TRF5 — Tribunal Regional Federal da 5ª Região

Public process consultation (cpopg) for the federal courts under the fifth region (AL, CE, PB, PE, RN, SE), via the PJe ConsultaPublica system at pje1g.trf5.jus.br/pjeconsulta/.

Feature	Available
cpopg	Yes
cposg	No
cjsg	No
cjpg	No

Looking up a single process

import juscraper as jus

trf5 = jus.scraper("trf5")

df = trf5.cpopg("0058457-31.2025.4.05.8000")
print(df.shape)
df[["id_cnj", "processo", "classe", "orgao_julgador"]]

TRF5 cpopg: 100%|██████████| 1/1 [00:01<00:00,  1.21s/it]

(1, 12)

	id_cnj	processo	classe	orgao_julgador
0	00584573120254058000	0058457-31.2025.4.05.8000	RECLAMAÇÃO PRÉ-PROCESSUAL (11875)	Ambiente do Centro de Conciliação de Maceió

Available columns

df.columns.tolist()

['processo',
 'data_distribuicao',
 'classe',
 'assunto',
 'jurisdicao',
 'orgao_julgador',
 'endereco_orgao',
 'polo_ativo',
 'polo_passivo',
 'movimentacoes',
 'documentos',
 'id_cnj']

The first three columns are the canonical scalars; the trailing four are list-typed and carry the nested arrays (parties, movements, attached documents).

Inspecting movements

movs = df.iloc[0]["movimentacoes"]
print(f"{len(movs)} events recorded")
for m in movs[:5]:
    print(f"  {m['data']} - {m['descricao']}")

15 events recorded
  10/04/2026 15:13:41 - Arquivado Definitivamente
  16/03/2026 04:23:15 - Decorrido prazo de NADIR BARBOSA DE ALMEIDA em 13/03/2026 23:59.
  10/03/2026 08:27:35 - Decorrido prazo de CONSELHO REGIONAL DE ODONTOLOGIA em 09/03/2026 23:59.
  23/02/2026 00:19:36 - Publicado Sentença em 23/02/2026.
  21/02/2026 00:29:17 - Disponibilizado no DJ Eletrônico em 20/02/2026

Inspecting parties

print("Polo ativo:")
for p in df.iloc[0]["polo_ativo"]:
    print(f"  - {p['participante']}")

print()
print("Polo passivo:")
for p in df.iloc[0]["polo_passivo"]:
    print(f"  - {p['participante']}")

Polo ativo:
  - CONSELHO REGIONAL DE ODONTOLOGIA (RECLAMANTE)
  - DEBORA SERAFIM DA SILVA BARBOSA - OAB AL18880 - CPF: 124.519.994-38 (ADVOGADO)

Polo passivo:
  - NADIR BARBOSA DE ALMEIDA - CPF: 678.266.364-34 (RECLAMADO)

Looking up multiple processes at once

cnjs = [
    "00584573120254058000",
    "00412666120254058100",
]
df_batch = trf5.cpopg(cnjs)
df_batch[["id_cnj", "processo", "classe", "orgao_julgador"]]

TRF5 cpopg: 100%|██████████| 2/2 [00:02<00:00,  1.12s/it]

	id_cnj	processo	classe	orgao_julgador
0	00584573120254058000	0058457-31.2025.4.05.8000	RECLAMAÇÃO PRÉ-PROCESSUAL (11875)	Ambiente do Centro de Conciliação de Maceió
1	00412666120254058100	0041266-61.2025.4.05.8100	RECLAMAÇÃO PRÉ-PROCESSUAL (11875)	Ambiente do Centro de Conciliação do Ceará

Handling processes the public portal cannot return

When a CNJ does not surface in the public consultation (sigilo, archived, or simply not found), the row carries only id_cnj. The other columns come back as None/NaN, so callers can still distinguish “looked up but missing” from “never tried”.

import pandas as pd

df_missing = trf5.cpopg("00000000020994050000")
print("processo:", df_missing.iloc[0].get("processo"))
print("classe:", df_missing.iloc[0].get("classe"))

TRF5 cpopg: 100%|██████████| 1/1 [00:00<00:00,  8.63it/s]

processo: None
classe: None

Splitting download from parse

cpopg is a thin wrapper over cpopg_download (raw HTML) + cpopg_parse (HTML → DataFrame). Splitting them is useful when you want to cache the raw HTMLs to disk before processing.

htmls = trf5.cpopg_download("0058457-31.2025.4.05.8000")
print(f"got {len(htmls)} HTML(s), {len(htmls[0])} chars")

df_again = trf5.cpopg_parse(htmls, ["00584573120254058000"])
df_again[["id_cnj", "processo", "data_distribuicao"]]

TRF5 cpopg: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]

got 1 HTML(s), 80218 chars

	id_cnj	processo	data_distribuicao
0	00584573120254058000	0058457-31.2025.4.05.8000	07/11/2025