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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 3 new columns ({'n_ixps', 'has_ixp', 'total_peers'}) and 5 missing columns ({'n_peers', 'ixp_name', 'net_count', 'ix_id', 'city'}).

This happened while the csv dataset builder was generating data using

hf://datasets/electricsheepafrica/africa-ixp-routing-exposure/ds3_ixp_country_coverage.csv (at revision 38da0ab20ede606bc8c3024ef491738f9e87e90e), [/tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              country_code: string
              country: string
              n_ixps: int64
              total_peers: int64
              has_ixp: bool
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 835
              to
              {'ix_id': Value('int64'), 'ixp_name': Value('string'), 'country_code': Value('string'), 'country': Value('string'), 'city': Value('string'), 'n_peers': Value('int64'), 'net_count': Value('int64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1348, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 3 new columns ({'n_ixps', 'has_ixp', 'total_peers'}) and 5 missing columns ({'n_peers', 'ixp_name', 'net_count', 'ix_id', 'city'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/electricsheepafrica/africa-ixp-routing-exposure/ds3_ixp_country_coverage.csv (at revision 38da0ab20ede606bc8c3024ef491738f9e87e90e), [/tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_african_ixps.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ixp_country_coverage.csv), /tmp/hf-datasets-cache/medium/datasets/94975246609912-config-parquet-and-info-electricsheepafrica-afric-7d876b51/hub/datasets--electricsheepafrica--africa-ixp-routing-exposure/snapshots/38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv (origin=hf://datasets/electricsheepafrica/africa-ixp-routing-exposure@38da0ab20ede606bc8c3024ef491738f9e87e90e/ds3_ripe_probe_coverage.csv)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

ix_id
int64
ixp_name
string
country_code
string
country
string
city
string
n_peers
int64
net_count
int64
592
NAPAfrica IX Johannesburg
ZA
South Africa
Johannesburg
768
548
597
NAPAfrica IX Cape Town
ZA
South Africa
Cape Town
368
281
129
JINX
ZA
South Africa
Johannesburg
252
197
969
NAPAfrica IX Durban
ZA
South Africa
Durban
161
137
236
KIXP - Nairobi
KE
Kenya
Nairobi
148
133
488
IXPN Lagos
NG
Nigeria
Lagos
142
117
344
CINX
ZA
South Africa
Cape Town
136
117
610
DINX
ZA
South Africa
Durban
115
100
2,381
AMS-IX Lagos
NG
Nigeria
Lagos
60
50
4,231
LINX Nairobi
KE
Kenya
Nairobi
58
54
4,653
LINX Mombasa
KE
Kenya
Mombasa
49
47
3,403
NAPAfrica MAPS Johannesburg
ZA
South Africa
Johannesburg
43
26
4,000
AF-CIX
NG
Nigeria
Lagos
41
39
2,362
KIXP-Mombasa
KE
Kenya
Mombasa
38
36
361
TIX Tanzania - Dar es Salaam
TZ
Tanzania
Dar es Salaam
33
32
3,812
EG-IX
EG
Egypt
Cairo
31
19
422
UIXP
UG
Uganda
Kampala
28
25
1,007
angonix
AO
Angola
Luanda
27
24
694
GIXA
GH
Ghana
Accra
27
24
1,508
MIXP
MU
Mauritius
Ebene
25
21
628
KINIX
CD
Congo (Kinshasa)
Kinshasa
25
23
967
AMS-IX Djibouti
DJ
Djibouti
Djibouti
21
20
4,259
Accra Internet Exchange LBG
GH
Ghana
Accra
21
21
421
Angola IXP
AO
Angola
Luanda
19
14
528
MOZIX
MZ
Mozambique
Maputo
18
18
1,201
TIX Tanzania - Arusha (AIXP)
TZ
Tanzania
Arusha
17
16
3,302
PyramIX
EG
Egypt
Cairo
17
18
1,870
IXPN Abuja
NG
Nigeria
Abuja
17
17
1,032
RINEX
RW
Rwanda
Kigali
17
15
2,729
BFIX Ouagadougou
BF
Burkina Faso
Ouagadougou
16
16
810
CIVIX
CI
Côte d'Ivoire
Abidjan
15
14
3,843
BGP.Exchange - Johannesburg
ZA
South Africa
Johannesburg
14
14
2,722
LUBIX
CD
Congo (Kinshasa)
Lubumbashi
14
12
4,148
NMBINX
ZA
South Africa
Gqeberha
14
12
3,633
GOMIX
CD
Congo (Kinshasa)
Goma
13
11
615
Lusaka Internet Exchange Point
ZM
Zambia
Lusaka
12
12
727
MIX-BT
MW
Malawi
Blantyre
10
10
2,541
CAMIX Douala
CM
Cameroon
Douala
10
10
4,081
N'Djamena IX
TD
Chad
N'Djamena
10
9
1,046
CGIX-BZV
CG
Congo (Brazzaville)
Brazzaville
9
9
2,552
BDIXP
BI
Burundi
Bujumbura
9
9
2,624
TIX Tanzania - Dodoma
TZ
Tanzania
Dodoma
9
8
3,561
Douala-IX
CM
Cameroon
Douala
8
8
2,388
TGIX
TG
Togo
Lomé
8
8
1,776
GABIX
GA
Gabon
Libreville
8
8
4,122
ACIX
CD
Congo (Kinshasa)
Kinshasa
7
6
4,769
LINX Accra
GH
Ghana
Accra
7
6
4,920
HubSIX
SN
Senegal
Dakar
6
5
4,037
CV-IXP
CV
Cabo Verde
Praia
6
5
2,414
IXPN Kano
NG
Nigeria
Kano
6
6
922
IXP Namibia
null
Namibia
Windhoek
6
6
3,401
BFIX Bobo-Dioulasso
BF
Burkina Faso
Bobo-Dioulasso
6
6
3,884
NAPAfrica MAPS Cape Town
ZA
South Africa
Cape Town
6
5
2,208
TIX Tanzania - Zanzibar
TZ
Tanzania
Zanzibar
6
6
274
CAIX
EG
Egypt
Cairo
5
5
1,335
MGIX
MG
Madagascar
Antananarivo
5
5
1,017
BENIN-IX
BJ
Benin
Cotonou
5
5
3,734
Asteroid Nairobi
KE
Kenya
Nairobi
5
5
4,446
LIONEX1
MW
Malawi
Lilongwe
5
4
1,574
TIX Tanzania - Mwanza
TZ
Tanzania
Mwanza
5
5
2,665
MLIX
ML
Mali
Bamako
5
5
2,554
CAMIX Yaounde
CM
Cameroon
Yaoundé
4
4
4,892
Michcom-IX
SL
Sierra Leone
Freetown
4
3
2,320
SIXP Sudan
SD
Sudan
Khartoum
4
4
1,105
TunIXP
TN
Tunisia
Tunis
4
4
2,861
JINX Voice
ZA
South Africa
Johannesburg
4
4
2,520
IXP-GUINEE
GN
Guinea
Conakry
4
4
4,573
DarIX
TZ
Tanzania
Dar es Salaam
3
3
3,117
FEZIX
MA
Morocco
Fez
3
3
2,682
SIXP Gambia
GM
Gambia
Serekunda
3
2
2,713
CAS-IX
MA
Morocco
Casablanca
3
3
5,015
Lesotho Internet Exchange Point
LS
Lesotho
Maseru
3
3
4,357
Addix
ET
Ethiopia
Addis Ababa
3
3
2,415
IXPN Port Harcourt
NG
Nigeria
Port Harcourt
2
2
3,097
TIX Tanzania - Mbeya
TZ
Tanzania
Mbeya
2
2
2,815
Asteroid Mombasa
KE
Kenya
Mombasa
2
2
2,617
Harare IX
ZW
Zimbabwe
Harare
2
2
262
SISPA
SZ
Eswatini
Swaziland
0
0
1,409
BINX
BW
Botswana
Gaborone
0
0
2,899
CINX Voice
ZA
South Africa
Cape Town
0
0
2,410
SoIXP
SO
Somalia
Mogadishu
0
0
4,293
CGIX-PNR
CG
Congo (Brazzaville)
Pointe-Noire
0
0
4,413
Asteroid Nairobi-IX
KE
Kenya
Nairobi
0
0
4,450
Tripoli IXP
LY
Libya
Tripoli
0
0
4,724
BGP.Exchange - Nairobi
KE
Kenya
Nairobi
0
0
4,898
PLUGINS IX
KE
Kenya
NAIROBI
0
0
5,002
Digital Delta IX
BW
Botswana
Gaborone
0
0
null
null
DZ
Algeria
null
null
null
null
null
CF
Central African Republic
null
null
null
null
null
KM
Comoros
null
null
null
null
null
GQ
Equatorial Guinea
null
null
null
null
null
ER
Eritrea
null
null
null
null
null
GW
Guinea-Bissau
null
null
null
null
null
LR
Liberia
null
null
null
null
null
MR
Mauritania
null
null
null
null
null
NE
Niger
null
null
null
null
null
ST
São Tomé and Príncipe
null
null
null
null
null
SC
Seychelles
null
null
null
null
null
SS
South Sudan
null
null
null
null
null
ZA
South Africa
null
null
null
End of preview.

Africa IXP & Routing Exposure

Electric Sheep Africa · Post-Quantum Cryptographic Exposure cluster · dataset DS-3 · v0.1

African digital infrastructure is being recorded by state actors today under the assumption it will be decryptable once quantum computers arrive (2030–2035 per NIST/NCSC/ENISA). This dataset is one dimension of the Africa-specific evidence for that claim.

What this dataset answers

Which African countries lack local internet exchange points and therefore route domestic traffic through foreign jurisdictions?

Key findings (v0.1)

  • 87 African IXPs are registered in PeeringDB across 42 of 54 countries.
  • 12 African countries have no IXP in PeeringDB; their domestic traffic leaves the continent and returns.
  • 262 RIPE Atlas probes across 37 countries are available to measure the routing detour penalty.

Files

ds3_ixp_country_coverage.csv (54 rows)

Column Example
country_code DZ
country Algeria
n_ixps 0
total_peers 0
has_ixp False

ds3_african_ixps.csv (87 rows)

Column Example
ix_id 592
ixp_name NAPAfrica IX Johannesburg
country_code ZA
country South Africa
city Johannesburg
n_peers 768
net_count 548

ds3_ripe_probe_coverage.csv (54 rows)

Column Example
country_code ZA
country South Africa
connected_probes 133

Method

African IXPs and their peering membership were pulled from PeeringDB. Country coverage marks states with no IXP present. RIPE Atlas probe counts establish where intra-African routing detours can be actively measured (the millisecond-detour leg).

Sources

PeeringDB API; RIPE Atlas probe API.

Limitations

PeeringDB undercounts vs on-the-ground IXP censuses (Coalition for Digital Africa reported 63 IXPs in 38 countries, 2024). The millisecond detour penalty is not yet measured in this version; the probe inventory shows the measurement is in reach.

How to cite

Electric Sheep Africa (2026). Africa IXP & Routing Exposure (africa-ixp-routing-exposure). African Cryptographic Exposure & Post-Quantum Risk dataset cluster. Hugging Face. https://huggingface.co/datasets/electricsheepafrica/africa-ixp-routing-exposure
@dataset{esa_africa_ixp_routing_exposure_2026,
  title  = {Africa IXP & Routing Exposure},
  author = {Electric Sheep Africa},
  year   = {2026},
  publisher = {Hugging Face},
  url    = {https://huggingface.co/datasets/electricsheepafrica/africa-ixp-routing-exposure}
}

Part of the cluster

This is one of eight datasets in the African Cryptographic Exposure & Post-Quantum Risk cluster by Electric Sheep Africa. The others cover TLS deployment, certificate-authority dependency, algorithm inventory, submarine cable topology, IXP/routing exposure, the regulatory gap, incident history, and PQC migration cost. See the collection on the electricsheepafrica org page.

Methodology & ethics

All collection is passive and uses public data, or standard TLS handshakes against publicly reachable endpoints (the same a browser performs). No interception, no exploitation, no private access. Figures are v0.1 and reproducible from the open collector code.

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