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Postal code geocoding and distance calculation

Home Page: https://pgeocode.readthedocs.io/

License: BSD 3-Clause "New" or "Revised" License

Python 100.00%

geocoding geolocation geonames postal-code zipcode

pgeocode's People

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rth samehmannai priya-gittest skyjiao barseghyanartur zaro djoguns dineshnemali sclipman cuongkta 0x38 sroecker long5270 amarchin egabancho sthagen djskripta willidert alfredosequeida dword4 loadsmart codruta musicpiano joaquincasares spijkervet konstantinklepikov martijnschouten s2t2 adalberto1986 garybake nadermx ryanbwolf sid6389 takeahsiaor eracle benwulmer cbiehl hedi-guedidi mateusz-koziel soysushi baipzix cimadure gordonaiken209 kevinwangl alessandrolorenzi chichacha zalmansoro brittdev31 khanfarhan10 thedotproduct hasancs3a4 ethicalsecurity-agency mwoss

pgeocode's Issues

Add a fallback data source when https://download.geonames.org/export/zip/{country}.zip fails

With issues #40 and #34 , we see that genonames data source that we rely on seems to have intermittent availability issues. To protect against such intermittent failures can we think of adding a fallback data source or a cache. Both the issues were short lived and resolved by itself.

In Issue #40 @richunger pointed out that the data was available at http://download.geonames.org/export/dump/ when we had the issue, can we rely on that as a backup data source.

KeyError: "There is no item named 'DE.txt' in the archive"

NL and FR are working fine, but when trying out other countries it gives me this error.

KeyError: "There is no item named 'DE.txt' in the archive"

But they are still accessible: https://symerio.github.io/postal-codes-data/data/geonames/DE.txt

Handle detailed postal codes for Morocco

Hi,

It is possible to add support for postal codes in Morocco?
Right now, I'm getting this error when I try to use the country code 'MA' with python package :
country=MA is not a known country code. See the README for a list of supported countries

I noticed in GeoNames that the zip code 'MA' was available.

Thanks you for this package !

Please Update Countries

Hi,
Useful package. Seems the Geonames folks have published some more countries:
AZ
CL
CY
EE
FM
HT
KR
MW
PE
PW
RS
SG
Can you update, please?

Issues with the new download location

Recently the new download location changed to "https://download.geonames.org/export/dump/{country}.zip" simply changing the URL doesn't work, as the downloaded file looks incorrect then in ~/pgeocode_data/

Downloading the file manually or with wget does download the right data.

I'm not sure what is going on, either the server serves cached data based on the user agent or there is some incorrect caching happening on the client side.

In any case this is a blocker for pgeocode.

Throwing HTTP 404 error

https://download.geonames.org/export/zip/{country}.zip , this link is throwing 404 error.

[Solved] Import from first hard coded URL fails with "[SSL: CERTIFICATE_VERIFY_FAILED"

On windows 10 using Python 3.9.7 the quickstart example crashes at

"nomi = pgeocode.Nominatim('fr')"

with the error

urllib.error.URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed:     certificate has expired (_ssl.c:1129)>

This is probably caused by the Let's Encrypt certificate.

You can do a quick fix by either removing the first URL in line 25 in pgeocode.py or by turning off ssl verification in line 141

import ssl
with urllib.request.urlopen(url, context=ssl._create_unverified_context()) as

Wrong mapping of Postal codes

There are some postal codes were the latitude and longitude that are estimated from postal codes that are shown in sea and also instances were the postal code is shown in another city.Following are sample postal codes where this is happening
Pincode latitude longitude
400069 18.9596 72.8604
400079 18.9596 72.88815
400054 18.9292 72.8856
395003 21.2659 72.55363636
395005 21.2218 72.28558182
395001 21.1941 72.5018

County Code for Naples is NA

Hi,

This is the data fetched from pgocode for 80030 postal code:

postal_code                                                   80030
country_code                                                     IT
place_name        Spartimento, Gallo, Cimitile, Carbonara Di Nol...
state_name                                                 Campania
state_code                                                        4
county_name                                                  Napoli
county_code                                                     NaN
community_name                                                  NaN
community_code                                                  NaN
latitude                                                  40.926694
longitude                                                 14.520376
accuracy                                                        4.0

This is the raw from GeoNames:

IT      80030   Spartimento     Campania        04      Napoli  NA                      40.891  14.4724 4
IT      80030   Gallo   Campania        04      Napoli  NA                      40.9424 14.5455 4
IT      80030   Cimitile        Campania        04      Napoli  NA                      40.9423 14.5256 4
IT      80030   Carbonara Di Nola       Campania        04      Napoli  NA                      40.8744 14.5788 4
IT      80030   Camposano       Campania        04      Napoli  NA                      40.9524 14.5299 4
IT      80030   San Vitaliano   Campania        04      Napoli  NA                      40.9244 14.4746 4
IT      80030   Castello Di Cisterna    Campania        04      Napoli  NA                      40.9159 14.4112 4
IT      80030   Mariglianella   Campania        04      Napoli  NA                      40.9296 14.437  4
IT      80030   Visciano        Campania        04      Napoli  NA                      40.9238 14.5824 4
IT      80030   Tufino  Campania        04      Napoli  NA                      40.9559 14.5657 4
IT      80030   Liveri  Campania        04      Napoli  NA                      40.9041 14.5654 4
IT      80030   San Paolo Bel Sito      Campania        04      Napoli  NA                      40.9135 14.5486 4
IT      80030   Comiziano       Campania        04      Napoli  NA                      40.9516 14.5512 4
IT      80030   Scisciano       Campania        04      Napoli  NA                      40.9066 14.4745 4
IT      80030   Roccarainola    Campania        04      Napoli  NA                      40.9725 14.5428 4
IT      80030   Schiava Campania        04      Napoli  NA                      40.9267 14.5204 3
IT      80030   Gargani Campania        04      Napoli  NA                      40.9267 14.5204 3

The data from GeoNames dataset is correct, I assume that the library is misinterpreting NA as NaN.

Incorrect distance showing

Hello,

I just used the library, but I noticed that the distance returned was incorrect.

dist = pgeocode.GeoDistance('PH')
dist.query_postal_code('0860', '1227')

returns 76 kms. I am sure that the distance is not 76kms. The source maybe was the lat, long provided as I tried googling the provided values for 1227 but it was located in a very far province.

Cannot create nominatim for country codes AS, LT, VA

I have a set of zip codes that I need to decode to countries. To do so, I plan to query each nominatim and return any country where a match is found.

In trying to instantiate each nominatum, I received an error:

import pgeocode
nomis = {cc: pgeocode.Nominatim(cc) for cc in pgeocode.COUNTRIES_VALID}

When investigating:

for cc in pgeocode.COUNTRIES_VALID:
     try:
         pgeocode.Nominatim(cc)
     except Exception as ex:
         print(cc, ex)

I get:

AS No numeric types to aggregate
LT sequence item 1: expected str instance, float found
VA No numeric types to aggregate

Suggest either investigating, or dropping from the valid countries list. Thanks!

Missing postal codes for germany

While I was playing with the code, I just recognized that there are some postal codes for germany that the code returns no information regarding latitude, longitude, state_name and etc. I checked them in google map and I found that they are indeed valid postal codes.
Here is the list of the postal codes with null results:

Thank you in advance for your support!

Bests,

Amin

Pgeocode not working for Brazil Z.P.

I have noticed that pgeocode v 0.2.1 request to get locations based on Z.P. from Brazil is not working. I have tried erasing the - or with it, but still, it returns an empty value.

Inverse postal code geocoding

It should be fairly straightforward to implement inverse geo-coding, i.e. find the closest city/region/country for given coordinates.

This would require downloading all the datasets however.

Ideally, the nearest neighbor lookup could be done efficiently with a KD-tree structure (e.g. in scipy). Though scipy is a fairly heavy dependency so maybe this could be an optional feature if scipy is installed.

Include a requirements.txt

Super easy fix, will save tons of dependency headaches.

pip freeze > requirements.txt

pgeocode: query_postal_code function

Regarding the query_postal_code function:
As seen on the code below. The actual postal code i'm searching for is 'K2C' but in-order to search for it i had to insert '5CA' in front of it. My understanding is the 5 - represents the accuracy and CA - is the Country code.
Why do these first three characters need to be added? Am i right in what they represent?

nomi = pgeocode.Nominatim('CA')
nomi.query_postal_code("5CA K2C")

thanks

Query location not working at all.

Hi,

The function query_location is not working at all. I found this website with the background information for pgeocode 0.1.0 and it seems the function has as argument pass.

My pgeocode version is 0.2.1.

Find cities at a specific distance

Given a location and a distance, what's the right way to find populated places that are exactly that distance from the location?

I don't want to search for everything inside a circle, just what is on its perimeter.

Thanks!

Pgeocode | HTTPError: HTTP Error 404: Not Found

Hello ,

I am using pgeocode to fetch longitude and latitude from postal code.
as i am using this package from last few months i am facing issue of HTTP

currently this issue happening more frequently than past.
This is hampering my pipeline run as well.

can you please give me solution or way around for this problem.

Thanks and regards,
nikhil

Support alternate download locations

It might be useful to support alternate download locations in case GeoNames website goes down. This would also help reproducibility (I'm not sure how often GeoNames database is updated and if that is tracked somewhere).

This would require storing the data somewhere. One possibility for free hosting could be to attach it to Github releases.

For instance, maybe @zaro's implementation in zaro@6a3c743 could be adapted.

How can i convert different country code?

I want to find 'KR' country code, but this package is not Offer default.

So, How Can i find 'KR' country_code.

Download URL Template Has Changed

The new template is https://download.geonames.org/export/dump/{country}.zip

pgeocode.py - ValueError: too many values to unpack (expected 3)

Description

At the first run, whenever trying to download a new country, you get this error.
A solution has been provided.

Pipfile

[[source]]
url = "https://pypi.org/simple"
verify_ssl = true
name = "pypi"

[packages]
pgeocode = '>=0.1.0'

[dev-packages]

[requires]
python_version = "3.7"

Error

Traceback (most recent call last):
  File ".../geocode.py", line 3, in <module>
    nomi = pgeocode.Nominatim('FR')
  File ".../lib/python3.7/site-packages/pgeocode.py", line 55, in __init__
    self._data_path, self._data = self._get_data(country)
  File ".../lib/python3.7/site-packages/pgeocode.py", line 71, in _get_data
    reader, encoding, compression = get_filepath_or_buffer(url)
ValueError: too many values to unpack (expected 3)

Change

File: pgeocode.py

-            reader, encoding, compression = get_filepath_or_buffer(url)
+            reader, encoding, compression, *rest = get_filepath_or_buffer(url)

country code DZ is not responding

import pgeocode
nomi = pgeocode.Nominatim()

if "DZ" in pgeocode.COUNTRIES_VALID:
print("country found")
nomi = pgeocode.Nominatim("DZ")
zipcodes = ["30200"]
for i in nomi.query_postal_code(zipcodes).to_dict("records"):
print("-----", i)

Inconsistency in "country code" column name

There seems to be some inconsistency with how to access data returned by the query_postal_code() function in addition to some errors thrown.

pgeocode==0.2.1
pandas==1.0.3

Here is the creation of the object with a postal code

Python 3.6.8 (default, Apr 25 2019, 21:02:35)                                                                                        [20/589]
[GCC 4.8.5 20150623 (Red Hat 4.8.5-36)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import pgeocode
>>> code = "M4B 1B3"
>>> loc = pgeocode.Nominatim('ca')
>>> s = loc.query_postal_code(code)
>>> print(s)
postal_code                                                M4B
country code                                                CA
place_name        East York (Parkview Hill / Woodbine Gardens)
state_name                                             Ontario
state_code                                                  ON
county_name                                         East York
county_code                                                NaN
community_name                                             NaN
community_code                                             NaN
latitude                                               43.7063
longitude                                             -79.3094
accuracy                                                     6
Name: 0, dtype: object

Now I will try to access s.country_code and get an error

>>> print(s.country_code)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib64/python3.6/site-packages/pandas/core/generic.py", line 5274, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'country_code'

And now another field with the same underscore styled name

>>> print(s.postal_code)
M4B

Now using the manner that is often seen with Pandas

>>> print(s['country code'])
CA

But when I try this for postal code it throws a different error

>>> print(s['postal code'])
Traceback (most recent call last):
  File "/usr/local/lib64/python3.6/site-packages/pandas/core/indexes/base.py", line 4411, in get_value
    return libindex.get_value_at(s, key)
  File "pandas/_libs/index.pyx", line 44, in pandas._libs.index.get_value_at
  File "pandas/_libs/index.pyx", line 45, in pandas._libs.index.get_value_at
  File "pandas/_libs/util.pxd", line 98, in pandas._libs.util.get_value_at
  File "pandas/_libs/util.pxd", line 83, in pandas._libs.util.validate_indexer
TypeError: 'str' object cannot be interpreted as an integer

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib64/python3.6/site-packages/pandas/core/series.py", line 871, in __getitem__
    result = self.index.get_value(self, key)
  File "/usr/local/lib64/python3.6/site-packages/pandas/core/indexes/base.py", line 4419, in get_value
    raise e1
  File "/usr/local/lib64/python3.6/site-packages/pandas/core/indexes/base.py", line 4405, in get_value
    return self._engine.get_value(s, k, tz=getattr(series.dtype, "tz", None))
  File "pandas/_libs/index.pyx", line 80, in pandas._libs.index.IndexEngine.get_value
  File "pandas/_libs/index.pyx", line 90, in pandas._libs.index.IndexEngine.get_value
  File "pandas/_libs/index.pyx", line 138, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 1618, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 1626, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'postal code'

ValueError: country=NL_FULL is not a known country code. See the README for a list of supported countries

The full variant is in the geonames : http://download.geonames.org/export/zip/

Can this be added?

Not able to identify few postal codes and find the distances between them for country CA

Kudos to the algorithm which makes work easier
But there are few postcodes in Canada which the algorithm is not able to identify though these codes exist in the geonames files
M5E 0C5 is one such code for which i couldnt find the lat and long or distance from the algorithm

Slow performance for Portugal (PT)

Hi,
I am querying latitude and longitude from the postcodes of 26 countries. When I made a test run where there are 10 rows for each country, Portugal (PT) takes much longer to process. For reference, all other countries run in the range of 1-3 seconds, while for Portugal this ranges in 30-40 seconds.

I'm not experienced in Python much, so probably my coding is not the most efficient but it is odd that one country stands out (Suggestions to improve the code below is most welcome).

for country_code in np.unique(df.COUNTRY_VALUE):
  print(country_code,len(df[df.COUNTRY_VALUE==country_code]))
  start_time = time.time()
  nomi = pgeocode.Nominatim(country_code)
  df.loc[df.COUNTRY_VALUE==country_code,'LAT']=df.POSTCODE.apply(get_city).latitude
  df.loc[df.COUNTRY_VALUE == country_code, 'LON'] = df.POSTCODE.apply(get_city).latitude
  print("--- %s seconds ---" % (time.time() - start_time))

def get_city(code):
    try:
        x=nomi.query_postal_code(code)
        return x
    except:
        return ('')

Faster dataset loading

Currently we load datasets with pd.read_csv from gzipped CSV format. Loading should be much improved by converting the data to parquet format and using pd.read_parquet (this might also reduce the size of downloads when using e.g. snappy compression).

Though the limitations of this approach is that datasets would need to be hosted somewhere and a new dependency (pyarrow) would need to be added. I'm not sure that it would be worth it.

Proposal for lightweight version of pgeocode without pandas and numpy dependencies

Hi @rth! :3 Thanks for your great work and for creating such a useful library. I deeply appreciate your hard work! :3

I love using it, but dependencies used underneath like pandas and numpy can be sometimes problematic. They are quite heavy and can be a bit troublesome to install on Apple devices with M* chips. I was thinking about an alternative that would provide an identical API, but use built-in functionalities/libraries such as csv or math instead.

I believe it could be beneficial for many workflows and projects. What do you think about such an idea? :D

Handle detailed postal codes for Great Britain

The GB dataset for Great Britain only includes outwards codes (i.e. only first 3 letters). The full dataset is included in GB_full, but currently this fails to load,

>>> import pgeocode
>>> dist = pgeocode.GeoDistance('GB_full')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/rth/src/pgeocode/pgeocode.py", line 174, in __init__
    super(GeoDistance, self).__init__(country)
  File "/home/rth/src/pgeocode/pgeocode.py", line 49, in __init__
    .format(country))
ValueError: country=GB_FULL is not a known country code. See the README for a list of supported countries

Mostly making sure input validation works, in this case, should fix this, I think.

Pgeocode throws HTTP Error 404: Not Found

AFAIK it's the same issue as #40

latitude indexing bug for _index_postal_codes

Hello,
New guy here using the pgeocode lib for one of my projects. I have just noticed that there may be a small bug while generating the -index.txt file that results the mean location for post code shift a bit.
Can anyone please double check if the latitude is calcualted properly? I can see there's a possible typo in the valid_keys derivation and latitude is spelled with two Ts.

Location: https://github.com/symerio/pgeocode/blob/main/pgeocode.py#L255

Occurs for PL post codes, e.g. 21-310 or 98-330

pgeocode: Accuracy scale

I think it's a great package. I am trying to use the package for Canadian postal codes.

Regarding the accuracy scale used. I can't find an explanation for each number (3,5 and the blanks). All i found was:
1=estimated,
4=geonameid,
6=centroid of addresses or shape

incorrect centroid in query_postal_code for duplicate postal code entries

query_postal_code sums the longitude.

nomi.query_postal_code("41-800")

Thats from GEOName file:
41-800 will return you 2 locations:
PL, 41-800, 50.2817, 18.6745
PL,41-800, 50.3055, 18.778

After running: nomi.query_postal_code("41-800")
postal_code 41-800
place_name Gliwice, Zabrze
latitude 50.2817
longitude 18.7263

and the longitude = SUM of the locations from file / number of results.

ValueError on CA, UK and IE postcodes

First off, this is a great package which has really helped me out! I have encountered a bug with postcodes for CA, UK and IE post codes. The error I am getting is

ValueError                                Traceback (most recent call last)
<ipython-input-1174-3c5ae744b055> in <module>
----> 1 import codecs, os;__pyfile = codecs.open('''/tmp/pyjoGiOo''', encoding='''utf-8''');__code = __pyfile.read().encode('''utf-8''');__pyfile.close();os.remove('''/tmp/pyjoGiOo''');exec(compile(__code, '''/home/Downloads//Data_Cleaning/cleaning.py''', 'exec'));

~/Downloads//Data_Cleaning/cleaning.py in <module>
    500         lookup.columns =
    501 
--> 502 
    503 
    504 df1_missing_city = df1.groupby('Target country code').apply(lambda x: len(x[x['Target city'].isnull() == True]) / len(x) * 100)

~/anaconda3/lib/python3.8/site-packages/pandas/core/series.py in apply(self, func, convert_dtype, args, **kwds)
   4198             else:
   4199                 values = self.astype(object)._values
-> 4200                 mapped = lib.map_infer(values, f, convert=convert_dtype)
   4201 
   4202         if len(mapped) and isinstance(mapped[0], Series):

pandas/_libs/lib.pyx in pandas._libs.lib.map_infer()

~/Downloads//Data_Cleaning/cleaning.py in <lambda>(x)
    500         lookup.columns =
    501 
--> 502 
    503 
    504 df1_missing_city = df1.groupby('Target country code').apply(lambda x: len(x[x['Target city'].isnull() == True]) / len(x) * 100)

~/Downloads//Data_Cleaning/cleaning.py in postcode_lookup(postcode, form)
    489                 'VA',
    490                 'VI',
--> 491                 'WF',
    492                 'YT',
    493                 'ZA']

~/anaconda3/lib/python3.8/site-packages/pgeocode.py in query_postal_code(self, codes)
    305 
    306         codes = self._normalize_postal_code(codes)
--> 307         response = pd.merge(
    308             codes, self._data_frame, on="postal_code", how="left"
    309         )

~/anaconda3/lib/python3.8/site-packages/pandas/core/reshape/merge.py in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate)
     72     validate=None,
     73 ) -> "DataFrame":
---> 74     op = _MergeOperation(
     75         left,
     76         right,

~/anaconda3/lib/python3.8/site-packages/pandas/core/reshape/merge.py in __init__(self, left, right, how, on, left_on, right_on, axis, left_index, right_index, sort, suffixes, copy, indicator, validate)
    654         # validate the merge keys dtypes. We may need to coerce
    655         # to avoid incompatible dtypes
--> 656         self._maybe_coerce_merge_keys()
    657 
    658         # If argument passed to validate,

~/anaconda3/lib/python3.8/site-packages/pandas/core/reshape/merge.py in _maybe_coerce_merge_keys(self)
   1163                     inferred_right in string_types and inferred_left not in string_types
   1164                 ):
-> 1165                     raise ValueError(msg)
   1166 
   1167             # datetimelikes must match exactly

ValueError: You are trying to merge on float64 and object columns. If you wish to proceed you should use pd.concat

I have traced back this error as far the _normalize_postal_code which seems to be throwing up the merge error latter query_postal_code function. Although I haven't been able to figure out what it is about splitting these postcodes which seems to be upsetting pandas so much.

query_location

Is there any plan for the query_location method? I think it would be great to have it. Cheers

Downloading US file 404's

The US file no longer exists http://download.geonames.org/export/zip/US.zip and the code throws a 404 when trying to download it.

HTTPError
HTTP Error 404: Not Found

HTTP Error 401, Authentication Required

I have pip installed pgeocode with the --user flag as I am on a shared server and lack permissions to write in most places except my home. As a test, I use this demo code:

import pgeocode
nomi = pgeocode.Nominatim('fr')
nomi.query_postal_code("75013")

Is this error below telling me it can't download the geonames database I've asked for?

Thanks.

HTTPError                                 Traceback (most recent call last)
<ipython-input-17-14e76cf7e5d5> in <module>
      1 import pgeocode
----> 2 nomi = pgeocode.Nominatim('fr')
      3 nomi.query_postal_code("75013")

~/.local/lib/python3.7/site-packages/pgeocode.py in __init__(self, country)
     53                           "in 1999.")
     54         self.country = country
---> 55         self._data_path, self._data = self._get_data(country)
     56         self._data_unique = self._index_postal_codes()
     57 

~/.local/lib/python3.7/site-packages/pgeocode.py in _get_data(country)
     69             url = DOWNLOAD_URL.format(country=country)
     70             compression = _infer_compression(url, "zip")
---> 71             reader, encoding, compression = get_filepath_or_buffer(url)[:3]
     72             with ZipFile(reader) as fh_zip:
     73                 with fh_zip.open(country.upper() + '.txt') as fh:

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/site-packages/pandas/io/common.py in get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode)
    200 
    201     if _is_url(filepath_or_buffer):
--> 202         req = _urlopen(filepath_or_buffer)
    203         content_encoding = req.headers.get('Content-Encoding', None)
    204         if content_encoding == 'gzip':

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in urlopen(url, data, timeout, cafile, capath, cadefault, context)
    220     else:
    221         opener = _opener
--> 222     return opener.open(url, data, timeout)
    223 
    224 def install_opener(opener):

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in open(self, fullurl, data, timeout)
    529         for processor in self.process_response.get(protocol, []):
    530             meth = getattr(processor, meth_name)
--> 531             response = meth(req, response)
    532 
    533         return response

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in http_response(self, request, response)
    639         if not (200 <= code < 300):
    640             response = self.parent.error(
--> 641                 'http', request, response, code, msg, hdrs)
    642 
    643         return response

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in error(self, proto, *args)
    561             http_err = 0
    562         args = (dict, proto, meth_name) + args
--> 563         result = self._call_chain(*args)
    564         if result:
    565             return result

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in _call_chain(self, chain, kind, meth_name, *args)
    501         for handler in handlers:
    502             func = getattr(handler, meth_name)
--> 503             result = func(*args)
    504             if result is not None:
    505                 return result

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in http_error_302(self, req, fp, code, msg, headers)
    753         fp.close()
    754 
--> 755         return self.parent.open(new, timeout=req.timeout)
    756 
    757     http_error_301 = http_error_303 = http_error_307 = http_error_302

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in open(self, fullurl, data, timeout)
    529         for processor in self.process_response.get(protocol, []):
    530             meth = getattr(processor, meth_name)
--> 531             response = meth(req, response)
    532 
    533         return response

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in http_response(self, request, response)
    639         if not (200 <= code < 300):
    640             response = self.parent.error(
--> 641                 'http', request, response, code, msg, hdrs)
    642 
    643         return response

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in error(self, proto, *args)
    567         if http_err:
    568             args = (dict, 'default', 'http_error_default') + orig_args
--> 569             return self._call_chain(*args)
    570 
    571 # XXX probably also want an abstract factory that knows when it makes

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in _call_chain(self, chain, kind, meth_name, *args)
    501         for handler in handlers:
    502             func = getattr(handler, meth_name)
--> 503             result = func(*args)
    504             if result is not None:
    505                 return result

/opt/anacondaShell/envs/ScientificPython3Stack/lib/python3.7/urllib/request.py in http_error_default(self, req, fp, code, msg, hdrs)
    647 class HTTPDefaultErrorHandler(BaseHandler):
    648     def http_error_default(self, req, fp, code, msg, hdrs):
--> 649         raise HTTPError(req.full_url, code, msg, hdrs, fp)
    650 
    651 class HTTPRedirectHandler(BaseHandler):

HTTPError: HTTP Error 401: authenticationrequired

pandas 1.0.1 _infer_compression error

requirements.txt

numpy==1.18.1
pandas==1.0.1
pgeocode==0.1.2

test.py

import pgeocode
nomi = pgeocode.Nominatim('fr')

error:

>\venv\lib\site-packages\pgeocode.py (line 69, in _get_data)
>from pandas.io.common import get_filepath_or_buffer, _infer_compression