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

Downloading peças (anexos)

By default cpopg returns metadata only: process info, parties, movements, and a documentos list (id / date / description). The actual peça files (HTML viewer payloads) are not downloaded.

To also download the peças, pass download_pecas=True and a diretorio. Each peça is saved as <diretorio>/<cnj>/<id_processo_doc>.html (a self- contained XHTML with images embedded as data: URLs), and the returned DataFrame gains a pecas column with the list of saved paths.

The flag lives on cpopg (instead of a separate cpopg_download_pecas method) because the ca tokens that identify each peça are bound to the Seam conversation that produced the detail page — peças must be fetched from the same requests.Session. A separate method would have to re-issue the detail GET internally just to obtain fresh tokens; folding the optional download into cpopg avoids that duplicate round-trip.

import tempfile

with tempfile.TemporaryDirectory() as tmp:
    df_pecas = trf5.cpopg(
        "0058457-31.2025.4.05.8000",
        download_pecas=True,
        diretorio=tmp,
    )
    saved = df_pecas.iloc[0]["pecas"]
    print(f"saved {len(saved)} peça(s)")
    for p in saved[:3]:
        print(" ", p)
TRF5 cpopg:   0%|          | 0/1 [00:00<?, ?it/s]TRF5 cpopg: 100%|██████████| 1/1 [00:25<00:00, 25.78s/it]TRF5 cpopg: 100%|██████████| 1/1 [00:25<00:00, 25.78s/it]
saved 1 peça(s)
  C:\Users\jtrec\AppData\Local\Temp\tmpa7l8mwax\00584573120254058000\145557160.html