10000" to 1 " and converts seconds to degrees (dec)
    lon = lon * 100 / 36
    lat = lat * 100 / 36
    return lat, lon

Quite often I find myself having to convert WGS84 to CH1903 coordinate systems and vice versa. Sometimes I even got neither and simply have a center point and some distance (looking at you ground-based remote sensing data). While swisstopo used to have (in 2017 or so) a library to download, the current easiest way is to actually use the github repo from Valentin Minder which contains converter for several programming languages.

However, the repo contains classes (which are great of course) but I often prefer a direct function (which in Python is also a class, but well …). As such, I used the same formulas you can find elsewhere from swisstopo to do the calculation. Since I usually do not care that much about the altitude in these cases there is no option (as of yet) to include it. One upside of this version of the conversion is that its array enabled, i.e. the respective coordinates can be either a single scalar or a numpy array (not a list though ;-)).

Further reading

Download data from the Lufft CHM 15k ceilometer webinterface

TL;DR; Summary

Download all newer data from the web interface of the Lufft CHM15k ceilometer into a main directory or directories according to Year/Month/Day format with the code below. An up-to-date version can also be found at my GitHub gists. Change according to your needs (esp. the format of the subfolders).

Python
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 15 09:22:30 2021

@author: spirrobe
"""

import os
import datetime
import requests
import json


class chm15ksession(requests.Session):
    """
    A class for interacting with the CHM-15k data server.

    This class inherits from the requests.Session class and is designed to
    facilitate downloading netCDF and zipped netCDF files from the CHM-15k.
    To use this class, you must have a valid password for accessing the
    server.

    Parameters
    ----------
    url : str
        The URL of the CHM-15k ceilometer. Can be local ip or http URl
    password : str, optional
        The password for accessing the CHM-15k.
        Default is "15k-Nimbus".
    outpath : str, optional
        The path to save downloaded files to. Default is the current directory.
    download2subdirs : bool, optional
        Whether to put files into a subdirectory as outpath/{year}/{month}/{day} 
        where year, month, day are inferred for each file based on the filename
    quiet : bool, optional
        Whether to print information about the download progress.
        Default is True.

    Attributes
    ----------
    url : str
        The URL of the CHM-15k.
    session : requests.Session
        The requests session object used to communicate with the server.
    password : str
        The password for accessing the CHM-15k data server.
    outpath : str
        The path to save downloaded files to.
    filecount : bool
        The number of files available on the server.
    quiet : bool
        Whether to print information about the download progress.
    sessionid : str
        The ID of the current session with the server.
    zipfiles : list of str
        The names of the zipped netCDF files available on the server.
    zipsizes : list of int
        The sizes of the zipped netCDF files available on the server, in bytes.
    ncfiles : list of str
        The names of the netCDF files available on the server.
    ncsizes : list of int
        The sizes of the netCDF files available on the server, in bytes.

    Methods
    -------
    connect()
        Connects to the CHM-15k data server and establishes a session.
    getfilelist()
        Returns a dictionary of available netCDF and zipped netCDF files on the
        CHM-15k data server.
    getncfiles(overwrite=False)
        Downloads all available netCDF files from the CHM-15k to the
        local file system.
    getzipfiles(overwrite=False)
        Downloads all available zipped netCDF files from the CHM-15k
        to the local file system.
    """

    def __init__(self,
                 url,
                 password="15k-Nimbus",
                 outpath='./',
                 download2subdirs=False,
                 timeout=20,
                 quiet=True,
                 *args, **kwargs,
                 ):
        """
        Initialize a new instance of the chm15ksession class.

        Parameters
        ----------
        url : str
            The URL of the CHM-15k.
        password : str, optional
            The password for accessing the CHM-15k data server. Default is
            "15k-Nimbus".
        outpath : str, optional
            The path to save downloaded files to.
            Default is the current directory.
        timeout : bool, optional
            The timeout in seconds for the get calls, adjust if on low bandwidth/slow network.
        quiet : bool, optional
            Whether to print information about the download progress.
            Default is True.
        """
        super().__init__(*args, **kwargs)
        # assert url, str, 'url must be a str'
        self.timeout = timeout
        self.url = url

        if not self.url.endswith('/'):
            self.url += '/'

        if not self.url.startswith('http'):
            self.url = 'http://' + self.url

        self.__cgi = "cgi-bin/chm-cgi"
        self.__cgiurl = self.url + self.__cgi
        #self.session = requests.Session()
        #self = requests.Session()
        self.password = password
        self.outpath = outpath
        self.__subpath = ''
        self.download2subdirs = download2subdirs
        if not self.outpath.endswith(os.sep):
            self.outpath += os.sep

        self.filecount = None
        self.sessionid = None
        self.zipfiles = []
        self.zipsizes = []
        self.ncfiles = []
        self.ncsizes = []
        self.quiet = quiet

    def _filename2date(self, filename):
        # pattern is YYYYMMDD
        _ = filename.split(os.sep)[-1].split('_')[0]
        if len(_) == 8:
            # typical netcdf files
            return _[:4], _[4:4+2], _[4+2:4+2+2]
        elif len(_) == 6:
            # zipfiles do not have a day as they are for the month
            return _[:4], _[4:4+2]
        else:
            print(f'Date could not be inferred from {filename}')
            return '', '', ''

    def _filename2datefolder(self, filename):
       date = self._filename2date(filename)
       if date[0]:
           date = [s + i for s, i in zip(['Y','M','D'], date)]
           date = os.sep.join(date) + os.sep

           if not self.outpath.endswith(os.sep):
               date = os.sep + date
           return date
       else:
           return ''

    def connect(self):
        """
        Connect to the CHM-15k using the provided password.

        This method sends a validation request to the CHM-15k data server
        with the provided passwordand obtains a session ID that can be
        used for subsequent requests.

        Raises
        ------
        requests.exceptions.RequestException
            If the request fails.

        """
        validationurl = self.__cgiurl+f"?validatetoken&code={self.password}"
        # this url could be used to check if the connection worked
        # checkurl = self.__cgiurl+"?checkvalidation"
        try:
            resp = self.get(validationurl, timeout=self.timeout)
        except requests.exceptions.RequestException:
            now = datetime.datetime.now(datetime.UTC)
            print(f'{now}: Connection failed, check url {self.url} and '
                  f'password {self.password}')
            return
        sessionid = resp.text.strip().split('{')[1].split('}')[0]
        resp.close()
        sessionid = sessionid.split(':')[1].split(',')[0]
        self.sessionid = sessionid
        self.cookies.set("session", self.sessionid,
                                 domain=self.url.split(':')[1][2:])
        if not self.quiet:
            now = datetime.datetime.now(datetime.UTC)
            print(f'{now}: Connection successful to {self.url}')
        self.sessionid = True

    def getfilelist(self):
        """
        Get a list of files from the CHM-15k.

        If the connection to the server has not been established,
        this method will establish a connection. Sets attributes of the
        object to contain the return values as well.

        Returns
        -------
        dict
            A dictionary containing the following keys:
            - 'zipfiles': A list of the names of zipped netCDF files.
            - 'netcdffiles': A list of the names of netCDF files.
            - 'zipsizes': A list of the sizes of zipped netCDF files.
            - 'ncsizes': A list of the sizes of netCDF files.
        """
        if self.sessionid:
            pass
        else:
            self.connect()
        resp = self.get(self.__cgiurl + '?filelist', timeout=self.timeout)
        filelist = resp.text
        resp.close()
        filelist = filelist[filelist.index('{'):]
        filelist = filelist[:-filelist[::-1].index('}')]
        try:
            filelist = json.loads(filelist)
        except json.JSONDecodeError:
            if not self.quiet:
                now = datetime.datetime.now(datetime.UTC)
                print('{now}: Issue with getting proper filelist, aborting getfilelist and potential callers')
            return None
        self.filecount = filelist['count']
        self.zipfiles = [i[0] for i in filelist["ncfiles"] if 'zip' in i[0]]
        self.zipsizes = [i[1] for i in filelist["ncfiles"] if 'zip' in i[0]]

        self.ncfiles = [i[0] for i in filelist["ncfiles"] if 'zip' not in i[0]]
        self.ncsizes = [i[1] for i in filelist["ncfiles"] if 'zip' not in i[0]]

        if not self.quiet:
            now = datetime.datetime.now(datetime.UTC)
            print(f'{now}: Found {filelist["count"]} files in total to be checked')
            print(f'{now}: Found {len(self.ncfiles)} netCDF files')
            print(f'{now}: Found {len(self.zipfiles)} zipped netCDF files')

        return {'zipfiles': self.zipfiles, 'netcdffiles': self.ncfiles,
                'zipsizes': self.zipsizes, 'ncsizes': self.ncsizes}

    def getsinglefile(self, filename, overwrite=True):
        """
        Download a single file from the CHM15k to the specified output path.

        Parameters
        ----------
        filename : str
            Name of the file to be downloaded. Can be either zip or nc file.
        overwrite : bool, optional
            Flag indicating whether to overwrite the file if it already
            exists in the output path and has the same size.
            Defaults to True.

        Returns
        -------
        None
            If the file is not available on the server or
            if the file transfer fails.

        Raises
        ------
        None

        Notes
        -----
        This method uses the requests library to download the file
        from the server, and saves it to the output path using
        the same filename as on the device.

        """
        if self.filecount:
            pass
        else:
            self.getfilelist()

        if filename not in self.ncfiles or filename in self.zipfiles:
            print(f'File {filename} not available')
            return
        else:
            if filename in self.ncfiles:
                filesize = self.ncsizes[self.ncfiles.index(filename)]
            elif filename in self.zipfiles:
                filesize = self.zipsizes[self.zipfiles.index(filename)]
            else:
                print(f'File {filename} not available')
                return

        if self.download2subdirs:
            self.__subpath = self._filename2datefolder(filename)

        os.makedirs(self.outpath + self.__subpath, exist_ok=True)

        # check if the file exists, and if it does has the same size
        # if so continue
        if os.path.exists(self.outpath + self.__subpath + filename):
            fs = os.path.getsize(self.outpath + self.__subpath + filename) // 1024
            if fs == filesize and not overwrite:
                if not self.quiet:
                    print(f'File {filename} already exists and has the same '
                          'size as the file on the CHM15k. Pass overwrite to',
                          'download anyway')

                return

        filecontent = self.get(self.__cgiurl+'/'+filename+"?getfile", timeout=self.timeout)
        # check if the transfer worked in the firstplace, if not continue
        if filecontent.status_code != 200:
            if not self.quiet:
                now = datetime.datetime.now(datetime.UTC)
                print(f'{now}: Filetransfer failed for {filename}')
            return

        with open(self.outpath + self.__subpath + filename, 'wb') as fo:
            fo.write(filecontent.content)

        if not self.quiet:
            now = datetime.datetime.now(datetime.UTC)
            print(f'{now}: Successfully downloaded {filename}')

        self.__subpath = ''

    def getncfiles(self, overwrite=False):
        """
        Download netCDF files from the CHM-15k to the specified `outpath`.

        Parameters
        ----------
        overwrite : bool, optional
            Whether to overwrite existing files with the same name and size
            in the `outpath`.
            Default is False.

        Raises
        ------
        ValueError
            If `filecount` attribute is False.

        Notes
        -----
        This method first checks whether the `filecount` attribute is set.
        If not, it calls the `getfilelist` method to obtain a list of files
        available for download. Then, for each netCDF file in the list,
        it checks whether the file already exists in the `outpath` and has
        the same size as the file.
        If not, it downloads the file using a GET request and saves it
        to the `outpath`.

        """
        if self.filecount:
            pass
        else:
            self.getfilelist()

        dlcount = 0
        for fileno, (filename, filesize) \
                in enumerate(zip(self.ncfiles, self.ncsizes)):
            if self.download2subdirs:
                self.__subpath = self._filename2datefolder(filename)
            # check if the file exists, and if it does has the same size
            # if so continue
            if os.path.exists(self.outpath + self.__subpath + filename):
                fs = os.path.getsize(self.outpath + self.__subpath + filename) // 1024
                if fs == filesize and not overwrite:
                    if not self.quiet:
                        now = datetime.datetime.now(datetime.UTC)
                        print(f'Not downloading {filename} as it exists and has the same size')
                        print(f'{now}: Progress at ',
                             f'{round((fileno+1)/len(self.ncfiles) * 100,1)} %')

                    continue
            else:
                os.makedirs(self.outpath + self.__subpath, exist_ok=True)

            filecontent = self.get(
                self.__cgiurl+'/'+filename+"?getfile", timeout=self.timeout)
            # check if the transfer worked in the firstplace, if not continue

            if filecontent.status_code != 200:
                if not self.quiet:
                    print(f'Filetransfer failed for {filename}')
                continue

            with open(self.outpath + self.__subpath + filename, 'wb') as fo:
                fo.write(filecontent.content)

            if not self.quiet:
                now = datetime.datetime.now(datetime.UTC)
                print(f'{now}: Successfully downloaded {filename}, the {dlcount+1} file')
                print(f'{now}: Progress at '
                      f'{round((fileno+1)/len(self.ncfiles) * 100,1)} %')
            dlcount += 1
        now = datetime.datetime.now(datetime.UTC)
        print(f'{now}: Downloaded all {dlcount} files that contained new data '
              f'to {self.outpath + self.__subpath}')
        self.__subpath = ''

    def getzipfiles(self, overwrite=False):
        """
        Download zip files from the CHM-15k to the specified `outpath`.

        Parameters
        ----------
        overwrite : bool, optional
            Whether to overwrite existing files with the same name and size
            in the `outpath`.
            Default is False.

        Raises
        ------
        ValueError
            If `filecount` attribute is False.

        Notes
        -----
        This method first checks whether the `filecount` attribute is set.
        If not, it calls the `getfilelist` method to obtain a list of files
        available for download. Then, for each zip file in the list,
        it checks whether the file already exists in the `outpath` and has
        the same size as the file.
        If not, it downloads the file using a GET request and saves it
        to the `outpath`.

        """
        if self.filecount:
            pass
        else:
            self.getfilelist()

        os.makedirs(self.outpath, exist_ok=True)

        for fileno, (filename, filesize) \
                in enumerate(zip(self.zipfiles, self.zipsizes)):
            if self.download2subdirs:
                self.__subpath =  self._filename2datefolder(filename)
            # check if the file exists, and if it does has the same size
            # if so continue
            if os.path.exists(self.outpath + self.__subpath + filename):
                fs = os.path.getsize(self.outpath + self.__subpath + filename) // 1024
                if fs == filesize and not overwrite:
                    if not self.quiet:
                        print('File already exists and has '
                              f'the same size ({filename})')
                    continue
            else:
                os.makedirs(self.outpath + self.__subpath, exist_ok=True)

            filecontent = self.get(
                self.__cgiurl+'/'+filename+"?getfile", timeout=self.timeout)
            # check if the transfer worked in the firstplace, if not continue
            if filecontent.status_code != 200:
                if not self.quiet:
                    print(f'Filetransfer failed for {filename}')
                continue

            with open(self.outpath + self.__subpath + filename, 'wb') as fo:
                fo.write(filecontent.content)

            if not self.quiet:
                now = datetime.datetime.now(datetime.UTC)
                print(f'{now}: Successfully downloaded {filename}')
                print(f'{now}: Progress at '
                      f'{round((fileno+1)/len(self.zipfiles) * 100,1)} %')
        now = datetime.datetime.now(datetime.UTC)
        print(f'{now}: Downloaded all {len(self.zipfiles)} available '
              f'zip files at {self.outpath + self.__subpath}')
        self.__subpath = ''

if __name__ == '__main__':
    url = ''  # the url to connect to, either http/s or ip directly of the chm15k
    a = chm15ksession(url
                      outpath='./',
                      quiet=False)
                      
    # establish a connection, setting up a session, this wil be done automatically
    # upon calling other get functions
    a.connect()
    
    # get the available files in case you want to download only one file
    a.getfilelist()
    
    # usually, one is interested only in the netcdf files that are available,
    # especially in an operational setting where other files have already
    # been downloaded. 
    # per default, existing files are not downloaded again
    # a.getncfiles()
    
    # zipfiles are created by the device for each month and can be downloaded as well
    # per default, existing files are not downloaded again
    # a.getzipfiles()

Background & motivation

The CHM15k offers the choice between serial and ethernet connection to sample data. While serial connections are true and tested, especially with data logger the reality might be that you don’t have one on-site, its serial ports are full or you would need a USB to serial adapter (which can be quite bothersome with Linux machines. We actually do sample a Parsivel2 with our data server at the CLOUDLAB field site which requires frequent self-compiled drivers as we are running Fedora with its frequent kernel updates….

So we choose to go via the web interface of the Lufft CHM15k even though it requires a login. The upside is that checking for missing data is quite straightforward, it can be interactive and if you forward ports to its network correctly you can also sample it from the outside.

For this purpose, I had a look with the browser inspection tool to see what is being done when the password is sent and used the requests session to stay validated. The rest is fairly standard file checking and downloading. The above allows the script to be changed once with the correct URL (can be the IP or similar, including a port of course). Be aware that you should probably (really really) change the password if you make your device world-accessible via port forwarding.

Once that is done you can run the file via a cronjob or task scheduler as many times as you want as only most recent files are downloaded. Alternatively, import the class and check functionalities yourself for downloading single files or similar. Hope this helps someone out there to facilitate sampling via their ceilometer